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How UBC gained TCO advantage via flash for its EduCloud cloud storage service

The next BriefingsDirect cloud efficiency case study explores how a storage-as-a-service offering in a university setting gains performance and lower total cost benefits by a move to all-flash storage.

We’ll now learn how the University of British Columbia (UBC) has modernized its EduCloud storage service and attained both efficiency as well as better service levels for its diverse user base.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or  download a copy.

Here to help us explore new breeds of SaaS solutions is Brent Dunington, System Architect at UBC in Vancouver. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: How is satisfying the storage demands at a large and diverse university setting a challenge? Is there something about your users and the diverse nature of their needs that provides you with a complex requirements list? 

Dunington: A university setting isn't much different than any other business. The demands are the same. UBC has about 65,000 students and about 15,000 staff. The students these days are younger kids, they all have iPhones and iPads, and they just want to push buttons and get instant results and instant gratification. And that boils down to the services that we offer.

Dunington

Dunington

We have to be able to offer those services, because as most people know, there are choices -- and they can go somewhere else and choose those other products.

Our team is a rather small team. There are 15 members in our team, so we have to be agile, we have to be able to automate things, and we need tools that can work and fulfill those needs. So it's just like any other business, even though it’s a university setting.

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Gardner: Can you give us a sense of the scale that describes your storage requirements?

Dunington: We do SaaS, we also do infrastructure-as-a-service (IaaS). EduCloud is a self-service IaaS product that we deliver to UBC, but we also deliver it to 25 other higher institutions in the Province of British Columbia.

We have been doing IaaS for five years, and we have been very, very successful. So more people are looking to us for guidance.

Because we are not just delivering to UBC, we have to be up running and always able to deliver, because each school has different requirements. At different times of the year -- because there is registration, there are exam times -- these things have to be up. You can’t not be functioning during an exam and have 600 students not able to take the tests that they have been studying for. So it impacts their life and we want to make sure that we are there and can provide the services for what they need.

Gardner: In order to maintain your service levels within those peak times, do you in your IaaS and storage services employ hybrid-cloud capabilities so that you can burst? Or are you doing this all through your own data center and your own private cloud?

On-Campus Cloud

Dunington: We do it all on-campus. British Columbia has a law that says all the data has to stay in Canada. It’s a data-sovereignty law, the data can't leave the borders.

That's why EduCloud has been so successful, in my opinion, because of that option. They can just go and throw things out in the private cloud.

The public cloud providers are providing more services in Canada: Amazon Web Services (AWS) and Microsoft Azure cloud are putting data centers in Canada, which is good and it gives people an option. Our team’s goal is to provide the services, whether it's a hybrid model or all on-campus. We just want to be able to fulfill those needs.

Gardner: It sounds like the best of all worlds. You are able to give that elasticity benefit, a lot of instant service requirements met for your consumers. But you are starting to use cloud pay-as-you-go types of models and get the benefit of the public cloud model -- but with the security, control and manageability of the private clouds.

What decisions have you made about your storage underpinnings, the infrastructure that supports your SaaS cloud?

Dunington: We have a large storage footprint. For our site, it’s about 12 petabytes of storage. We realized that we weren’t meeting the needs with spinning disks. One of the problems was that we had runaway virtual workloads that would cause problems, and they would impact other services. We needed some mechanism to fix that.

We wanted to make sure that we had the ability to attain quality of service levels and control those runaway virtual machines in our footprint.

We went through the whole request for proposal (RFP) process, and all the IT infrastructure vendors responded, but we did have some guidelines that we wanted to go through. One of the things we did is present our problems and make sure that they understood what the problems were and what they were trying to solve.

And there were some minimum requirements. We do have a backup vendor of choice that they needed to merge with. And quality of service is a big thing. We wanted to make sure that we had the ability to attain quality of service levels and control those runaway virtual machines in our footprint.

Gardner: You gained more than just flash benefits when you got to flash storage, right?

Streamlined, safe, flash storage

Dunington: Yes, for sure. With an entire data center full of spinning disks, it gets to the point where the disks start to manage you; you are no longer managing the disks. And the teams out there changing drives, removing volumes around it, it becomes unwieldy. I mean, the power, the footprint, and all that starts to grow.

Also, Vancouver is in a seismic zone, we are right up against the Pacific plate and it's a very active seismic area. Heaven forbid anything happens, but one of the requirements we had was to move the data center into the interior of the province. So that was what we did.

When we brought this new data center online, one of the decisions the team made was to move to an all-flash storage environment. We wanted to be sure that it made financial sense because it's publicly funded, and also improved the user experience, across the province.

Gardner: As you were going about your decision-making process, you had choices, what made you choose what you did? What were the deciding factors?

Dunington: There were a lot of deciding factors. There’s the technology, of being able to meet the performance and to manage the performance. One of the things was to lock down runaway virtual machines and to put performance tiers on others.

But it’s not just the technology; it's also the business part, too. The financial part had to make sense. When you are buying any storage platform, you are also buying the support team and the sales team that come with it.

Our team believes that technology is a certain piece of the pie, and the rest of it is relationship. If that relationship part doesn't work, it doesn’t matter how well the technology part works -- the whole thing is going to break down.

Because software is software, hardware is hardware -- it breaks, it has problems, there are limitations. And when you have to call someone, you have to depend on him or her. Even though you bought the best technology and got the best price -- if it doesn't work, it doesn’t work, and you need someone to call.

So those service and support issues were all wrapped up into the decision.

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We chose the Hewlett Packard Enterprise (HPE) 3PAR all-flash storage platform. We have been very happy with it. We knew the HPE team well. They came and worked with us on the server blade infrastructure, so we knew the team. The team knew how to support all of it. 

We also use the HPE OneView product for provisioning, and it integrated into that all. It also supported the performance optimization tool (IT Operations Management for HPE OneView) to let us set those values, because one of the things in EduCloud is customers choose their own storage tier, and we mark the price on it. So basically all we would do is present that new tier as new data storage within VMware and then they would just move their workloads across non-disruptively. So it has worked really well.

The 3PAR storage piece also integrates with VMware vRealize Operations Manager. We offer that to all our clients as a portal so they can see how everything is working and they can do their own diagnostics. Because that’s the one goal we have with EduCloud, it has to be self-service. We can let the customers do it, that's what they want.

Gardner: Not that long ago people had the idea that flash was always more expensive and that they would use it for just certain use-cases rather than pervasively. You have been talking in terms of a total cost of ownership reduction. So how does that work? How does the economics of this over a period of time, taking everything into consideration, benefit you all?

Economic sense at scale

Dunington: Our IT team and our management team are really good with that part. They were able to break it all down, and they found that this model would work at scale. I don’t know the numbers per se, but it made economic sense.

Spinning disks will still have a place in the data center. I don't know a year from now if an all-flash data center will make sense, because there are some records that people will throw in and never touch. But right now with the numbers on how we worked it out, it makes sense, because we are using the standard bronze, the gold, the silver tiers, and with the tiers it makes sense.

The 3PAR solution also has dedupe functionality and the compression that they just released. We are hoping to see how well that trends. Compression has only been around for a short period of time, so I can’t really say, but the dedupe has done really well for us.

Gardner: The technology overcomes some of the other baseline economic costs and issues, for sure.

We have talked about the technology and performance requirements. Have you been able to qualify how, from a user experience, this has been a benefit?

Dunington: The best benchmark is the adoption rate. People are using it, and there are no help desk tickets, so no one is complaining. People are using it, and we can see that everything is ramping up, and we are not getting tickets. No one is complaining about the price, the availability. Our operational team isn't complaining about it being harder to manage or that the backups aren’t working. That makes me happy.

The big picture

Gardner: Brent, maybe a word of advice to other organizations that are thinking about a similar move to private cloud SaaS. Now that you have done this, what might you advise them to do as they prepare for or evaluate a similar activity?

Not everybody needs that speed, not everybody needs that performance, but it is the future and things will move there.

Dunington: Look at the full picture, look at the total cost of ownership. There’s the buying of the hardware, and there's also supporting the hardware, too. Make sure that you understand your requirements and what your customers are looking for first before you go out and buy it. Not everybody needs that speed, not everybody needs that performance, but it is the future and things will move there. We will see in a couple of years how it went.

Look at the big picture, step back. It’s just not the new shiny toy, and you might have to take a stepped approach into buying, but for us it worked. I mean, it’s a solid platform, our team sleeps well at night, and I think our customers are really happy with it.

Gardner: This might be a little bit of a pun in the education field, but do your homework and you will benefit.

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Flash Performance

Dunington: Yes, for sure.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or  download a copy. Sponsor: Hewlett Packard Enterprise.

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How modern storage provides hints on optimizing and best managing hybrid IT and multi-cloud resources

The next BriefingsDirect Voice of the Analyst interview examines the growing need for proper rationalizing of which apps, workloads, services and data should go where across a hybrid IT continuum.

Managing hybrid IT necessitates not only a choice between public cloud and private cloud, but a more granular approach to picking and choosing which assets go where based on performance, costs, compliance, and business agility.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy.

Here to report on how to begin to better assess what IT variables should be managed and thoughtfully applied to any cloud model is Mark Peters, Practice Director and Senior Analyst at Enterprise Strategy Group (ESG). The discussion is moderated by Dana Gardner, principal analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Now that cloud adoption is gaining steam, it may be time to step back and assess what works and what doesn’t. In past IT adoption patterns, we’ve seen a rapid embrace that sometimes ends with at least a temporary hangover. Sometimes, it’s complexity or runaway or unmanaged costs, or even usage patterns that can’t be controlled. Mark, is it too soon to begin assessing best practices in identifying ways to hedge against any ill effects from runaway adoption of cloud? 

Peters: The short answer, Dana, is no. It’s not that the IT world is that different. It’s just that we have more and different tools. And that is really what hybrid comes down to -- available tools.

Peters

Peters

It’s not that those tools themselves demand a new way of doing things. They offer the opportunity to continue to think about what you want. But if I have one repeated statement as we go through this, it will be that it’s not about focusing on the tools, it’s about focusing on what you’re trying to get done. You just happen to have more and different tools now.

Gardner: We hear sometimes that at as high as board of director levels, they are telling people to go cloud-first, or just dump IT all together. That strikes me as an overreaction. If we’re looking at tools and to what they do best, is cloud so good that we can actually just go cloud-first or cloud-only?

Cloudy cloud adoption

Peters: Assuming you’re speaking about management by objectives (MBO), doing cloud or cloud-only because that’s what someone with a C-level title saw on a Microsoft cloud ad on TV and decided that is right, well -- that clouds everything.

You do see increasingly different people outside of IT becoming involved in the decision. When I say outside of IT, I mean outside of the operational side of IT.

You get other functions involved in making demands. And because the cloud can be so easy to consume, you see people just running off and deploying some software-as-a-service (SaaS) or infrastructure-as-a-service (IaaS) model because it looked easy to do, and they didn’t want to wait for the internal IT to make the change.

All of the research we do shows that the world is hybrid for as far ahead as we can see.

Running away from internal IT and on-premises IT is not going to be a good idea for most organizations -- at least for a considerable chunk of their workloads. All of the research we do shows that the world is hybrid for as far ahead as we can see. 

Gardner: I certainly agree with that. If it’s all then about a mix of things, how do I determine the correct mix? And if it’s a correct mix between just a public cloud and private cloud, how do I then properly adjust to considerations about applications as opposed to data, as opposed to bringing in microservices and Application Programming Interfaces (APIs) when they’re the best fit?

How do we begin to rationalize all of this better? Because I think we’ve gotten to the point where we need to gain some maturity in terms of the consumption of hybrid IT.

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Peters: I often talk about what I call the assumption gap. And the assumption gap is just that moment where we move from one side where it’s okay to have lots of questions about something, in this case, in IT. And then on the other side of this gap or chasm, to use a well-worn phrase, is where it’s not okay to ask anything because you’ll see you don’t know what you’re talking about. And that assumption gap seems to happen imperceptibly and very fast at some moment.

So, what is hybrid IT? I think we fall into the trap of allowing ourselves to believe that having some on-premises workloads and applications and some off-premises workloads and applications is hybrid IT. I do not think it is. It’s using a couple of tools for different things.

It’s like having a Prius and a big diesel and/or gas F-150 pickup truck in your garage and saying, “I have two hybrid vehicles.” No, you have one of each, or some of each. Just because someone has put an application or a backup off into the cloud, “Oh, yeah. Well, I’m hybrid.” No, you’re not really.

The cloud approach

The cloud is an approach. It’s not a thing per se. It’s another way. As I said earlier, it’s another tool that you have in the IT arsenal. So how do you start figuring what goes where?

I don’t think there are simple answers, because it would be just as sensible a question to say, “Well, what should go on flash or what should go on disk, or what should go on tape, or what should go on paper?” My point being, such decisions are situational to individual companies, to the stage of that company’s life, and to the budgets they have. And they’re not only situational -- they’re also dynamic.

I want to give a couple of examples because I think they will stick with people. Number one is you take something like email, a pretty popular application; everyone runs email. In some organizations, that is the crucial application. They cannot run without it. Probably, what you and I do would fall into that category. But there are other businesses where it’s far less important than the factory running or the delivery vans getting out on time. So, they could have different applications that are way more important than email.

When instant messaging (IM) first came out, Yahoo IM text came out, to be precise. They used to do the maintenance between 9 am and 5 pm because it was just a tool to chat to your friends with at night. And now you have businesses that rely on that. So, clearly, the ability to instant message and text between us is now crucial. The stock exchange in Chicago runs on it. IM is a very important tool.

The answer is not that you or I have the ability to tell any given company, “Well, x application should go onsite and Y application should go offsite or into a cloud,” because it will vary between businesses and vary across time.

If something is or becomes mission-critical or high-risk, it is more likely that you’ll want the feeling of security, I’m picking my words very carefully, of having it … onsite.

You have to figure out what you're trying to get done before you figure out what you're going to do with it.

But the extent to which full-production apps are being moved to the cloud is growing every day. That’s what our research shows us. The quick answer is you have to figure out what you’re trying to get done before you figure out what you’re going to do it with. 

Gardner: Before we go into learning more about how organizations can better know themselves and therefore understand the right mix, let’s learn more about you, Mark. 

Tell us about yourself, your organization at ESG. How long have you been an IT industry analyst? 

Peters: I grew up in my working life in the UK and then in Europe, working on the vendor side of IT. I grew up in storage, and I haven’t really escaped it. These days I run ESG’s infrastructure practice. The integration and the interoperability between the various elements of infrastructure have become more important than the individual components. I stayed on the vendor side for many years working in the UK, then in Europe, and now in Colorado. I joined ESG 10 years ago.

Lessons learned from storage

Gardner: It’s interesting that you mentioned storage, and the example of whether it should be flash or spinning media, or tape. It seems to me that maybe we can learn from what we’ve seen happen in a hybrid environment within storage and extrapolate to how that pertains to a larger IT hybrid undertaking.

Is there something about the way we’ve had to adjust to different types of storage -- and do that intelligently with the goals of performance, cost, and the business objectives in mind? I’ll give you a chance to perhaps go along with my analogy or shoot it down. Can we learn from what’s happened in storage and apply that to a larger hybrid IT model?

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Peters: The quick answer to your question is, absolutely, we can. Again, the cloud is a different approach. It is a very beguiling and useful business model, but it’s not a panacea. I really don’t believe it ever will become a panacea.

Now, that doesn’t mean to say it won’t grow. It is growing. It’s huge. It’s significant. You look at the recent announcements from the big cloud providers. They are at tens of billions of dollars in run rates.

But to your point, it should be viewed as part of a hierarchy, or a tiering, of IT. I don’t want to suggest that cloud sits at the bottom of some hierarchy or tiering. That’s not my intent. But it is another choice of another tool.

Let’s be very, very clear about this. There isn’t “a” cloud out there. People talk about the cloud as if it exists as one thing. It does not. Part of the reason hybrid IT is so challenging is you’re not just choosing between on-prem and the cloud, you’re choosing between on-prem and many clouds -- and you might want to have a multi-cloud approach as well. We see that increasingly.

What we should be looking for are not bright, shiny objects -- but bright, shiny outcomes.

Those various clouds have various attributes; some are better than others in different things. It is exactly parallel to what you were talking about in terms of which server you use, what storage you use, what speed you use for your networking. It’s exactly parallel to the decisions you should make about which cloud and to what extent you deploy to which cloud. In other words, all the things you said at the beginning: cost, risk, requirements, and performance.

People get so distracted by bright, shiny objects. Like they are the answer to everything. What we should be looking for are not bright, shiny objects -- but bright, shiny outcomes. That’s all we should be looking for.

Focus on the outcome that you want, and then you figure out how to get it. You should not be sitting down IT managers and saying, “How do I get to 50 percent of my data in the cloud?” I don’t think that’s a sensible approach to business. 

Gardner: Lessons learned in how to best utilize a hybrid storage environment, rationalizing that, bringing in more intelligence, software-defined, making the network through hyper-convergence more of a consideration than an afterthought -- all these illustrate where we’re going on a larger scale, or at a higher abstraction.

Going back to the idea that each organization is particular -- their specific business goals, their specific legacy and history of IT use, their specific way of using applications and pursuing business processes and fulfilling their obligations. How do you know in your organization enough to then begin rationalizing the choices? How do you make business choices and IT choices in conjunction? Have we lost sufficient visibility, given that there are so many different tools for doing IT?

Get down to specifics

Peters: The answer is yes. If you can’t see it, you don’t know about it. So to some degree, we are assuming that we don’t know everything that’s going on. But I think anecdotally what you propose is absolutely true.

I’ve beaten home the point about starting with the outcomes, not the tools that you use to achieve those outcomes. But how do you know what you’ve even got -- because it’s become so easy to consume in different ways? A lot of people talk about shadow IT. You have this sprawl of a different way of doing things. And so, this leads to two requirements.

Number one is gaining visibility. It’s a challenge with shadow IT because you have to know what’s in the shadows. You can’t, by definition, see into that, so that’s a tough thing to do. Even once you find out what’s going on, the second step is how do you gain control? Control -- not for control’s sake -- only by knowing all the things you were trying to do and how you’re trying to do them across an organization. And only then can you hope to optimize them.

You can't manage what you can't measure. You also can't improve things that can't be managed or measured.

Again, it’s an old, old adage. You can’t manage what you can’t measure. You also can’t improve things that can’t be managed or measured. And so, number one, you have to find out what’s in the shadows, what it is you’re trying to do. And this is assuming that you know what you are aiming toward.

This is the next battleground for sophisticated IT use and for vendors. It’s not a battleground for the users. It’s a choice for users -- but a battleground for vendors. They must find a way to help their customers manage everything, to control everything, and then to optimize everything. Because just doing the first and finding out what you have -- and finding out that you’re in a mess -- doesn’t help you.

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Visibility is not the same as solving. The point is not just finding out what you have – but of actually being able to do something about it. The level of complexity, the range of applications that most people are running these days, the extremely high levels of expectations both in the speed and flexibility and performance, and so on, mean that you cannot, even with visibility, fix things by hand.

You and I grew up in the era where a lot of things were done on whiteboards and Excel spreadsheets. That doesn’t cut it anymore. We have to find a way to manage what is automated. Manual management just will not cut it -- even if you know everything that you’re doing wrong. 

Gardner: Yes, I agree 100 percent that the automation -- in order to deal with the scale of complexity, the requirements for speed, the fact that you’re going to be dealing with workloads and IT assets that are off of your premises -- means you’re going to be doing this programmatically. Therefore, you’re in a better position to use automation.

I’d like to go back again to storage. When I first took a briefing with Nimble Storage, which is now a part of Hewlett Packard Enterprise (HPE), I was really impressed with the degree to which they used intelligence to solve the economic and performance problems of hybrid storage.

Given the fact that we can apply more intelligence nowadays -- that the cost of gathering and harnessing data, the speed at which it can be analyzed, the degree to which that analysis can be shared -- it’s all very fortuitous that just as we need greater visibility and that we have bigger problems to solve across hybrid IT, we also have some very powerful analysis tools.

Mark, is what worked for hybrid storage intelligence able to work for a hybrid IT intelligence? To what degree should we expect more and more, dare I say, artificial intelligence (AI) and machine learning to be brought to bear on this hybrid IT management problem?

Intelligent automation a must

Peters: I think it is a very straightforward and good parallel. Storage has become increasingly sophisticated. I’ve been in and around the storage business now for more than three decades. The joke has always been, I remember when a megabyte was a lot, let alone a gigabyte, a terabyte, and an exabyte.

And I’d go for a whole day class, when I was on the sales side of the business, just to learn something like dual parsing or about cache. It was so exciting 30 years ago. And yet, these days, it’s a bit like cars. I mean, you and I used to use a choke, or we’d have to really go and check everything on the car before we went on 100-mile journey. Now, we press the button and it better work in any temperature and at any speed. Now, we just demand so much from cars.

To stretch that analogy, I’m mixing cars and storage -- and we’ll make it all come together with hybrid IT in that it’s better to do things in an automated fashion. There’s always one person in every crowd I talk to who still believes that a stick shift is more economic and faster than an automatic transmission. It might be true for one in 1,000 people, and they probably drive cars for a living. But for most people, 99 percent of the people, 99.9 percent of the time, an automatic transmission will both get you there faster and be more efficient in doing so. The same became true of storage.

We used to talk about how much storage someone could capacity-plan or manage. That’s just become old hat now because you don’t talk about it in those terms. Storage has moved to be -- how do we serve applications? How do we serve up the right place in the right time, get the data to the right person at the right time at the right price, and so on?

We don’t just choose what goes where or who gets what, we set the parameters -- and we then allow the machine to operate in an automated fashion. These days, increasingly, if you talk to 10 storage companies, 10 of them will talk to you about machine learning and AI because they know they’ve got to be in that in order to make that execution of change ever more efficient and ever faster. They’re just dealing with tremendous scale, and you could not do it even with simple automation that still involves humans.

It will be self-managing and self-optimizing. It will not be a “recommending tool,” it will be an “executing tool.”

We have used cars as a social analogy. We used storage as an IT analogy, and absolutely, that’s where hybrid IT is going. It will be self-managing and self-optimizing. Just to make it crystal clear, it will not be a “recommending tool,” it will be an “executing tool.” There is no time to wait for you and me to finish our coffee, think about it, and realize we have to do something, because then it’s too late. So, it’s not just about the knowledge and the visibility. It’s about the execution and the automated change. But, yes, I think your analogy is a very good one for how the IT world will change.

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Gardner: How you execute, optimize and exploit intelligence capabilities can be how you better compete, even if other things are equal. If everyone is using AWS, and everyone is using the same services for storage, servers, and development, then how do you differentiate?

How you optimize the way in which you gain the visibility, know your own business, and apply the lessons of optimization, will become a deciding factor in your success, no matter what business you’re in. The tools that you pick for such visibility, execution, optimization and intelligence will be the new real differentiators among major businesses.

So, Mark, where do we look to find those tools? Are they yet in development? Do we know the ones we should expect? How will organizations know where to look for the next differentiating tier of technology when it comes to optimizing hybrid IT?

What’s in the mix?

Peters: We’re talking years ahead for us to be in the nirvana that you’re discussing.

I just want to push back slightly on what you said. This would only apply if everyone were using exactly the same tools and services from AWS, to use your example. The expectation, assuming we have a hybrid world, is they will have kept some applications on-premises, or they might be using some specialist, regional or vertical industry cloud. So, I think that’s another way for differentiation. It’s how to get the balance. So, that’s one important thing.

And then, back to what you were talking about, where are those tools? How do you make the right move?

We have to get from here to there. It’s all very well talking about the future. It doesn’t sound great and perfect, but you have to get there. We do quite a lot of research in ESG. I will throw just a couple of numbers, which I think help to explain how you might do this.

We already find that the multi-cloud deployment or option is a significant element within a hybrid IT world. So, asking people about this in the last few months, we found that about 75 percent of the respondents already have more than one cloud provider, and about 40 percent have three or more.

You’re getting diversity -- whether by default or design. It really doesn’t matter at this point. We hope it’s by design. But nonetheless, you’re certainly getting people using different cloud providers to take advantage of the specific capabilities of each.

This is a real mix. You can’t just plunk down some new magic piece of software, and everything is okay, because it might not work with what you already have -- the legacy systems, and the applications you already have. One of the other questions we need to ask is how does improved management embrace legacy systems?

Some 75 percent of our respondents want hybrid management to be from the infrastructure up, which means that it’s got to be based on managing their existing infrastructure, and then extending that management up or out into the cloud. That’s opposed to starting with some cloud management approach and then extending it back down to their infrastructure.

People want to enhance what they currently have so that it can embrace the cloud. It’s enhancing your choice of tiers so you can embrace change.

People want to enhance what they currently have so that it can embrace the cloud. It's enhancing your choice of tiers so you can embrace change. Rather than just deploying something and hoping that all of your current infrastructure -- not just your physical infrastructure but your applications, too -- can use that, we see a lot of people going to a multi-cloud, hybrid deployment model. That entirely makes sense. You're not just going to pick one cloud model and hope that it  will come backward and make everything else work. You start with what you have and you gradually embrace these alternative tools. 

Gardner: We’re creating quite a list of requirements for what we’d like to see develop in terms of this management, optimization, and automation capability that’s maybe two or three years out. Vendors like Microsoft are just now coming out with the ability to manage between their own hybrid infrastructures, their own cloud offerings like Azure Stack and their public cloud Azure.

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Where will we look for that breed of fully inclusive, fully intelligent tools that will allow us to get to where we want to be in a couple of years? I’ve heard of one from HPE, it’s called Project New Hybrid IT Stack. I’m thinking that HPE can’t be the only company. We can’t be the only analysts that are seeing what to me is a market opportunity that you could drive a truck through. This should be a big problem to solve.

Who’s driving?

Peters: There are many organizations, frankly, for which this would not be a good commercial decision, because they don’t play in multiple IT areas or they are not systems providers. That’s why HPE is interested, capable, and focused on doing this. 

Many vendor organizations are either focused on the cloud side of the business -- and there are some very big names -- or on the on-premises side of the business. Embracing both is something that is not as difficult for them to do, but really not top of their want-to-do list before they’re absolutely forced to.

From that perspective, the ones that we see doing this fall into two categories. There are the trendy new startups, and there are some of those around. The problem is, it’s really tough imagining that particularly large enterprises are going to risk [standardizing on them]. They probably even will start to try and write it themselves, which is possible – unlikely, but possible.

Where I think we will get the list for the other side is some of the other big organizations --- Oracle and IBM spring to mind in terms of being able to embrace both on-premises and off-premises.  But, at the end of the day, the commonality among those that we’ve mentioned is that they are systems companies. At the end of the day, they win by delivering the best overall solution and package to their clients, not individual components within it.

If you’re going to look for a successful hybrid IT deployment took, you probably have to look at a hybrid IT vendor.

And by individual components, I include cloud, on-premises, and applications. If you’re going to look for a successful hybrid IT deployment tool, you probably have to look at a hybrid IT vendor. That last part I think is self-descriptive. 

Gardner: Clearly, not a big group. We’re not going to be seeking suppliers for hybrid IT management from request for proposals (RFPs) from 50 or 60 different companies to find some solutions. 

Peters: Well, you won’t need to. Looking not that many years ahead, there will not be that many choices when it comes to full IT provisioning. 

Gardner: Mark, any thoughts about what IT organizations should be thinking about in terms of how to become proactive rather than reactive to the hybrid IT environment and the complexity, and to me the obvious need for better management going forward?

Management ends, not means

Peters: Gaining visibility into not just hybrid IT but the on-premise and the off-premise and how you manage these things. Those are all parts of the solution, or the answer. The real thing, and it’s absolutely crucial, is that you don’t start with those bright shiny objects. You don’t start with, “How can I deploy more cloud? How can I do hybrid IT?” Those are not good questions to ask. Good questions to ask are, “What do I need to do as an organization? How do I make my business more successful? How does anything in IT become a part of answering those questions?”

In other words, drum roll, it’s the thinking about ends, not means.

Gardner:  If our listeners and readers want to follow you and gain more of your excellent insight, how should they do that? 

Peters: The best way is to go to our website, www.esg-global.com. You can find not just me and all my contact details and materials but those of all my colleagues and the many areas we cover and study in this wonderful world of IT.

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Globalization risks and data complexity demand new breed of hybrid IT management, says Wikibon’s Burris

The next BriefingsDirect Voice of the Analyst interview explores how globalization and distributed business ecosystems factor into hybrid cloud challenges and solutions.

Mounting complexity and a lack of multi-cloud services management maturity are forcing companies to seek new breeds of solutions so they can grow and thrive as digital enterprises. 

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy.

Here to report on how international companies must factor localization, data sovereignty and other regional factors into any transition to sustainable hybrid IT is Peter Burris, Head of Research at Wikibon. The discussion is moderated by Dana Gardner, principal analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Peter, companies doing business or software development just in North America can have an American-centric view of things. They may lack an appreciation for the global aspects of cloud computing models. We want to explore that today. How much more complex is doing cloud -- especially hybrid cloud -- when you’re straddling global regions?

Burris: There are advantages and disadvantages to thinking cloud-first when you are thinking globalization first. The biggest advantage is that you are able to work in locations that don’t currently have the broad-based infrastructure that’s typically associated with a lot of traditional computing modes and models.

Burris

Burris

The downside of it is, at the end of the day, that the value in any computing system is not so much in the hardware per se; it’s in the data that’s the basis of how the system works. And because of the realities of working with data in a distributed way, globalization that is intended to more fully enfranchise data wherever it might be introduces a range of architectural implementation and legal complexities that can’t be discounted.

So, cloud and globalization can go together -- but it dramatically increases the need for smart and forward-thinking approaches to imagining, and then ultimately realizing, how those two go together, and what hybrid architecture is going to be required to make it work.

Gardner: If you need to then focus more on the data issues -- such as compliance, regulation, and data sovereignty -- how is that different from taking an applications-centric view of things?

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Burris: Most companies have historically taken an infrastructure-centric approach to things. They start by saying, “Where do I have infrastructure, where do I have servers and storage, do I have the capacity for this group of resources, and can I bring the applications up here?” And if the answer is yes, then you try to ultimately economize on those assets and build the application there.

That runs into problems when we start thinking about privacy, and in ensuring that local markets and local approaches to intellectual property management can be accommodated.

But the issue is more than just things like the General Data Protection Regulation (GDPR) in Europe, which is a series of regulations in the European Union (EU) that are intended to protect consumers from what the EU would regard as inappropriate leveraging and derivative use of their data.

It can be extremely expensive and sometimes impossible to even conceive of a global cloud strategy where the service is being consumed a few thousand miles away from where the data resides, if there is any dependency on time and how that works.

Ultimately, the globe is a big place. It’s 12,000 miles or so from point A to the farthest point B, and physics still matters. So, the first thing we have to worry about when we think about globalization is the cost of latency and the cost of bandwidth of moving data -- either small or very large -- across different regions. It can be extremely expensive and sometimes impossible to even conceive of a global cloud strategy where the service is being consumed a few thousand miles away from where the data resides, if there is any dependency on time and how that works.

So, the issues of privacy, the issues of local control of data are also very important, but the first and most important consideration for every business needs to be: Can I actually run the application where I want to, given the realities of latency? And number two: Can I run the application where I want to given the realities of bandwidth? This issue can completely overwhelm all other costs for data-rich, data-intensive applications over distance.

Gardner: As you are factoring your architecture, you need to take these local considerations into account, particularly when you are factoring costs. If you have to do some heavy lifting and make your bandwidth capable, it might be better to have a local closet-sized data center, because they are small and efficient these days, and you can stick with a private cloud or on-premises approach. At the least, you should factor the economic basis for comparison, with all these other variables you brought up.

Edge centers

Burris: That’s correct. In fact, we call them “edge centers.” For example, if the application features any familiarity with Internet of Things (IoT), then there will likely be some degree of latency considerations obtained, and the cost of doing a round trip message over a few thousand miles can be pretty significant when we consider the total cost of how fast computing can be done these days.

The first consideration is what are the impacts of latency for an application workload like IoT and is that intending to drive more automation into the system? Imagine, if you will, the businessperson who says, “I would like to enter into a new market expand my presence in the market in a cost-effective way. And to do that, I want to have the system be more fully automated as it serves that particular market or that particular group of customers. And perhaps it’s something that looks more process manufacturing-oriented or something along those lines that has IoT capabilities.”

The goal is to bring in the technology in a way that does not explode the administration, management, and labor cost associated with the implementation.

The goal, therefore, is to bring in the technology in a way that does not explode the administration, managements, and labor cost associated with the implementation.

The other way you are going to do that is if you do introduce a fair amount of automation and if, in fact, that automation is capable of operating within the time constraints required by those automated moments, as we call them.

If the round-trip cost of moving the data from a remote global location back to somewhere in North America -- independent of whether it’s legal or not – comes at a cost that exceeds the automation moment, then you just flat out can’t do it. Now, that is the most obvious and stringent consideration.

On top of that, these moments of automation necessitate significant amounts of data being generated and captured. We have done model studies where, for example, the cost of moving data out of a small wind farm can be 10 times as expensive. It can cost hundreds of thousands of dollars a year to do relatively simple and straightforward types of data analysis on the performance of that wind farm.

Process locally, act globally

It’s a lot better to have a local presence that can handle local processing requirements against models that are operating against locally derived data or locally generated data, and let that work be automated with only periodic visibility into how the overall system is working closely. And that’s where a lot of this kind of on-premise hybrid cloud thinking is starting.

It gets more complex than in a relatively simple environment like a wind farm, but nonetheless, the amount of processing power that’s necessary to run some of those kinds of models can get pretty significant. We are going to see a lot more of this kind of analytic work be pushed directly down to the devices themselves. So, the Sense, Infer, and Act loop will occur very, very closely in some of those devices. We will try to keep as much of that data as we can local.

But there are always going to be circumstances when we have to generate visibility across devices, we have to do local training of the data, we have to test the data or the models that we are developing locally, and all those things start to argue for sometimes much larger classes of systems.

Gardner: It’s a fascinating subject as to what to push down the edge given that the storage cost and processing costs are down and footprint is down and what to then use the public cloud environment or Infrastructure-as-a-Service (IaaS) environment for.

But before we go into any further, Peter, tell us about yourself, and your organization, Wikibon.

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Burris: Wikibon is a research firm that’s affiliated with something known as TheCUBE. TheCUBE conducts about 5,000 interviews per year with thought leaders at various locations, often on-site at large conferences.

I came to Wikibon from Forrester Research, and before that I had been a part of META Group, which was purchased by Gartner. I have a longstanding history in this business. I have also worked with IT organizations, and also worked inside technology marketing in a couple of different places. So, I have been around.

Wikibon's objective is to help mid-sized to large enterprises traverse the challenges of digital transformation. Our opinion is that digital transformation actually does mean something. It's not just a set of bromides about multichannel or omnichannel or being “uberized,” or anything along those lines.

The difference between a business and a digital business is the degree to which data is used as an asset. 

The difference between a business and a digital business is the degree to which data is used as an asset. In a digital business, data absolutely is used as a differentiating asset for creating and keeping customers.

We look at the challenges of what does it mean to use data differently, how to capture it differently, which is a lot of what IoT is about. We look at how to turn it into business value, which is a lot of what big data and these advanced analytics like artificial intelligence (AI), machine learning and deep learning are all about. And then finally, how to create the next generation of applications that actually act on behalf of the brand with a fair degree of autonomy, which is what we call “systems of agency” are all about. And then ultimately how cloud and historical infrastructure are going to come together and be optimized to support all those requirements.

We are looking at digital business transformation as a relatively holistic thing that includes IT leadership, business leadership, and, crucially, new classes of partnerships to ensure that the services that are required are appropriately contracted for and can be sustained as it becomes an increasing feature of any company’s value proposition. That's what we do.

Global risk and reward

Gardner: We have talked about the tension between public and private cloud in a global environment through speeds and feeds, and technology. I would like to elevate it to the issues of culture, politics and perception. Because in recent years, with offshoring and looking at intellectual property concerns in other countries, the fact is that all the major hyperscale cloud providers are US-based corporations. There is a wide ecosystem of other second tier providers, but certainly in the top tier.

Is that something that should concern people when it comes to risk to companies that are based outside of the US? What’s the level of risk when it comes to putting all your eggs in the basket of a company that's US-based?

Burris: There are two perspectives on that, but let me add one more just check on this. Alibaba clearly is one of the top-tier, and they are not based in the US and that may be one of the advantages that they have. So, I think we are starting to see some new hyperscalers emerge, and we will see whether or not one will emerge in Europe.

I had gotten into a significant argument with a group of people not too long ago on this, and I tend to think that the political environment almost guarantees that we will get some kind of scale in Europe for a major cloud provider.

If you are a US company, are you concerned about how intellectual property is treated elsewhere? Similarly, if you are a non-US company, are you concerned that the US companies are typically operating under US law, which increasingly is demanding that some of these hyperscale firms be relatively liberal, shall we say, in how they share their data with the government? This is going to be one of the key issues that influence choices of technology over the course of the next few years.

Cross-border compute concerns

We think there are three fundamental concerns that every firm is going to have to worry about.

I mentioned one, the physics of cloud computing. That includes latency and bandwidth. One computer science professor told me years ago, “Latency is the domain of God, and bandwidth is the domain of man.” We may see bandwidth costs come down over the next few years, but let's just lump those two things together because they are physical realities.

The second one, as we talked about, is the idea of privacy and the legal implications.

The third one is intellectual property control and concerns, and this is going to be an area that faces enormous change over the course of the next few years. It’s in conjunction with legal questions on contracting and business practices.

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From our perspective, a US firm that wants to operate in a location that features a more relaxed regime for intellectual property absolutely needs to be concerned. And the reason why they need to be concerned is data is unlike any other asset that businesses work with. Virtually every asset follows the laws of scarcity. 

Money, you can put it here or you can put it there. Time, people, you can put here or you can put there. That machine can be dedicated to this kind of wire or that kind of wire.

Data is weird, because data can be copied, data can be shared. The value of data appreciates as we us it more successfully, as we integrate it and share it across multiple applications.

Scarcity is a dominant feature of how we think about generating returns on assets. Data is weird, though, because data can be copied, data can be shared. Indeed, the value of data appreciates as we use it more successfully, as we use it more completely, as we integrate it and share it across multiple applications.

And that is where the concern is, because if I have data in one location, two things could possibly happen. One is if it gets copied and stolen, and there are a lot of implications to that. And two, if there are rules and regulations in place that restrict how I can combine that data with other sources of data. That means if, for example, my customer data in Germany may not appreciate, or may not be able to generate the same types of returns as my customer data in the US.

Now, that sets aside any moral question of whether or not Germany or the US has better privacy laws and protects the consumers better. But if you are basing investments on how you can use data in the US, and presuming a similar type of approach in most other places, you are absolutely right. On the one hand, you probably aren’t going to be able to generate the total value of your data because of restrictions on its use; and number two, you have to be very careful about concerns related to data leakage and the appropriation of your data by unintended third parties.

Gardner: There is the concern about the appropriation of the data by governments, including the United States with the PATRIOT Act. And there are ways in which governments can access hyperscalers’ infrastructure, assets, and data under certain circumstances. I suppose there’s a whole other topic there, but at least we should recognize that there's some added risk when it comes to governments and their access to this data.

Burris: It’s a double-edged sword that US companies may be worried about hyperscalers elsewhere, but companies that aren't necessarily located in the US may be concerned about using those hyperscalers because of the relationship between those hyperscalers and the US government.

These concerns have been suppressed in the grand regime of decision-making in a lot of businesses, but that doesn’t mean that it’s not a low-intensity concern that could bubble up, and perhaps, it’s one of the reasons why Alibaba is growing so fast right now.

All hyperscalers are going to have to be able to demonstrate that they can protect their clients, their customers’ data, utilizing the regime that is in place wherever the business is being operated.  

All hyperscalers are going to have to be able to demonstrate that they can, in fact, protect their clients, their customers’ data, utilizing the regime that is in place wherever the business is being operated. [The rationale] for basing your business in these types of services is really immature. We have made enormous progress, but there’s a long way yet to go here, and that’s something that businesses must factor as they make decisions about how they want to incorporate a cloud strategy.

Gardner: It’s difficult enough given the variables and complexity of deciding a hybrid cloud strategy when you’re only factoring the technical issues. But, of course, now there are legal issues around data sovereignty, privacy, and intellectual property concerns. It’s complex, and it’s something that an IT organization, on its own, cannot juggle. This is something that cuts across all the different parts of a global enterprise -- their legal, marketing, security, risk avoidance and governance units -- right up to the board of directors. It’s not just a willy-nilly decision to get out a credit card and start doing cloud computing on any sustainable basis.

Burris: Well, you’re right, and too frequently it is a willy-nilly decision where a developer or a business person says, “Oh, no sweat, I am just going to grab some resources and start building something in the cloud.”

I can remember back in the mid-1990s when I would go into large media companies to meet with IT people to talk about the web, and what it would mean technically to build applications on the web. I would encounter 30 people, and five of them would be in IT and 25 of them would be in legal. They were very concerned about what it meant to put intellectual property in a digital format up on the web, because of how it could be misappropriated or how it could lose value. So, that class of concern -- or that type of concern -- is minuscule relative to the broader questions of cloud computing, of the grabbing of your data and holding it a hostage, for example.

There are a lot of considerations that are not within the traditional purview of IT, but CIOs need to start thinking about them on their own and in conjunction with their peers within the business.

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Gardner: We’ve certainly underlined a lot of the challenges. What about solutions? What can organizations do to prevent going too far down an alley that’s dark and misunderstood, and therefore have a difficult time adjusting?

How do we better rationalize for cloud computing decisions? Do we need better management? Do we need better visibility into what our organizations are doing or not doing? How do we architect with foresight into the larger picture, the strategic situation? What do we need to start thinking about in terms of the solutions side of some of these issues?

Cloud to business, not business to cloud

Burris: That’s a huge question, Dana. I can go on for the next six hours, but let’s start here. The first thing we tell senior executives is, don’t think about bringing your business to the cloud -- think about bringing the cloud to your business. That’s the most important thing. A lot of companies start by saying, “Oh, I want to get rid of IT, I want to move my business to the cloud.”

It’s like many of the mistakes that were made in the 1990s regarding outsourcing. When I would go back and do research on outsourcing, I discovered that a lot of the outsourcing was not driven by business needs, but driven by executive compensation schemes, literally. So, where executives were told that they would be paid on the basis of return in net assets, there was a high likelihood that the business was going to go to outsourcers to get rid of the assets, so the executives could pay themselves an enormous amount of money.

Think about how to bring the cloud to your business, and to better manage your data assets, and don't automatically default to the notion that you're going to take your business to the cloud.

The same type of thinking pertains here -- the goal is not to get rid of IT assets since those assets, generally speaking, are becoming less important features of the overall proposition of digital businesses.

Think instead about how to bring the cloud to your business, and to better manage your data assets, and don’t automatically default to the notion that you’re going to take your business to the cloud.

Every decision-maker needs to ask himself or herself, “How can I get the cloud experience wherever the data demands?” The goal of the cloud experience, which is a very, very powerful concept, ultimately needs to be able to get access to a very rich set of services associated with automation. We need visible pricing and metering, self-sufficiency, and self-service. These are all the experiences that we want out of cloud.

What we want, however, are those experiences wherever the data requires it, and that’s what’s driving hybrid cloud. We call it “true private cloud,” and the idea is of having a technology stack that provides a consistent cloud experience wherever the data has to run -- whether that’s because of IoT or because of privacy issues or because of intellectual property concerns. True private cloud is our concept for describing how the cloud experience is going to be enacted where the data requires, so that you don’t just have to move the data to get to the cloud experience.

Weaving IT all together

The third thing to note here is that ultimately this is going to lead to the most complex integration regime we’ve ever envisioned for IT. By that I mean, we are going to have applications that span Software-as-a-Service (SaaS), public cloud, IaaS services, true private cloud, legacy applications, and many other types of services that we haven’t even conceived of right now.

And understanding how to weave all of those different data sources, and all those different service sources, into coherent application framework that runs reliably and providers a continuous ongoing service to the business is essential. It must involve a degree of distribution that completely breaks most models. We’re thinking about infrastructure, architecture, but also, data management, system management, security management, and as I said earlier, all the way out to even contractual management, and vendor management.

The arrangement of resources for the classes of applications that we are going to be building in the future are going to require deep, deep, deep thinking.

That leads to the fourth thing, and that is defining the metric we’re going to use increasingly from a cost standpoint. And it is time. As the costs of computing and bandwidth continue to drop -- and they will continue to drop -- it means ultimately that the fundamental cost determinant will be, How long does it take an application to complete? How long does it take this transaction to complete? And that’s not so much a throughput question, as it is a question of, “I have all these multiple sources that each on their own are contributing some degree of time to how this piece of work finishes, and can I do that piece of work in less time if I bring some of the work, for example, in-house, and run it close to the event?”

This relationship between increasing distribution of work, increasing distribution of data, and the role that time is going to play when we think about the event that we need to manage is going to become a significant architectural concern.

The fifth issue, that really places an enormous strain on IT is how we think about backing up and restoring data. Backup/restore has been an afterthought for most of the history of the computing industry.

As we start to build these more complex applications that have more complex data sources and more complex services -- and as these applications increasingly are the basis for the business and the end-value that we’re creating -- we are not thinking about backing up devices or infrastructure or even subsystems.

We are thinking about what does it mean to backup, even more importantly, applications and even businesses. The issue becomes associated more with restoring. How do we restore applications in business across this incredibly complex arrangement of services and data locations and sources?

There's a new data regime that's emerging to support application development. How's that going to work -- the role the data scientists and analytics are going to play in working with application developers?

I listed five areas that are going to be very important. We haven’t even talked about the new regime that’s emerging to support application development and how that’s going to work. The role the data scientists and analytics are going to play in working with application developers – again, we could go on and on and on. There is a wide array of considerations, but I think all of them are going to come back to the five that I mentioned.

Gardner: That’s an excellent overview. One of the common themes that I keep hearing from you, Peter, is that there is a great unknown about the degree of complexity, the degree of risk, and a lack of maturity. We really are venturing into unknown territory in creating applications that draw on these resources, assets and data from these different clouds and deployment models.

When you have that degree of unknowns, that lack of maturity, there is a huge opportunity for a party to come in to bring in new types of management with maturity and with visibility. Who are some of the players that might fill that role? One that I am familiar with, and I think I have seen them on theCUBE is Hewlett Packard Enterprise (HPE) with what they call Project New Hybrid IT Stack. We still don’t know too much about it. I have also talked about Cloud28+, which is an ecosystem of global cloud environments that helps mitigate some of the concerns about a single hyperscaler or a handful of hyperscale providers. What’s the opportunity for a business to come in to this problem set and start to solve it? What do you think from what you’ve heard so far about Project New Hybrid IT Stack at HPE?

Key cloud players

Burris: That’s a great question, and I’m going to answer it in three parts. Part number one is, if we look back historically at the emergence of TCP/IP, TCP/IP killed the mini-computers. A lot of people like to claim it was microprocessors, and there is an element of truth to that, but many computer companies had their own proprietary networks. When companies wanted to put those networks together to build more distributed applications, the mini-computer companies said, “Yeah, just bridge our network.” That was an unsatisfyingly bad answer for the users. So along came Cisco, TCP/IP, and they flattened out all those mini-computer networks, and in the process flattened the mini-computer companies.

HPE was one of the few survivors because they embraced TCP/IP much earlier than anybody else.

We are going to need the infrastructure itself to use deep learning, machine learning, and advanced technology for determining how the infrastructure is managed, optimized, and economized.

The second thing is that to build the next generations of more complex applications -- and especially applications that involve capabilities like deep learning or machine learning with increased automation -- we are going to need the infrastructure itself to use deep learning, machine learning, and advanced technology for determining how the infrastructure is managed, optimized, and economized. That is an absolute requirement. We are not going to make progress by adding new levels of complexity and building increasingly rich applications if we don’t take full advantage of the technologies that we want to use in the applications -- inside how we run our infrastructures and run our subsystems, and do all the things we need to do from a hybrid cloud standpoint.

Ultimately, the companies are going to step up and start to flatten out some of these cloud options that are emerging. We will need companies that have significant experience with infrastructure, that really understand the problem. They need a lot of experience with a lot of different environments, not just one operating system or one cloud platform. They will need a lot of experience with these advanced applications, and have both the brainpower and the inclination to appropriately invest in those capabilities so they can build the type of platforms that we are talking about. There are not a lot of companies out there that can.

There are few out there, and certainly HPE with its New Stack initiative is one of them, and we at Wikibon are especially excited about it. It’s new, it’s immature, but HPE has a lot of piece parts that will be required to make a go of this technology. It’s going to be one of the most exciting areas of invention over the next few years. We really look forward to working with our user clients to introduce some of these technologies and innovate with them. It’s crucial to solve the next generation of problems that the world faces; we can’t move forward without some of these new classes of hybrid technologies that weave together fabrics that are capable of running any number of different application forms.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy. Sponsor: Hewlett Packard Enterprise.

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As enterprises face hybrid IT complexity, new management solutions beckon

The next BriefingsDirect Voice of the Analyst interview examines how new machine learning and artificial intelligence (AI) capabilities are being applied to hybrid IT complexity challenges.

We'll explore how mounting complexity and a lack of multi-cloud services management maturity must be solved in order for businesses to grow and thrive as digital enterprises. 

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy. 

Here to report on how companies and IT leaders are seeking new means to manage an increasingly complex transition to sustainable hybrid IT is Paul Teich, Principal Analyst at TIRIAS Research in Austin, Texas. The discussion is moderated by Dana Gardner, principal analyst at Interarbor Solutions.


Here are some excerpts:

Gardner: Paul, there’s a lot of evidence that businesses are adopting cloud models at a rapid pace. There is also lingering concern about the complexity of managing so many fast-moving parts. We have legacy IT, private cloud, public cloud, software as a service (SaaS) and, of course, multi-cloud. So as someone who tracks technology and its consumption, how much has technology itself been tapped to manage this sprawl, if you will, across hybrid IT.

Teich

Teich

Teich: So far, not very much, mostly because of the early state of multi-cloud and the hybrid cloud business model. As you know, it takes a while for management technology to catch up with the actual compute technology and storage. So I think we are seeing that management is the tail of the dog, it’s getting wagged by the rest of it, and it just hasn’t caught up yet.

Gardner: Things have been moving so quickly with cloud computing that few organizations have had an opportunity to step back and examine what’s actually going on around them -- never mind properly react to it. We really are playing catch up.

Teich: As we look at the options available, the cloud giants -- the public cloud services -- don’t have much incentive to work together. So you are looking at a market where there will be third parties stepping in to help manage multi-cloud environments, and there’s a lag time between having those services available and having the cloud services available and then seeing the third-party management solution step in.

Gardner: It’s natural to see that a specific cloud environment, whether it’s purely public like AWS or a hybrid like Microsoft Azure and Azure Stack, want to help their customers, but they want to help their customers all get to their solutions first and foremost. It’s a natural thing. We have seen this before in technology.

There are not that many organizations willing to step into the neutral position of being ecumenical, of saying they want to help the customer first, manage it all from the first.

As we look to how this might unfold, it seems to me that the previous models of IT management -- agent-based, single-pane-of-glass, and unfortunately still in some cases spreadsheets and Post-It notes -- have been brought to bear on this. But we might be in a different ball game, Paul, with hybrid IT, that there’s just too many moving parts, too much complexity, and that we might need to look at data-driven approaches. What is your take on that?

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Teich: I think that’s exactly correct. One of the jokes in the industry right now is if you want to find your stranded instances in the cloud, cancel your credit card and AWS or Microsoft will be happy to notify you of all of the instances that you are no longer paying for because your credit card expired. It’s hard to keep track of this, because we don’t have adequate tools yet.

When you are an IT manager and you have a lot of folks on public cloud services, you don't have a full picture.

That single pane of glass, looking at a lot of data and information, is soon overloaded. When you are an IT manager, you are at a mid-sized or a large corporation, you have a lot of folks paying out-of-pocket right now, slapping a credit card down on public cloud services, so you don’t have a full picture. Where you do have a picture, there are so many moving parts.

I think we have to get past having a screen full of data, a screen full of information, and to a point where we have insight. And that is going to require a new generation of tools, probably borrowing from some of the machine learning evolution that’s happening now in pattern analytics.

Gardner: The timing in some respects couldn’t be better, right? Just as we are facing this massive problem of complexity of volume and velocity in managing IT across a hybrid environment, we have some of the most powerful and cost-effective means to deal with big data problems just like that.

Life in the infrastructure

Paul, before we go further let’s hear about you and your organization, and tell us, if you would, what a typical day is like in the life of Paul Teich?

Teich: At TIRIAS Research we are boutique industry analysts. By boutique we mean there are three of us -- three principal analysts; we have just added a few senior analysts. We are close to the metal. We live in the infrastructure. We are all former engineers and/or product managers. We are very familiar with deep technology.

My day tends to be first, a lot of reading. We look at a lot of chips, we look at a lot of service-level information, and our job is to, at a very fundamental level, take very complex products and technologies and surface them to business decision-makers, IT decision-makers, folks who are trying to run lines of business (LOB) and make a profit. So we do the heavy lifting on why new technology is important, disruptive, and transformative.

Gardner: Thanks. Let’s go back to this idea of data-driven and analytical values as applied to hybrid IT management and complexity. If we can apply AI and machine learning to solve business problems outside of IT -- in such verticals as retail, pharmaceutical, transportation -- with the same characteristics of data volume, velocity, and variety, why not apply that to IT? Is this a case of the cobbler’s kids having no shoes? You would think that IT would be among the first to do this.

Dig deep, gain insight

Teich: The cloud giants have already implemented systems like this because of necessity. So they have been at the front-end of that big data mantra of volume, velocity -- and all of that.

To successfully train for the new pattern recognition analytics, especially the deep learning stuff, you need a lot of data. You can’t actually train a system usefully without presenting it with a lot of use cases.

The public clouds have this data. They are operating social media services, large retail storefronts, and e-tail, for example. As the public clouds became available to enterprises, the IT management problem ballooned into a big data problem. I don’t think it was a big data problem five or 10 years ago, but it is now.

That’s a big transformation. We haven’t actually internalized what that means operationally when your internal IT department no longer runs all of your IT jobs anymore.

We are generating big data and that means we need big data tools to go analyze it and to get that relevant insight.

That’s the biggest sea change -- we are generating big data in the course of managing our IT infrastructure now, and that means we need big data tools to go analyze it, and to get that relevant insight. It’s too much data flowing by for humans to comprehend in real time.

Gardner: And, of course, we are also talking about islands of such operational data. You might have a lot of data in your legacy operations. You might have tier 1 apps that you are running on older infrastructure, and you are probably happy to do that. It might be very difficult to transition those specific apps into newer operating environments.

You also have multiple SaaS and cloud data repositories and logs. There’s also not only the data within those apps, but there’s the metadata as to how those apps are running in clusters and what they are doing as a whole. It seems to me that not only would you benefit from having a comprehensive data and analytics approach for your IT operations, but you might also have a workflow and process business benefit by being an uber analyst, by being on top of all of these islands of operational data. 

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To me, moving toward a comprehensive intelligence and data analysis capability for IT is the gift that keeps giving. You would then be able to also provide insight for an uber approach to processes across your entire organization -- across the supply chains, across partner networks, and back to your customers. Paul, do you also see that there’s an ancillary business benefit to having that data analysis capability, and not ceding it to your cloud providers?

Manage data, improve workflow

Teich: I do. At one end of the spectrum it’s simply what do you need to do to keep the lights on, where is your data, all of it, in the various islands and collections and the data you are sharing with your supply chain as well. Where is the processing that you can apply to that data? Increasingly, I think, we are looking at a world in which the location of the stored data is more important than the processing power.

The management of all the data you have needs to segue into visible workflows.

We have processing power pretty much everywhere now. What’s key is moving data from place to place and setting up the connections to acquire it. It means that the management of all the data you have needs to segue into visible workflows.

Once I know what I have, and I am managing it at a baseline effectively, then I can start to improve my processes. Then I can start to get better workflows, internally as well as across my supply chain. But I think at first it’s simply, “What do I have going on right now?”

As an IT manager, how can I rein in some of these credit card instances, credit card storage on the public clouds, and put that all into the right mix. I have to know what I know first -- then I can start to streamline. Then I can start to control my costs. Does that make sense?

Gardner: Yes, absolutely. And how can you know which people you want to give even more credit to on their credit cards – and let them do more of what they are doing? It might be very innovative, and it might be very cost-effective. There might also be those wasting money, spinning their wheels, repaving cow paths, over and over again.

If you don’t have the ability to make those decisions with insight, without the visibility, and then further analyze it as to how best to go about it – it seems to me a no-brainer.

It also comes at an auspicious time as IT is trying to re-factor its value to the organization. If in fact they are no longer running servers and networks and keeping the trains running on time, they have to start being more in the business of defining what trains should be running and then how to make them the best business engines, if you will.

If IT departments needs to rethink their role and step up their game, then they need to use technologies like advanced hybrid IT management from vendors with a neutral perspective. Then they become the overseers of operations at a fundamentally different level. 

Data revelation, not revolution

Teich: I think that’s right. It’s evolutionary stuff. I don’t think it’s revolutionary. I think that in the same way you add servers to a virtual machine farm, as your demand increases, as your baseline demand increases, IT needs to keep a handle on costs -- so you can understand which jobs are running where and how much more capacity you need.

One of the things they are missing with random access to the cloud is bulk purchasing. And so at a very fundamental level, helping your organization manage which clouds you are spending on by aggregating the purchase of storage, aggregating the purchase of compute instances to get just better buying power, doing price arbitrage when you can. To me, those are fundamental qualities of IT going forward in a multi-cloud environment.

They are extensions of where we are today; it just doesn’t seem like it yet. They have always added new servers to increasing internal capacity and this is just the next evolutionary step.

Gardner: It certainly makes sense that you would move as maturity occurs in any business function toward that orchestration, automation and optimization – rather than simply getting the parts in place. What you are describing is that IT is becoming more like a procurement function and less like a building, architecture, or construction function, which is just as powerful.

Not many people can make those hybrid IT procurement decisions without knowing a lot about the technology. Someone with just business acumen can’t walk in and make these decisions. I think this is an opportunity for IT to elevate itself and become even more essential to the businesses.

Teich: The opportunity is a lot like the Sabre airline scheduling system that nearly every airline uses now. That’s a fundamental capability for doing business, and it’s separate from the technology of Sabre. It’s the ability to schedule -- people and airplanes – and it’s a lot like scheduling storage and jobs on compute instances. So I think there will be this step.

But to go back to the technology versus procurement, I think some element of that has always existed in IT in terms of dealing with vendors and doing the volume purchases on one side, but also having some architect know how to compose the hardware and the software infrastructure to serve those applications.

Connect the clouds

We’re simply translating that now into a multi-cloud architecture. How do I connect those pieces? What network capacity do I need to buy? What kind of storage architectures do I need? I don’t think that all goes away. It becomes far more important as you look at, for example, AWS as a very large bag of services. It’s very powerful. You can assemble it in any way you want, but in some respect, that’s like programming in C. You have all the power of assembly language and all the danger of assembly language, because you can walk up in the memory and delete stuff, and so, you have to have architects who know how to build a service that’s robust, that won’t go down, that serves your application most efficiently and all of those things are still hard to do.

So, architecture and purchasing are both still necessary. They don’t go away. I think the important part is that the orchestration part now becomes as important as deploying a service on the side of infrastructure because you’ve got multiple sets of infrastructure.

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Gardner: For hybrid IT, it really has to be an enlightened procurement, not just blind procurement. And the people in the trenches that are just buying these services -- whether the developers or operations folks -- they don’t have that oversight, that view of the big picture to make those larger decisions about optimization of purchasing and business processes.

That gets us back to some of our earlier points of, what are the tools, what are the management insights that these individuals need in order to make those decisions? Like with Sabre, where they are optimizing to fill every hotel room or every airplane seat, we’re going to want in hybrid IT to fill every socket, right? We’re going to want all that bare metal and all those virtualization instances to be fully optimized -- whether it’s your cloud or somebody else’s.

It seems to me that there is an algorithmic approach eventually, right? Somebody is going to need to be the keeper of that algorithm as to how this all operates -- but you can’t program that algorithm if you don’t have the uber insights into what’s going on, and what works and what doesn’t.

What’s the next step, Paul, in terms of the technology catching up to the management requirements in this new hybrid IT complex environment?

Teich: People can develop some of that experience on a small scale, but there are so many dimensions to managing a multi-cloud, hybrid IT infrastructure business model. It’s throwing off all of this metadata for performance and efficiency. It’s ripe for machine learning.

We're moving so fast right now that if you are an organization of any size, machine learning has to come into play to help you get better economies of scale.

In a strong sense, we’re moving so fast right now that if you are an organization of any size, machine learning has to come into play to help you get better economies of scale. It’s just going to be looking at a bigger picture, it’s going to be managing more variables, and learning across a lot more data points than a human can possibly comprehend.

We are at this really interesting point in the industry where we are getting deep-learning approaches that are coming online cost effectively; they can help us do that. They have a little while to go before they are fully mature. But IT organizations that learn to take advantage of these systems now are going to have a head start, and they are going to be more efficient than their competitors.

Gardner: At the end of the day, if you’re all using similar cloud services then that differentiation between your company and your competitor is in how well you utilize and optimize those services. If the baseline technologies are becoming commoditized, then optimization -- that algorithm-like approach to smartly moving workloads and data, and providing consumption models that are efficiency-driven -- that’s going to be the difference between a 1 percent margin and a 5 percent margin over time.

The deep-learning difference

Teich: The important part to remember is that these machine-training algorithms are somewhat new, so there are several challenges with deploying them. First is the transparency issue. We don’t quite yet know how a deep-learning model makes specific decisions. We can’t point to one aspect and say that aspect is managing the quality of our AWS services, for example. It’s a black box model.

We can’t yet verify the results of these models. We know they are being efficient and fast but we can’t verify that the model is as efficient as it could possibly be. There is room for improvement over the next few years. As the models get better, they’ll leave less money on the table.

We’re also validating that when you build a machine-learning model that it’s covering all the situations you want it to cover. You need an audit trail for specific sets of decisions, especially with data that is subject to regulatory constraints. You need to know why you made decisions.

So the net is, once you are training a machine-learning model, you have to keep retraining it over time. Your model is not going to do the same thing as your competitor's model. There is a lot of room for differentiation, a lot of room for learning. You just have to go into it with your eyes open that, yeah, occasionally things will go sideways. Your model might do something unexpected, and you just have to be prepared for that. We’re still in the early days of machine learning.

Gardner: You raise an interesting point, Paul, because even as the baseline technology services in the multi-cloud era become commoditized, you’re going to have specific, unique, and custom approaches to your own business’ management.

Your hybrid IT optimization is not going to be like that of any other company. I think getting that machine-learning capability attuned to your specific hybrid IT panoply of resources and assets is going to be a gift that keeps giving. Not only will you run your IT better, you will run your business better. You’ll be fleet and agile.

If some risk arises -- whether it’s a cyber security risk, a natural disaster risk, a business risk of unintended or unexpected changes in your supply chain or in your business environment -- you’re going to be in a better position to react. You’re going to have your eyes to the ground, you’re going to be well tuned to your specific global infrastructure, and you’ll be able to make good choices. So I am with you. I think machine learning is essential, and the sooner you get involved with it, the better.

Before we sign off, who are the vendors and some of the technologies that we will look to in order to fill this apparent vacuum on advanced hybrid IT management? It seems to me that traditional IT management vendors would be a likely place to start.

Who’s in?

Teich: They are a likely place to start. All of them are starting to say something about being in a multi-cloud environment, about being in a multi-cloud-vendor environment. They are already finding themselves there with virtualization, and the key is they have recognized that they are in a multi-vendor world.

There are some start-ups, and I can’t name them specifically right now. But a lot of folks are working on this problem of how do I manage hybrid IT: In-house IT, and multi-cloud orchestration, a lot of work going on there. We haven’t seen a lot of it publicly yet, but there is a lot of venture capital being placed.

I think this is the next step, just like PCs came in the office, smartphones came in the office as we move from server farms to the clouds, going from cloud to multi-cloud, it’s attracting a lot of attention. The hard part right now is nailing whom to place your faith in. The name brands that people are buying their internal IT from right now are probably good near-term bets. As the industry gets more mature, we’ll have to see what happens.

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Gardner: We did hear a vision described on this from Hewlett Packard Enterprise (HPE) back in June at their Discover event in Las Vegas. I’m expecting to hear quite a bit more on something they’ve been calling New Hybrid IT Stack that seems to possess some of the characteristics we’ve been describing, such as broad visibility and management.

So at least one of the long-term IT management vendors is looking in this direction. That’s a place I’m going to be focusing on, wondering what the competitive landscape is going to be, and if HPE is going to be in the leadership position on hybrid IT management.

Teich: Actually, I think HPE is the only company I’ve heard from so far talking at that level. Everybody is voicing some opinion about it, but from what I’ve heard, it does sound like a very interesting approach to the problem.

Microsoft actually constrained their view on Azure Stack to a very small set of problems, and is actively saying, “No, I don’t.” If you’re looking at doing virtual machine migration and taking advantage of multi-cloud for general-purpose solutions, it’s probably not something that you want to do yet. It was very interesting for me then to hear about the HPE Project New Hybrid IT Stack and what HPE is planning to do there.

Gardner: For Microsoft, the more automated and constrained they can make it, the more likely you’d be susceptible or tempted to want to just stay within an Azure and/or Azure Stack environment. So I can appreciate why they would do that.

Before we sign off, one other area I’m going to be keeping my eyes on is around orchestration of containers, Kubernetes, in particular. If you follow orchestration of containers and container usage in multi-cloud environments, that’s going to be a harbinger of how the larger hybrid IT management demands are going to go as well. So a canary in the coal mine, if you will, as to where things could get very interesting very quickly.

The place to be

Teich: Absolutely. And I point out that the Linux Foundation’s CloudNativeCon in early December 2017 looks like the place to be -- with nearly everyone in the server infrastructure community and cloud infrastructure communities signing on. Part of the interest is in basically interchangeable container services. We’ll see that become much more important. So that sleepy little technical show is going to be invaded by “suits,” this year, and we’re paying a lot of attention to it.

Gardner: Yes, I agree. I’m afraid we’ll have to leave it there. Paul, how can our listeners and readers best follow you to gain more of your excellent insights?

Teich: You can follow us at www.tiriasresearch.com, and also we have a page on Forbes Tech, and you can find us there.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy. Sponsor: Hewlett Packard Enterprise.

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Inside story on HPC’s AI role in Bridges 'strategic reasoning' research at CMU

The next BriefingsDirect high performance computing (HPC) success interview examines how strategic reasoning is becoming more common and capable -- even using imperfect information.

We’ll now learn how Carnegie Mellon University and a team of researchers there are producing amazing results with strategic reasoning thanks in part to powerful new memory-intense systems architectures.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript ordownload a copy. 

To learn more about strategic reasoning advances, please join me in welcoming Tuomas Sandholm, Professor and Director of the Electronic Marketplaces Lab at Carnegie Mellon University in Pittsburgh. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Tell us about strategic reasoning and why imperfect information is often the reality that these systems face?

Sandholm: In strategic reasoning we take the word “strategic” very seriously. It means game theoretic, so in multi-agent settings where you have more than one player, you can't just optimize as if you were the only actor -- because the other players are going to act strategically. What you do affects how they should play, and what they do affects how you should play.

Sandholm

Sandholm

That's what game theory is about. In artificial intelligence (AI), there has been a long history of strategic reasoning. Most AI reasoning -- not all of it, but most of it until about 12 years ago -- was really about perfect information games like Othello, Checkers, Chess and Go.

And there has been tremendous progress. But these complete information, or perfect information, games don't really model real business situations very well. Most business situations are of imperfect information.

Know what you don’t know

So you don't know the other guy's resources, their goals and so on. You then need totally different algorithms for solving these games, or game-theoretic solutions that define what rational play is, or opponent exploitation techniques where you try to find out the opponent's mistakes and learn to exploit them.

So totally different techniques are needed, and this has way more applications in reality than perfect information games have.

Gardner: In business, you don't always know the rules. All the variables are dynamic, and we don't know the rationale or the reasoning behind competitors’ actions. People sometimes are playing offense, defense, or a little of both.

Before we dig in to how is this being applied in business circumstances, explain your proof of concept involving poker. Is it Five-Card Draw?

Heads-Up No-Limit Texas Hold'em has become the leading benchmark in the AI community.

Sandholm: No, we’re working on a much harder poker game called Heads-Up No-Limit Texas Hold'em as the benchmark. This has become the leading benchmark in the AI community for testing these application-independent algorithms for reasoning under imperfect information.

The algorithms have really nothing to do with poker, but we needed a common benchmark, much like the IC chip makers have their benchmarks. We compare progress year-to-year and compare progress across the different research groups around the world. Heads-Up No-limit Texas Hold'em turned out to be great benchmark because it is a huge game of imperfect information.

It has 10 to the 161 different situations that a player can face. That is one followed by 161 zeros. And if you think about that, it’s not only more than the number of atoms in the universe, but even if, for every atom in the universe, you have a whole other universe and count all those atoms in those universes -- it will still be more than that.

Gardner: This is as close to infinity as you can probably get, right?

Sandholm: Ha-ha, basically yes.

Gardner: Okay, so you have this massively complex potential data set. How do you winnow that down, and how rapidly does the algorithmic process and platform learn? I imagine that being reactive, creating a pattern that creates better learning is an important part of it. So tell me about the learning part.

Three part harmony

Sandholm: The learning part always interests people, but it's not really the only part here -- or not even the main part. We basically have three main modules in our architecture. One computes approximations of Nash equilibrium strategies using only the rules of the game as input. In other words, game-theoretic strategies.

That doesn’t take any data as input, just the rules of the game. The second part is during play, refining that strategy. We call that subgame solving.

Then the third part is the learning part, or the self-improvement part. And there, traditionally people have done what’s called opponent modeling and opponent exploitation, where you try to model the opponent or opponents and adjust your strategies so as to take advantage of their weaknesses.

However, when we go against these absolute best human strategies, the best human players in the world, I felt that they don't have that many holes to exploit and they are experts at counter-exploiting. When you start to exploit opponents, you typically open yourself up for exploitation, and we didn't want to take that risk. In the learning part, the third part, we took a totally different approach than traditionally is taken in AI.

We are letting the opponents tell us where the holes are in our strategy. Then, in the background, using supercomputing, we are fixing those holes.

We said, “Okay, we are going to play according to our approximate game-theoretic strategies. However, if we see that the opponents have been able to find some mistakes in our strategy, then we will actually fill those mistakes and compute an even closer approximation to game-theoretic play in those spots.”

One way to think about that is that we are letting the opponents tell us where the holes are in our strategy. Then, in the background, using supercomputing, we are fixing those holes.

All three of these modules run on the Bridges supercomputer at the Pittsburgh Supercomputing Center (PSC), for which the hardware was built by Hewlett Packard Enterprise (HPE).

HPC from HPE

Overcomes Barriers

To Supercomputing and Deep Learning

Gardner: Is this being used in any business settings? It certainly seems like there's potential there for a lot of use cases. Business competition and circumstances seem to have an affinity for what you're describing in the poker use case. Where are you taking this next?

Sandholm: So far this, to my knowledge, has not been used in business. One of the reasons is that we have just reached the superhuman level in January 2017. And, of course, if you think about your strategic reasoning problems, many of them are very important, and you don't want to delegate them to AI just to save time or something like that.

Now that the AI is better at strategic reasoning than humans, that completely shifts things. I believe that in the next few years it will be a necessity to have what I call strategic augmentation. So you can't have just people doing business strategy, negotiation, strategic pricing, and product portfolio optimization.

You are going to have to have better strategic reasoning to support you, and so it becomes a kind of competition. So if your competitors have it, or even if they don't, you better have it because it’s a competitive advantage.

Gardner: So a lot of what we're seeing in AI and machine learning is to find the things that the machines do better and allow the humans to do what they can do even better than machines. Now that you have this new capability with strategic reasoning, where does that demarcation come in a business setting? Where do you think that humans will be still paramount, and where will the machines be a very powerful tool for them?

Human modeling, AI solving

Sandholm: At least in the foreseeable future, I see the demarcation as being modeling versus solving. I think that humans will continue to play a very important role in modeling their strategic situations, just to know everything that is pertinent and deciding what’s not pertinent in the model, and so forth. Then the AI is best at solving the model.

That's the demarcation, at least for the foreseeable future. In the very long run, maybe the AI itself actually can start to do the modeling part as well as it builds a better understanding of the world -- but that is far in the future.

Gardner: Looking back as to what is enabling this, clearly the software and the algorithms and finding the right benchmark, in this case the poker game are essential. But with that large of a data set potential -- probabilities set like you mentioned -- the underlying computersystems must need to keep up. Where are you in terms of the threshold that holds you back? Is this a price issue that holds you back? Is it a performance limit, the amount of time required? What are the limits, the governors to continuing?

Sandholm: It's all of the above, and we are very fortunate that we had access to Bridges; otherwise this wouldn’t have been possible at all.  We spent more than a year and needed about 25 million core hours of computing and 2.6 petabytes of data storage.

This amount is necessary to conduct serious absolute superhuman research in this field -- but it is something very hard for a professor to obtain. We were very fortunate to have that computing at our disposal.

Gardner: Let's examine the commercialization potential of this. You're not only a professor at Carnegie Mellon, you’re a founder and CEO of a few companies. Tell us about your companies and how the research is leading to business benefits.

Superhuman business strategies

Sandholm: Let’s start with Strategic Machine, a brand-new start-up company, all of two months old. It’s already profitable, and we are applying the strategic reasoning technology, which again is application independent, along with the Libratus technology, the Lengpudashi technology, and a host of other technologies that we have exclusively licensed to Strategic Machine. We are doing research and development at Strategic Machine as well, and we are taking these to any application that wants us.

HPC from HPE

Overcomes Barriers 

To Supercomputing and Deep Learning

Such applications include business strategy optimization, automated negotiation, and strategic pricing. Typically when people do pricing optimization algorithmically, they assume that either their company is a monopolist or the competitors’ prices are fixed, but obviously neither is typically true.

We are looking at how do you price strategically where you are taking into account the opponent’s strategic response in advance. So you price into the future, instead of just pricing reactively. The same can be done for product portfolio optimization along with pricing.

Let's say you're a car manufacturer and you decide what product portfolio you will offer and at what prices. Well, what you should do depends on what your competitors do and vice versa, but you don’t know that in advance. So again, it’s an imperfect-information game.

Gardner: And these are some of the most difficult problems that businesses face. They have huge billion-dollar investments that they need to line up behind for these types of decisions. Because of that pipeline, by the time they get to a dynamic environment where they can assess -- it's often too late. So having the best strategic reasoning as far in advance as possible is a huge benefit.

If you think about machine learning traditionally, it's about learning from the past. But strategic reasoning is all about figuring out what's going to happen in the future.

Sandholm: Exactly! If you think about machine learning traditionally, it's about learning from the past. But strategic reasoning is all about figuring out what's going to happen in the future. And you can marry these up, of course, where the machine learning gives the strategic reasoning technology prior beliefs, and other information to put into the model.

There are also other applications. For example, cyber security has several applications, such as zero-day vulnerabilities. You can run your custom algorithms and standard algorithms to find them, and what algorithms you should run depends on what the other opposing governments run -- so it is a game.

Similarly, once you find them, how do you play them? Do you report your vulnerabilities to Microsoft? Do you attack with them, or do you stockpile them? Again, your best strategy depends on what all the opponents do, and that's also a very strategic application.

And in upstairs blocks trading, in finance, it’s the same thing: A few players, very big, very strategic.

Gaming your own immune system

The most radical application is something that we are working on currently in the lab where we are doing medical treatment planning using these types of sequential planning techniques. We're actually testing how well one can steer a patient's T-cell population to fight cancers, autoimmune diseases, and infections better by not just using one short treatment plan -- but through sophisticated conditional treatment plans where the adversary is actually your own immune system.

Gardner: Or cancer is your opponent, and you need to beat it?

Sandholm: Yes, that’s right. There are actually two different ways to think about that, and they lead to different algorithms. We have looked at it where the actual disease is the opponent -- but here we are actually looking at how do you steer your own T-cell population.

Gardner: Going back to the technology, we've heard quite a bit from HPE about more memory-driven and edge-driven computing, where the analysis can happen closer to where the data is gathered. Are these advances of any use to you in better strategic reasoning algorithmic processing?

Algorithms at the edge

Sandholm: Yes, absolutely! We actually started running at the PSC on an earlier supercomputer, maybe 10 years ago, which was a shared-memory architecture. And then with Bridges, which is mostly a distributed system, we used distributed algorithms. As we go into the future with shared memory, we could get a lot of speedups.

We have both types of algorithms, so we know that we can run on both architectures. But obviously, the shared-memory, if it can fit our models and the dynamic state of the algorithms, is much faster.

Gardner: So the HPE Machine must be of interest to you: HPE’s advanced concept demonstration model, with a memory-driven architecture, photonics for internal communications, and so forth. Is that a technology you're keeping a keen eye on?

HPC from HPE

Overcomes Barriers 

To Supercomputing and Deep Learning

Sandholm: Yes. That would definitely be a desirable thing for us, but what we really focus on is the algorithms and the AI research. We have been very fortunate in that the PSC and HPE have been able to take care of the hardware side.

We really don’t get involved in the hardware side that much, and I'm looking at it from the outside. I'm trusting that they will continue to build the best hardware and maintain it in the best way -- so that we can focus on the AI research.

Gardner: Of course, you could help supplement the cost of the hardware by playing superhuman poker in places like Las Vegas, and perhaps doing quite well.

Sandholm: Actually here in the live game in Las Vegas they don't allow that type of computational support. On the Internet, AI has become a big problem on gaming sites, and it will become an increasing problem. We don't put our AI in there; it’s against their site rules. Also, I think it's unethical to pretend to be a human when you are not. The business opportunities, the monetary opportunities in the business applications, are much bigger than what you could hope to make in poker anyway.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript ordownload a copy. Sponsor: Hewlett Packard Enterprise.

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Philips teams with HPE on ecosystem approach to improve healthcare informatics-driven outcomes

The next BriefingsDirect healthcare transformation use-case discussion focuses on how an ecosystem approach to big data solutions brings about improved healthcare informatics-driven outcomes.

We'll now learn how a Philips Healthcare Informatics and Hewlett Packard Enterprise (HPE) partnership creates new solutions for the global healthcare market and provides better health outcomes for patients by managing data and intelligence better.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript ordownload a copy.

Joining us to explain how companies tackle the complexity of solutions delivery in healthcare by using advanced big data and analytics is Martijn Heemskerk, Healthcare Informatics Ecosystem Director for Philips, based in Eindhoven, the Netherlands. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.


Here are some excerpts:

Gardner: Why are partnerships so important in healthcare informatics? Is it because there are clinical considerations combined with big data technology? Why are these types of solutions particularly dependent upon an ecosystem approach?

Heemskerk: It’s exactly as you say, Dana. At Philips we are very strong at developing clinical solutions for our customers. But nowadays those solutions also require an IT infrastructure layer

Heemskerk

Heemskerk

underneath to solve the total equation. As such, we are looking for partners in the ecosystem because we at Philips recognize that we cannot do everything alone. We need partners in the ecosystem that can help address the total solution -- or the total value proposition -- for our customers.

Gardner: I'm sure it varies from region to region, but is there a cultural barrier in some regard to bringing cutting-edge IT in particular into healthcare organizations? Or have things progressed to where technology and healthcare converge?

Heemskerk: Of course, there are some countries that are more mature than others. Therefore the level of healthcare and the type of solutions that you offer to different countries may vary. But in principle, many of the challenges that hospitals everywhere are going through are similar.

Some of the not-so-mature markets are also trying to leapfrog so that they can deliver different solutions that are up to par with the mature markets.

Gardner: Because we are hearing a lot about big data and edge computing these days, we are seeing the need for analytics at a distributed architecture scale. Please explain how big data changes healthcare.

Big data value add

Heemskerk: What is very interesting for big data is what happens if you combine it with value-based care. It's a very interesting topic. For example, nowadays, a hospital is not reimbursed for every procedure that it does in the hospital – the value is based more on the total outcome of how a patient recovers.

This means that more analytics need to be gathered across different elements of the process chain before reimbursement will take place. In that sense, analytics become very important for hospitals on how to measure on how things are being done efficiently, and determining if the costs are okay.

Gardner: The same data that can used to be more efficient can also be used for better healthcare outcomes and understanding the path of the disease, or for the efficacy of procedures, and so on. A great deal can be gained when data is gathered and used properly.

Heemskerk: That is correct. And you see, indeed, that there is much more data nowadays, and you can utilize it for all kind of different things.

Learn About HPE

Digital Solutions

That Drive Healthcare and Life Sciences

Gardner: Please help us understand the relationship between your organization and HPE. Where does your part of the value begin and end, and how does HPE fill their role on the technology side?

Healthy hardware relationships 

Heemskerk: HPE has been a highly valued supplier of Philips for quite a long time. We use their technologies for all kinds of different clinical solutions. For example, all of the hardware that we use for our back-end solutions or for advanced visualization is sourced by HPE. I am focusing very much on the commercial side of the game, so to speak, where we are really looking at how can we jointly go to market.

As I said, customers are really looking for one-stop shopping, a complete value proposition, for the challenges that they are facing. That’s why we partner with HPE on a holistic level.

Gardner: Does that involve bringing HPE into certain accounts and vice versa, and then going in to provide larger solutions together?

Heemskerk: Yes, that is exactly the case, indeed. We recognized that we are not so much focusing on problems related to just the clinical implications, and we are not just focusing on the problems that HPE is facing -- the IT infrastructure and the connectivity side of the value chain. Instead, we are really looking at the problems that the C-suite-level healthcare executives are facing.

You can think about healthcare industry consolidation, for example, as a big topic. Many hospitals are now moving into a cluster or into a network and that creates all kinds of challenges, both on the clinical application layer, but also on the IT infrastructure. How do you harmonize all of this? How do you standardize all of your different applications? How do you make sure that hospitals are going to be connected? How do you align all of your processes so that there is a more optimized process flow within the hospitals?

By addressing these kinds of questions and jointly going to our customers with HPE, we can improve user experiences for the customers, we can create better services, we have optimized these solutions, and then we can deliver a lot of time savings for the hospitals as well.

Learn About HPE

Digital Solutions

That Drive Healthcare and Life Sciences

Gardner: We have certainly seen in other industries that if you try IT modernization without including the larger organization -- the people, the process, and the culture -- the results just aren’t as good. It is important to go at modernization and transformation, consolidation of data centers, for example, with that full range of inputs and getting full buy-in.

Who else makes up the ecosystem? It takes more than two players to make an ecosystem.

Heemskerk: Yes, that's very true, indeed. In this, system integrators also have a very important role. They can have an independent view on what would be the best solution to fit a specific hospital.

Of course, we think that the Philips healthcare solutions are quite often the best, jointly focused with the solutions from HPE, but from time to time you can be partnering with different vendors.

Besides that, we don't have all of the clinical applications. By partnering with other vendors in the ecosystem, sometimes you can enhance the solutions that we have to think about; such as 3D solutions and 3D printing solutions.

Gardner: When you do this all correctly, when you leverage and exploit an ecosystem approach, when you cover the bases of technology, finance, culture, and clinical considerations, how much of an impressive improvement can we typically see?

Saving time, money, and people

Heemskerk: We try to look at it customer by customer, but generically what we see is that there are really a lot of savings.

First of all, addressing standardization across the clinical application layer means that a customer doesn't have to spend a lot of money on training all of its hospital employees on different kinds of solutions. So that's already a big savings.

Secondly, by harmonizing and making better effective use of the clinical applications, you can drive the total cost of ownership down.

Thirdly, it means that on the clinical applications layer, there are a lot of efficiency benefits possible. For example, advanced analytics make it possible to reduce the time that clinicians or radiologists are spending on analyzing different kinds of elements, which also creates time savings.

Gardner: Looking more to the future, as technologies improve, as costs go down, as they typically do, as hybrid IT models are utilized and understood better -- where do you see things going next for the healthcare sector when it comes to utilizing technology, utilizing informatics, and improving their overall process and outcomes?

Learn About HPE

Digital Solutions

That Drive Healthcare and Life Sciences

Heemskerk: What for me would be very interesting is to see is if we can create some kind of a patient-centric data file for each patient. You see that consumers are increasingly engaged in their own health, with all the different devices like Fitbit, Jawbone, Apple Watch, etc. coming up. This is creating a massive amount of data. But there is much more data that you can put into such a patient-centric file, with the chronic diseases information now that people are being monitored much more, and much more often.

If you can have a chronological view of all of the different touch points that the patient has in the hospital, combined with the drugs that the patient is using etc., and you have that all in this patient-centric file -- it will be very interesting. And everything, of course, needs to be interconnected. Therefore, Internet of Things (IoT) technologies will become more important. And as the data is growing, you will have smarter algorithms that can also interpret that data – and so artificial intelligence (AI) will become much more important.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript ordownload a copy. Sponsor: Hewlett Packard Enterprise.

You may also be interested in:

·       How IoT capabilities open new doors for Miami Telecoms Platform Provider Identidad

·       DreamWorks Animation crafts its next era of dynamic IT infrastructure

·       How Enterprises Can Take the Ecosystem Path to Making the Most of Microsoft Azure Stack Apps

·       Hybrid Cloud ecosystem readies for impact from Microsoft Azure Stack

·       Converged IoT systems: Bringing the data center to the edge of everything

·       IDOL-powered appliance delivers better decisions via comprehensive business information searches

·        OCSL sets its sights on the Nirvana of hybrid IT—attaining the right mix of hybrid cloud for its clients

·       Fast acquisition of diverse unstructured data sources makes IDOL API tools a star at LogitBot

·       How lastminute.com uses machine learning to improve travel bookings user experience

·       HPE takes aim at customer needs for speed and agility in age of IoT, hybrid everything

How IoT and OT collaborate to usher in the data-driven factory of the future

The next BriefingsDirect Internet of Things (IoT) technology trends interview explores how innovation is impacting modern factories and supply chains.

We’ll now learn how a leading-edge manufacturer, Hirotec, in the global automotive industry, takes advantage of IoT and Operational Technology (OT) combined to deliver dependable, managed, and continuous operations.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy.

Here to help us to find the best factory of the future attributes is Justin Hester, Senior Researcher in the IoT Lab at Hirotec Corp. in Hiroshima, Japan. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: What's happening in the market with business and technology trends that’s driving this need for more modern factories and more responsive supply chains?

Hester: Our customers are demanding shorter lead times. There is a drive for even higher quality, especially in automotive manufacturing. We’re also seeing a much higher level of customization requests coming from our customers. So how can we create products that better match the unique needs of each customer?

As we look at how we can continue to compete in an ever-competitive environment, we are starting to see how the solutions from IoT can help us.

Gardner: What is it about IoT and Industrial IoT (IIoT) that allows you to do things that you could not have done before?

Hester: Within the manufacturing space, a lot of data has been there for years; for decades. Manufacturing has been very good at collecting data. The challenges we've had, though, is bringing in that data in real-time, because the amount of data is so large. How can we act on that data quicker, not on a day-by-day basis or week-by-week basis, but actually on a minute-by-minute basis, or a second-by-second basis? And how do we take that data and contextualize it?

Hester

Hester

It's one thing in a manufacturing environment to say, “Okay, this machine is having a challenge.” But it’s another thing if I can say, “This machine is having a challenge, and in the context of the factory, here's how it's affecting downstream processes, and here's what we can do to mitigate those downstream challenges that we’re going to have.” That’s where IoT starts bringing us a lot of value.

The analytics, the real-time contextualization of that data that we’ve already had in the manufacturing area, is very helpful.

Gardner: So moving from what may have been a gather, batch, analyze, report process -- we’re now taking more discrete analysis opportunities and injecting that into a wider context of efficiency and productivity. So this is a fairly big change. This is not incremental; this is a step-change advancement, right?

A huge step-change 

Hester: It’s a huge change for the market. It's a huge change for us at Hirotec. One of the things we like to talk about is what we jokingly call the Tuesday Morning Meeting. We talk about this idea that in the morning at a manufacturing facility, everyone gets together and talks about what happened yesterday, and what we can do today to make up for what happened yesterday.

Instead, now we’re making that huge step-change to say,  “Why don't we get the data to the right people with the right context and let them make a decision so they can affect what's going on, instead of waiting until tomorrow to react to what's going on?” It’s a huge step-change. We’re really looking at it as how can we take small steps right away to get to that larger goal.

In manufacturing areas, there's been a lot of delay, confusion, and hesitancy to move forward because everyone sees the value, but it's this huge change, this huge project. At Hirotec, we’re taking more of a scaled approach, and saying let's start small, let’s scale up, let’s learn along the way, let's bring value back to the organization -- and that's helped us move very quickly.

Gardner: We’d like to hear more about that success story but in the meantime, tell us about Hirotec for those who don't know of it. What role do you play in the automotive industry, and how are you succeeding in your markets?

Hester: Hirotec is a large, tier-1 automotive supplier. What that means is we supply parts and systems directly to the automotive original equipment manufacturers (OEMs), like Mazda, General Motors, FCA, Ford, and we specialize in door manufacturing, as well as exhaust system manufacturing. So every year we make about 8 million doors, 1.8 million exhaust systems, and we provide those systems mainly to Mazda and General Motors, but also we provide that expertise through tooling.

For example, if an automotive OEM would like Hirotec’s expertise in producing these parts, but they would like to produce them in-house, Hirotec has a tooling arm where we can provide that tooling for automotive manufacturing. It's an interesting strategy that allows us to take advantage of data both in our facilities, but then also work with our customers on the tooling side to provide those lessons learned and bring them value there as well.

Gardner: How big of a distribution are we talking about? How many factories, how many countries; what’s the scale here?

Hester: We are based in Hiroshima, Japan, but we’re actually in nine countries around the world, currently with 27 facilities. We have reached into all the major continents with automotive manufacturing: we’re in North America, we’re in Europe, we’re all throughout Asia, in China and India. We have a large global presence. Anywhere you find automotive manufacturing, we’re there supporting it.

Discover How the

IoT Advantage

Works in Multiple Industries

Gardner: With that massive scale, very small improvements can turn into very big benefits. Tell us why the opportunity in a manufacturing environment to eke out efficiency and productivity has such big payoffs.

Hester: So especially in manufacturing, what we find when we get to those large scales like you're alluding to is that a 1 percent or 2 percent improvement has huge financial benefits. And so the other thing is in manufacturing, especially automotive manufacturing, we tend to standardize our processes, and within Hirotec, we’ve done a great job of standardizing that world-class leadership in door manufacturing.

And so what we find is when we get improvements not only in IoT but anywhere in manufacturing, if we can get 1 percent or 2 percent, not only is that a huge financial benefit but because we standardized globally, we can move that to our other facilities very quickly, doubling down on that benefit.

Gardner: Well, clearly Hirotec sees this as something to really invest in, they’ve created the IoT Lab. Tell me a little bit about that and how that fits into this?

The IoT Lab works

Hester: The IoT Lab is a very exciting new group, it's part of our Advanced Engineering Center (AEC). The AEC is a group out of our global headquarters and this group is tasked with the five- to 10-year horizon. So they're able to work across all of our global organizations with tooling, with engineering, with production, with sales, and even our global operations groups. Our IoT group goes and finds solutions that can bring value anywhere in the organization through bringing in new technologies, new ideas, and new solutions.

And so we formed the IoT Lab to find how can we bring IoT-based solutions into the manufacturing space, into the tooling space, and how actually can those solutions not only help our manufacturing and tooling teams but also help our IT teams, our finance teams, and our sales teams.

Gardner: Let's dig back down a little bit into why IT, IoT and Operational Technology (OT) are into this step-change opportunity, looking for some significant benefits but being careful in how to institute that. What is required when you move to a more an IT-focused, a standard-platform approach -- across all the different systems -- that allows you to eke these great benefits?

Tell us about how IoT as a concept is working its way into the very edge of the factory floor.

Discover How the

IoT Advantage

Works in Multiple Industries

Hester: One of the things we’re seeing is that IT is beginning to meld, like you alluded to, with OT -- and there really isn't a distinction between OT and IT anymore. What we're finding is that we’re starting to get to these solution levels by working with partners such as PTC and Hewlett Packard Enterprise (HPE) to bring our IT group and our OT group all together within Hirotec and bring value to the organization.

What we find is there is no longer a need in OT that becomes a request for IT to support it, and also that IT has a need and so they go to OT for support. What we are finding is we have organizational needs, and we’re coming to the table together to make these changes. And that actually within itself is bringing even more value to the organization.

Instead of coming last-minute to the IT group and saying, “Hey, we need your support for all these different solutions, and we’ve already got everything set, and you are just here to put it in,” what we are seeing, is that they bring the expertise in, help us out upfront, and we’re finding better solutions because we are getting experts both from OT and IT together.

We are seeing this convergence of these two teams working on solutions to bring value. And they're really moving everything to the edge. So where everyone talks about cloud-based computing -- or maybe it’s in their data center -- where we are finding value is in bringing all of these solutions right out to the production line.

We are doing data collection right there, but we are also starting to do data analytics right at the production line level, where it can bring the best value in the fastest way.

Gardner: So it’s an auspicious time because just as you are seeking to do this, the providers of technology are creating micro data centers, and they are creating Edgeline converged systems, and they are looking at energy conservation so that they can do this in an affordable way -- and with storage models that can support this at a competitive price.

What is it about the way that IT is evolving and providing platforms and systems that has gotten you and The IoT Lab so excited?

Excitement at the edge  

Hester: With IoT and IT platforms, originally to do the analytics, we had to go up to the cloud -- that was the only place where the compute power existed. Solution providers now are bringing that level of intelligence down to the edge. We’re hearing some exciting things from HPE on memory-driven computing, and that's huge for us because as we start doing these very complex analytics at the edge, we need that power, that horsepower, to run different applications at the same time at the production line. And something like memory-driven solutions helps us accomplish that.

It's one thing to have higher-performance computing, but another thing to gain edge computing that's proper for the factory environment. In a manufacturing environment it's not conducive to a standard servers, a standard rack where it needs dust protection and heat protection -- that doesn't exist in a manufacturing environment.

The other thing we're beginning to see with edge computing, that HPE provides with Edgeline products, is that we have computers that have high power, high ability to perform the analytics and data collection capabilities -- but they're also proper for the environment.

I don't need to build out a special protection unit with special temperature control, humidity control – all of which drives up energy costs, which drives up total costs. Instead, we’re able to run edge computing in the environment as it should be on its own, protected from what comes in a manufacturing environment -- and that's huge for us.

Gardner: They are engineering these systems now with such ruggedized micro facilities in mind. It's quite impressive that the very best of what a data center can do, can now be brought to the very worst types of environments. I'm sure we'll see more of that, and I am sure we'll see it get even smaller and more powerful.

Do you have any examples of where you have already been able to take IoT in the confluence of OT and IT to a point where you can demonstrate entirely new types of benefits? I know this is still early in the game, but it helps to demonstrate what you can do in terms of efficiency, productivity, and analytics. What are you getting when you do this well?

IoT insights save time and money

Hester: Taking the stepped strategy that we have, we actually started at Hirotec very small with only eight machines in North America and we were just looking to see if the machines are on, are they running, and even from there, we saw a value because all of a sudden we were getting that real-time contextualized insight into the whole facility. We then quickly moved over to one of our production facilities in Japan, where we have a brand-new robotic inspection system, and this system uses vision sensors, laser sensors, force sensors -- and it's actually inspecting exhaust systems before they leave the facility.

We very quickly implemented an IoT solution in that area, and all we did was we said, “Hey, we just want to get insight into the data, so we want to be able to see all these data points. Over 400 data points are created every inspection. We want to be able to see this data, compared in historical ways -- so let’s bring context to that data, and we want to provide it in real-time.”

Discover How the

IoT Advantage

Works in Multiple Industries

What we found from just those two projects very quickly is that we're bringing value to the organization because now our teams can go in and say, “Okay, the system is doing its job, it's inspecting things before they leave our facility to make sure our customers always get a high-quality product.” But now, we’re able to dive in and find different trends that we weren't able to see before because all we were doing is saying, “Okay, this system leaves the facility or this system doesn't.”

And so already just from that application, we’ve been able to find ways that our engineers can even increase the throughput and the reliability of the system because now they have these historical trends. They were able to do a root-cause analysis on some improvements that would have taken months of investigation; it was completed in less than a week for us.

And so that's a huge value -- not only in that my project costs go down but now I am able to impact the organization quicker, and that's the big thing that Hirotec is seeing. It’s one thing to talk about the financial cost of a project, or I can say, “Okay, here is the financial impact,” but what we are seeing is that we’re moving quicker.

And so, we're having long-term financial benefits because we’re able to react to things much faster. In this case, we’re able to reduce months of investigation down to a week. That means that when I implement my solution quicker, I'm now bringing that impact to the organization even faster, which has long-term benefits. We are already seeing those benefits today.

Gardner: You’ll obviously be able to improve quality, you’ll be able to reduce the time to improving that quality, gain predictive analytics in your operations, but also it sounds like you are going to gain metadata insights that you can take back into design for the next iteration of not only the design for the parts but the design for the tooling as well and even the operations around that. So that intelligence at the edge can be something that is a full lifecycle process, it goes right back to the very initiation of both the design and the tooling.

Data-driven design, decisions 

Hester: Absolutely, and so, these solutions, they can't live in a silo. We're really starting to look at these ideas of what some people call the Digital Thread, the Digital Twin. We’re starting to understand what does that mean as you loop this data back to our engineering teams -- what kind of benefits can we see, how can we improve our processes, how can we drive out into the organization?

And one of the biggest things with IoT-based solutions is that they can't stay inside this box, where we talked about OT to IT, we are talking about manufacturing, engineering, these IoT solutions at their best, all they really do is bring these groups together and bring a whole organization together with more contextualized data to make better decisions faster.

And so, exactly to your point, as we are looping back, we’re able to start understanding the benefit we’re going to be seeing from bringing these teams together.

Gardner: One last point before we close out. It seems to me as well that at a macro level, this type of data insight and efficiency can be brought into the entire supply chain. As you're providing certain elements of an automobile, other suppliers are providing what they specialize in, too, and having that quality control and integration and reduced time-to-value or mean-time-to-resolution of the production issues, and so forth, can be applied at a macro level.

So how does the automotive supplier itself look at this when it can take into consideration all of its suppliers like Hirotec are doing?

Start small 

Hester: It's a very early phase, so a lot of the suppliers are starting to understand what this means for them. There is definitely a macro benefit that the industry is going to see in five to 10 years. Suppliers now need to start small. One of my favorite pictures is a picture of the ocean and a guy holding a lighter. It [boiling the ocean] is not going to happen. So we see these huge macro benefits of where we’re going, but we have to start out somewhere.

Discover How the

IoT Advantage

Works in Multiple Industries

A lot of suppliers, what we’re recommending to them, is to do the same thing we did, just start small with a couple of machines, start getting that data visualized, start pulling that data into the organization. Once you do that, you start benefiting from the data, and then start finding new use-cases.

As these suppliers all start doing their own small projects and working together, I think that's when we are going to start to see the macro benefits but in about five to 10 years out in the industry.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy. Sponsor: Hewlett Packard Enterprise.

You may also be interested in:

·       DreamWorks Animation crafts its next era of dynamic IT infrastructure

·       How Enterprises Can Take the Ecosystem Path to Making the Most of Microsoft Azure Stack Apps

·       Hybrid Cloud ecosystem readies for impact from Microsoft Azure Stack

·       Converged IoT systems: Bringing the data center to the edge of everything

·       IDOL-powered appliance delivers better decisions via comprehensive business information searches

·        OCSL sets its sights on the Nirvana of hybrid IT—attaining the right mix of hybrid cloud for its clients

·       Fast acquisition of diverse unstructured data sources makes IDOL API tools a star at LogitBot

·       How lastminute.com uses machine learning to improve travel bookings user experience

·       Veikkaus digitally transforms as it emerges as new combined Finnish national gaming company

 ·       HPE takes aim at customer needs for speed and agility in age of IoT, hybrid everything

DreamWorks Animation crafts its next era of dynamic IT infrastructure

The next BriefingsDirect Voice of the Customer thought leader interview examines how DreamWorks Animation is building a multipurpose, all-inclusive, and agile data center capability.

Learn here why a new era of responsive and dynamic IT infrastructure is demanded, and how one high-performance digital manufacturing leader aims to get there sooner rather than later. 

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy.

Here to describe how an entertainment industry innovator leads the charge for bleeding-edge IT-as-a-service capabilities is Jeff Wike, CTO of DreamWorks Animation in Glendale, California. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Tell us why the older way of doing IT infrastructure and hosting apps and data just doesn't cut it anymore. What has made that run out of gas?

Wike: You have to continue to improve things. We are in a world where technology is advancing at an unbelievable pace. The amount of data, the capability of the hardware, the intelligence of the infrastructure are coming. In order for any business to stay ahead of the curve -- to really drive value into the business – it has to continue to innovate.

Gardner: IT has become more pervasive in what we do. I have heard you all refer to yourselves as digital manufacturing. Are the demands of your industry also a factor in making it difficult for IT to keep up?

Wike: When I say we are a digital manufacturer, it’s because we are a place that manufacturers content, whether it's animated films or TV shows; that content is all made on the computer. An artist sits in front of a workstation or a monitor, and is basically building these digital assets that we put through simulations and rendering so in the end it comes together to produce a movie.

Wike

Wike

That's all about manufacturing, and we actually have a pipeline, but it's really like an assembly line. I was looking at a slide today about Henry Ford coming up with the first assembly line; it's exactly what we are doing, except instead of adding a car part, we are adding a character, we’re adding a hair to a character, we’re adding clothes, we’re adding an environment, and we’re putting things into that environment.

We are manufacturing that image, that story, in a linear way, but also in an iterative way. We are constantly adding more details as we embark on that process of three to four years to create one animated film.

Gardner: Well, it also seems that we are now taking that analogy of the manufacturing assembly line to a higher plane, because you want to have an assembly line that doesn't just make cars -- it can make cars and trains and submarines and helicopters, but you don't have to change the assembly line, you have to adjust and you have to utilize it properly.

So it seems to me that we are at perhaps a cusp in IT where the agility of the infrastructure and its responsiveness to your workloads and demands is better than ever.

Greater creativity, increased efficiency

Wike: That's true. If you think about this animation process or any digital manufacturing process, one issue that you have to account for is legacy workflows, legacy software, and legacy data formats -- all these things are inhibitors to innovation. There are a lot of tools. We actually write our own software, and we’re very involved in projects related to computer science at the studio.

We’ll ask ourselves, “How do you innovate? How can you change your environment to be able to move forward and innovate and still carry around some of those legacy systems?”

How HPE Synergy

Automates

Infrastructure Operations

And one of the things we’ve done over the past couple of years is start to re-architect all of our software tools in order to take advantage of massive multi-core processing to try to give artists interactivity into their creative process. It’s about iterations. How many things can I show a director, how quickly can I create the scene to get it approved so that I can hand it off to the next person, because there's two things that you get out of that.

One, you can explore more and you can add more creativity. Two, you can drive efficiency, because it's all about how much time, how many people are working on a particular project and how long does it take, all of which drives up the costs. So you now have these choices where you can add more creativity or -- because of the compute infrastructure -- you can drive efficiency into the operation.

So where does the infrastructure fit into that, because we talk about tools and the ability to make those tools quicker, faster, more real-time? We conducted a project where we tried to create a middleware layer between running applications and the hardware, so that we can start to do data abstraction. We can get more mobile as to where the data is, where the processing is, and what the systems underneath it all are. Until we could separate the applications through that layer, we weren’t really able to do anything down at the core.

Core flexibility, fast

Now that we have done that, we are attacking the core. When we look at our ability to replace that with new compute, and add the new templates with all the security in it -- we want that in our infrastructure. We want to be able to change how we are using that infrastructure -- examine usage patterns, the workflows -- and be able to optimize.

Before, if we wanted to do a new project, we’d say, “Well, we know that this project takes x amount of infrastructure. So if we want to add a project, we need 2x,” and that makes a lot of sense. So we would build to peak. If at some point in the last six months of a show, we are going to need 30,000 cores to be able to finish it in six months, we say, “Well, we better have 30,000 cores available, even though there might be times when we are only using 12,000 cores.” So we were buying to peak, and that’s wasteful.

What we wanted was to be able to take advantage of those valleys, if you will, as an opportunity -- the opportunity to do other types of projects. But because our infrastructure was so homogeneous, we really didn't have the ability to do a different type of project. We could create another movie if it was very much the same as a previous film from an infrastructure-usage standpoint.

By now having composable, or software-defined infrastructure, and being able to understand what the requirements are for those particular projects, we can recompose our infrastructure -- parts of it or all of it -- and we can vary that. We can horizontally scale and redefine it to get maximum use of our infrastructure -- and do it quickly.

Gardner: It sounds like you have an assembly line that’s very agile, able to do different things without ripping and replacing the whole thing. It also sounds like you gain infrastructure agility to allow your business leaders to make decisions such as bringing in new types of businesses. And in IT, you will be responsive, able to put in the apps, manage those peaks and troughs.

Does having that agility not only give you the ability to make more and better movies with higher utilization, but also gives perhaps more wings to your leaders to go and find the right business models for the future?

Wike: That’s absolutely true. We certainly don't want to ever have a reason to turn down some exciting project because our digital infrastructure can’t support it. I would feel really bad if that were the case.

In fact, that was the case at one time, way back when we produced Spirit: Stallion of the Cimarron. Because it was such a big movie from a consumer products standpoint, we were asked to make another movie for direct-to-video. But we couldn't do it; we just didn’t have the capacity, so we had to just say, “No.” We turned away a project because we weren’t capable of doing it. The time it would take us to spin up a project like that would have been six months.

The world is great for us today, because people want content -- they want to consume it on their phone, on their laptop, on the side of buildings and in theaters. People are looking for more content everywhere.

Yet projects for varied content platforms require different amounts of compute and infrastructure, so we want to be able to create content quickly and avoid building to peak, which is too expensive. We want to be able to be flexible with infrastructure in order to take advantage of those opportunities.

HPE Synergy

Automates

Infrastructure Operations

Gardner: How is the agility in your infrastructure helping you reach the right creative balance? I suppose it’s similar to what we did 30 years ago with simultaneous engineering, where we would design a physical product for manufacturing, knowing that if it didn't work on the factory floor, then what's the point of the design? Are we doing that with digital manufacturing now?

Artifact analytics improve usage, rendering

Wike: It’s interesting that you mention that. We always look at budgets, and budgets can be money budgets, it can be rendering budgets, it can be storage budgets, and networking -- I mean all of those things are commodities that are required to create a project.

Artists, managers, production managers, directors, and producers are all really good at managing those projects if they understand what the commodity is. Years ago we used to complain about disk space: “You guys are using too much disk space.” And our production department would say, “Well, give me a tool to help me manage my disk space, and then I can clean it up. Don’t just tell me it's too much.”

One of the initiatives that we have incorporated in recent years is in the area of data analytics. We re-architected our software and we decided we would re-instrument everything. So we started collecting artifacts about rendering and usage. Every night we ran every digital asset that had been created through our rendering, and we also collected analytics about it. We now collect 1.2 billion artifacts a night.

And we correlate that information to a specific asset, such as a character, basket, or chair -- whatever it is that I am rendering -- as well as where it’s located, which shot it’s in, which sequence it’s in, and which characters are connected to it. So, when an artist wants to render a particular shot, we know what digital resources are required to be able to do that.

One of the things that’s wasteful of digital resources is either having a job that doesn't fit the allocation that you assign to it, or not knowing when a job is complete. Some of these rendering jobs and simulations will take hours and hours -- it could take 10 hours to run.

At what point is it stuck? At what point do you kill that job and restart it because something got wedged and it was a dependency? And you don't really know, you are just watching it run. Do I pull the plug now? Is it two minutes away from finishing, or is it never going to finish?

Just the facts

Before, an artist would go in every night and conduct a test render. And they would say, “I think this is going to take this much memory, and I think it's going to take this long.” And then we would add a margin of error, because people are not great judges, as opposed to a computer. This is where we talk about going from feeling to facts.

So now we don't have artists do that anymore, because we are collecting all that information every night. We have machine learning that then goes in and determines requirements. Even though a certain shot has never been run before, it is very similar to another previous shot, and so we can predict what it is going to need to run.

Now, if a job is stuck, we can kill it with confidence. By doing that machine learning and taking the guesswork out of the allocation of resources, we were able to save 15 percent of our render time, which is huge.

I recently listened to a gentleman talk about what a difference of 1 percent improvement would be. So 15 percent is huge, that's 15 percent less money you have to spend. It's 15 percent faster time for a director to be able to see something. It's 15 percent more iterations. So that was really huge for us.

Gardner: It sounds like you are in the digital manufacturing equivalent of working smarter and not harder. With more intelligence, you can free up the art, because you have nailed the science when it comes to creating something.

Creative intelligence at the edge

Wike: It's interesting; we talk about intelligence at the edge and the Internet of Things (IoT), and that sort of thing. In my world, the edge is actually an artist. If we can take intelligence about their work, the computational requirements that they have, and if we can push that data -- that intelligence -- to an artist, then they are actually really, really good at managing their own work.

It's only a problem when they don't have any idea that six months from now it's going to cause a huge increase in memory usage or render time. When they don't know that, it's hard for them to be able to self-manage. But now we have artists who can access Tableau reports everyday and see exactly what the memory usage was or the compute usage of any of the assets they’ve created, and they can correct it immediately.

On Megamind, a film DreamWorks Animation released several years ago, it was prior to having the data analytics in place, and the studio encountered massive rendering spikes on certain shots. We really didn't understand why.

After the movie was complete, when we could go back and get printouts of logs to analyze, we determined that these peaks in rendering resources were caused by his watch. Whenever the main character’s watch was in a frame, the render times went up. We looked at the models, and well-intended artists had taken a model of a watch and every gear was modeled, and it was just a huge, heavy asset to render.

But it was too late to do anything about it. But now, if an artist were to create that watch today, they would quickly find out that they had really over-modeled that watch. We would then need to go in and reduce that asset down, because it's really not a key element to the story. And they can do that today, which is really great.

HPE Synergy

Automates

Infrastructure Operations

Gardner: I am a big fan of animated films, and I am so happy that my kids take me to see them because I enjoy them as much as they do. When you mention an artist at the edge, it seems to me it’s more like an army at the edge, because I wait through the end of the movie, and I look at the credits scroll -- hundreds and hundreds of people at work putting this together.

So you are dealing with not just one artist making a decision, you have an army of people. It's astounding that you can bring this level of data-driven efficiency to it.

Movie-making’s mobile workforce

Wike: It becomes so much more important, too, as we become a more mobile workforce. 

Now it becomes imperative to be able to obtain the information about what those artists are doing so that they can collaborate. We know what value we are really getting from that, and so much information is available now. If you capture it, you can find so many things that we can really understand better about our creative process to be able to drive efficiency and value into the entire business.

Gardner: Before we close out, maybe a look into the crystal ball. With things like auto-scaling and composable infrastructure, where do we go next with computing infrastructure? As you say, it's now all these great screens in people's hands, handling high-definition, all the networks are able to deliver that, clearly almost an unlimited opportunity to bring entertainment to people. What can you now do with the flexible, efficient, optimized infrastructure? What should we expect?

Wike: There's an explosion in content and explosion in delivery platforms. We are exploring all kinds of different mediums. I mean, there’s really no limit to where and how one can create great imagery. The ability to do that, the ability to not say “No” to any project that comes along is going to be a great asset.

We always say that we don't know in the future how audiences are going to consume our content. We just know that we want to be able to supply that content and ensure that it’s the highest quality that we can deliver to audiences worldwide.

Gardner: It sounds like you feel confident that the infrastructure you have in place is going to be able to accommodate whatever those demands are. The art and the economics are the variables, but the infrastructure is not.

Wike: Having a software-defined environment is essential. I came from the software side; I started as a programmer, so I am coming back into my element. I really believe that now that you can compose infrastructure, you can change things with software without having to have people go in and rewire or re-stack, but instead change on-demand. And with machine learning, we’re able to learn what those demands are.

I want the computers to actually optimize and compose themselves so that I can rest knowing that my infrastructure is changing, scaling, and flexing in order to meet the demands of whatever we throw at it.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy. Sponsor: Hewlett Packard Enterprise.

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How a Florida school district tames the wild west of education security at scale and on budget

Bringing a central IT focus to large public school systems has always been a challenge, but bringing a security focus to thousands of PCs and devices has been compared to bringing law and order to the Wild West.

For the Clay County School District in Florida, a team of IT administrators is grabbing the bull by the horns nonetheless to create a new culture of computing safety -- without breaking the bank.

The next BriefingsDirect security insight’s discussion examines how Clay County is building a secure posture for their edge, network, and data centers while allowing the right mix and access for exploration necessary in an educational environment. 

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy. 

To learn how to ensure that schools are technically advanced and secure at low cost and at high scale, we're joined by Jeremy Bunkley, Supervisor of the Clay County School District Information and Technology Services Department; Jon Skipper, Network Security Specialist at the Clay County School District, and Rich Perkins, Coordinator for Information Services at the Clay County School District. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: What are the biggest challenges to improving security, compliance, and risk reduction at a large school district?

Bunkley: I think the answer actually scales across the board. The problem even bridges into businesses. It’s the culture of change -- of making people recognize security as a forethought, instead of an afterthought. It has been a challenge in education, which can be a technology laggard.

Getting people to start the recognition process of making sure that they are security-aware has been quite the battle for us. I don’t think it’s going to end anytime soon. But we are starting to get our key players on board with understanding that you can't clear-text Social Security numbers and credit card numbers and personally identifiable information (PII). It has been an interesting ride for us, let’s put it that way.

Gardner: Jon, culture is such an important part of this, but you also have to have tools and platforms in place to help give reinforcement for people when they do the right thing. Tell us about what you have needed on your network, and what your technology approach has been?

Skipper: Education is one of those weird areas where the software development has always been lacking in the security side of the house. It has never even been inside the room. So one of the things that we have tried to do in education, at least with the Clay County School District, is try to modify that view, with doing change management. We are trying to introduce a security focus. We try to interject ourselves and highlight areas that might be a bad practice.

Skipper

Skipper

One of our vendors uses plain text for passwords, and so we went through with them and showed them how that’s a bad practice, and we made a little bit of improvement with that.

I evaluate our policies and how we manage the domains, maybe finding some stuff that came from a long time ago where it's no longer needed. We can pull the information out, whereas before they put all the Social Security numbers into a document that was no longer needed. We have been trying really hard to figure that stuff out and then to try and knock it down, as much as we can.

Access for all, but not all-access

Gardner: Whenever you are trying to change people's perceptions, behaviors, culture, it’s useful to have both the carrot and a stick approach.

So to you Rich, what's been working in terms of a carrot? How do you incentivize people? What works in practice there?

Perkins: That's a tough one. We don't really have a carrot that we use. We basically say, “If you are doing the wrong things, you are not going to be able to use our network.”  So we focus more on negatives.

Perkins

Perkins

The positives would be you get to do your job. You get to use the Internet. We don't really give them something more. We see security as directly intertwined with our customer service. Every person we have is our customer and our job is to protect them -- and sometimes that's from themselves.

So we don't really have a carrot-type of system. We don't allow students to play games if they have no problems. We give everybody the same access and treat everybody the same. Either you are a student and you get this level of access, or you are a staff member, you get this level of access, or you don't get access.

Gardner: Let’s get background on the Clay County School District. Tell us how many students you have, how many staff administrators, the size and scope of your school district?

Bunkley: Our school district is the 22nd largest in Florida, we are right on the edge of small and medium in Florida, which in most districts is a very large school district. We run about 38,500 students.

And as far as our IT team, which is our student information system, our Enterprise Resource Planning (ERP) system, security, down to desktop support, network infrastructure support, our web services, we have about 48 people total in our department.

Our scope is literally everything. For some reason IT means that if it plugs into a wall, we are responsible for it. That's generally a true statement in education across the board, where the IT staff tends to be a Jack-of-all-trades, and we fix everything.

Practical IT

Gardner: Where you are headed in terms of technology? Is there a one-to-one student-to-device ratio in the works? What sort of technology do you enable for them?

Bunkley: I am extremely passionate about this, because the one-to-one scenario seems to be the buzzword, and we generally despise buzzwords in this office and we prefer a more practical approach.

The idea of one-to-one is itself to me flawed, because if I just throw a device in a student's hand, what am I actually doing besides throwing a device in a student's hand? We haven't trained them. We haven’t given them the proper platform. All we have done is thrown technology.

And when I hear the terms, well, kids inherently know how to use technology today; it kind of just bothers me, because kids inherently know how to use social media, not technology. They are not production-driven, they are socially driven, and that is a sticking point with me.

We are in fact moving to a one-to-one, but in a nontraditional sense. We have established a one-to-one platform so we can introduce a unified platform for all students and employees to see through a portal system; we happen to use ClassLink, there are various other vendors out there, that’s just the one we happen to use.

We have integrated that in moving to Google Apps for Education and we have a very close relationship with Google. It’s pretty awesome, to be quite honest with you.

So we are moving in the direction of Chromebooks, because it’s just a fiscally more responsible move for us.

I know Microsoft is coming out with Windows 10 S, it’s kind of a strong move on their part. But for us, just because we have the expertise on the Google Apps for Education, or G Suite, it just made a lot of sense for us to go that direction.

So we are moving in one-to-one now with the devices, but the device is literally the least important -- and the last -- step in our project.

Non-stop security, no shenanigans

Gardner: Tell us about the requirements now for securing the current level of devices, and then for the new one. It seems like you are going to have to keep the airplane flying while changing the wings, right? So what is the security approach that works for you that allows for that?

Skipper: Clay County School District has always followed trends as far as devices go. So we actually have a good mixture of devices in our network, which means that no one solution is ever the right solution.

So, for example, we still have some iPads out in our networks, we still have some older Apple products, and then we have a mixture of Chromebooks and also Windows devices. We really need to make sure that we are running the right security platform for the full environment.

As we are transitioning more and more to a take-home philosophy -- and that’s where we as an IT department are seeing this going – so that if the decision is made to make the entire student population go home, we are going to be ready to go.

We have coordinated with our content filter company, and they have some extensions that we can deploy that lock the Chromebooks into a filter situation regardless of their network. That’s been really successful in identifying, maybe blocking students, from those late-night searches. We have also been able to identify some shenanigans that might be taking place due to some interesting web searches that they might do over YouTube, for example. That’s worked really well.

Our next objective is to figure out how to secure our Windows devices and possibly even the Mac devices. While our content filter does a good job as far as securing the content on the Internet, it’s a little bit more difficult to deploy into a Windows device, because users have the option of downloading different Internet browsers. So, content filtering doesn’t really work as well on those.

I have deployed Bitdefender to my laptops, and also to take-home Apple products. That allows me to put in more content filtering, and use that to block people from malicious websites that maybe the content filter didn’t see or was unable to see due to a different browser being used.

In those aspects we definitely are securing our network down further than it ever has been before.

Block and Lock

Perkins: With Bitdefender, one of the things we like is that if we have those devices go off network, we can actually have it turn on the Bitdefender Firewall that allows us to further lock down those machines or protect them if they are in an open environment, like at a hotel or whatever, from possible malicious activity.

And it allows us to block executables at some point. So we can actually go in and say, “No, I don’t want you to be able to run this browser, because I can’t do anything to protect you. Or I can’t watch what you do, or I can’t keep you from doing things you shouldn’t do.” So those are all very useful tools in a single pane of glass that we can see all of those devices at one time and monitor and manage. It saves us a lot of time.

Bunkley: I would follow up on that with a base concept, Dana, and our base concept is of an external network. We come from the concept of, we are an everywhere network. We are not only aiming to defend our internal network while you are here and maybe do some stuff while you are at our house, we are literally an externally built network, where our network will extend directly down into the student and teacher’s home.

We have gone as far as moving everything we physically can out of this network, right down to our firewall. We are moving our domain controllers, external to the network to create literally an everywhere network. And so our security focus is not just internal, it is focused on external first, then internal.

Gardner: With security products, what have you been using, what wasn't working, and where do you expect to go next given those constraints?

No free lunch

Perkins: Well, we can tell you that “free” is not always the best option; as a matter of fact, it’s almost never a good option, but we have had to deal with it.

We were previously using an antivirus called Avast, and it’s a great home product. We found out that it has not been the best business-level product. It’s very much marketed to education, and there are some really good things about it. Transferring away from it hasn’t been the easiest because it’s next to impossible to uninstall. So we have been having some problems with that.

We have also tested some other security measures and programs along the way that haven’t been so successful. And we are always in the process of evaluating where we are. We are never okay with status quo. Even if we achieve where we want to be, I don't think any of us will be satisfied, and that’s actually something that a lot of this is built on -- we always want to go that step further. And I know that’s cliché, but I would say for an institution of this size, the reason we are able to do some of the stuff is the staff that has been assembled here is second to none for an educational institution.

So even in the processes that we have identified, which were helter-skelter before we got here, we have some more issues to continue working out, but we won’t be satisfied with where we are even if we achieve the task.

Skipper: One of the things that our office actually hates is just checking the box on a security audit. I mean, we are very vocal to the auditors when they come in. We don’t do things just to satisfy their audit. We actually look at the audit and we look at the intent of the question and if we find merit in it, we are going to go and meet that expectation and then make it better. Audits are general. We are going to exceed and make it a better functioning process than just saying, “Yes, I have purchased an antivirus product,” or “I have purchased x.” To us that’s unacceptable.

Bunkley: Audits are a good thing, and nobody likes to do them because they are time-consuming. But you do them because they are required by law, for our institution anyways. So instead of just having a generic audit, where we ignore the audit, we have adopted the concept of the audit as a very useful thing for us to have as a self-reflection tool. It’s nice to not have the same set of eyes on your work all the time. And instead of taking offense to someone coming in and saying, “You are not doing this good enough,” we have literally changed our internal culture here, audits are not a bad thing; audits are a desired thing.

Gardner: Let’s go around the table and hear how you began your journey into IT and security, and how the transition to an educational environment went.

IT’s the curriculum

Bunkley: I started in the banking industry. Those hours were crazy and the pressure was pretty high. So as soon as I left that after a year, I entered education, and honestly, I entered education because I thought the schedule was really easy and I kind of copped out on that. Come to find out, I am working almost as many hours, but that’s because I have come to love it.

This is my 17th year in education, so I have been in a few districts now. Wholesale change is what I have been hired to do, that’s also what I was hired here to do in Clay. We want to change the culture, make IT part of the instruction instead of a separate segment of education.

We have to be interwoven into everything, otherwise we are going to be on an island, and the last time I heard the definition of education is to educate children. So IT can never by itself be a high-functioning department in education. So we have decided instead to go to instruction, and go to professional development, and go to administration and intervene ourselves.

Gardner: Jon, tell us about your background and how the transition has been for you.

Skipper: I was at active-duty Air Force until 2014 when I retired after 20 years. And then I came into education on the side. I didn’t really expect this job, wasn’t mentally searching for it. I tried it out, and that was three years ago.

It’s been an interesting environment. Education, and especially a small IT department like this one, is one of those interesting places where you can come and really expand on your weak areas. So that’s what I actually like about this. If I need to practice on my group policy knowledge, I can dive in there and I can affect that change. Overall this has been an effective change, totally different from the military, a lot looser as far as a lot of things go, but really interesting.

Gardner: Rick, same question to you, your background and how did the transition go?

Perkins: I spent 21 years in the military, I was Navy. When I retired in 2010, I actually went to work for a smaller district in education mainly because they were the first one to offer me a job. In that smaller district, just like here, we have eight people doing operations, and we have this big department. Jeremy understands from where he came from. It was pretty much me doing every aspect of it, so you do a little security, you do a little bit of everything, which I enjoyed because you are your own boss, but you are not your own boss.

You still have people residing over you and dictating how you are going to work, but I really enjoyed the challenge. Coming from IT security in the military and then coming into education, it’s almost a role reversal where we came in and found next to no policies.

I am used to a black-and-white world. So we are trying to interject some of that and some of the security best practices into education. You have to be flexible because education is not the military, so you can’t be that stringent. So that’s a challenge.

Gardner: What are you using to put policies in place enforce them? How does that work?

Policy plans

Perkins: From a [Microsoft] Active Directory side, we use group policy like most people do, and we try and automate it as much as we can. We are switching over, on the student side, very heavily to Google. They effectively have their own version of Active Directory with group policy. And then I will let Jon speak more to the security side though we have used various programs like PDQ for our patch management system that allows us to push out stuff. We use some logging systems with ManageEngine. And then as we have said before we use Bitdefender to push a lot of policy and security out as well, and we've been reevaluating some other stuff.

We also use SolarWinds to monitor our network and we actually manage changes to our network and switching using SolarWinds, but on the actual security side, I will let Jon get more specific for you.

Skipper: When we came in … there was a fear of having too much in policy equated to too much auditing overhead. One of the first things we did was identify what we can lock down, and the easiest one was the filter.

The content filter met such stipulations as making sure adult material is not acceptable on the network. We had that down. But it didn't really take into account the dynamic of the Internet as far as sites are popping up every minute or second, and how do you maintain that for unclassified and uncategorized sites?

So one of the things we did was we looked at a vendor, like, okay, does this vendor have a better product for that aspect of it, and we got that working, I think that's been working a lot better. And then we started moving down, we were like, okay, cool, so now we have content filtering down, luckily move on to active network, actually not about finding someone else who is doing it, and borrowing their work and making their own.

We look into some of the bigger school districts and see how they are doing it. I think Chicago, Los Angeles. We both looked at some of their policies where we can find it. I found a lot of higher education in some of the universities. Their policies are a lot more along the lines of where we want to be. I think they have it better than what some of the K-12s do.

So we have been going through there and we are going to have to rewrite policy – we are in an active rewrite of our policies right now, we are taking all of those in and we are looking at them, and we are trying to figure out which ones work in our environment and then make sure we do a really good search and replace.

Gardner: We have talked about people, process and technology. We have heard that you are on a security journey and that it’s long-term and culturally oriented.

Let's look at this then as to what you get when you do it right, particularly vis-à-vis education. Do you have any examples of where you have been able to put in the right technology, add some policy and process improvements, and then culturally attune the people? What does that get for you? How do you turn a problem student into a computer scientist at some point? Tell us some of the examples of when it works, what it gets you.

Positive results

Skipper: When we first got in here, we were a Microsoft district. We had some policies in place to help prevent data loss, and stuff like that.

One of the first things we did is review those policies and activate them, and we started getting some hits. We were surprised at some of hits that we saw, and what we saw going out. We already knew we were moving to the Google networks, continuing the process.

We researched a lot and one of the things we discovered is that just by a minor tweak in a user’s procedures, we were able to identify that we could introduce that user to and get them used to using email encryption, for example. With the Gmail solution, we are able to add an extension, and that extension actually looks at their email as it goes out and finds keywords -- or it may be PII -- and automatically encrypt the email, preventing those kinds of breaches from going out there. So that’s really been helpful.

As far as taking a student who may be on the wrong path and reeducating them and bringing them back into the fold, Bitdefender has actually helped out on that one.

We had a student a while back who went out to YouTube and find out how he could just do a simple search on how to crash the school network, and he found about five links. And he researched those links and went out there and found that this batch filed with this type will crash a school server.

He was able to implement it and started trying to get that attack out there, and Bitdefender was able to actually go out there and see the batch file, see what it did and prevent it. By quarantining the file, I was able to get that reported very quickly from the moment that he introduced the attack, and it identified the student and we were able to sit down with the administrators and talk to the student about that process and educate them on the dangers of actually attacking a school network and the possible repercussions of it.

Gardner: It certainly helps when you can let them know that you are able to track and identify those issues, and then trace them back to an individual. Any other anecdotes about where the technology process and people have come together for a positive result?

Applied IT knowledge for the next generation

Skipper: One of the things that’s really worked well for the school district is what we call Network Academy. It’s taught by one of our local retired master chiefs, and he is actually going in there and teaching students at the high school level how to go as far as earning a Cisco Certified Network Associate (CCNA)-level IT certificate.

If a student comes in and they try hard enough, they will actually figure it out and they can leave when they graduate with a CCNA, which is pretty awesome. A high school student can walk away with a pretty major industry certification.

We like to try and grab these kids as soon as they leave high school, or even before they leave high school, and start introducing them to our network. They may have a different viewpoint on how to do something that’s revolutionary to us.

But we like having that aspect of it, we can educate those kids who are coming in and  getting their industry certifications, and we are able to utilize them before they move on to a college or another job that pays more than we do.

Bunkley: Charlie Thompson leads this program that Jon is speaking of, and actually over half of our team has been through the program. We didn’t create it, we have just taken advantage of the opportunity. We even tailor the classes to some of the specific things that we need. We have effectively created our own IT hiring pipeline out of this program.

Gardner: Next let’s take a look to the future. Where do you see things going, such as more use of cloud services, interest in unified consoles and controls from the cloud as APIs come into play more for your overall IT management? Encryption? Where do you take it from here?

Holistic solutions in the cloud

Bunkley: Those are some of the areas we are focusing on heavily as we move that “anywhere network.” The unified platform for management is going to be a big deal to us. It is a big deal to us already. Encryption is something we take very seriously because we have a team of eight protecting the data of  about 42,000 users..

If you consider the perfect cyber crime reaching down into a 7th or an 8th grader and stealing all of their personal information, taking that kid’s identity and using it, that kid won’t even know that their identity has been stolen.

We consider that a very serious charge of ours to take on. So we will continue to improve our protection of the students’ and teachers’ PII -- even if it sometimes means protecting them from themselves. We take it very seriously.

As we move to the cloud, that unified management platform leads to a more unified security platform. As the operating systems continue to mature, they seem to be going different ways. And what’s good for Mac is not always good for Chrome, is not always good for Windows. But as we move forward with our projects we bring everything back to that central point -- can the three be operated from the single point of connection, so that we can save money moving forward? Just because it’s a cool technology and we want to do, it doesn't mean it's the right thing for us.

Sometimes we have to choose an option that we don’t necessarily like as much, but pick it because it is better for the whole. As we continue to move forward, everything will be focused on that centralization. We can remain a small and flexible department to continue making sure that we are able to provide the services needed internally as well as protect our users.

Skipper: I think Jeremy hit it pretty solid on that one. As we integrate more with the cloud services, Google, etc., we are utilizing those APIs and we are leading our vendors that we use and forcing them into new areas. Lightspeed, for instance, is integrating more-and-more with Google and utilizing their API to ensure that content filtering -- even to the point of mobile device management (MDM) that is more integrated into the Google and Apple platforms to make sure that students are well protected and we have all the tools available that they need at any given time.

We are really leaning heavily on more cloud services, and also the interoperability between APIs and vendors.

Perkins: Public education is changing more to the realm of college education where the classroom is not a classroom -- a classroom is anywhere in the world. We are tasked with supporting them and protecting them no matter where they are located. We have to take care of our customers either way.

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How Imagine Communications leverages edge computing and HPC for live multiscreen IP video

The next BriefingsDirect Voice of the Customer HPC and edge computing strategies interview explores how a video delivery and customization capability has moved to the network edge -- and closer to consumers -- to support live, multi-screen Internet Protocol (IP) entertainment delivery. 

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy.

We’ll learn how hybrid technology and new workflows for IP-delivered digital video are being re-architected -- with significant benefits to the end-user experience, as well as with new monetization values to the content providers.

Our guest is Glodina Connan-Lostanlen, Chief Marketing Officer at Imagine Communications in Frisco, Texas. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Your organization has many major media clients. What are the pressures they are facing as they look to the new world of multi-screen video and media?

Connan-Lostanlen: The number-one concern of the media and entertainment industry is the fragmentation of their audience. We live with a model supported by advertising and subscriptions that rely primarily on linear programming, with people watching TV at home.

Connan-Lostanlen

Connan-Lostanlen

And guess what? Now they are watching it on the go -- on their telephones, on their iPads, on their laptops, anywhere. So they have to find the way to capture that audience, justify the value of that audience to their advertisers, and deliver video content that is relevant to them. And that means meeting consumer demand for several types of content, delivered at the very time that people want to consume it.  So it brings a whole range of technology and business challenges that our media and entertainment customers have to overcome. But addressing these challenges with new technology that increases agility and velocity to market also creates opportunities.

For example, they can now try new content. That means they can try new programs, new channels, and they don’t have to keep them forever if they don’t work. The new models create opportunities to be more creative, to focus on what they are good at, which is creating valuable content. At the same time, they have to make sure that they cater to all these different audiences that are either static or on the go.

Gardner: The media industry has faced so much change over the past 20 years, but this is a major, perhaps once-in-a-generation, level of change -- when you go to fully digital, IP-delivered content.

As you say, the audience is pulling the providers to multi-screen support, but there is also the capability now -- with the new technology on the back-end -- to have much more of a relationship with the customer, a one-to-one relationship and even customization, rather than one-to-many. Tell us about the drivers on the personalization level.

Connan-Lostanlen: That’s another big upside of the fragmentation, and the advent of IP technology -- all the way from content creation to making a program and distributing it. It gives the content creators access to the unique viewers, and the ability to really engage with them -- knowing what they like -- and then to potentially target advertising to them. The technology is there. The challenge remains about how to justify the business model, how to value the targeted advertising; there are different opinions on this, and there is also the unknown or the willingness of several generations of viewers to accept good advertising.

That is a great topic right now, and very relevant when we talk about linear advertising and dynamic ad insertion (DAI). Now we are able to -- at the very edge of the signal distribution, the video signal distribution -- insert an ad that is relevant to each viewer, because you know their preferences, you know who they are, and you know what they are watching, and so you can determine that an ad is going to be relevant to them.

But that means media and entertainment customers have to revisit the whole infrastructure. It’s not necessary rebuilding, they can put in add-ons. They don’t have to throw away what they had, but they can maintain the legacy infrastructure and add on top of it the IP-enabled infrastructure to let them take advantage of these capabilities.

Gardner: This change has happened from the web now all the way to multi-screen. With the web there was a model where you would use a content delivery network (CDN) to take the object, the media object, and place it as close to the edge as you could. What’s changed and why doesn’t that model work as well?

Connan-Lostanlen: I don’t know yet if I want to say that model doesn’t work anymore. Let’s let the CDN providers enhance their technology. But for sure, the volume of videos that we are consuming everyday is exponentially growing. That definitely creates pressure in the pipe. Our role at the front-end and the back-end is to make sure that videos are being created in different formats, with different ads, and everything else, in the most effective way so that it doesn’t put an undue strain on the pipe that is distributing the videos.

We are being pushed to innovate further on the type of workflows that we are implementing at our customers’ sites today, to make it efficient, to not leave storage at the edge and not centrally, and to do transcoding just-in-time. These are the things that are being worked on. It’s a balance between available capacity and the number of programs that you want to send across to your viewers – and how big your target market is.

The task for us on the back-end is to rethink the workflows in a much more efficient way. So, for example, this is what we call the digital-first approach, or unified distribution. Instead of planning a linear channel that goes the traditional way and then adding another infrastructure for multi-screen, on all those different platforms and then cable, and satellite, and IPTV, etc. -- why not design the whole workflow digital-first. This frees the content distributor or provider to hold off on committing to specific platforms until the video has reached the edge. And it’s there that the end-user requirements determine how they get the signal.

This is where we are going -- to see the efficiencies happen and so remove the pressure on the CDNs and other distribution mechanisms, like over-the-air.

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Gardner: It means an intelligent edge capability, whereas we had an intelligent core up until now. We’ll also seek a hybrid capability between them, growing more sophisticated over time.

We have a whole new generation of technology for video delivery. Tell us about Imagine Communications. How do you go to market? How do you help your customers?

Education for future generations

Connan-Lostanlen: Two months ago we were in Las Vegas for our biggest tradeshow of the year, the NAB Show. At the event, our customers first wanted to understand what it takes to move to IP -- so the “how.” They understand the need to move to IP, to take advantage of the benefits that it brings. But how do they do this, while they are still navigating the traditional world?

It’s not only the “how,” it’s needing examples of best practices. So we instructed them in a panel discussion, for example, on Over the Top Technology (OTT), which is another way of saying IP-delivered, and what it takes to create a successful multi-screen service. Part of the panel explained what OTT is, so there’s a lot of education.

There is also another level of education that we have to provide, which is moving from the traditional world of serial digital interfaces (SDIs) in the broadcast industry to IP. It’s basically saying analog video signals can be moved into digital. Then not only is there a digitally sharp signal, it’s an IP stream. The whole knowledge about how to handle IP is new to our own industry, to our own engineers, to our own customers. We also have to educate on what it takes to do this properly.

One of the key things in the media and entertainment industry is that there’s a little bit of fear about IP, because no one really believed that IP could handle live signals. And you know how important live television is in this industry – real-time sports and news -- this is where the money comes from. That’s why the most expensive ads are run during the Super Bowl.

It’s essential to be able to do live with IP – it’s critical. That’s why we are sharing with our customers the real-life implementations that we are doing today.

We are also pushing multiple standards forward. We work with our competitors on these standards. We have set up a trade association to accelerate the standards work. We did all of that. And as we do this, it forces us to innovate in partnership with customers and bring them on board. They are part of that trade association, they are part of the proof-of-concept trials, and they are gladly sharing their experiences with others so that the transition can be accelerated.

Gardner: Imagine Communications is then a technology and solutions provider to the media content companies, and you provide the means to do this. You are also doing a lot with ad insertion, billing, in understanding more about the end-user and allowing that data flow from the edge back to the core, and then back to the edge to happen.

At the heart of it all

Connan-Lostanlen: We do everything that happens behind the camera -- from content creation all the way to making a program and distributing it. And also, to your point, on monetizing all that with a management system. We have a long history of powering all the key customers in the world for their advertising system. It’s basically an automated system that allows the selling of advertising spots, and then to bill them -- and this is the engine of where our customers make money. So we are at the heart of this.

We are in the prime position to help them take advantage of the new advertising solutions that exist today, including dynamic ad insertion. In other words, how you target ads to the single viewer. And the challenge for them is now that they have a campaign, how do they design it to cater both to the linear traditional advertising system as well as the multi-screen or web mobile application? That's what we are working on. We have a whole set of next-generation platforms that allow them to take advantage of both in a more effective manner.

Gardner: The technology is there, you are a solutions provider. You need to find the best ways of storing and crunching data, close to the edge, and optimizing networks. Tell us why you choose certain partners and what are the some of the major concerns you have when you go to the technology marketplace?

Connan-Lostanlen: One fundamental driver here, as we drive the transition to IP in this industry, is in being able to rely on consumer-off-the-shelf (COTS) platforms. But even so, not all COTS platforms are born equal, right?

For compute, for storage, for networking, you need to rely on top-scale hardware platforms, and that’s why about two years ago we started to work very closely with Hewlett Packard Enterprise (HPE) for both our compute and storage technology.

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We develop the software appliances that run on those platforms, and we sell this as a package with HPE. It’s been a key value proposition of ours as we began this journey to move to IP. We can say, by the way, our solutions run on HPE hardware. That's very important because having high-performance compute (HPC) that scales is critical to the broadcast and media industry. Having storage that is highly reliable is fundamental because going off the air is not acceptable. So it's 99.9999 percent reliable, and that’s what we want, right?

It’s a fundamental part of our message to our customers to say, “In your network, put Imagine solutions, which are powered by one of the top compute and storage technologies.”

Gardner: Another part of the change in the marketplace is this move to the edge. It’s auspicious that just as you need to have more storage and compute efficiency at the edge of the network, close to the consumer, the infrastructure providers are also designing new hardware and solutions to do just that. That's also for the Internet of Things (IoT) requirements, and there are other drivers. Nonetheless, it's an industry standard approach.

What is it about HPE Edgeline, for example, and the architecture that HPE is using, that makes that edge more powerful for your requirements? How do you view this architectural shift from core data center to the edge?

Optimize the global edge

Connan-Lostanlen: It's a big deal because we are going to be in a hybrid world. Most of our customers, when they hear about cloud, we have to explain it to them. We explain that they can have their private cloud where they can run virtualized applications on-premises, or they can take advantage of public clouds.

Being able to have a hybrid model of deployment for their applications is critical, especially for large customers who have operations in several places around the globe. For example, such big names as Disney, Turner –- they have operations everywhere. For them, being able to optimize at the edge means that you have to create an architecture that is geographically distributed -- but is highly efficient where they have those operations. This type of technology helps us deliver more value to the key customers.

Gardner: The other part of that intelligent edge technology is that it has the ability to be adaptive and customized. Each region has its own networks, its own regulation, and its own compliance, security, and privacy issues. When you can be programmatic as to how you design your edge infrastructure, then a custom-applications-orientation becomes possible.

Is there something about the edge architecture that you would like to see more of? Where do you see this going in terms of the capabilities of customization added-on to your services?

Connan-Lostanlen: One of the typical use-cases that we see for those big customers who have distributed operations is that they like to try and run their disaster recovery (DR) site in a more cost-effective manner. So the flexibility that an edge architecture provides to them is that they don’t have to rely on central operations running DR for everybody. They can do it on their own, and they can do it cost-effectively. They don't have to recreate the entire infrastructure, and so they do DR at the edge as well.

We especially see this a lot in the process of putting the pieces of the program together, what we call “play out,” before it's distributed. When you create a TV channel, if you will, it’s important to have end-to-end redundancy -- and DR is a key driver for this type of application.

Gardner: Are there some examples of your cutting-edge clients that have adopted these solutions? What are the outcomes? What are they able to do with it?

Pop-up power

Connan-Lostanlen: Well, it’s always sensitive to name those big brand names. They are very protective of their brands. However, one of the top ones in the world of media and entertainment has decided to move all of their operations -- from content creation, planning, and distribution -- to their own cloud, to their own data center.

They are at the forefront of playing live and recorded material on TV -- all from their cloud. They needed strong partners in data centers. So obviously we work with them closely, and the reason why they do this is simply to really take advantage of the flexibility. They don't want to be tied to a restricted channel count; they want to try new things. They want to try pop-up channels. For the Oscars, for example, it’s one night. Are you going to recreate the whole infrastructure if you can just check it on and off, if you will, out of their data center capacity? So that's the key application, the pop-up channels and ability to easily try new programs.

Gardner: It sounds like they are thinking of themselves as an IT company, rather than a media and entertainment company that consumes IT. Is that shift happening?

Connan-Lostanlen: Oh yes, that's an interesting topic, because I think you cannot really do this successfully if you don’t start to think IT a little bit. What we are seeing, interestingly, is that our customers typically used to have the IT department on one side, the broadcast engineers on the other side -- these were two groups that didn't speak the same language. Now they get together, and they have to, because they have to design together the solution that will make them more successful. We are seeing this happening.

I wouldn't say yet that they are IT companies. The core strength is content, that is their brand, that's what they are good at -- creating amazing content and making it available to as many people as possible.

They have to understand IT, but they can't lose concentration on their core business. I think the IT providers still have a very strong play there. It's always happening that way.

In addition to disaster recovery being a key application, multi-screen delivery is taking advantage of that technology, for sure.

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Gardner: These companies are making this cultural shift to being much more technically oriented. They think about standard processes across all of what they do, and they have their own core data center that's dynamic, flexible, agile and cost-efficient. What does that get for them? Is it too soon, or do we have some metrics of success for companies that make this move toward a full digitally transformed organization?

Connan-Lostanlen: They are very protective about the math. It is fair to say that the up-front investments may be higher, but when you do the math over time, you do the total cost of ownership for the next 5 to 10 years -- because that’s typically the life cycle of those infrastructures – then definitely they do save money. On the operational expenditure (OPEX) side [of private cloud economics] it’s much more efficient, but they also have upside on additional revenue. So net-net, the return on investment (ROI) is much better. But it’s kind of hard to say now because we are still in the early days, but it’s bound to be a much greater ROI.

Another specific DR example is in the Middle East. We have a customer there who decided to operate the DR and IP in the cloud, instead of having a replicated system with satellite links in between. They were able to save $2 million worth of satellite links, and that data center investment, trust me, was not that high. So it shows that the ROI is there.

My satellite customers might say, “Well, what are you trying to do?” The good news is that they are looking at us to help them transform their businesses, too. So big satellite providers are thinking broadly about how this world of IP is changing their game. They are examining what they need to do differently. I think it’s going to create even more opportunities to reduce costs for all of our customers.

IT enters a hybrid world

Gardner: That's one of the intrinsic values of a hybrid IT approach -- you can use many different ways to do something, and then optimize which of those methods works best, and also alternate between them for best economics. That’s a very powerful concept.

Connan-Lostanlen: The world will be a hybrid IT world, and we will take advantage of that. But, of course, that will come with some challenges. What I think is next is the number-one question that I get asked.

Three years ago costumers would ask us, “Hey, IP is not going to work for live TV.” We convinced them otherwise, and now they know it’s working, it’s happening for real.

Secondly, they are thinking, “Okay, now I get it, so how do I do this?” We showed them, this is how you do it, the education piece.

Now, this year, the number-one question is security. “Okay, this is my content, the most valuable asset I have in my company. I am not putting this in the cloud,” they say. And this is where another piece of education has to start, which is: Actually, as you put stuff on your cloud, it’s more secure.

And we are working with our technology providers. As I said earlier, the COTS providers are not equal. We take it seriously. The cyber attacks on content and media is critical, and it’s bound to happen more often.

Initially there was a lack of understanding that you need to separate your corporate network, such as emails and VPNs, from you broadcast operations network. Okay, that’s easy to explain and that can be implemented, and that's where most of the attacks over the last five years have happened. This is solved.

They are going to get right into the servers, into the storage, and try to mess with it over there. So I think it’s super important to be able to say, “Not only at the software level, but at the hardware firmware level, we are adding protection against your number-one issue, security, which everybody can see is so important.”

However, the cyber attackers are becoming more clever, so they will overcome these initial defenses.They are going to get right into the servers, into the storage, and try to mess with it over there. So I think it’s super important to be able to say, “Not only at the software level, but at the hardware firmware level, we are adding protection against your number-one issue, security, which everybody can see is so important.”

Gardner: Sure, the next domino to fall after you have the data center concept, the implementation, the execution, even the optimization, is then to remove risk, whether it's disaster recovery, security, right down to the silicon and so forth. So that’s the next thing we will look for, and I hope I can get a chance to talk to you about how you are all lowering risk for your clients the next time we speak.

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How The Open Group Healthcare Forum and Health Enterprise Reference Architecture cures process and IT ills

The next BriefingsDirect healthcare thought leadership panel discussion examines how a global standards body, The Open Group, is working to improve how the healthcare industry functions.

We’ll now learn how The Open Group Healthcare Forum (HCF) is advancing best practices and methods for better leveraging IT in healthcare ecosystems. And we’ll examine the forum’s Health Enterprise Reference Architecture (HERA) initiative and its role in standardizing IT architectures. The goal is to foster better boundaryless interoperability within and between healthcare public and private sector organizations.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy.

To learn more about improving the processes and IT that better supports healthcare, please welcome our panel of experts: Oliver Kipf, The Open Group Healthcare Forum Chairman and Business Process and Solution Architect at Philips, based in Germany; Dr. Jason Lee, Director of the Healthcare Forum at The Open Group, in Boston, and Gail Kalbfleisch, Director of the Federal Health Architecture at the US Department of Health and Human Services in Washington, D.C. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: For those who might not be that familiar with the Healthcare Forum and The Open Group in general, tell us about why the Healthcare Forum exists, what its mission is, and what you hope to achieve through your work.

Lee: The Healthcare Forum exists because there is a huge need to architect the healthcare enterprise, which is approaching 20 percent of the gross domestic product (GDP) of the economy in the US, and approaching that level in other developing countries in Europe.

Lee

Lee

 

There is a general feeling that enterprise architecture is somewhat behind in this industry, relative to other industries. There are important gaps to fill that will help those stakeholders in healthcare -- whether they are in hospitals or healthcare delivery systems or innovation hubs in organizations of different sorts, such as consulting firms. They can better leverage IT to achieve business goals, through the use of best practices, lessons learned, and the accumulated wisdom of the various Forum members over many years of work. We want them to understand the value of our work so they can use it to address their needs.

Our mission, simply, is to help make healthcare information available when and where it’s needed and to accomplish that goal through architecting the healthcare enterprise. That’s what we hope to achieve.

Gardner: As the chairman of the HCF, could you explain what a forum is, Oliver? What does it consist of, how many organizations are involved?

Kipf: The HCF is made up of its members and I am really proud of this team. We are very passionate about healthcare. We are in the technology business, so we are more than just the governing bodies; we also have participation from the provider community. That makes the Forum true to the nature of The Open Group, in that we are global in nature, we are vendor-neutral, and we are business-oriented. We go from strategy to execution, and we want to bridge from business to technology. We take the foundation of The Open Group, and then we apply this to the HCF.

Kipf

Kipf

 

As we have many health standards out there, we really want to leverage [experience] from our 30 members to make standards work by providing the right type of tools, frameworks, and approaches. We partner a lot in the industry.

The healthcare industry is really a crowded place and there are many standard development organizations. There are many players. It’s quite vital as a forum that we reach out, collaborate, and engage with others to reach where we want to be.

Gardner: Gail, why is the role of the enterprise architecture function an important ingredient to help bring this together? What’s important about EA when we think about the healthcare industry?

Kalbfleisch: From an EA perspective, I don’t really think that it matters whether you are talking about the healthcare industry or the finance industry or the personnel industry or the gas and electric industry. If you look at any of those, the organizations or the companies that tend to be highly functioning, they have not just architecture -- because everyone has architecture for what they do. But that architecture is documented and it’s available for use by decision-makers, and by developers across the system so that each part can work well together.

Kalbfleisch

Kalbfleisch

 

We know that within the healthcare industry it is exceedingly complicated, and it’s a mixture of a lot of different things. It’s not just your body and your doctor, it’s also your insurance, your payers, research, academia -- and putting all of those together.

If we don’t have EA, people new to the system -- or people who were deeply embedded into their parts of the system -- can’t see how that system all works together usefully. For example, there are a lot of different standards organizations. If we don’t see how all of that works together -- where everybody else is working, and how to make it fit together – then we’re going to have a hard time getting to interoperability quickly and efficiently.

It's important that we get to individual solution building blocks to attain a more integrated approach. 

Kipf: If you think of the healthcare industry, we’ve been very good at developing individual solutions to specific problems. There’s a lot of innovation and a lot of technology that we use. But there is an inherent risk of producing silos among the many stakeholders who, ultimately, work for the good of the patient. It's important that we get to individual solution building blocks to attain a more integrated approach based on architecture building blocks, and based on common frameworks, tools and approaches.

Gardner: Healthcare is a very complex environment and IT is very fast-paced. Can you give us an update on what the Healthcare Forum has been doing, given the difficulty of managing such complexity?

Bird’s-eye view mapping

Lee: The Healthcare Forum began with a series of white papers, initially focusing on an information model that has a long history in the federal government. We used enterprise architecture to evaluate the Federal Health Information Model (FHIM).  People began listening and we started to talk to people outside of The Open Group, and outside of the normal channels of The Open Group. We talked to different types of architects, such as information architects, solution architects, engineers, and initially settled on the problem that is essential to The Open Group -- and that is the problem of boundaryless information flow.

We need to get beyond the silos that Oliver mentioned and that Gail alluded to. As I mentioned in my opening comments, this is a huge industry, and Gail illustrated it by naming some of the stakeholders within the health, healthcare and wellness enterprises. If you think of your hospital, it can be difficult to achieve boundaryless information flow to enable your information to travel digitally, securely, quickly, and in a way that’s valid, reliable and understandable by those who send it and by those who receive it.  But if that is possible, it’s all to the betterment of the patient.

Initially, in our focus on what healthcare folks call interoperability -- what we refer to as boundaryless information flow -- we came to realize through discussions with stakeholders in the public sector, as well as the private sector and globally, that understanding how the different pieces are linked together is critical. Anybody who works in an organization or belongs to a church, school or family understands that sometimes getting the right message communicated from point A to point B can be difficult.

To address that issue, the HCF members have decided to create a Health Enterprise Reference Architecture (HERA) that is essentially a framework and a map at the highest level. It helps people see that what they do relates to what others do, regardless of their position in their company. You want to deliver value to those people, to help them understand how their work is interconnected, and how IT can help them achieve their goals.

Gardner: Oliver, who should be aware of and explore engaging with the HCF?

Kipf: The members of The Open Group themselves, many of them are players in the field of healthcare, and so they are the natural candidates to really engage with. In that healthcare ecosystem we have providers, payers, governing bodies, pharmaceuticals, and IT companies.

Those who deeply need planning, management and architecting -- to make big thinking a reality out there -- those decision-makers are the prime candidates for engagement in the Healthcare Forum. They can benefit from the kinds of products we produce, the reference architecture, and the white papers that we offer. In a nutshell, it’s the members, and it’s the healthcare industry, and the healthcare ecosystem that we are targeting.

Gardner: Gail, perhaps you could address the reference architecture initiative? Why do you see that as important? Who do you think should be aware of it and contribute to it?

Shared reference points

Kalbfleisch: Reference architecture is one of those building block pieces that should be used. You can call it a template. You can have words that other people can relate to, maybe easier than the architecture-speak.

If you take that template, you can make it available to other people so that we can all be designing our processes and systems with a common understanding of our information exchange -- so that it crosses boundaries easily and securely. If we are all running on the same template, that’s going to enable us to identify how to start, what has to be included, and what standards we are going to use.

A reference architecture is one of those very important pieces that not only forms a list of how we want to do things, and what we agreed to, but it also makes it so that every organization doesn’t have to start from scratch. It can be reused and improved upon as we go through the work. If someone improves the architecture, that can come back into the reference architecture.

Who should know about it? Decision makers, developers, medical device innovators, people who are looking to improve the way information flows within any health sector -- whether it’s Oliver in Europe, whether it’s someone over in California, Australia, it really doesn't matter. Anyone who wants to make interoperability better should know about it.

My focus is on decision-makers, policymakers, process developers, and other people who look at it from a device-design perspective. One of the things that has been discussed within the HCF’s reference architecture work is the need to make sure that it’s all at a high-enough level, where we can agree on what it looks like. Yet it also must go down deeply enough so that people can apply it to what they are doing -- whether it’s designing a piece of software or designing a medical device.

Gardner: Jason, The Open Group has been involved with standards and reference architectures for decades, with such recent initiatives as the IT4IT approach, as well as the longstanding TOGAF reference architecture. How does the HERA relate to some of these other architectural initiatives?

Building on a strong foundation

Lee: The HERA starts by using the essential components and insights that are built into the TOGAF ArchitecturalDevelopment Model (ADM) and builds from there. It also uses the ArchiMate language, but we have never felt restricted to using only those existing Open Group models that have been around for some time and are currently being developed further.

We are a big organization in terms of our approach, our forum, and so we want to draw from the best there is in order to fill in the gaps. Over the last few decades, an incredible amount of talent has joined The Open Group to develop architectural models and standards that apply across multiple industries, including healthcare. We reuse and build from this important work.

In addition, as we have dug deeper into the healthcare industry, we have found other issues – gaps -- that need filling. There are related topics that would benefit. To do that, we have been working hard to establish relationships with other organizations in the healthcare space, to bring them in, and to collaborate. We have done this with the Health Level Seven Organization (HL7), which is one of the best-known standards organizations in the world.

We are also doing this now with an organization called Healthcare Services Platform Consortium (HSPC), which involves academic, government and hospital organizations, as well as people who are focused on developing standards around terminology.

IT’s getting better all the time

Kipf: If you think about reference architecture in a specific domain, such as in the healthcare industry, you look at your customers and the enterprises -- those really concerned with the delivery of health services. You need to ask yourself the question: What are their needs?

And the need in this industry is a focus on the person and on the service. It’s also highly regulatory, so being compliant is a big thing. Quality is a big thing. The idea of lifetime evolution -- that you become better and better all the time -- that is very important, very intrinsic to the healthcare industry.

When we are looking into the customers out there that we believe that the HERA could be of value, it’s the small- to mid-sized and the large enterprises that you have to think of, and it’s really across the globe. That’s why we believe that the HERA is something that is tuned into the needs of our industry.

And as Jason mentioned, we build on open standards and we leverage them where we can. ArchiMate is one of the big ones -- not only the business language, but also a lot of the concepts are based on ArchiMate. But we need to include other standards as well, obviously those from the healthcare industry, and we need to deviate from specific standards where this is of value to our industry.

Gardner: Oliver, in order to get this standard to be something that's used, that’s very practical, people look to results. So if you were to take advantage of such reference architectures as HERA, what should you expect to get back? If you do it right, what are the payoffs?

Capacity for change and collaboration

Kipf: It should enable you to do a better job, to become more efficient, and to make better use of technology. Those are the kinds of benefits that you see realized. It’s not only that you have a place where you can model all the elements of your enterprise, where you can put and manage your processes and your services, but it’s also in the way you are architecting your enterprise.

It gives you the ability to change. From a transformation management perspective, we know that many healthcare systems have great challenges and there is this need to change. The HERA gives you the tools to get where you want to be, to define where you want to be -- and also how to get there. This is where we believe it provides a lot of benefits.

Gardner: Gail, similar question, for those organizations, both public and private sector, that do this well, that embrace HERA, what should they hope to get in return?

Kalbfleisch: I completely agree with what Oliver said. To add, one of the benefits that you get from using EA is a chance to have a perspective from outside your own narrow silos. The HERA should be able to help a person see other areas that they have to take into consideration, that maybe they wouldn’t have before.

Another value is to engage with other people who are doing similar work, who may have either learned lessons, or are doing similar things at the same time. So that's one of the ways I see the effectiveness and of doing our jobs better, quicker, and faster.

Also, it can help us identify where we have gaps and where we need to focus our efforts. We can focus our limited resources in much better ways on specific issues -- where we can accomplish what we are looking to -- and to gain that boundaryless information flow.

Reaching your goals

Lee: Essentially, the HERA will provide a framework that enables companies to leverage IT to achieve their goals. The wonderful thing about it is that we are not telling organizations what their goals should be. We show them how they can follow a roadmap to accomplish their self-defined goals more effectively. Often this involves communicating the big picture, as Gail said, to those who are in siloed positions within their organizations.

There is an old saying: “What you see depends on where you sit.” The HERA helps stakeholders gain this perspective by helping key players understand the relationships, for example, between business processes and engineering. So whether a stakeholder’s interest is increasing patient satisfaction, reducing error, improving quality, and having better patient outcomes and gaining more reimbursement where reimbursement is tied to outcomes -- using the product and the architecture that we are developing helps all of these goals.

Gardner: Jason, for those who are intrigued by what you are doing with HERA, tell us about its trajectory, its evolution, and how that journey unfolds. Who can they learn more or get involved?

Lee: We have only been working on the HERA per se for the last year, although its underpinnings go back 20 years or more. Its trajectory is not to a single point, but to an evolutionary process. We will be producing products, white papers, as well as products that others can use in a modular fashion to leverage what they already use within their legacy systems.

We encourage anyone out there, particularly in the health system delivery space, to join us. That can be done by contacting me at j.lee@opengroup.org and at www.opengroup.org/healthcare.

It’s an incredible time, a very opportune time, for key players to be involved because we are making very important decisions that lay the foundation for the HERA. We collaborate with key players, and we lay down the tracks from which we will build increasing levels of complexity.

But we start at the top, using non-architectural language to be able to talk to decision-makers, whether they are in the public sector or private sector. So we invite any of these organizations to join us.

Learn from others’ mistakes

Kalbfleisch: My first foray into working with The Open Group was long before I was in the health IT sector. I was with the US Air Force and we were doing very non-health architectural work in conjunction with The Open Group.

The interesting part to me is in ensuring boundaryless information flow in a manner that is consistent with the information flowing where it needs to go and who has access to it. How does it get from place to place across distinct mission areas, or distinct business areas where the information is not used the same way or stored in the same way? Such dissonance between those business areas is not a problem that is isolated just to healthcare; it’s across all business areas.

That was exciting. I was able to take awareness of The Open Group from a previous life, so to speak, and engage with them to get involved in the Healthcare Forum from my current position.

A lot of the technical problems that we have in exchanging information, regardless of what industry you are in, have been addressed by other people, and have already been worked on. By leveraging the way organizations have already worked on it for 20 years, we can leverage that work within the healthcare industry. We don't have to make the same mistakes that were made before. We can take what people have learned and extend it much further. We can do that best by working together in areas like The Open Group HCF.

Kipf: On that evolutionary approach, I also see this as a long-term journey. Yes, there will be releases when we have a specification, and there will guidelines. But it's important that this is an engagement, and we have ongoing collaboration with customers in the future, even after it is released. The coming together of a team is what really makes a great reference architecture, a team that places the architecture at a high level.

We can also develop distinct flavors of the specification. We should expect much more detail. Those implementation architectures then become spin-offs of reference architectures such as the HERA.

Lee: I can give some concrete examples, to bookend the kinds of problems that can be addressed using the HERA. At the micro end, a hospital can use the HERA structure to implement a patient check-in to the hospital for patients who would like to bypass the usual process and check themselves in. This has a number of positive value outcomes for the hospital in terms of staffing and in terms of patient satisfaction and cost savings.

At the other extreme, a large hospital system in Philadelphia or Stuttgart or Oslo or in India finds itself with patients appearing at the emergency room or in the ambulatory settings unaffiliated with that particular hospital. Rather than have that patient come as a blank sheet of paper, and redo all the tests that had been done prior, the HERA will help these healthcare organizations figure out how to exchange data in a meaningful way. So the information can flow digitally, securely, and it means the same thing to those who get it as much as it does to those who receive it, and everything is patient-focused, patient-centric.

Gardner: Oliver, we have seen with other Open Group standards and reference architectures, a certification process often comes to bear that helps people be recognized for being adept and properly trained. Do you expect to have a certification process with HERA at some point?

Certifiable enterprise expertise

Kipf: Yes, the more we mature with the HERA, along with the defined guidelines and the specifications and the HERA model, the more there will be a need and demand for health enterprise-focused employees in the marketplace. They can show how consulting services can then use HERA.

And that's a perfect place when you think of certification. It helps make sure that the quality of the workforce is strong, whether it's internal or in the form of a professional services role. They can comply with the HERA.

Gardner: Clearly, this has applicability to healthcare payer organizations, provider organizations, government agencies, and the vendors who supply pharmaceuticals or medical instruments. There are a great deal of process benefits when done properly, so that enterprise architects could become certified eventually.

My question then is how do we take the HERA, with such a potential for being beneficial across the board, and make it well-known? Jason, how do we get the word out? How can people who are listening to this or reading this, help with that?

Spread the word, around the world

Lee: It's a question that has to be considered every time we meet. I think the answer is straightforward. First, we build a product [the HERA] that has clear value for stakeholders in the healthcare system. That’s the internal part.

Second—and often, simultaneously—we develop a very important marketing/collaboration/socialization capability. That’s the external part. I've worked in healthcare for more than 30 years, and whether it's public or private sector decision-making, there are many stakeholders, and everybody's focused on the same few things: improving value, enhancing quality, expanding access, and providing security.

We will continue developing relationships with key players to ensure them that what they’re doing is key to the HERA. At the broadest level, all companies must plan, build, operate and improve.

There are immense opportunities for business development. There are innumerable ways to use the HERA to help health enterprise systems operate efficiently and effectively. There are opportunities to demonstrate to key movers and shakers in healthcare system how what we're doing integrates with what they're doing. This will maximize the uptake of the HERA and minimize the chances it sits on a shelf after it's been developed.

Gardner: Oliver, there are also a variety of regional conferences and events around the world. Some of them are from The Open Group. How important is it for people to be aware of these events, maybe by taking part virtually online or in person? Tell us about the face-time opportunities, if you will, of these events, and how that can foster awareness and improvement of HERA uptake.

Kipf: We began with the last Open Group event. I was in Berlin, presenting the HERA. As we see more development, more maturity, we can then show more. The uptake will be there and we also need to include things like cyber security, things like risk compliance. So we can bring in a lot of what we have been doing in various other initiatives within The Open Group. We can show how it can be a fusion, and make this something that is really of value.

I am confident that through face-to-face events, such as The Open Group events, we can further spread the message.

Lee: And a real shout-out to Gail and Oliver who have been critical in making introductions and helping to share The Open Group Healthcare Forum’s work broadly. The most recent example is the 2016 HIMSS conference, a meeting that brings together more than 40,000 people every year. There is a federal interoperability showcase there, and we have been able to introduce and discuss our HERA work there.

We’ve collaborated with the Office of the National Coordinator where the Federal Heath Architecture sits, with the US Veterans Administration, with the US Department of Defense, and with the Centers for Medicare and Medicaid (CMS). This is all US-centered, but there are lots of opportunities globally to not just spread the word in public for domains and public venues, but also to go to those key players who are moving the industry forward, and in some cases convince them that enterprise architecture does provide that structure, that template that can help them achieve their goals.

Future forecast

Gardner: I’m afraid we are almost out of time. Gail, perhaps a look into the crystal ball. What do you expect and hope to see in the next few years when it comes to improvements initiatives like HERA at The Open Group Forum can provide? What do you hope to see in the next couple of years in terms of improvement?

Kalbfleisch: What I would like to see happen in the next couple of years as it relates to the HERA, is the ability to have a place where we can go from anywhere and get a glimpse of the landscape. Right now, it’s hard to find anywhere where someone in the US can see the great work that Oliver is doing, or the people in Norway, or the people in Australia are doing.

It’s really important that we have opportunities to communicate as large groups, but also the one-on-one. Yet when we are not able to communicate personally, I would like to see a resource or a tool where people can go and get the information they need on the HERA on their own time, or as they have a question. Reference architecture is great to have, but it has no power until it’s used.

My hope for the future is for the HERA to be used by decision-makers, developers, and even patients. So when an organizations such as some hospital wants to develop a new electronic health record (EHR) system, they have a place to go and get started, without having to contact Jason or wait for a vendor to come along and tell them how to solve a problem. That would be my hope for the future.

Lee: You can think of the HERA as a soup with three key ingredients. First is the involvement and commitment of very bright people and top-notch organizations. Second, we leverage the deep experience and products of other forums of The Open Group. Third, we build on external relationships. Together, these three things will help make the HERA successful as a certifiable product that people can use to get their work done and do better.

Gardner: Jason, perhaps you could also tee-up the next Open Group event in Amsterdam. Can you tell us more about that and how to get involved?

Lee: We are very excited about our next event in Amsterdam in October. You can go to www.opengroup.org and look under Events, read about the agendas, and sign up there. We will have involvement from experts from the US, UK, Germany, Australia, Norway, and this is just in the Healthcare Forum!

The Open Group membership will be giving papers, having discussions, moving the ball forward. It will be a very productive and fun time and we are looking forward to it. Again, anyone who has a question or is interested in joining the Healthcare Forum can please send me, Jason Lee, an email at j.lee@opengroup.org.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy. Sponsor: The Open Group.

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Advanced IoT systems provide analysis catalyst for the petrochemical refinery of the future

The next BriefingsDirect Voice of the Customer Internet-of-Things (IoT) technology trends interview explores how IT combines with IoT to help create the refinery of the future

We’ll now learn how a leading-edge petrochemical company in Texas is rethinking data gathering and analysis to foster safer environments and greater overall efficiency.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy. 

To help us define the best of the refinery of the future vision is Doug Smith, CEO of Texmark Chemicals in Galena Park, Texas, and JR Fuller, Worldwide Business Development Manager for Edgeline IoT at Hewlett Packard Enterprise (HPE). The discussion is moderated by Dana Gardner, principal analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: What are the top trends driving this need for a new refinery of the future? Doug, why aren’t the refinery practices of the past good enough?

Smith: First of all, I want to talk about people. People are the catalysts who make this refinery of the future possible. At Texmark Chemicals, we spent the last 20 years making capital investments in our infrastructure, in our physical plant, and in the last four years we have put together a roadmap for our IT needs.

Through our introduction to HPE, we have entered into a partnership that is not just a client-customer relationship. It’s more than that, and it allows us to work together to discover IoT solutions that we can bring to bear on our IT challenges at Texmark. So, we are on the voyage of discovery together -- and we are sailing out to sea. It’s going great.

Gardner: JR, it’s always impressive when a new technology trend aids and abets a traditional business, and then that business can show through innovation what should then come next in the technology. How is that back and forth working? Where should we expect IoT to go in terms of business benefits in the not-to-distant future?

Fuller

Fuller

Fuller: One of powerful things about the partnership and relationship we have is that we each respect and understand each other's “swim lanes.” I’m not trying to be a chemical company. I’m trying to understand what they do and how I can help them.

And they’re not trying to become an IT or IoT company. Their job is to make chemicals; our job is to figure out the IT. We’re seeing in Texmark the transformation from an Old World economy-type business to a New World economy-type business.

This is huge, this is transformational. As Doug said, they’ve made huge investments in their physical assets and what we call Operational Technology (OT). They have done that for the past 20 years. The people they have at Texmark who are using these assets are phenomenal. They possess decades of experience.

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Yet IoT is really new for them. How to leverage that? They have said, “You know what? We squeezed as much as we can out of OT technology, out of our people, and our processes. Now, let’s see what else is out there.”

And through introductions to us and our ecosystem partners, we’ve been able to show them how we can help squeeze even more out of those OT assets using this new technology. So, it’s really exciting.

Gardner: Doug, let’s level-set this a little bit for our audience. They might not all be familiar with the refinery business, or even the petrochemical industry. You’re in the process of processing. You’re making one material into another and you’re doing that in bulk, and you need to do it on a just-in-time basis, given the demands of supply chains these days.

You need to make your business processes and your IT network mesh, to reach every corner. How does a wireless network become an enabler for your requirements?

The heart of IT 

Smith: In a large plant facility, we have different pieces of equipment. One piece of equipment is a pump -- the analogy would be the heart of the process facility of the plant.

Smith

Smith

So your question regarding the wireless network, if we can sensor a pump and tie it into a mesh network, there are incredible cost savings for us. The physical wiring of a pump runs anywhere from $3,000 to $5,000 per pump. So, we see a savings in that.

Being able to have the information wirelessly right away -- that gives us knowledge immediately that we wouldn’t have otherwise. We have workers and millwrights at the plant that physically go out and inspect every single pump in our plant, and we have 133 pumps. If we can utilize our sensors through the wireless network, our millwrights can concentrate on the pumps that they know are having problems.

Gardner: You’re also able to track those individuals, those workers, so if there’s a need to communicate, to locate, to make sure that they hearing the policy, that’s another big part of IoT and people coming together.

Safety is good business

Smith: The tracking of workers is more of a safety issue -- and safety is critical, absolutely critical in a petrochemical facility. We must account for all our people and know where they are in the event of any type of emergency situation.

Gardner: We have the sensors, we can link things up, we can begin to analyze devices and bring that data analytics to the edge, perhaps within a mini data center facility, something that’s ruggedized and tough and able to handle a plant environment.

Given this scenario, JR, what sorts of efficiencies are organizations like Texmark seeing? I know in some businesses, they talk about double digit increases, but in a mature industry, how does this all translate into dollars?

Fuller: We talk about the power of one percent. A one percent improvement in one of the major companies is multi-billions of dollars saved. A one percent change is huge, and, yes, at Texmark we’re able to see some larger percentage-wise efficiency, because they’re actually very nimble.

It’s hard to turn a big titanic ship, but the smaller boat is actually much better at it. We’re able to do things at Texmark that we are not able to do at other places, but we’re then able to create that blueprint of how they do it. 

You’re absolutely right, doing edge computing, with our HPE Edgeline products, and gathering the micro-data from the extra compute power we have installed, provides a lot of opportunities for us to go into the predictive part of this. It’s really where you see the new efficiencies.

Recently I was with the engineers out there, and we’re walking through the facility, and they’re showing us all the equipment that we’re looking at sensoring up, and adding all these analytics. I noticed something on one of the pumps. I’ve been around pumps, I know pumps very well.

I saw this thing, and I said, “What is that?”

“So that’s a filter,” they said.

I said, “What happens if the filter gets clogged?”

“It shuts down the whole pump,” they said.

“What happens if you lose this pump?” I asked.

“We lose the whole chemical process,” they explained.

“Okay, are there sensors on this filter?”

“No, there are only sensors on the pump,” they said.

There weren’t any sensors on the filter. Now, that’s just something that we haven’t thought of, right? But again, I’m not a chemical guy. So I can ask questions that maybe they didn’t ask before.

So I said, “How do you solve this problem today?”

“Well, we have a scheduled maintenance plan,” they said.

They don’t have a problem, but based on the scheduled maintenance plan that filter gets changed whether it needs to or not. It just gets changed on a regular basis. Using IoT technology, we can tell them exactly when to change that filter. Therefore IoT saves on the cost of the filter and the cost of the manpower -- and those types of potential efficiencies and savings are just one small example of the things that we’re trying to accomplish.

Continuous functionality

Smith: It points to the uniqueness of the people-level relationship between the HPE team, our partners, and the Texmark team. We are able to have these conversations to identify things that we haven’t even thought of before. I could give you 25 examples of things just like this, where we say, “Oh, wow, I hadn’t thought about that.” And yet it makes people safer and it all becomes more efficient.

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Gardner: You don’t know until you have that network in place and the data analytics to utilize what the potential use-cases can be. The name of the game is utilization efficiency, but also continuous operations.

How do you increase your likelihood or reduce the risk of disruption and enhance your continuous operations using these analytics?

Smith: To answer, I’m going to use the example of toll processing. Toll processing is when we would have a customer come to us and ask us to run a process on the equipment that we have at Texmark.

Normally, they would give us a recipe, and we would process a material. We take samples throughout the process, the production, and deliver a finished product to them. With this new level of analytics, with the sensoring of all these components in the refinery of the future vision, we can provide a value-add to the customers by giving them more data than they could ever want. We can document and verify the manufacture and production of the particular chemical that we’re toll processing for them.

Fuller: To add to that, as part of the process, sometimes you may have to do multiple runs when you're tolling, because of your feed stock and the way it works.

By usingadvanced analytics, and some of the predictive benefits of having all of that data available, we're looking to gain efficiencies to cut down the number of additional runs needed. If you take a process that would have taken three runs and we can knock that down to two runs -- that's a 30 percent decrease in total cost and expense. It also allows them produce more products, and to get it out to people a lot faster

Smith: Exactly. Exactly!

Gardner: Of course, the more insight that you can obtain from a pump, and the more resulting data analysis, that gives you insight into the larger processes. You can extend that data and information back into your supply chain. So there's no guesswork. There's no gap. You have complete visibility -- and that's a big plus when it comes to reducing risk in any large, complex, multi-supplier undertaking.

Beyond data gathering, data sharing

Smith: It goes back to relationships at Texmark. We have relationships with our neighbors that are unique in the industry, and so we would be able to share the data that we have.

Fuller: With suppliers.

Smith: Exactly, with suppliers and vendors. It's transformational.

Gardner: So you're extending a common standard industry-accepted platform approach locally into an extended process benefit. And you can share that because you are using common, IT-industry-wide infrastructurefrom HPE.

Fuller: And that's very important. We have a three-phase project, and we've just finished the first two phases. Phase 1 was to put ubiquitous WiFi infrastructure in there, with the location-based services, and all of the things to enable that. The second phase was to upgrade the compute infrastructure with our Edgeline compute and put in our HPE Micro Datacenter in there. So now they have some very robust compute.

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With that infrastructure in place, it now allows us to do that third phase, where we're bringing in additional IoT projects. We will create a data infrastructure with data storage, and application programming interfaces (APIs), and things like that. That will allow us to bring in a specialty video analytic capability that will overlay on top of the physical and logical infrastructure. And it makes it so much easier to integrate all that.

Gardner: You get a chance to customize the apps much better when you have a standard IT architecture underneath that, right?

Trailblazing standards for a new workforce

Smith: Well, exactly. What are you saying, Dana is – and it gives me chills when I start thinking about what we're doing at Texmark within our industry – is the setting of standards, blazing a new trail. When we talk to our customers and our suppliers and we tell them about this refinery of the future project that we're initiating, all other business goes out the window. They want to know more about what we're doing with the IoT -- and that's incredibly encouraging.

Gardner: I imagine that there are competitive advantages when you can get out in front and you're blazing that trail. If you have the experience, the skills of understanding how to leverage an IoT environment, and an edge computing capability, then you're going to continue to be a step ahead of the competition on many levels: efficiency, safety, ability to customize, and supply chain visibility.

Smith: It surely allows our Texmark team to do their jobs better. I use the example of the millwrights going out and inspecting pumps, and they do that everyday. They do it very well. If we can give them the tools, where they can focus on what they do best over a lifetime of working with pumps, and only work on the pumps that they need to, that's a great example.

I am extremely excited about the opportunities at the refinery of the future to bring new workers into the petrochemical industry. We have a large number of people within our industry who are retiring; they’re taking intellectual capital with them. So to be able to show young people that we are using advanced technology in new and exciting ways is a real draw and it would bring more young people into our industry.

Gardner: By empowering that facilities edge and standardizing IT around it, that also gives us an opportunity to think about the other part of this spectrum -- and that's the cloud. There are cloud services and larger data sets that could be brought to bear.

How does the linking of the edge to the cloud have a benefit?

Cloud watching

Fuller: Texmark Chemicals has one location, and they service the world from that location as a global leader in dicyclopentadiene (DCPD) production. So the cloud doesn't have the same impact as it would for maybe one of the other big oil or big petrochemical companies. But there are ways that we're going to use the cloud at Texmark and rally around it for safety and security.

Utilizing our location-based services, and our compute, if there is an emergency -- whether it's at Texmark or a neighbor -- using cloud-based information like weather, humidity, and wind direction -- and all of these other things that are constantly changing -- we can provide better directed responses. That's one way we would be using cloud at Texmark.

When we start talking about the larger industry -- and connecting multiple refineries together or upstream, downstream and midstream kinds of assets together with a petrochemical company -- cloud becomes critical. And you have to have hybrid infrastructure support.

You don't want to send all your video to the cloud to get analyzed. You want to do that at the edge. You don't want to send all of your vibration data to the cloud, you want to do that at the edge. But, yes, you do want to know when a pump fails, or when something happens so you can educate and train and learn and share that information and institutional knowledge throughout the rest of the organization.

Gardner: Before we sign off, let’s take a quick look into the crystal ball. Refinery of the future, five years from now, Doug, where do you see this going?

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Smith: The crystal ball is often kind of foggy, but it’s fun to look into it. I had mentioned earlier opportunities for education of a new workforce. Certainly, I am focused on the solutions that IoT brings to efficiencies, safety, and profitability of Texmark as a company. But I am definitely interested in giving people opportunities to find a job to work in a good industry that can be a career.

Gardner: JR, I know HPE has a lot going on with edge computing, making these data centers more efficient, more capable, and more rugged. Where do you see the potential here for IoT capability in refineries of the future?

Future forecast: safe, efficient edge

Fuller: You're going to see the pace pick up. I have to give kudos to Doug. He is a visionary. Whether he admits that or not, he is actually showing an industry that has been around for many years how to do this and be successful at it. So that's incredible. In that crystal ball look, that five-year look, he's going to be recognized as someone who helped really transform this industry from old to new economy.

As far as edge-computing goes, what we're seeing with our converged Edgeline systems, which are our first generation, and we've created this market space for converged edge systems with the hardening of it. Now, we’re working on generation 2. We're going to get faster, smaller, cheaper, and become more ubiquitous. I see our IoT infrastructure as having a dramatic impact on what we can actually accomplish and the workforce in five years. It will be more virtual and augmented and have all of these capabilities. It’s going to be a lot safer for people, and it’s going to be a lot more efficient.

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How AI, IoT and blockchain will shake up procurement and supply chains

The next BriefingsDirect digital business thought leadership panel discussion focuses on how artificial intelligence (AI), the Internet of things (IoT), machine learning (ML), and blockchain will shake up procurement and supply chain optimization.

Stay with us now as we develop a new vision for how today's cutting-edge technologies will usher in tomorrow's most powerful business tools and processes. The panel was assembled and recorded at the recent 2017 SAP Ariba LIVE conference in Las Vegas. The discussion is moderated by Dana Gardner, principal analyst at Interarbor Solutions.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy.

To learn more about the data-driven, predictive analytics, and augmented intelligence approach to supply chain management and procurement, please welcome the executives from SAP Ariba:

Here are some excerpts:

Gardner: It seems like only yesterday we were confident to have a single view of a customer, or clean data, or maybe a single business process end–to-end value. But now, we are poised to leapfrog the status quo by using words like predictive and proactive for many business functions.

Why are AI and ML such disrupters to how we've been doing business processes?

Shahane: If you look back, some of the technological impact  in our private lives, is impacting our public life. Think about the amount of data and signals that we are gathering; we call it big data.

We not only do transactions in our personal life, we also have a lot of content that gets pushed at us. Our phone records, our location as we move, so we are wired and we are hyper-connected.

Shahane

Shahane

Similar things are happening to businesses. Since we are so connected, a lot of data is created. Having all that big data – and it could be a problem from the privacy perspective -- gives you an opportunity to harness that data, to optimize it and make your processes much more efficient, much more engaged.

If you think about dealing with big data, you try and find patterns in that data, instead of looking at just the raw data. Finding those patterns collectively as a discipline is called machine learning. There are various techniques, and you can find a regression pattern, or you can find a recommendation pattern -- you can find all kinds of patterns that will optimize things, and make your experience a lot more engaging.

If you combine all these machine learning techniques with tools such as natural language processing (NLP), higher-level tools such as inference engines, and text-to-speech processing -- you get things like Siri and Alexa. It was created for the consumer space, but the same thing could be available for your businesses, and you can train that for your business processes. Overall, these improve efficiency, give delight, and provide a very engaging user experience.

Gardner: Sanjay, from the network perspective it seems like we are able to take advantage of really advanced cloud services, put that into a user experience that could be conversational, like we do with our personal consumer devices.

What is it about the cloud services in the network, however, that are game-changers when it comes to applying AI and ML to just good old business processes?

Multiple intelligence recommended

Almeida: Building on Dinesh’s comment, we have a lot of intelligent devices in our homes. When we watch Netflix, there are a lot of recommendations that happen. We control devices through voice. When we get home the lights are on. There is a lot of intelligence built into our personal lives. And when we go to work, especially in an enterprise, the experience is far different. How do we make sure that your experience at home carries forward to when you are at work?

From the enterprise and business networks perspective, we have a lot of data; a lot of business data about the purchases, the behaviors, the commodities. We can use that data to make the business processes a lot more efficient, using some of the models that Dinesh talked about.

Almeida

Almeida

How do we actually do a recommendation so that we move away from traditional search, and take action on rows and columns, and drive that through a voice interface? How do we bring that intelligence together, and recommend the next actions or the next business process? How do we use the data that we have and make it a more recommended-based interaction versus the traditional forms-based interaction?

Gardner: Sudhir, when we go out to the marketplace with these technologies, and people begin to use them for making better decisions, what will that bring to procurement and supply chain activities? Are we really talking about letting the machines make the decisions? Where does the best of what machines do and the best of what people do meet?

Bhojwani: Quite often I get this question, What will be the role of procurement in 2025? Are the machines going to be able to make all the decisions and we will have no role to play? You can say the same thing about all aspects of life, so why only procurement?

I think human intelligence is still here to stay. I believe, personally, it can be augmented. Let's take a concrete example to see what it means. At SAP Ariba, we are working on a product called product sourcing. Essentially this product takes a bill of material (BOM), and it tells you the impact. So what is so cool about it?

One of our customers has a BOM, which is an eight-level deep tree with 10 million nodes in it. In this 10 million-node commodity tree, or BOM, a person is responsible for managing all the items. But how does he or she know what is the impact of a delay on the entire tree? How do you visualize that?

Bhojwani

Bhojwani

I think humans are very poor at visualizing a 10-million node tree; machines are really good at it. Well, where the human is still going to be required is that eventually you have to make a decision. Are we comfortable that the machine alone makes a decision? Only time will tell. I continue to think that this kind of augmented intelligence is what we are looking for, not some machine making complete decisions on our behalf.

Gardner: Dinesh, in order to make this more than what we get in our personal consumer space, which in some cases is nice to have, it doesn't really change the game. But we are looking for a higher productivity in business. The C-Suite is looking for increased margins; they are looking for big efficiencies. What is it from a business point of view that these technologies can bring? Is this going to be just a lipstick on a pig, so to speak, or do we really get to change how business productivity comes about?

Humans and machines working together

Shahane: I truly believe it will change the productivity. The whole intelligence advantage -- if you look at it from a highest perspective like enhanced user experience -- provides an ability to help you make your decisions.

When you make decisions having this augmented assistant helping you along the way -- and at the same time dealing with large amount of data combined in a business benefit -- I think it will make a huge impact.

Let me give you an example. Think about supplier risk. Today, at first you look at risk as the people on the network, and how you are directly doing business with them. You want to know everything about them, their profile, and you care about them being a good business partner to you.

But think about the second, third and fourth years, and some things become not so interesting for your business. All that information for those next years is not directly available on the network; that is distant. But if those signals can be captured and somehow surface in your decision-making, it can really reduce risk.

Reducing risk means more productivity, more benefits to your businesses. So that is one advantage I could see, but there will be a number of advantages. I think we'll run out of time if we start talking about all of those.

Gardner: Sanjay, help us better understand. When we take these technologies and apply them to procurement, what does that mean for the procurement people themselves?

Almeida: There are two inputs that you need to make strategic decisions, and one is the data. You look at that data and you try to make sense out of it. As Sudhir mentioned, there is a limit to human beings in terms of how much data processing that they can do -- and that's where some of these technologies will help quite a bit to make better decisions.

The other part is personal biases, and eliminating personal biases by using the data. It will improve the accuracy of your strategic decisions. A combination of those two will help make better decisions, faster decisions, and procurement groups can focus on the right stuff, versus being busy with the day-to-day tasks.

Using these technologies, the data, and the power of the data from computational excellence -- that's taking the personal biases out of making decisions. That combination will really help them make better strategic decisions.

Bhojwani: Let me add something to what Sanjay said. One of the biggest things we're seeing now in procurement, especially in enterprise software in general, is people's expectations have clearly gone up based on their personal experience outside. I mean, 10 years back I could not have imagined that I would never go to a store to buy shoes. I thought, who buys shoes online? Now, I never go to stores. I don't know when was the last time I bought shoes anywhere but online? It's been few years, in fact. Now, think about that expectation on procurement software.

Currently procurement has been looked upon as a gatekeeper; they ensure that nobody does anything wrong. The problem with that approach is it is a “stick” model, there is no “carrot” behind it. What users want is, “Hey, show me the benefit and I will follow the rules.” We can't punish the entire company because of a couple of bad apples.

By and large, most people want to follow the rules. They just don't know what the rules are; they don't have a platform that makes that decision-making easy, that enables them to get the job done sooner, faster, better. And that happens when the user experience is acceptable and where procurement is no longer looked down upon as a gatekeeper. That is the fundamental shift that has to happen, procurement has to start thinking about themselves as an enabler, not a gatekeeper. That's the fundamental shift.

Gardner: Here at SAP Ariba LIVE 2017, we're hearing about new products and services. Are there any of the new products and services that we could point to that say, aha, this is a harbinger of things to come

In blockchain we trust

Shahane: The conversational interfaces and bots, they are a fairly easy technology for anyone to adopt nowadays, especially because some of these algorithms are available so easily. But -- from my perspective -- I think one of the technologies that will have a huge impact on our life will be advent of IoT devices, 3D printing, and blockchain.

To me, blockchain is themost exciting one. That will have huge impact on the way people look at the business network. Some people think about blockchain as a complementary idea to the network. Other people think that it is contradictory to the network. We believe it is complementary to the network.

Blockchain reaches out to the boundary of your network, to faraway places that we are not even connected to, and brings that into a governance model where all of your processes and all your transactions are captured in the central network.

I believe that a trusted transactional model combined with other innovations like IoT, where a machine could order by itself … My favorite example is when a washing machine starts working when the energy is cheaper … it’s a pretty exciting use-case.

This is a combination of open platforms and IoT combining with blockchain-based energy-rate brokering. These are the kind of use cases that will become possible in the future. I see a platform sitting in the center of all these innovations.

Gardner: Sanjay, let’s look at blockchain from your perspective. How do you see that ability of a distributed network authority fitting into business processes? Maybe people hadn't quite put those two together.

Almeida: The core concept of blockchain is distributed trust and transparency. When we look at business networks, we obviously have the largest network in the world. We have more than 2.5 million buyers and suppliers transacting on the SAP Ariba Network -- but there are hundreds of millions of others who are not on the network. Obviously we would like to get them.

If you use the blockchain technology to bring that trust together, it’s a federated trust model. Then our supply chain would be lot more efficient, a lot more trustworthy. It will improve the efficiency, and all the risk that’s associated with managing suppliers will be managed better by using that technology.

Gardner: So this isn’t a “maybe,” or an “if.” It’s “definitely,” blockchain will be a significant technology for advancing productivity in business processes and business platforms?

Almeida: Absolutely. And you have to have the scale of an SAP Ariba, have the scale from the number of suppliers, the amount of business that happens on the network. So you have to have a scale and technology together to make that happen. We want to be a center of a blockchain, we want to be a blockchain provider, and so that other third-party ecosystem partners can be part of this trusted network and make this process a lot more efficient.

Gardner: Sudhir, for those who are listening and reading this information and are interested in taking advantage of ML and better data, of what the IoT will bring, and AI where it makes sense -- what in your estimation should they be doing now in order to prepare themselves as an organization to best take advantage of these? What would you advise them to be doing now in order to better take advantage of these technologies and the services that folks like SAP Ariba can provide so that they can stand out in their industry?

Bhojwani: That’s a very good question, and that's one of our central themes. At the core of it, I fundamentally believe the tool cannot solve the problem completely on its own, you have to change as well. If the companies continue to want to stick to the old processes -- but try to apply the new technology -- it doesn’t solve the problem. We have seen that movie played before. People get our tool, they say, hey, we were sold very good visions, so we bought the SAP Ariba tool. We tried to implement it and it didn’t work for us.

When you question that, generally the answer is, we just tried to use the tool -- tried to change the tool to fit our model, to fit our process. We didn’t try to change the processes. As for blockchain, enterprises are not used to being for track and trace, they are not really exposing that kind of information in any shape or form – or they are very secretive about it.

So for them to suddenly participate in this requires a change on their side. It requires seeing what is the benefit for me, what is the value that it offers me? Slowly but surely that value is starting to become very, very clear. You hear more companies -- especially on the payment side -- starting to participate in blockchain. A general ledger will be available on blockchain some day. This is one of the big ideas for SAP.

If you think about SAP, they run more general ledgers in the world than any other company. They are probably the biggest general ledger company that connects all of that. Those things are possible, but it’s still a technology only until the companies want to say, “Hey, this is the value … but I have to change myself as well.”

This changing yourself part, even though it sounds so simple, is what we are seeing in the consumer world. There, change happens a little bit faster than in the enterprise world. But, even that is actually changing, because of the demands that the end-user, the Millennials, when they come into the workforce; the force that they have and the expectations that they have. Enterprises, if they continue to resist, won’t be sustainable.

They will be forced to change. So I personally believe in next three to five years when there are more-and-more Millennials in the workforce, you will see people adopting blockchain and new ledgers at a much faster pace.

A change on both sides

Shahane: I think Sudhir put it very nicely. I think enterprises need to be open to change. You can achieve transformation if the value is clearly articulated. One of the big changes for procurement is you need to transition yourself from being a spend controller into a value creator. There is a lot of technology that will benefit you, and some of the technology vendors like us, we cannot just throw a major change at our users. We have to do it gradually. For example, with AI it will start as augmented first, before it starts making algorithmic decisions.

So it is a change on both sides, and once that happens -- and once we trust each other on the system -- nice things will happen.

Almeida: One thing I would add to that is organizations need to think about what they want to achieve in the future and adopt the tool and technology and business processes for their future business goals. It’s not about living in the past because the past is going to be gone. So how do you differentiate yourself, your business with the rest of the competition that you have?

The past business processes and people and technology many not necessarily get you over there. So how do you leverage the technology that companies like SAP and Ariba provide? Think about what should be your future business processes. The people that you will have, as Sudhir mentioned, the Millennials, they have different expectations and they won’t accept the status quo.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy. Sponsor: SAP Ariba.

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Fast acquisition of diverse unstructured data sources makes IDOL API tools a star at LogitBot

The next BriefingsDirect Voice of the Customer digital transformation case study highlights how high-performing big-data analysis powers an innovative artificial intelligence (AI)-based investment opportunity and evaluation tool. We'll learn how LogitBot in New York identifies, manages, and contextually categorizes truly massive and diverse data sources.

By leveraging entity recognition APIs, LogitBot not only provides investment evaluations from across these data sets, it delivers the analysis as natural-language information directly into spreadsheets as the delivery endpoint. This is a prime example of how complex cloud-to core-to edge processes and benefits can be managed and exploited using the most responsive big-data APIs and services.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy. 

To describe how a virtual assistant for targeting investment opportunities is being supported by cloud-based big-data services, we're joined by Mutisya Ndunda, Founder and CEO of LogitBot and Michael Bishop, CTO of LogicBot, in New York. The discussion is moderated by BriefingsDirect's Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Let’s look at some of the trends driving your need to do what you're doing with AI and bots, bringing together data, and then delivering it in the format that people want most. What’s the driver in the market for doing this?

Ndunda: LogitBot is all about trying to eliminate friction between people who have very high-value jobs and some of the more mundane things that could be automated by AI.

 

Today, in finance, the industry, in general, searches for investment opportunities using techniques that have been around for over 30 years. What tends to happen is that the people who are doing this should be spending more time on strategic thinking, ideation, and managing risk. But without AI tools, they tend to get bogged down in the data and in the day-to-day. So, we've decided to help them tackle that problem.

Gardner: Let the machines do what the machines do best. But how do we decide where the demarcation is between what the machines do well and what the people do well, Michael?

Bishop: We believe in empowering the user and not replacing the user. So, the machine is able to go in-depth and do what a high-performing analyst or researcher would do at scale, and it does that every day, instead of once a quarter, for instance, when research analysts would revisit an equity or a sector. We can do that constantly, react to events as they happen, and replicate what a high-performing analyst is able to do.

Gardner: It’s interesting to me that you're not only taking a vast amount of data and putting it into a useful format and qualitative type, but you're delivering it in a way that’s demanded in the market, that people want and use. Tell me about this core value and then the edge value and how you came to decide on doing it the way you do?

Evolutionary process

Ndunda: It’s an evolutionary process that we've embarked on or are going through. The industry is very used to doing things in a very specific way, and AI isn't something that a lot of people are necessarily familiar within financial services. We decided to wrap it around things that are extremely intuitive to an end user who doesn't have the time to learn technology.

So, we said that we'll try to leverage as many things as possible in the back via APIs and all kinds of other things, but the delivery mechanism in the front needs to be as simple or as friction-less as possible to the end-user. That’s our core principle.

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Bishop: Finance professionals generally don't like black boxes and mystery, and obviously, when you're dealing with money, you don’t want to get an answer out of a machine you can’t understand. Even though we're crunching a lot of information andmaking a lot of inferences, at the end of the day, they could unwind it themselves if they wanted to verify the inferences that we have made.

 

We're wrapping up an incredibly complicated amount of information, but it still makes sense at the end of the day. It’s still intuitive to someone. There's not a sense that this is voodoo under the covers.

Gardner: Well, let’s pause there. We'll go back to the data issues and the user-experience issues, but tell us about LogitBot. You're a startup, you're in New York, and you're focused on Wall Street. Tell us how you came to be and what you do, in a more general sense.

Ndunda: Our professional background has always been in financial services. Personally, I've spent over 15 years in financial services, and my career led me to what I'm doing today.

In the 2006-2007 timeframe, I left Merrill Lynch to join a large proprietary market-making business called Susquehanna International Group. They're one of the largest providers of liquidity around the world. Chances are whenever you buy or sell a stock, you're buying from or selling to Susquehanna or one of its competitors.

What had happened in that industry was that people were embracing technology, but it was algorithmic trading, what has become known today as high-frequency trading. At Susquehanna, we resisted that notion, because we said machines don't necessarily make decisions well, and this was before AI had been born.

Internally, we went through this period where we had a lot of discussions around, are we losing out to the competition, should we really go pure bot, more or less? Then, 2008 hit and our intuition of allowing our traders to focus on the risky things and then setting up machines to trade riskless or small orders paid off a lot for the firm; it was the best year the firm ever had, when everyone else was falling apart.

That was the first piece that got me to understand or to start thinking about how you can empower people and financial professionals to do what they really do well and then not get bogged down in the details.

Then, I joined Bloomberg and I spent five years there as the head of strategy and business development. The company has an amazing business, but it's built around the notion of static data. What had happened in that business was that, over a period of time, we began to see the marketplace valuing analytics more and more.

Make a distinction

Part of the role that I was brought in to do was to help them unwind that and decouple the two things -- to make a distinction within the company about static information versus analytical or valuable information. The trend that we saw was that hedge funds, especially the ones that were employing systematic investment strategies, were beginning to do two things, to embrace AI or technology to empower your traders and then also look deeper into analytics versus static data.

That was what brought me to LogitBot. I thought we could do it really well, because the players themselves don't have the time to do it and some of the vendors are very stuck in their traditional business models.

Bishop: We're seeing a kind of renaissance here, or we're at a pivotal moment, where we're moving away from analytics in the sense of business reporting tools or understanding yesterday. We're now able to mine data, get insightful, actionable information out of it, and then move into predictive analytics. And it's not just statistical correlations. I don’t want to offend any quants, but a lot of technology [to further analyze information] has come online recently, and more is coming online every day.

For us, Google had released TensorFlow, and that made a substantial difference in our ability to reason about natural language. Had it not been for that, it would have been very difficult one year ago.

At the moment, technology is really taking off in a lot of areas at once. That enabled us to move from static analysis of what's happened in the past and move to insightful and actionable information.

Ndunda: What Michael kind of touched on there is really important. A lot of traditional ways of looking at financial investment opportunities is to say that historically, this has happened. So, history should repeat itself. We're in markets where nothing that's happening today has really happened in the past. So, relying on a backward-looking mechanism of trying to interpret the future is kind of really dangerous, versus having a more grounded approach that can actually incorporate things that are nontraditional in many different ways.

So, unstructured data, what investors are thinking, what central bankers are saying, all of those are really important inputs, one part of any model 10 or 20 years ago. Without machine learning and some of the things that we are doing today, it’s very difficult to incorporate any of that and make sense of it in a structured way.

Gardner: So, if the goal is to make outlier events your friend and not your enemy, what data do you go to to close the gap between what's happened and what the reaction should be, and how do you best get that data and make it manageable for your AI and machine-learning capabilities to exploit?

Ndunda: Michael can probably add to this as well. We do not discriminate as far as data goes. What we like to do is have no opinion on data ahead of time. We want to get as much information as possible and then let a scientific process lead us to decide what data is actually useful for the task that we want to deploy it on.

As an example, we're very opportunistic about acquiring information about who the most important people at companies are and how they're connected to each other. Does this guy work on a board with this or how do they know each other? It may not have any application at that very moment, but over the course of time, you end up building models that are actually really interesting.

We scan over 70,000 financial news sources. We capture news information across the world. We don't necessarily use all of that information on a day-to-day basis, but at least we have it and we can decide how to use it in the future.

We also monitor anything that companies file and what management teams talk about at investor conferences or on phone conversations with investors.

Bishop: Conference calls, videos, interviews.
Audio to text

Ndunda: HPE has a really interesting technology that they have recently put out. You can transcribe audio to text, and then we can apply our text processing on top of that to understand what management is saying in a structural, machine-based way. Instead of 50 people listening to 50 conference calls you could just have a machine do it for you.

Gardner: Something we can do there that we couldn't have done before is that you can also apply something like sentiment analysis, which you couldn’t have done if it was a document, and that can be very valuable.

Bishop: Yes, even tonal analysis. There are a few theories on that, that may or may not pan out, but there are studies around tone and cadence. We're looking at it and we will see if it actually pans out.

Gardner: And so do you put this all into your own on-premises data-center warehouse or do you take advantage of cloud in a variety of different means by which to corral and then analyze this data? How do you take this fire hose and make it manageable?

Bishop: We do take advantage of the cloud quite aggressively. We're split between SoftLayer and Google. At SoftLayer we have bare-metal hardware machines and some power machines with high-power GPUs.

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On the Google side, we take advantage of Bigtable and BigQuery and some of their infrastructure tools. And we have good, old PostgreSQL in there, as well as DataStax, Cassandra, and their Graph as the graph engine. We make liberal use of HPE Haven APIs as well and TensorFlow, as I mentioned before. So, it’s a smorgasbord of things you need to corral in order to get the job done. We found it very hard to find all of that wrapped in a bow with one provider.

We're big proponents of Kubernetes and Docker as well, and we leverage that to avoid lock-in where we can. Our workload can migrate between Google and the SoftLayer Kubernetes cluster. So, we can migrate between hardware or virtual machines (VMs), depending on the horsepower that’s needed at the moment. That's how we handle it.

Gardner: So, maybe 10 years ago you would have been in a systems-integration capacity, but now you're in a services-integration capacity. You're doing some very powerful things at a clip and probably at a cost that would have been impossible before.

Bishop: I certainly remember placing an order for a server, waiting six months, and then setting up the RAID drives. It's amazing that you can just flick a switch and you get a very high-powered machine that would have taken six months to order previously. In Google, you spin up a VM in seconds. Again, that's of a horsepower that would have taken six months to get.

Gardner: So, unprecedented innovation is now at our fingertips when it comes to the IT side of things, unprecedented machine intelligence, now that the algorithms and APIs are driving the opportunity to take advantage of that data.

Let's go back to thinking about what you're outputting and who uses that. Is the investment result that you're generating something that goes to a retail type of investor? Is this something you're selling to investment houses or a still undetermined market? How do you bring this to market?

Natural language interface

Ndunda: Roboto, which is the natural-language interface into our analytical tools, can be custom tailored to respond, based on the user's level of financial sophistication.

At present, we're trying them out on a semiprofessional investment platform, where people are professional traders, but not part of a major brokerage house. They obviously want to get trade ideas, they want to do analytics, and they're a little bit more sophisticated than people who are looking at investments for their retirement account.  Rob can be tailored for that specific use case.

He can also respond to somebody who is managing a portfolio at a hedge fund. The level of depth that he needs to consider is the only differential between those two things.

In the back, he may do an extra five steps if the person asking the question worked at a hedge fund, versus if the person was just asking about why is Apple up today. If you're a retail investor, you don’t want to do a lot of in-depth analysis.

Bishop: You couldn’t take the app and do anything with it or understand it.

Ndunda: Rob is an interface, but the analytics are available via multiple venues. So, you can access the same analytics via an API, a chat interface, the web, or a feed that streams into you. It just depends on how your systems are set up within your organization. But, the data always will be available to you.

Gardner: Going out to that edge equation, that user experience, we've talked about how you deliver this to the endpoints, customary spreadsheets, cells, pivots, whatever. But it also sounds like you are going toward more natural language, so that you could query, rather than a deep SQL environment, like what we get with a Siri or the Amazon Echo. Is that where we're heading?

Bishop: When we started this, trying to parameterize everything that you could ask into enough checkboxes and forums pollutes the screen. The system has access to an enormous amount of data that you can't create a parameterized screen for. We found it was a bit of a breakthrough when we were able to start using natural language.

TensorFlow made a huge difference here in natural language understanding, understanding the intent of the questioner, and being able to parameterize a query from that. If our initial findings here pan out or continue to pan out, it's going to be a very powerful interface.

I can't imagine having to go back to a SQL query if you're able to do it natural language, and it really pans out this time, because we’ve had a few turns of the handle of alleged natural-language querying.

Gardner: And always a moving target. Tell us specifically about SentryWatch and Precog. How do these shake out in terms of your go-to-market strategy?
How everything relates

Ndunda: One of the things that we have to do to be able to answer a lot of questions that our customers may have is to monitor financial markets and what's impacting them on a continuous basis. SentryWatch is literally a byproduct of that process where, because we're monitoring over 70,000 financial news sources, we're analyzing the sentiment, we're doing deep text analysis on it, we're identifying entities and how they're related to each other, in all of these news events, and we're sticking that into a knowledge graph of how everything relates to everything else.

It ends up being a really valuable tool, not only for us, but for other people, because while we're building models. there are also a lot of hedge funds that have proprietary models or proprietary processes that could benefit from that very same organized relational data store of news. That's what SentryWatch is and that's how it's evolved. It started off with something that we were doing as an import and it's actually now a valuable output or a standalone product.

Precog is a way for us to showcase the ability of a machine to be predictive and not be backward looking. Again, when people are making investment decisions or allocation of capital across different investment opportunities, you really care about your forward return on your investments. If I invested a dollar today, am I likely to make 20 cents in profit tomorrow or 30 cents in profit tomorrow?

We're using pretty sophisticated machine-learning models that can take into account unstructured data sources as part of the modeling process. That will give you these forward expectations about stock returns in a very easy-to-use format, where you don't need to have a PhD in physics or mathematics.

You just ask, "What is the likely return of Apple over the next six months," taking into account what's going on in the economy.  Apple was fined $14 billion. That can be quickly added into a model and reflect a new view in a matter of seconds versus sitting down in a spreadsheet and trying to figure out how it all works out.

Gardner: Even for Apple, that's a chunk of change.

Bishop: It's a lot money, and you can imagine that there were quite a few analysts on Wall Street in Excel, updating their models around this so that they could have an answer by the end of the day, where we already had an answer.

Gardner: How do the HPE Haven OnDemand APIs help the Precog when it comes to deciding those sources, getting them in the right format, so that you can exploit?

Ndunda: The beauty of the platform is that it simplifies a lot of development processes that an organization of our size would have to take on themselves.

The nice thing about it is that a drag-and-drop interface is really intuitive; you don't need to be specialized in Java, Python, or whatever it is. You can set up your intent in a graphical way, and then test it out, build it, and expand it as you go along. The Lego-block structure is really useful, because if you want to try things out, it's drag and drop, connect the dots, and then see what you get on the other end.

For us, that's an innovation that we haven't seen with anybody else in the marketplace and it cuts development time for us significantly.

Gardner: Michael, anything more to add on how this makes your life a little easier?

Lowering cost

Bishop: For us, lowering the cost in time to run an experiment is very important when you're running a lot of experiments, and the Combinations product enables us to run a lot of varied experiments using a variety of the HPE Haven APIs in different combinations very quickly. You're able to get your development time down from a week, two weeks, whatever it is to wire up an API to assist them.

In the same amount of time, you're able to wire the initial connection and then you have access to pretty much everything in Haven. You turn it over to either a business user, a data scientist, or a machine-learning person, and they can drag and drop the connectors themselves. It makes my life easier and it makes the developers’ lives easier because it gets back time for us.

Gardner: So, not only have we been able to democratize the querying, moving from SQL to natural language, for example, but we’re also democratizing the choice on sources and combinations of sources in real time, more or less for different types of analyses, not just the query, but the actual source of the data.

Bishop: Correct.

Ndunda: Again, the power of a lot of this stuff is in the unstructured world, because valuable information typically tends to be hidden in documents. In the past, you'd have to have a team of people to scour through text, extract what they thought was valuable, and summarize it for you. You could miss out on 90 percent of the other valuable stuff that's in the document.

With this ability now to drag and drop and then go through a document in five different iterations by just tweaking, a parameter is really useful.

Gardner: So those will be IDOL-backed APIs that you are referring to.

Ndunda: Exactly.

Bishop: It’s something that would be hard for an investment bank, even a few years ago, to process. Everyone is on the same playing field here or starting from the same base, but dealing with unstructured data has been traditionally a very difficult problem. You have a lot technologies coming online as APIs; at the same time, they're also coming out as traditional on-premises [software and appliance] solutions.

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We're all starting from the same gate here. Some folks are little ahead, but I'd say that Facebook is further ahead than an investment bank in their ability to reason over unstructured data. In our world, I feel like we're starting basically at the same place that Goldman or Morgan would be.

Gardner: It's a very interesting reset that we’re going through. It's also interesting that we talked earlier about the divide between where the machine and the individual knowledge worker begins or ends, and that's going to be a moving target. Do you have any sense of how that changes its characterization of what the right combination is of machine intelligence and the best of human intelligence?

Empowering humans

Ndunda: I don’t foresee machines replacing humans, per se. I see them empowering humans, and to the extent that your role is not completely based on a task, if it's based on something where you actually manage a process that goes from one end to another, those particular positions will be there, and the machines will free our people to focus on that.

But, in the case where you have somebody who is really responsible for something that can be automated, then obviously that will go away. Machines don't eat, they don’t need to take vacation, and if it’s a task where you don't need to reason about it, obviously you can have a computer do it.

What we're seeing now is that if you have a machine sitting side by side with a human, and the machine can pick up on how the human reasons with some of the new technologies, then the machine can do a lot of the grunt work, and I think that’s the future of all of this stuff.

Bishop: What we're delivering is that we distill a lot of information, so that a knowledge worker or decision-maker can make an informed decision, instead of watching CNBC and being a single-source reader. We can go out and scour the best of all the information, distill it down, and present it, and they can choose to act on it.

Our goal here is not to make the next jump and make the decision. Our job is to present the information to a decision-maker.
Gardner: It certainly seems to me that the organization, big or small, retail or commercial, can make the best use of this technology. Machine learning, in the end, will win.

Ndunda: Absolutely. It is a transformational technology, because for the first time in a really long time, the reasoning piece of it is within grasp of machines. These machines can operate in the gray area, which is where the world lives.

Gardner: And that gray area can almost have unlimited variables applied to it.

Ndunda: Exactly. Correct.

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