How Rapid Machine Learning Accelerates Venturi Formula E Team Racing to a Top-Efficiency Strategy

A discussion on how data-driven technology and innovation are making electric racing cars an example for all endeavors where limits are tested and bested.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: Hewlett Packard Enterprise.

Dana Gardner: Hello, and welcome to the next edition of the BriefingsDirect Voice of the Customer podcast series. I’m Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator for this ongoing discussion on digital transformation success stories.

Gardner

Our next advanced automobile racing technology innovation discussion explores the Formula E racing sport. We will now learn how data-driven technology and innovation are making high-performance electric cars an example for all endeavors where limits are tested and bested.

To learn more about the latest in data-driven Formula E growth and refinement, please join me in welcoming, Susie Wolff, Team Principal at Venturi Formula E Team in Monaco.

Welcome to the show, Susie.

Susie Wolff: Thank you for having me.

Gardner: Aside from providing a great viewing and fan experience, what are the primary motivators for Formula E racing? Why did it start at all?

Race on down to Electric Avenue 

Wolff: It’s a really interesting story, because Formula E is like a startup. We are only in our fifth season, and Formula E and the management of Formula E disrupted the world of motorsport because it brought to the table a new concept of growing racing.

Wolff

We race in city centers. That means that the tracks are built up just for one-day events, right in the heart of some of the most iconic capitals throughout the world. Because it’s built up within a city center and it’s usually only a one-day event, you get very limited track time, which is quite unusual in motorsport. In the morning we get up, we test, we go straight into qualifying, and then we race.

Yet, it’s attracting a new audience because people don’t need to travel to a race circuit. They don’t need to buy an expensive ticket. The race comes to the people, as opposed to the people going out to see racing.

Obviously, the technology is something completely new for people. There is very little noise, mostly you hear the whooshing of the cars going past. It’s a showcase for new technologies, which we are all going to see appearing on the road in the next three to five years.

The automotive industry is going through a massive change with electric mobility and motorsport is following suit with Formula E.

We already see some of the applications on the roads, and I think that will increase year on year. What motorsport is so good at is testing and showcasing the very latest technology.

Gardner: I was going to ask you about the noise because I had the privilege and joy of watching a Formula One event in Monaco years ago, and the noise was a big part of it. Aside from these cars being so quiet, what is also different in terms of an electric Formula E race compared to traditional Formula One?

Wolff: The noise is the biggest factor, and that takes a bit of getting used to. It’s the roaring of the engines that creates emotion and passion. Obviously, in the Formula E cars you are missing any kind of noise.

Even the cars we are starting to drive on the roads now have a little electric start and every time I switch it on I think, “Oh, the car is not working, I have a problem.” I forget that there is no noise when you switch an electric car on.

Also, in Formula E, the way that technology is developing and how quickly it’s developing is very clear through the racing. Last season, the drivers had two cars and they had to switch cars in the middle of the race because the battery wouldn’t last long enough for a complete race distance. Now, because the battery technology has advanced so quickly, we are doing one race with one car and one battery. So I think that’s really the beauty of what Formula E is. It’s showcasing this new technology and electric mobility. Add to this the incredible racing and the excitement that brings, and you have a really enticing offering.

Gardner: Please tell us about Venturi, as a startup, and how you became Team Principal. You have been involved with racing for quite some time.

A new way to manage a driving career

Wolff: Yes, my background is predominately in racing. I started racing cars when I was only eight years old, and I made it through the ranks as a racing driver, all the way to becoming a test driver in Formula One.

Then I stepped away and decided to do something completely different and started a second career. I was pretty sure it wouldn’t be in motorsport, because my husband, Toto Wolff, works in motorsport. I didn’t want to work for him and didn’t want to work against him, so I was very much looking for a different challenge and then Venturi came along.

The President of Venturi, a great gentleman, Gildo Pastor, is a pioneer in electric mobility. He was one of the first to see the possibility of using batteries in cars, and he set a number of land speed records -- all electric. He joined Formula E from the very beginning, realizing the potential it had.

The team is based in Monaco, which is a very small principality, but one with a very rich history in racing because of the Grand Prix. Gildo had approached me previously when I was still racing to drive for his team in Formula E. I was one of the cynics, not sure Formula E was going to be for the long-term. So I said, “Thank you, but no thank you.”

But then he contacted me last year and said, “Look, I think we should work together. I think you will be fantastic running the team.” We very quickly found a great way to work together, and for me, it was just the perfect challenge. It’s a new form of racing, it’s breaking new ground and it’s at such an exciting stage of development. So, it was the perfect step for me into the business and management side of motorsports.

Gardner: For me, the noise difference is not much of an issue because the geek factor gets me jazzed about automobiles, and I don’t think I am alone in that. I love the technology. I love the idea of the tiny refinements that improve things and that interaction between the best of what people can do and what machines can do.

Tell us about your geek factor. What is new and fascinating for you about Formula E cars? What’s different from the refinement process that goes on with traditional motorsport and the new electric version?

The software challenge 

Wolff: It’s a massively different challenge than what we are used to within traditional forms of motorsport.

The new concept behind Formula E has functioned really well. Just this season, for example, we had eight races with eight different winners. In other categories, for example in Formula One, you just don’t get that. There is only the possibility for three teams to win a race, whereas in Formula E, the competition is very different.

Also, as a team, we don’t build the cars from scratch. A Formula One team would be responsible for the design and build of their whole car. In Formula E, 80 percent of the car is standardized. So every team receives the same car up to that 80 percent. The last part is the power train, the rear suspension, and some of the rear-end design of the car.

The big challenge within Formula E then, is in the software. It’s ultimately a software race: Who can develop, upgrade, and react quickly enough on the software side. And obviously, as soon as you deal with software, you are dealing with a lot of data.

That’s one of the biggest challenges in Formula E -- it’s predominantly a software race as opposed to a hardware race. If it’s hardware, it’s set at the beginning of the season, it’s homologated, and it can’t be changed.

In Formula E, the performance differentiators are the software and how quickly you can analyze, use, and redevelop your data to enable you to find the weak points and correct them quickly enough to bring to the on-track performance.

Gardner: It’s fascinating to me that this could be the ultimate software development challenge, because the 80/20 rule applies to a lot of other software development, too. The first 80 percent can be fairly straightforward and modular; it’s the last 20 percent that can make or break an endeavor.

Tell us about the real-time aspects. Are you refining the software during the race day? How does that possibly happen?

Winning: When preparation meets data 

Wolff: Well, the preparation work is a big part of a race performance. We have a simulator based back at our factory in Monaco. That’s where the bulk of the preparation work is done. Because we are dealing with only a one-day event, it means we have to get everything crammed into an eight-hour window, which leaves us very little time between stations to analyze and use the data.

The bulk of the preparation work is done in the simulator back at the factory. Each driver does between four to six days in a simulator preparing for a race. That’s where we do all of the coding and try to find the most efficient ways to get from the start to the finish of the race. That’s where we do the bulk of the analytical work.

When we arrive at the actual race, we are just doing the very fine tweaks because the race day is so compact. It means that you need to be really efficient. You need to minimize the errors and maximize the opportunities, and that’s something that is hugely challenging.

If you had a team of 200 engineers, it would be doable. But in Formula E, the regulations limit you to 20 people on your technical team on a race day. So that means that efficiency is of the utmost importance to get the best performance.

Gardner: I’m sure in the simulation and modeling phase you leverage high-performance computing (HPC) and other data technologies. But I’m particularly curious about that real-time aspect, with a limit of 20 people and the ability to still make some tweaks. How did you solve the data issues in a real-time, intensive, human-factor-limited environment like that?

Wolff: First of all, it’s about getting the right people on-board and being able to work with the right people to make sure that we have the knowhow on the team. The data is real-time, so in a race situation we are aware if there is a problem starting to arise in the car. It’s very much up to the driver to control that themselves, from within the car, because they have a lot of the controls. The very important data numbers are on their steering wheel.

They have the ability to change settings within the car -- and that’s also what makes it massively challenging for the driver. This is not just about how fast you can go, it’s also how much extra capacity you have to manage in your car and your battery -- to make sure that you are being efficient.

The data is utmost in importance for how it's created and then how quickly it can be analyzed and used to help performance. That's something HPE has been a huge benefit for us for. ... We can apply that ability to crunch the numbers more quickly.

The data is utmost in importance for how it’s created and then how quickly it can be analyzed and used to help performance. That’s something that Hewlett Packard Enterprise (HPE) has been a huge benefit to us for. First of all, HPE has been able to increase the speed at which we can send data from factory to race track, between engineers. That technology has also increased the level of our simulator and what it’s able to crunch through in the preparation work.

And that was just the start. We are now looking at all the different areas where we can apply that ability to crunch the numbers more quickly. It allows us to look at every different aspect, and it will all come down to those marginal gains in the end.

Gardner: Given that this is a team sport on many levels, you are therefore working with a number of technology partners. What do you look for in a technology partner?

Partner for performance 

Wolff: In motorsport, you very quickly realize if you are doing a good job or not. Every second weekend you go racing, and the results are shown on the track. It’s brutal because if you are at the top step of the podium, you have done a great job. If you are at the end, you need to do a better job. That’s a reality check we get every time we go racing.

For us to be the best, we need to work with the best. We’re obviously very keen to always work with the best-in-field, but also with companies able to identify the exact needs we have and build a product or a package that helps us. Within motorsports, it’s very specific. It’s not like a normal IT company or a normal business where you can plug-and-play. We need to redefine what we can do, and what will bring added performance.

We need to work with companies that are agile. Ideally they have experience within motorsports. They know what you need, and they are able to deliver. They know what’s not needed in motorsports because everything is very time sensitive. We need to make sure we are working on the areas that bring performance -- and not wasting resources and time in areas that ultimately are not going to help our track performance.

Gardner: A lot of times with motorsports it’s about eking out the most performance and the highest numbers when it comes to variables like skidpad and the amounts of friction versus acceleration. But I can see that Formula E is more about the interplay between the driver, the performance, and the electrical systems efficiency.

Is there something we can learn from Formula E and apply back to the more general electric automobile industry? It seems to me they are also fighting the battle to make the batteries last longest and make the performance so efficient that every electron is used properly.

Wolff: Absolutely. That’s why we have so many manufacturers in Formula E … the biggest names in the industry, like BMW, Audi, Jaguar and now Mercedes and Porsche. They are all in Formula E because they are all using it as a platform to develop and showcase their technology. And there are huge sums of money being spent within the automotive industry now because there is such a race on to get the right technology in the next generation of electric cars. The technology is advancing so quickly. The beauty of Formula E is that we are at the very pinnacle of that.

We are purely performance-based and it means that those race cars and power trains need to be the most efficient, and the quickest. All of the technology and everything that’s learned from the manufacturers doing Formula E eventually filters back into the organizations. It helps them to understand where they can improve and what the main challenges are for their electrification and electric mobility in the end.

Gardner: There is also an auspicious timing element here. You are pursuing the refinement and optimization of electric motorsports at the same time that artificial intelligence (AI) and machine learning (ML) technologies are becoming more pervasive, more accessible, and brought right to the very edge … such as on a steering wheel.

Is there an opportunity for you to also highlight the use of such intelligence technologies? Will data analytics start to infer what should be happening next, rather than just people analyzing data? Is there a new chapter, if you will, in how AI can come to bear on your quest for the Formula E best?

AI accelerates data 

Wolff: A new chapter is just beginning. Certainly, in some of the conversations we’ve had with our partners -- and particularly with HPE -- it’s like opening up a treasure chest, because the one thing we are very good at in motorsports is generating lots of data.

The one thing that we are clear at, and it’s purely down to manpower and time and resource, is the analyzing of data. There is only so much that we have capacity for. And with AI there are a couple of examples that I wouldn’t even want to share because I wouldn’t want my competitors to know what’s possible.

There are a couple of examples where we have seen that AI can constitute the numbers in a matter of seconds and spit out the results. I can’t even comprehend how long it would take us to get to those numbers otherwise. It’s a clear example of how much AI is going to accelerate our learning on the data side, and, particularly, because it’s software, there’s so much analyzing of the data needed to bring new levels of performance. For us it’s going to be game changer and we are only at the start.

It’s incredibly exciting but also so important to make sure that we are getting it right. There is so much possibility that if we don’t get it right, there could be big areas that we could end up losing on.

Gardner: Perhaps soon, race spectators will not only be watching the cars and how fast they are going. Perhaps there will be a dashboard that provides views of the AI environment’s performance, too. It could be a whole new type of viewer experience -- when you’re looking at what the AI can do as well as the car. Whoever thought that AI would be a spectator sport?

Wolff: It’s true and it’s not far away. It’s very exciting to think that that could be coming.

Gardner: I’ll be watching. I am afraid we will have to leave it there. We have been discussing how data-driven technology and innovation are making Formula E racing an example for all endeavors where limits are tested and bested.

Please join me in thanking our guest, Susie Wolff, Team Principal at Venturi Formula E based in Monaco. Thank you so much, Susie.

Wolff: Thank you very much.

Gardner: And a big thank you as well to our audience for joining this BriefingsDirect Voice of the Customer digital transformation success story. I’m Dana Gardner, Principal Analyst at Interarbor Solutions, your host for this ongoing series of Hewlett Packard Enterprise-sponsored interviews.

Thanks again for listening, please pass this along to your IT community, and do come back next time.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: Hewlett Packard Enterprise.

A discussion on how data-driven technology and innovation are making electric cars an example for all endeavors where limits are tested and bested. Copyright Interarbor Solutions, LLC, 2005-2019. All rights reserved.

You may also be interested in:

• How HPC supports 'continuous integration of new ideas' for optimizing Formula 1 car design
• The budding storage relationship between HPE and Cohesity brings the best of startup innovation to global enterprise reach
• HPE’s Erik Vogel on what's driving success in hybrid cloud adoption and optimization
• The budding storage relationship between HPE and Cohesity brings the best of startup innovation to global enterprise reach
• Using AI to Solve Data and IT Complexity--And Better Enable AI
• How automation and intelligence blend with design innovation to enhance the experience of modern IT
• How HCI forms a simple foundation for hybrid cloud, edge, and composable infrastructure
• How Ferrara Candy depends on automated IT intelligence to support rapid business growth
• How real-time data streaming and integration set the stage for AI-driven DataOps

HPE’s Erik Vogel on Key Factors for Driving Success in Hybrid Cloud Adoption and Optimization

A discussion on innovation around maturing hybrid cloud models and how proper common management of hybrid cloud operations makes or breaks the expected benefits.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: Hewlett Packard Enterprise.

Dana Gardner: Hello, and welcome to the next edition of the BriefingsDirect Voice of the Innovator podcast series. I’m Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator for this ongoing discussion on the latest insights into hybrid cloud strategies.

Gardner

While many businesses recognize there’s a hybrid cloud future, far fewer are adopting a hybrid cloud approach with an overabundance of due diligence, governance, and cost optimization -- at least not yet. As with the often ad hoc adoption of public cloud services by various groups across an enterprise, getting the right mix and operational coordination required of true hybrid cloud cannot be successful if it’s not well managed.

Stay with us now as we examine the innovation maturing around hybrid cloud models, operations, and how proper common management of hybrid cloud can make or break the realization of its promised returns.

Here to help us learn more about safeguarding successful hybrid cloud deployments and operations is Erik Vogel, Global Vice President of Hybrid IT and Cloud at Hewlett Packard Enterprise (HPE). Welcome, Erik.

Erik Vogel: Thank you, Dana.

Gardner: Let’s dive into why businesses are getting stuck. Cloud was very attractive, people jumped into it, but like many things, there are unintended consequences. What’s driving cloud and hybrid cloud adoption, and what’s holding people back?

Vogel: All enterprises are hybrid at this point, and whether they have accepted that realization depends on the client. But pretty much all of them are hybrid. They are all using a combination of on-premises, public cloud, and software-as-a-service (SaaS) solutions. They have brought all of that into the enterprise. There are very few enterprises we talk to that don’t have some hybrid mix already in place.

Hybrid is here, but needs sorting

Vogel

But when we ask them how they got there; most have done it in an ad hoc fashion. Most have had developers who went out to one or multiple hyperscale cloud providers, or the business units went out and started to consume SaaS solutions, or IT organizations built their own on-premises solutions whether that’s an open private cloud or a Microsoft Azure Stack environment.

They have done all of this in pockets within the organization. Now, they are seeing the challenge of how to start managing and operating this in a consistent, common fashion. There are a lot of different solutions and technologies, yet everyone has their own operating model, own consoles, and own rules to work within.

And that is where we see our clients struggling. They don’t have a holistic strategy or approach to hybrid, but rather they’ve done it in this bespoke or ad hoc fashion. Now they realize they are going to have to take a step back to think this through and decide what is the right approach to enforce common governance and gain common management and operating principles, so that they’re not running 5, 6, 8 or even 10 different operating models. Rather, they need to ask, “How do we get back to where we started?” And that is a common operating model across the entire IT estate.

Gardner: IT traditionally over the years has had waves of adoption that led to heterogeneity that created complexity. Then that had to be managed. When we deal with multicloud and hybrid cloud, how is that different from the UNIX wars, or distributed computing, and N-tier computing? Why is cloud a more difficult heterogeneity problem to solve than the previous ones?

Vogel: It’s more challenging. It’s funny, we typically referred to what we used to see in the data center as the Noah’s Ark data center. You would typically walk into a data center and you’d see two of everything, two of every vendor, just about everything within the data center.

How to Better Manage
Multicloud Sprawl

And it was about 15 years ago when we started to consolidate all of that into common infrastructures, common platforms to reduce the operational complexity. It was an effort to reduce total cost of ownership (TCO) within the data center and to reduce that Noah’s Ark data center into common, standardized elements.

Now that pendulum is starting to swing back. It’s becoming more of a challenge because it’s now so easy to consume non-standard and heterogeneous solutions. Before there was still that gatekeeper to everything within the data center. Somebody had to make a decision that a certain piece of infrastructure or component would be deployed within the data center.

Now, we have developers go to a cloud and consume with just a swipe of a credit card, any of the three or four hybrid hyperscale solutions, and literally thousands of SaaS solutions. Just look at the Salesforce.com platform and all of the different options that surround that.

All of a sudden, we lost the gatekeeper. Now we are seeing sprawl toward more heterogeneous solutions occurring even much faster than what we saw 10 or 15 years ago with the Noah’s Ark data center.

The pendulum is definitely shifting back toward consuming lots of different solutions with lots of different capabilities and services. And we are seeing it moving much faster than it did before because of that loss of a gatekeeper.

Gardner: Another difference is that we’re talking mostly about services. By consuming things as services, we’re acquiring them not as a capital expenditure that has a three- to five-year cycle of renewal, this is on-demand consumption, as you use it.

That makes it more complicated, but it also makes it a problem that can be solved more easily. Is there something about the nature of an all-services’ hybrid and multicloud environment on an operations budget that makes it more solvable?

Services become the norm 

Vogel: Yes, absolutely. The economics definitely play into this. I have this vision that within the next five years, we will no longer call things “as a service” because it will be the norm, the standard. We will only refer to things that are not as a service, because as an industry we are seeing a push toward everything being consumed as a service.

From an operating standpoint, the idea of consuming and paying for only what we use is very, very attractive. ... [Before] we would end up overbuying, pay the full load, and still pay for full maintenance and support, too.

From an operating standpoint, the idea of consuming and paying for only what we use is very, very attractive. Again, if you look back 10 or 15 years, typically within a data center, we’d be buying for a three- or four-year lifespan. That forced us to make predictions as to what type of demand we would be placing on capital expenditures.

And what would happen? We would always overestimate. If you looked at utilization of CPU, of disk, of memory, they were always 20 to 25 percent; very low utilization, especially pre-virtualization. We would end up overbuying, pay the full load, and still pay for full maintenance and support, too.

There was very little ability to dial that up or down. The economic capability of being able to consume everything as a service is definitely changing the game, even for things you wouldn’t think of as a service, such as buying a server. Our enterprise customers are really taking notice of that because it gives them the ability to flex the expenditures as their business cycles go up and down.

Rarely do we see enterprises with constant demand for compute capacity. So, it’s very nice for them to be able to flex that up and down, adjust the normal seasonal effects within a business, and be able to flex that operating expense as their business fluctuates.

That is a key driver of moving everything to an as-a-service model, giving flexibility that just a few years ago we did not have.

Gardner: The good news is that these are services -- and we can manage them as services. The bad news is these are services coming from different providers with different economic and consumption models. There are different application programming interfaces (APIs), stock keeping unit (SKU) definitions, and management definitions that are unique to their own cloud organization. So how do we take advantage of the fact that it’s all services but conquer the fact that it’s from different organizations speaking, in effect, different languages?

Vogel: You’re getting to the heart of the challenge in terms of managing a hybrid environment. If you think about how applications are becoming more and more composed now, they are built with various different pieces, different services, that may or may not be on-premises solutions.

One of our clients, for example, has built an application for their sales teams that provides real-time client data and client analytics before a seller goes in and talks to a customer. And when you look at the complexity of that application, they are using Salesforce.com, they have an on-premises customer database, and they get point of sales solutions from another SaaS provider.

Why You Need Everything
As a Service

They also have analytics engines they get from one of the cloud hyperscalers. And all of this comes together to drive a mobile app that presents all of this information seamlessly to their end-user seller in real-time. They become better armed and have more information when they go meet with their end customer.

When we look at how these new applications or services – I don’t even call them applications because they are more services built from multiple applications -- they are crossing multiple service providers, multiple SaaS providers, and multiple hyperscalers.

And as you look at how we interface and connect with those, how we pass data, exchange information across these different service providers, you are absolutely right, the taxonomies are different, the APIs are different, the interfaces and operations challenges are different.

When that seller goes to make that call, and they bring up their iPad app and all of a sudden, there is no data or it hasn’t been refreshed in three months, who do you call? How do you start to troubleshoot that? How do you start to determine if it’s a Salesforce problem, a database problem, a third-party service provider problem? Maybe it’s my encrypted connection I had to install between Salesforce and my on-premises solution. Maybe it’s the mobile app. Maybe it’s a setting on the iPad itself.

Adding up all of that complexity is what’s building the problem. We don’t have consistent APIs, consistent taxonomies, or even the way we look at billing and the underlying components for billing. And when we break that out, it varies greatly between service providers.

This is where we understand the complexity of hybrid IT. We have all of these different service providers all working and operating independently. Yet we’re trying to bring them together to provide end-customer services. Composing those different services creates one of the biggest challenges we have today within hybrid cloud environment.

Gardner: Even if we solve the challenge on the functional level -- of getting the apps and services to behave as we want -- it seems as much or more a nightmare for the chief financial officer (CFO) who has to determine whether you’re getting a good deal or buying redundancy across different cloud providers. A lot of times in procurement you cut a deal on volume. But how you do that if you don’t know what you’re buying from whom?

How do we pay for these aggregate cloud services in some coordinated framework with the least amount of waste?

How to pay the bills 

Vogel: That is probably one of the most difficult jobs within IT today, the finance side of it. There are a lot of challenges of putting that bill together. What does that bill really look like? And not just at an individual component level. I may be able to see what I’m paying from Amazon Web Services (AWS) or what Azure Stack is costing me. But how do we aggregate that? What is the cost to provide a service? And this has been a challenge for IT forever. It’s always been difficult to slice it by service.

We knew what compute costs, what network costs, and what the storage costs were. But it was always difficult to make that vertical slice across the budget. And now we have made that problem worse because we have all these different bills coming in from all of these different service providers.

The procurement challenge is even more acute because now we have these different service providers. How do we know what we are really paying? Developers swipe credit cards, where they don’t even see the bill or a true accounting of what’s being spent across the public clouds. It comes through as a credit card expense and so not really directed to IT.

We need to get our hands around these different expenses, where we are spending money, and think differently about our procurement models for these services.

In the past, we talked about this as a brokerage but it’s a lot more than that. It’s more about strategic sourcing procurement models for cloud and hybrid cloud-related services.

Our IT procurement models have to change to address the problem of how we really know what we are paying for. Are we getting the strategic value out of the expenses within hybrid that we had expected?

It’s less about brokerage and looking for that lowest-cost provider and trying to reduce the spend. It’s more about, are we getting the service-level agreements (SLAs) we are paying for? Are we getting the services we are paying for? Are we getting the uptime we are paying for?

Our IT procurement models have to change to address the problem of how we really know what we are paying for. Are we getting the strategic value out of the expenses within hybrid that we had expected?

Gardner: In business over the years, when you have a challenge, you can try to solve it yourself and employ intelligence technologies to tackle complexity. Another way is to find a third-party that knows the business better than you do, especially for small- to medium-sized businesses (SMBs).

Are we starting to see an ecosystem develop where the consumption model for cloud services is managed more centrally, and then those services are repurposed and resold to the actual consumer business?

Third-parties help hybrid manage costs 

Vogel: Yes, I am definitely starting to see that. There’s a lot is being developed to help customers in terms of consuming and buying these services and being smarter about it. I always joke that the cheapest thing you can buy is somebody else’s experience, and that is absolutely the case when it comes to hybrid cloud services providers.

The reality is no enterprise can have expertise in all three of the hyperscalers, in all of the hundreds of SaaS providers, for all of the on-premises solutions that are out there. It just doesn’t exist. You just can’t do it all.

It really becomes important to look for people who can aggregate this capability and bring the collective experience back to you. You have to reduce overspend and make smarter purchasing decisions. You can prevent things like lock-in to and reduce the risk of buying via these third-party services. There is tremendous value being created by these firms that are jumping into that model and helping clients address these challenges.

The third-parties have people who have actually gone out and consumed and purchased within the hyperscalers, who have run workloads within those environments, and who can help predict what the true cost should be -- and, more importantly, maintain that optimization going forward.

How to Remove Complexity
From Multicloud and Hybrid IT

It’s not just about going in and buying anymore. There is ongoing optimization that has to incur, ongoing cost optimization where we’re continuously evaluating about the right decisions. And we are finding that the calculus changes over time.

So, while it might have made a lot of sense to put a workload, for example, on-premises today, based on the demand for that application and on pricing changes, it may make more sense to move that same workload off-premises tomorrow. And then in the future it may also make sense to bring it back on-premises for a variety of reasons.

You have to constantly be evaluating that. That’s where a lot of the firms playing in the space can add a lot of value now, in helping with ongoing optimization, by making sure that we are always making the smart decision. It’s a very dynamic ecosystem, and the calculus, the metrics are constantly changing. We have the ability to constantly reevaluate. That’s the beauty of cloud, it’s the ability to flex between these different providers.

Gardner: Erik, for those organizations interested in getting a better handle on this, are there any practical approaches available now?

The right mix of data and advice 

Vogel: We have a tool, called HPE Right Mix Advisor, which is our ability to go in and assess very large application portfolios. The nice thing is, it scales up and down very nicely. It is delivered in a service model so we are able to go in and assess a set of applications against the variables I mentioned, in the weighing of the factors, and come up with a concrete list of recommendations as to what should our clients do right now.

In fact, we like to talk not about the thousand things they could do -- but what are the 10 or 20 things they should start on tomorrow morning. The ones that are most impactful for their business.

The Right Mix Advisor tool helps identify those things that matter the most for the business right now, and provides a tactical plan to say, “This is what we should start on.”

And it’s not just the tool, we also bring our expertise, whether that’s from our Cloud Technology Partners (CTP) acquisition, RedPixie, or our existing HPE business where we have done this for years and years. So, it’s not just the tool, but also experts, looking at that data, helping to refine that data, and coming up with a smart list that makes sense for our clients to get started on right now.

And of course, once they have accomplished those things, we can come back and look at it again and say, “Here is your next list, the next 10 or 20 things.” And that’s really how Right Mix Advisor was designed to work.

Gardner: It seems to me there would be a huge advantage if you were able to get enough data about what’s going on at the market level, that is to aggregate how the cloud providers are selling, charging, and the consumption patterns.

If you were in a position to gather all of the data about enterprise consumption among and between the cloud providers, you would have a much better idea of how to procure properly, manage properly, and optimize. Is such a data well developing? Is there anyone in the right position to be able to gather the data and start applying machine learning (ML) technologies to develop predictions about the best course of action for a hybrid cloud or hybrid IT environment?

Vogel: Yes. In fact, we have started down that path. HPE has started to tackle this by developing an expert system, a set of logic rules that helps make those decisions. We did it by combining a couple of fairly large datasets that we have developed over the last 15 years, primarily with HPE’s history of doing a lot of application migration work. We really understand on the on-premises side where applications should reside based on how they are architected and what the requirements are, and what type of performance needs to be derived from that application.

HPE has developed an expert system, a set of logic rules, that helps make those hybrid decisions. We did it by combining a couple of fairly large datasets that we have developed over the last 15 years. We understand the on-premises side ... We have now combined that with our other datasets from our acquisitions of CTP and RedPixie.

We have combined that with other datasets from some of our recent cloud acquisitions, CTP and RedPixie, for example. That has brought us a huge wealth of information based on a tremendous number of application migrations to the public clouds. And we are able to combine those datasets and develop this expert system that allows us to make those decisions pretty quickly as to where applications should reside based on a number of factors. Right now, we look at about 60 different variables.

But what’s really important when we do that is to understand from a client’s perspective what matters. This is why I go back to that strategic sourcing discussion. It’s easy to go in and assume that every client wants to reduce cost. And while every client wants to do that -- no one would ever say no to that -- usually that’s not the most important thing. Clients are worried about performance. They also want to drive agility, and faster time to market. To them that is more important than the amount they will save from a cost-reduction perspective.

The first thing we do when we run our expert system, is we go in and weight the variables based on what’s important to that specific client, aligned to their strategy. This is where it gets challenging for any enterprise trying to make smart decisions. In order to make strategic sourcing decisions, you have to understand strategically what’s important to your business. You have to make intelligent decisions about where workloads should go across the hybrid IT options that you have. So we run an expert system to help make those decisions.

Now, as we collect more data, this will move toward more artificial intelligence (AI). I am sure everybody is aware AI requires a lot of data, since we are still in the very early stages of true hybrid cloud and hybrid IT. We don’t have a massive enough dataset yet to make these decisions in a truly automated or learning-type model.

We started with an expert system to help us do that, to move down that path. But very quickly we are learning, and we are building those learnings into our models that we use to make decisions.

So, yes, there is a lot of value in people who have been there and done that. Being able to bring that data together in a unified fashion is exactly what we have done to help our clients. These decisions can take a year to figure out. You have to be able to make these decisions quickly because it’s a very dynamic model. A lot of things are constantly changing. You have to keep loading the models with the latest and greatest data so you are always making the best, smartest decision, and always optimizing the environment.

Innovation, across the enterprise 

Gardner: Not that long ago, innovation in a data center was about speeds and feeds. You would innovate on technology and pass along those fruits to your consumers. But now we have innovated on economics, management, and understanding indirect and direct procurement models. We have had to innovate around intelligence technologies and AI. We have had to innovate around making the right choices -- not just on cost but on operations benefits like speed and agility.

How has innovation changed such that it used to be a technology innovation but now cuts across so many different dynamic principles of business?

Vogel: It’s a really interesting observation. That’s exactly what’s happening. You are right, even as recently as five years ago we talked about speeds and feeds, trying to squeeze a little more out of every processor, trying to enhance the speed of the memory or the storage devices.

But now, as we have pivoted toward a services mentality, nobody asks when you buy from a hyperscaler -- Google Cloud, for example -- what central processing unit (CPU) chips they are running or what the chip speeds are. That’s not really relevant in an as-a-service world. So, the innovation then is around the service sets, the economic models, the pricing models, that’s really where innovation is being driven.

At HPE, we have moved in that direction as well. We provide our HPE GreenLake model and offer a flex-capacity approach where clients can buy capacity on-demand. And it becomes about buying compute capacity. How we provide that, what speeds and feeds we are providing becomes less and less important. It’s the innovation around the economic model that our clients are looking for.

We are only going to continue to see that type of innovation going forward, where it’s less about the underlying components. In reality, if you are buying the service, you don’t care what sort of chips and speeds and feeds are being provided on the back end as long as you are getting the service you have asked for, with the SLA, the uptime, the reliability, and the capabilities you need. All of what sits behind that becomes less and less important.

Think about how you buy electricity. You just expect 110 volts at 60 hertz coming out of the wall, and you expect it to be on all the time. You expect it to be consistent, reliable, and safely delivered to you. How it gets generated, where it gets generated -- whether it’s a wind turbine, a coal-burning plant, a nuclear plant -- that’s not important to you. If it’s produced in one state and transferred to another over the grid, or if it’s produced in your local state, that all becomes less important. What really matters is that you are getting consistent and reliable services you can count on.

How to Leverage Cloud, IoT,
Big Data, and Other Disruptive Technologies

And we are seeing the same thing within IT as we move to that service model. The speeds and feeds, the infrastructure, become less important. All of the innovation is now being driven around the as-a-service model and what it takes to provide that service. We innovate at the service level, whether that’s for flex capacity or management services, in a true as-a-service capability.

Gardner: What do your consumer organizations need to think about to be innovative on their side? How can they be in a better position to consume these services such as hybrid IT management-as-a-service, hybrid cloud decision making, and the right mixture of decisions-as-a-service?

What comes next when it comes to how the enterprise IT organization needs to shift?

Business cycles speed IT up 

Vogel: At a business level, within almost every market or every industry, we are moving from what used to be slow-cycle business to standard-cycles. In a lot of cases it’s moving from standard-cycle business to a fast-cycle business. Even businesses that were traditionally slow-cycle or standard-cycle are accelerating. This underlying technology is creating that.

So every company is a technology company. That is becoming more and more true every day. As a result, it’s driving business cycles faster and faster. So, IT, in order to support those business cycles, has to move at that same speed.

And we see enterprises moving away from a traditional IT model when those enterprises’ IT cannot move at the speed the business is demanding. We will still see IT, for example, take six months to provide a platform when the business says, “I need it in 20 minutes.”

We will see a split between traditional IT and a digital innovation group within the enterprise. This group will be owned by the business unit as opposed to core IT.

So, businesses are responding to IT not being able to move fast enough and not being able to provide the responsiveness and the level of service by going out and looking outside and consuming services externally.

At HPE, as we look at some of the services we have announced, they are to help our clients move faster and to provide operational support and management for hybrid to remove that burden from IT so they can focus on the things that accelerate their businesses.

As we move forward, how can clients start to move in this direction? At HPE, as we look at some of the services we have announced and will be rolling out in the next six-12 months, they are to help our clients move faster. They are designed to provide operational support and management for hybrid to take that burden away from IT, especially where IT may not have the skill sets or capability and be able to provide that seamless operating experience to our IT customers. Those customers need to focus on the things that accelerate their business -- that is what the business units are demanding.

To stay relevant, IT is going to have to do that, too. They are going to have to look for help and support so that they can move at the same speed and pace that businesses are demanding today. And I don’t see that slowing down. I don’t think anybody sees that slowing down; if anything, we see the pace continuing to accelerate.

When I talked about fast-cycle -- where services or solutions we put into the market may have had a market shelf life of two to three years -- we are seeing it compressed to six months. It’s amazing how fast competition comes in even if we are doing innovative type of solutions. So, IT has to accelerate at that speed as well.

The HPE GreenLake hybrid cloud offering, for example, gives our clients the ability to operate at that speed by providing managed services capabilities across the hybrid estate. It provides a consistent platform, and then allows them to innovate on top of it. It takes away the management operation from their focus and lets them focus on what matters to the business today, which is innovation.

Gardner: For you personally, Erik, where do you get inspiration for innovation? How do you think out of the box when we can now see that that’s a necessary requirement? 

Inspired by others 

Vogel: One of the best parts about my job is the time I get to spend with our customers and to really understand what their challenges are and what they are doing. One of the things we look at are adjacent businesses.

We try to learn what is working well in retail, for example. What innovation is there and what lessons learned can we apply elsewhere? A lot of times the industry shifts so quickly that we don’t have all of the answers. We can’t take a product-out approach any longer. We really have to start looking at the customers’ back end. And I think having kind of that broad view and looking outside is really helping us. It’s where we are getting a lot of our inspiration.

For example, we are really focused on the overall experience that our clients have with HPE, and trying to drive a very consistent, standardized, easy-to-choose type of experience with us as a company. And it’s interesting as an engineering company, with a lot of good development and engineering capabilities, that we tend to look at it from a product-out view. We build a portal that they can work within, we create better products, and we get that out in front of the customer.

But by looking outside, we are saying, “Wait a minute, what is it, for example, about Uber that everybody likes?” It’s not necessarily that their app is good, but it’s really about the clean car, it’s about not having to pay when you get out of the car, not have to fumble for a credit card. It’s about seeing a map and knowing where the driver is. It’s about a predictable cost, where you know what it’s going to cost. And that experience, that overall experience is what makes Uber, Uber. It’s not just creating an app and saying, “Well, the app is the experience.”

We are learning a lot from adjacent businesses, adjacent industries, and incorporating that into what we are doing. It’s just part of that as-a-service mentality where we have to think about the experience our customers are asking for and how do we start building solutions that meet that experience requirement -- not just the technical requirement. We are very good at that, but how do we start to meet that experience requirement?

How to Develop Hybrid
Cloud Strategies With Confidence

And this has been a real eye-opener for me personally. It has been a really fun part of the job, to look at the experience we are trying to create. How do we think differently? Rather than producing products and putting them out into the market, how do we think about creating that experience first and then designing and creating the solutions that sit underneath it?

When you talk about where we get inspiration, it’s really about looking at those adjacencies. It’s understanding what’s happening in the broader as-a-service market and taking the best of what’s happening and saying, “How can we employ those types of techniques, those tricks, those lessons learned into what we are doing?” And that’s really driving a lot of our development and inspiration in terms of how we are innovating as a company within HPE.

Gardner: I’m afraid we will have to leave it there. We have been exploring how innovation is maturing around hybrid cloud models and operations. And we have learned how a proper management of hybrid cloud and hybrid IT can make or break the realization of the promised benefits.

So please join me in thanking our guest, Erik Vogel, Global Vice President of Hybrid IT and Cloud at HPE. Thank you so much, Erik.

Vogel: Thank you.

Gardner: And a big thank you as well to our audience for joining this BriefingsDirect Voice of the Innovator interview. I’m Dana Gardner, Principal Analyst at Interarbor Solutions, your host for this ongoing series of Hewlett Packard Enterprise-sponsored discussions.

Thanks again for listening, please pass this along to your IT community, and do come back next time.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: Hewlett Packard Enterprise.

A discussion on innovation around maturing hybrid cloud models and how proper common management of hybrid cloud operations makes or breaks the expected benefits. Copyright Interarbor Solutions, LLC, 2005-2019. All rights reserved.

You may also be interested in:

• How total deployment intelligence overcomes the growing complexity of multicloud management
• Using AI to solve data and IT complexity -- and thereby better enable AI
• How Automation and Intelligence Blend with Design Innovation to Enhance the Experience of Modern IT
• How HCI forms a simple foundation for hybrid cloud, edge, and composable infrastructure
• How Ferrara Candy depends on automated IT intelligence to support rapid business growth
• How real-time data streaming and integration set the stage for AI-driven DataOps
• How the composable approach to IT aligns automation and intelligence to overcome mounting complexity
• How Texmark Chemicals pursues analysis-rich, IoT-pervasive path to the ‘refinery of the future’
• How HPC supports 'continuous integration of new ideas' for optimizing Formula 1 car design