Friday, February 8, 2019

Manufacturer gains advantage by expanding IoT footprint from many machines to many insights

https://www.cubep.com/

The next BriefingsDirect manufacturing modernization and optimization case study centers on how a Canadian maker of containers leverages the Internet of Things (IoT) to create a positive cycle of insights and applied learning.

We will now hear how CuBE Packaging Solutions, Inc. in Aurora, Ontario has deployed edge intelligence to make 21 formerly isolated machines act as a single, coordinated system as it churns out millions of reusable package units per month.

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

Stay with us as we explore how harnessing edge data with more centralized real-time analytics integration cooks up the winning formula for an ongoing journey of efficiency, quality control, and end-to-end factory improvement.


Here to describe the challenges and solutions for injecting IoT into a plastic container’s production advancement success journey is Len Chopin, President at CuBE Packaging Solutions. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Len, what are the top trends and requirements driving the need for you to bring more insights into your production process?

Chopin
Chopin: The very competitive nature of injection molding requires us to stay ahead of the competition and utilize the intelligent edge to stay abreast of that competition. By tapping into and optimizing the equipment, we gain on downtime efficiencies, improved throughput, and all the things that help drive more to the bottom line.

Gardner: And this is a win-win because you’re not only improving quality but you're able to improve the volume of output. So it’s sort of the double-benefit of better and bigger.

Chopin: Correct. Driving volume is key. When we are running, we are making money, and we are profitable. By optimizing that production, we are even that much more profitable. And by using analytics and protocols for preventive and predictive maintenance, the IoT solutions drive an increase the uptime on the equipment.

Gardner: Why are sensors in of themselves not enough to attain intelligence at the edge?

Chopin: The sensors are reactive. They give you information. It’s good information. But leaving it up to the people to interpret [the sensor data] takes time. Utilizing analytics, by pooling the data, and looking for trends, means IoT is pushing to us what we need to know and when.

Otherwise we tend to look at a lot of information that’s not useful. Utilizing the intelligent edge means it's pushing to us the information we need, when we need it, so we can react appropriately with the right resources.

Gardner: In order to understand the benefits of when you do this well, let's talk about the state at CuBE Packaging when you didn't have sensors. You weren't processing and you weren't creating a cycle of improvement?
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Chopin: That was firefighting mode. You really have no idea of what's running, how it’s running, is it trending down, is it fast enough, and is it about to go down. It equates to flying blind, with blinders on. It’s really hard in a manufacturing environment to run a business that way. A lot of people do it, and it’s affordable -- but not very economical. It really doesn’t drive more value to the bottom line.

Gardner: What have been the biggest challenges in moving beyond that previous “firefighting” state to implementing a full IoT capability?

Chopin: The dynamic within our area in Canada is resources. There is lot of technology out there. We rise to the top by learning all about what we can do at the edge, how we can best apply it, and how we can implement that into a meaningful roadmap with the right resources and technical skills of our IT staff.

It’s a new venture for us, so it's definitely been a journey. It is challenging. Getting that roadmap and then sticking to the roadmap is challenging, but as we go through the journey we learn the more relevant things. It's been a dynamic roadmap, which it has to be as the technology evolves and we delve into the world of IoT, which is quite fascinating for us.

Gardner: What would you say has been the hardest nut to crack? Is it the people, the process, or the technology? Which has been the most challenging?

Trust the IoT process

Chopin: I think the process, the execution. But we found that once you deploy IoT, and you begin collecting data and embarking on analytics, then the creative juices become engaged with a lot of the people who previously were disinterested in the whole process.

But then they help steer the ship, and some will change the direction slightly or identify a need that we previously didn't know about – a more valuable way than the path we were on. So people are definitely part of the solution, not part of the problem. For us, it’s about executing to their new expectations and applying the information and technology to find solutions to their specific problems.

We have had really good buy-in with the people, and it’s just become about layering on the technical resources to help them execute their vision.

Gardner: You have referred to becoming, “the Google of manufacturing.” What do you mean by that, and how has Hewlett Packard Enterprise (HPE) supported you in gaining that capability and intelligence?

People are definitely part of the solution, not part of the problem. For us, it's about executing to their new expectations and applying information and technology to find solutions to specific problems.
Chopin: “The Google of manufacturing” was first coined by our owner, JR. It’s his vision so it’s my job to bring it to fruition. The concept is that there’s a lot of cool stuff out there, and we see that IoT is really fascinating.

My job is to take that technology and turn it into an investment with a return on investment (ROI) from execution. How is that all going to help the business? The “Google of manufacturing” is about growth for us -- by using any technology that we see fit and having the leadership to be open to those new ideas and concepts. Even without having a clear vision of the roadmap, it means focusing on the end results. It’s been a unique situation. So far it’s been very good for us.

Gardner: How has HPE helped in your ability to exploit technologies both at the edge and at the data center core?

Chopin: We just embarked on a large equipment expansion [with HPE], which is doubling our throughput. Our IT backbone, our core, was just like our previous equipment -- very old, antiquated, and not cutting edge at all. It was a burden as opposed to an asset.

Part of moving to IoT was putting in a solid platform, which HPE has provided. We work with our integrator and a project team that mapped out our core for the future. It’s not just built for today's needs -- it's built for expansion capabilities. It's built for year-two, year-three. Even if we’re not fully utilizing it today -- it has been built for the future.

https://www.cubep.com/
HPE has more things coming down the pipeline that are built on and integrated to this core, so that there are no real limitations to the system. No longer will we have to scrap an old system and put a new one in. It’s now scalable, which we think of as the platform for becoming the “Google of manufacturing,” and which is going to be critical for us.

Gardner: Future-proofing infrastructure is always one of my top requirements. All right, please tell us about CuBE Packaging, your organization’s size, what you're doing, and what end products are.

The CuBE takeaway

Chopin: We have a 170,000-square-foot facility, with about 120 employees producing injection-molded plastic containers for the food service industry, for home-meal replacement, and takeout markets, distributed to Canada as well as the US, which is obviously a huge and diverse market.

We also have a focus on sustainability. Our products are reusable and recyclable. They are a premier product that come with a premier price. They are also customizable and brandable, which has been a key to CuBE’s success. We partner with restaurants, with sophisticated customers, who see a value in the specific branding and of having a robust packaging solution.

Gardner: Len, you mentioned that you're in a competitive industry and that margin is therefore under pressure. For you to improve your bottom line, how do you account for more productivity? How are you turning what we have described in terms of an IoT and data capability into that economic improvement to your business outcome?

Chopin: I refer to this as having a plant within a plant. There is always lot more you can squeeze out of an operation by knowing what it’s up to, not day-by-day, but minute-by-minute. Our process is run quite quickly and so slippage in machine cycle times can occur rapidly. We must grasp the small slippages, or predict failures, or when something is out of technical specifications from the injection molding standpoint or we could be producing a poor-quality product.

Getting a handle on what the machines are doing, minute-by-minute-by-minute gives us the advantage to utilize the assets and the people and so to optimize the uptime, as well as improve our quality, to get more of the best product to the market. So it really does drive value right to the bottom line.
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Gardner: A big buzzword in the industry now is artificial intelligence (AI). We are seeing lots of companies dabble in that. But you need to put in place certain things before you can take advantage of those capabilities that not only react but have the intelligence to prescribe new processes for doing things even more efficiently.

Are you working in conjunction with your integrator and HPE to allow you to exploit AI when it becomes mature enough for organizations like your own?

AI adds uptime 

Chopin: We are already embarking on using sensors for things that were seemingly unrelated. For example, we are picking up data points off of peripheral equipment that feed into the molding process. This provides us a better handle on those inputs to the process, inputs to the actual equipment, rather than focusing on the throughput and of how many parts we get in a given day.

For us, the AI is about that equipment uptime and of preventing any of it going down. By utilizing the inputs to the machines, it can notify us in advance, when we need to be notified.

Rather than monitoring equipment performance manually with a clipboard and a pen, we can check on run conditions or temperatures of some equipment up on the roof that's critical to the operation. The AI will hopefully alert us to things that we don't know about or don't see because it could be at the far end of the operations. Yet there is a codependency on a lot of that pre-upstream equipment that feeds to the downstream equipment.

So for us to gain transparency into that end-to-end process and having intelligence built-in enough to say, “Hey, you have a problem -- not yet, but you're going to have a problem,” allows us to react before the problem occurs and causes a production upset.

Rather than monitoring equipment performance manually with a clipboard and a pen, we can check on run conditions or temperatures of some equipment up on the roof if that is critical to the operations.
Gardner: You can attain a total data picture across your entire product lifecycle, and your entire production facility. Having that allows you to really leverage AI.

Sounds like that means a lot of data over long period of time. Is there anything about what's happening at that data center core, around storage, that makes it more attractive to do this sooner than later?

Chopin: As I mentioned previously, there are a lot of data points coming off the machines. The bulk of it is useless, other than from an historical standpoint. So by utilizing that data -- not pushing forward what we don't need, but just taking the relevant points -- we piggyback on the programmable logic controllers to just gather the data that we need. Then we further streamline that data to give us what we're looking for within that process.


It's like pushing out only the needle from the haystack, as opposed to pushing the whole haystack forward. That’s the analogy we use.

Gardner: So being more intelligent about how you gather intelligence?

Chopin: Absolutely! Yes.

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

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Wednesday, February 6, 2019

Why enterprises struggle with adopting public cloud as a culture


The next BriefingsDirect digital strategies interview examines why many businesses struggle with cloud computing adoption, and how they could improve by attaining a culture directed at cloud consumption and total productivity.

Due to inertia, a lack of skills, and even outright hostility, some enterprises are stumbling in their march to cloud use due to behavior and perception -- and not the actual technology hurdles.

We will now hear from an observer of cloud adoption patterns on why a cultural solution to adoption may be more important than any other aspect of digital business transformation. 

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

Here to help us explore why cloud inertia can derail business advancement is Edwin Yuen, Senior Analyst for Cloud Services and Orchestration, Data Protection, and DevOps at Enterprise Strategy Group (ESG). [Note: Since this podcast was recorded on Nov. 15, 2018, Yuen has become principal product marketing manager at Amazon Web Services.] The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Edwin, why are enterprises finding themselves unready for public cloud adoption culturally?

Yuen: Culturally the issue with public cloud adoption is whether IT is prepared to bring in public cloud. I bring up the IT issue because public cloud usage is actually really high within business organizations.

Yuen
At ESG, we have found that cloud use is pretty significant -- well over 80 percent are using some sort of public cloud service. It’s very high for infrastructure- (IaaS) and platform-as-a-service (PaaS).

But the key here is, “What is the role of IT?” We see a lot of business end-users and others essentially doing Shadow IT – of going around IT if they feel like their needs are not met. That actually increases the friction between IT and the business.

It also leads to people going into the public cloud before they are ready, before there’s been a proper evaluation – from a technical, cost, or even a convenience point of view. That can potentially derail things.

But there is an opportunity for IT to reset the boundaries and meet the needs of the end users, of thoughtfully getting into the public cloud.

Gardner: We may be at the point of having too much of a good thing. Even if people are doing great things with cloud computing inside of an organization, unless it’s strategically oriented to process, fulfillment, and a business outcome, then the benefits be can lost. 

Plan before you go to public cloud

Yuen: When line of business (LOB) or other groups are not working with core IT in going to the public cloud, they get some advantages from it -- but they are not getting the full advantage. It’s like going from an old piece of smartphone technology, at 7 or 8 years old, and then only going up to the fifth or sixth best phone. It’s a significant upgrade, but it’s not the optimal way to do it. They’re not getting the full benefits.

The question is, “Are you getting the most out of it, and is that thoughtfulness there?” You want to maximize the capabilities and advantages you get from public cloud and minimize the inconvenience and cost. Planning is absolutely critical for that -- and it involves core IT.

So how do you bring about a cultural shift that says, “Yes, we are going into the public cloud. We are not trying to stop you. We are not being overly negative. But what we are trying to do is optimize it for everybody across the board, so that we as a company can get the most out of it because there are so many benefits -- not just incremental benefits that you get from immediately jumping in.”
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Gardner: IT needs to take a different role, of putting in guardrails in terms of cloud services consumption, compliance, and security. It seems to me that procurement is also a mature function in most enterprises. They may also want to step in.

When you have people buying goods individually on a credit card, you don’t necessarily take advantage of volume purchasing, or you don’t recognize that you can buy things in bulk and distribute them and get better deals or terms. Yet procurement groups are very good at that.

Is there an opportunity to better conduct cloud consumption like with procuring any other business service, with all the checks, balances, and best practices?

Cut cloud costs, buy in bulk

Yuen: Absolutely, and that’s an excellent point. I think people will often leave out procurement, auditing, acquisitions or whatever department that there is for cloud. It becomes critically important organizationally, especially from the end-user point of view.

From the organizational point of view, you can lose economies of scale. A lot of the cloud providers will provide those economies of scales via an enterprise agreement. That allows for purchasing power to be taken.

Yet if individuals go out and leave procurement behind, it’s like shopping at a retailer for groceries without ever checking for sales or coupons. Buying in volume is just a smarter way to centralize the entire organization so you can leverage it. It becomes a better cost for the line of business, obviously. Cloud is really a consumption-based model, so planning needs to be there.

We’ve talked to a lot of organizations. As they jump into cloud, they expect cost savings, but sometimes they get an increase in cost because once you have that consumption model available, people just go ahead and consume.

We've talked to a lot of organizations. As they jump into cloud, they expect cost savings, but sometimes they get an increase in cost because once you have that consumption model available, people just go ahead and consume.
And what that generates is a variability in the cost of consumption; a variability in cost of cloud. A lot of companies very quickly realize that they don’t have variable budgets -- they have fixed budgets. So they need to think about how they use cloud and the consumption cost for an entire year. You can’t just go about your work and have some flexibility but then find that you are out of budget when you get to the second half of the third or fourth quarter of the fiscal year.

You can’t budget on open-ended consumption. It requires a balance across the organization, where you have flexibility enough to be active -- and go into the cloud. But you also need to understand what the costs are throughout the entire lifecycle, especially if you have fixed budgets.

Gardner: If you get to the fourth quarter and you run out of funds, you can’t exactly turn off the mission-critical applications either. You have to find a way to pay for that, and that can wreak havoc, particularly in a public company.

In the public sector, in particular, they are very much geared to a CAPEX budget. In cities, states, and the federal government, they have to bond large purchases, and do that in advance. So, there is dissonance culturally in terms of the economics around cloud and major buying patterns.

Yuen: We absolutely see that. There was an assumption by many that you would simply want to go to an OPEX model and leave the CAPEX model behind. Realistically, what you’re doing is leaving the CAPEX model behind from a consumption point of view -- but you’re not leaving it behind from a budgeting and a planning point of view.

The economic reality is that it just doesn’t work that way. People need to be more flexible, and that’s exactly what the providers have been adapting to. But the providers will also have to allow you to consume in a way that allows you to lock down costs. But that only occurs when the organization works together in terms of its total requirements as opposed to just simply going out and using it.

The key for organizational change is to drive a culture where you have flexibility and agility but work within the culture to know what you want to do ahead of time. Then the organization can do the proper planning to be fiscally responsible, and fiscally execute on the operational plan.

Gardner: Going to a cloud model really does force behavioral changes at the holistic business level. IT needs to think more like procurement. Procurement needs to get more technical and savvier about how to acquire and use cloud computing services. This gets complex. There are literally thousands, if not tens of thousands, of SKUs, different types of services, you could acquire from any of the major public cloud providers.

Then, of course, the LOB people need to be thinking differently about how they use and consume services. They need to think about whether they should coordinate with developers for customization or not. It’s rather complex.

So let’s identify where the cultural divide is. Is it between IT of the old caliber and the new version of IT? Is it a divide between the line of business people and IT? Between development and operations? All the above? How serious is this cultural divide?

Holistic communication plans 

Yuen: It really is all of the above, and in varying areas. What we are seeing is that the traditional roles within an organization have really been monolithic roles. End-users were consumers, the central IT was a provider, and finances were handled by acquisitions and the administration. Now, what we are seeing, is that everybody needs to work together, and to have a much more holistic plan. There needs to be a new level of communication between those groups, and more of a give-and-take.

It’s similar to the running of a restaurant. In the past, we had a diner, that was the end user, and they said: “I want this food.” The chef says, “I am going to cook this food.” The management says, “This food costs this much.” They never really talked to each other.

They would do some back-and-forth dialog, but there wasn’t a holistic understanding of the actual need. And, to be perfectly honest, not everybody was totally satisfied. The diners were not totally satisfied with the meal because it’s wasn’t made the way they wanted. They weren’t going to pay for something they didn’t actually want. Finance fixed the menu prices, but they would have liked to charge a little bit more. The chef really wanted to cook a little bit differently or have the ability to shift things around.
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The key for improved cloud adoption is opening the lines of communication, bridging the divides, and gaining new levels of understanding. As in the restaurant analogy, the chef says, “Well, I can add these ingredients, but it will change the flavor and it might increase the cost.” And then the finance people say, “Well, if we make better food, then more people will eat it.” Or, “If we lower prices, we will get more economies of scale.” Or, “If we raise prices we will reduce volume of diners down.” It’s all about that balance -- and it’s an open discussion among and between those three parts of the organization.

This is the digital transformation we are seeing across the board. It’s about IT being more flexible, listening to the needs of the end users, and being willing to be agile in providing services. In exchange, the end users come to IT first, understand where the cloud use is going, and can IT be responsive. IT knows better what the users want. It becomes not just that they want solutions faster, but by how much. They can negotiate based on actual requirements.

And then they all work with operations and other teams and say, “Hey, can we get those resources? Should we put them on-premises or off-premises? Should we purchase it? Should we use CAPEX, or should we use OPEX?” It becomes about changing the organization’s communication across the board and having the ability to look at it from more than just one point of view. And, honestly, most organizations really need help in that.

It’s not just scheduling a meeting and sitting at a table. Most organizations are looking for solutions and software. They need to bridge the gap, provide a translation of where management of software can come together and say, “Hey, here are the costs related to the capacity that we need.” So everyone sits together and says, “Okay, well, if we need more capacity and the cost turns into this and the capacity turns into that, you can do the analysis. You can determine if it’s better in the cloud, or better on-premises. But it’s about more than just bringing people together and communicating. It has to provide them the information they need in order to have a similar discussion and gain common ground to work together.

Gardner: Edwin, tell us about yourself and ESG.

Pathway to the cloud 

Yuen: Enterprise Strategy Group is a research and analyst firm. We do a lot of work with both vendors and customers, covering a wide range of topics. And we do custom research and syndicated research. And that backs a lot of the findings that we have when we have discussions about where the market is going.

I cover cloud orchestration and services, data protection, and DevOps, which is really the whole spectrum of how people manage resources and how to get the most out of the cloud -- the great optimization of all of that.

As background, I have worked at Hewlett Packard Enterprise (HPE), Microsoft, and at several startups. I have seen this whole process come together for the growth of the cloud, and I have seen different changes -- when we had virtualization, when we had great desktops, and seeing how IT and end-users have had to change.

This is a really exciting time as we get public cloud going; more than just an idea. It’s like when we first had the Internet. We are not just talking about cloud, we are talking what we are doing in the cloud and how the cloud helps us. And that’s the sign of the maturity of the market, but also the sign of what we need to do in order to change, in order to take the best out of it.

This is a really exciting time as we get public cloud going. It's more than an idea. We are talking about how the cloud helps us. That's a sign of maturity and what we need to do to take the best out of it.
Gardner: Your title is even an indicator that you have to rethink things -- not just in slices or categories or buckets -- but in the holistic sense. Your long, but very apropos, job title really shows what we have been talking about that companies need to be thinking differently.

So that gets me to the issue about skills. So maybe the typical IT person -- and I don’t want to get into too much of a generalization or even stereotyping -- seems to be content to find a requirement set, beaver along in their cubicle, maybe not be too extroverted in terms of their skills or temperament, and really get the job done. It is detail-oriented, it is highly focused.

But in order to accomplish what companies need to do now -- to cross-pollinate, break down boundaries, think outside of the box -- that requires different skills, not just technical but business; not just business but extroverted or organizationally aggressive in terms of opening up channels with other groups inside the company, even helping people get out of their comfort zone.

So what do you think is the next step when it comes to finding the needed talent and skills to create this new digitally transformed business environment?

Curious IT benefits business

Yuen: In order to find that skill set, you need to expand your boundaries in two ways.

One is the ability to take your natural interest in learning and expand it. I think a lot of us, especially in the IT industry, have been pushed to specialize in certain things and get certifications, and you need to get as deep as possible. We have closed our eyes to having to learn about other technologies or other items.

Most technical people, in general, are actually fairly inquisitive. We have the latest iPhone or Android. We are generally interested. We want to know the market because we want to make the best decisions for ourselves.

We need to apply that generally within our business lives and in our jobs in terms of going beyond IT. We need to understand the different technologies out there. We don’t have to be masters of them, we just need to understand them. If we need to do specialization, we go ahead. But we need to take our natural curiosity -- especially in our private lives -- and expand that into our work lives and get interested in other areas.

The second area is accepting that you don’t have to be the expert in everything. I think that’s another skill that a lot in business should have. We don’t want to speak up or learn if we fear we can’t be the best or we might get corrected if we are wrong.

But we really need to go ahead and learn those new areas that we are not expert in. We may never be experts, but we want to get that secondary perspective. We want to understand where finance is coming from in terms of budgetary realities. We need to learn about how they do the budget, what the budget is, and what influences the costs.

If we want to understand the end users’ needs, we need to learn more about what their requirements are, how an application affects them, and how it affects their daily lives. So that when we go to the table and they say, “I need this,” you have that base understanding and know their role.

By having greater knowledge and expanding it, that allows you to go ahead and learn a lot more and as you expand from that area. You will discover areas that you might become interested in or that your company needs. That’s where you go ahead, double-down, and take your existing learning capabilities and go really, really deep.

A good example is if I have a traditional IT infrastructure. Maybe I have learned virtual machines, but now I am faced with such things as cloud virtual machines, containers, and Kubernetes, and with serverless. You may not be sure in what direction to go, and with analysis paralysis -- you may not do anything.

What you should do is learn about each of those, how it relates, and what your skills are. If one of those technologies booms suddenly, or it becomes an important point, then you can very quickly make a pivot and learn it -- as opposed to just isolating yourself.

So, the ability to learn and expand the skills gap creates opportunities for everybody.

Gardner: Well, we are not operating in a complete vacuum. The older infrastructure vendors are looking to compete and remain viable in the new cloud era. They are trying to bring out solutions that automate. And so are the cloud vendors.

What are you seeing from cloud providers and the vendors as they try to ameliorate these issues? Will new tools, capabilities, and automation help gain that holistic, strategic focus on the people and the process?

Cloud coordinators needed 

Yuen: The providers and vendors are delivering the tools and interfaces to do what we call automation and orchestration. Sometimes those two terms get mixed together, but generally I see them as separate. Automation is taking an existing task, or a series of tasks or process, and making it into a single, one-button-click type of thing. The best way I would describe it is almost like an Excel macro. You have steps 1, 2, 3, and 4, I am going to go ahead and do 1, 2, 3 and 4 as a script with a single button.

But orchestration is taking those processes and coordinating them. What if I need to have decision points in coordination? What if I need to decide when to run this and when not to run that? The cloud providers are delivering the APIs, entry points, and the data feedback so you have the process information. You can only automate based on the information coming in. We are not blindly saying we are going to do one, two and three or A, B and C; we are going to react based on the situation.

So we really must rely on the cloud providers to deliver that level of information and the APIs to execute on what we want to do.

And, meanwhile, the vendors are creating the ability to bring all of those tools together as an information center, or what we traditionally have called a monitoring tool. But it’s really cloud management where we see across all of the different clouds. We can see all of the workloads and requirements. Then we can build out the automation and orchestration around that.

The vendors are creating the ability to bring all of those tools together as an information center, what we traditionaly called a monitoring tool. But it's really cloud management across all of the different clouds.
Some people are concerned that if we build a lot of automation and orchestration, that they will automate themselves out of a job. But realistically what we have seen is with cloud and with orchestration is that IT is getting more complex, not less complex. Different environments, different terminologies, different way to automate, the complexities of integrating more than just the steps that IT has – this has created a whole new area for IT professionals to get into. Instead of deciding what button to press and doing the task, they will automate the tests. Then we are left to focus on determining the proper orchestration, of coordinating amongst all the other areas.

So as the management has gone up a level, the skills and the capabilities for the operators are also going to go up.

Gardner: It seems to me that this is a unique time in the long history of IT. We can now apply those management principles and tools not just to multicloud or public cloud, but across private cloud, legacy, bare-metal, virtualization, managed service providers, and SaaS applications. Do you share my optimism that if you can, in effect, adjust to cloud heterogeneity that you can encompass all of IT heterogeneity and get comprehensive, data-driven insights and management for your entire IT apparatus regardless of where it resides, how it operates, and how it's even paid for?

Seeing through the clouds

Yuen: Absolutely! I mean that’s where we are going to end up. It’s an inverse of the mindset that we currently have in IT, which is we maintain a specific type of infrastructure, we optimize and modify it, and then the end result is it’s going to impact the application in a positive way, we hope.

What we are doing now is we are inverting that thinking. We are managing applications and the applications help deliver the proper experience. That’s what we are monitoring the most, and it doesn’t matter what the underlying infrastructure or the systems are. It’s not that we don’t care, we just don’t care necessarily what the systems are.
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Once we care about the application, then we look at the underlying infrastructure, and then we optimize that. And that infrastructure could be in the public cloud, across multiple providers, it could be in a private cloud, or a traditional backend and large mainframe systems.

It’s not that we don’t care about those backend systems. In fact, we care just as much as we did before – it’s just that we don’t have to have that alignment. Our orientation isn’t system-based or application-based. Now, there potentially could be anything -- and the vendors with systems management software, they are extending that out.

So it doesn’t matter if it’s a VMware system, or a bare metal system, or a public cloud. We are just managing the end-result relative to how those systems operate. We are going to let the tools go ahead and make sure they execute.

Our ability to understand and monitor is going to be critical. It’s going to allow us to extend out and manage across all the different environments effectively. But most importantly, it’s all affecting the application at the top. So you’re becoming a purveyor and providing better skills to the end-users and to finance.

Gardner: While you’re getting a better view application-by-application, you’re also getting a better opportunity to do data analysis across all of these different deployments. You can find ways of corralling that data and its metadata and move the workloads into the proper storage environment that best suits your task at the moment under the best economics of the moment.

Not only is there an application workload benefit, but you can argue that there is an opportunity to finally get a comprehensive view of all of the IT data and then manage that data into the right view -- whether it’s a system of record benefit, application support benefit or advanced analytics, and even out to the edge.

Do you share my view that the applications revolution you are describing also is impacting how data is going to be managed, corralled, and utilized?

Data-driven decision making

Yuen: It is, and that data viewpoint is applicable in many ways. It’s one of the reasons why data protection and analysis of that data becomes incredibly important. From the positive side, we are going to get a wealth of data that we need in order to do the optimizations.

If I want to know the best location for my apps, I need all the information to understand that. Now that we are getting that data in, it can be passed to machine learning (ML) or artificial intelligence (AI) systems that can make decisions for us going forward. Once we train the models, they can be self-learning, self-healing, and self-operating. That’s going to relieve a lot of work from us.

Data also impacts the end-users. People are taking in data, and they understand that they can use it for secondary users. It can be used for development, it can be used for sales. I can make copies of that data, so I don’t want to touch the production data all the time. There is so much insight I can provide to the end users. In fact, the explosion of data is a leading cause of increased IT complexity.

We want to maximize the information that we get out of all that data, to maximize the information the end-users are getting out of it, and also leverage our tools to minimize the negative impact it has for management.

Gardner: What should enterprises be doing differently in order to recognize the opportunity, but not fall to the wayside in terms of these culture and adoption issues?

Come together, right now, over cloud

Yuen: The number one thing is to start talking and developing a measured, sustainable approach to going into the cloud. Come together and have that discussion, and don’t be afraid to have that discussion. Whether you’re ready for cloud or you’ve already gone in and need to rein it back in. No matter what you need to do, you always have that centralized approach because that approach is not going to be a one-time thing. You don’t make a cloud plan and then not revisit it for 20 years -- you live it. It’s an ongoing, living, breathing thing -- and you’re always going to be making adjustments.

But bring the team together, develop a plan, build an approach to cloud that you’re going to be living with. Consider how you want to make decisions and bring that together with how you want to interact with each other. That plan is going to help build the communication plan and build the organization to help make that cultural shift.

Companies honestly need to do an assessment of what they have. It’s surprising that a lot of companies just don’t know how much cloud they are using. They don’t know where it’s going. And even if it’s not in the cloud yet, they don’t know what they need.

A lot of the work is understanding what you have. Once you build out the plan of what you want to do, you essentially get your house in order, understand what you have, then you know where you want to go, where you are, and then you can begin that journey.

The biggest problem we have right now is companies that try and do both at the same time. They move forward without planning it out. They may potentially move forward without understanding what they already have, and that leads to inefficiencies and cultural conflicts, and the organizational skills gaps issues that we talked about.
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So again, lay out a plan and understand what you have, those are the first two steps. Then look for solutions to help you understand and capture the information about the resources you already have and how you are using them. By pulling those things together, you can really go forward and get the best use out of cloud.

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

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