TEC37 E19: Rapid Insights for an Optimized Data Center Environment

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Robb Boyd:                   More data is always better, right? Well, we all know data has been called the new oil, but when it comes to using the data you already have, stuff from within your own organization, it's more than challenging. It's overwhelming. Well, today's show features two leaders who have already helped multiple organizations get a handle on what their data is and how it can quickly be turned into actionable insights. Welcome to TEC37, your home for technology, education and collaboration. My name is Robb Boyd.

                                    All right. Gentlemen, thank you so much for taking the time to join us and help me. Let's do it that way. Help me understand this topic so much better. But I want to start with some introductions, because I'm very impressed with both of your backgrounds and the amount of information you bring to this specific topic. But let's start with you, Steve. Tell us a little bit more about what you do, what you're responsible for.

Steve Gregory:              Sure. Yeah. Steve Gregory. I've been in the industry for 20 plus years and I've been with World Wide Technology for the last seven years. My specialty in working with WWT has been around data management and secondary storage. I've always been a storage industry expert, but I'm specializing in this particular case, helping our customers understand their data and understanding how to better manage it. That's kind of my role at WWT. I'm part of our global engineering team, which is a universal front to help support our customers, better understand how they're engineering and how they're going about modernizing their data centers.

Robb Boyd:                   All right. Now you started to present there a little bit, but we're going to come back to that. I like that. But let's get Aaron in on this. Aaron, so tell us a little bit about what you are doing at World Wide Technology.

Aaron Plaza:                 Sure. So Aaron Plaza. I've been with World Wide for almost a year now, so fairly new to the organization. But long story short, my team is responsible for our specialty solutions practice, all things essentially centered around data center, cloud and security. In our mind, when we define what exactly do we refer to as a specialty practice is to say, we have highly technical folks that know these complex solutions. As we talk about data center, strategy, cloud strategy and security strategy. And at the end of the day, how do we take these complex solutions and ultimately make them simple? Right? So our job is to go very deep into those particular aspects and ultimately help customers connect these solutions up in a way that ultimately drives business value for them.

Robb Boyd:                   Excellent. Okay. Well, thank you both again. It's obvious you both are senior leaders. You've got teams of people that you represent in different disciplines, both on the helping people understand what's possible as well as actually helping people implement and get hands-on with understanding this stuff. And just to keep us from being too vague as we move forward, here's the way I was kind of setting this up. I think I'm safe in saying that everybody understands the value of data and that and as I said, open data is kind of this new oil. But I want to be distinct here and make sure we all understand we're not talking about, of course personal data. We're not talking about your Facebook stream or other things like that being used to sell you as a product.

                                    What we're really talking about is organizations and the fact that every device, be it in the cloud, be it on premises, wherever it may be, on premise, it's putting out information that could be used in a way that could help the business. And you guys have been specializing in capturing that and then making sense of it. Because I think what really happens is, if you guys are okay with me setting it up this way, is that there's just so much data that we're drowning in it. Even if we understand that there's value, the next step of actually extracting the value to do something becomes problematic or certainly challenging. So Aaron, I wonder if I could start with you on that. How would you describe the challenge from your experience that needs to be addressed? How are you seeing it?

Aaron Plaza:                 Yeah. I think that summary you kind of gave is spot on, right? That there's no shortage of information in terms of what our customers ultimately have, right? Whether it's internal tools, different outside influences, different industry analysts in terms of what they should or should not be doing, or of course, the data that they ultimately have internally to how they make decisions. There's no shortage of the information in terms of what's available to them. I would argue to your point again, is that the primary challenge that most of our customers have is how do I make frankly quick decisions, but well-informed? And I know that sounds ultra generic, but what I'm really saying here is that what customers don't necessarily know how to do is how do I sift through this information in order to make quantitative directions towards what is my data center strategy? What is my cloud strategy?

                                    A big part of ultimately what World Wide's help is to our customers is how do we take the information, remove the static, remove the noise, but ultimately prescribe solutions and ultimately show financial, technical, and business justification as to why these particular solutions make sense? Because again, you can talk with a thousand different people and get a thousand different opinions, and I promise you, they're all going to be a slightly different angle on how they approach it. And if I was to summarize what I think World Wide can help customers do best, it's ultimately, how can you make fact-based data-driven decisions, but more importantly, do it quickly and of course, quantifiably so you can see if I make this decision, what's the impact? What's the business value that I'm going to get from it? So remove the noise and keep it simple is maybe the simplest way I'd describe it.

Robb Boyd:                   Well, I liked the fact you doubled down on quantitative. Steve, what do you think? Is that the challenge as you see it?

Steve Gregory:              Yeah. It's two. It's two things. It's both quantitative based on the amount of information that is available and collectible. And from a corporate perspective, they don't really even understand that that's available to them most of the time. There's a lot of tools and things that some SMEs, subject matter expert, if you will, or somebody is trying to be on top of it, it just loses value when you're trying to tie that to the business. Then it's the qualitative piece, meaning what is this information actually telling me? So I can make a faster and better decision based on the quality of the data and how many different ways do I go about doing that, and it's complex.

                                    So what we find is people are just overwhelmed, like we said earlier, is that they don't know really where to start on taking these collaborative types of quality data sets and saying, where are my gaps? Where are my challenges? What decisions do I need to make? What isn't being protected? What am I overprescribing for storage? It all comes together in a spend, in the amount of cost associated to making these choices. So I think what we're providing and the way that we kind of look at it is we have to do both quantitative and qualitative analysis of a customer's environment.

Robb Boyd:                   Let me ask you guys, because I think that the very next thing is, I think the challenge is probably the easiest to understand. No harm intended there, but I think the how then, how do you begin to approach this? You guys have worked with customers at different levels. Believe you've even been a customer you've been on this side of things where you've had to do it well before you were with World Wide helping others do it. But in your experience, and I always love good stories if you've got any good examples that people could relate to, we don't need no names, but what is the best approach? How would you begin tackling something like this? Aaron, you were nodding your head there.

Aaron Plaza:                 Yeah, yeah. No, I totally agree. I think the simplest way to ultimately start is to know exactly what you have, right? The reason why I say that is if we don't know where we've been and what problems and ultimately what's in our existing environment today, it's hard to figure out how we ultimately prescribe the right solution going forward. The first thing I normally work with customers on, and even back to when I was a customer, this is the same way that I would ultimately ask of my partners and OEMs that I worked with is essentially, help me number one, diagnose exactly what I have on the floor today, quantify potentially what those challenges are, what those problems are. So we know exactly in a simple way, calling it requirements, so that I can ultimately figure out then what are the priorities of things that I want to adjust to?

                                    For example, we hear all the time from customers. "I must be 50% of the cloud by 2023 because my board said so." My first question is, why? Or, "I've got a lot of tech debt in my environment that I ultimately need to... I'm faced with high maintenance bills. I'm not getting the performance or capacity or the speed in terms of delivery for my IT services." And my question of course is again, back to the why, but more importantly, right after that is, "Let's take a look at what you ultimately have. What are the business value pieces that the business is saying we need IT to deliver in these new ways?" Faster time to market, lower cost, whatever those key pieces are that frankly, every customer would say, "Yes, yes and yes," is usually the answer from them.

                                    But again, I go back to this mindset of, we have to know what you currently have, what you're trying to solve for. So that then once we know kind of the start and finish, how do we bridge that gap? So the assessment approach of let's make sure we can understand very specifically quantitative metrics, what you ultimately are focused on addressing in the future, and then we can ultimately help design those solutions that bridge that gap for you.

Robb Boyd:                   Well, you guys are sparking something I'm wondering about is do customers not know what they have? What have you seen in your engagements? Is that a thing? Steve, you laughed.

Steve Gregory:              Yeah. That's always a thing. We find most of the time customers absolutely really don't understand their current asset lists, capacity, performance metrics. They might have tools. They might have some resource available to them, but no one is really interested in showing that they're not performing well, as an example. Right? And we're not there to come in and introduce any type of way to demonstrate where they're not performing well, but it's certainly an eye-opener. When we come in and we demonstrate the types of qualitative information relative to their data assets of their current state, they're just like, "I was not able to do that. I was not able to build that correlation between this information over here on this asset, tied to this information, I'm protecting that asset. And I didn't know where..." Maybe there's a thousand virtual machines that aren't protected, for example, or there's something going on in their environment that they didn't realize. Or if they did, they didn't know how to take action.

Robb Boyd:                   Well, here's what I'm struggling with is I want to make sure... I want to get much more specific if we could, because what I don't know that we've fully made obvious is what we're actually talking about with regards to like, what we mean by what data would look like, and what do you mean? Because I know in my experience, the amount of detail I would gather now as a salesperson is to ask somebody, what are you running? What do you have? And I'm just going to base recommendations and stuff based on pain points, different things that they're telling me. But it feels like you guys are saying you're not relying on anybody telling you what they have. You're actually talking about somehow measuring it yourself, which doesn't sound simple to me. Could you [crosstalk 00:11:56].

Aaron Plaza:                 Yeah. Let me give you a kind of a real world example. So we had a customer here recently in town that ultimately came to us and said... They're doing a big data center relocation. Moving from one production facility to another. Data center migration in short. And of course, as we first started engaging with them in terms of how will that migration take place? It also became very clear the scope was increasing. Some applications will go to the cloud, some will stay on-prem. But more importantly, the first step was how do we ultimately put or deploy new infrastructure in the new data center to move into. As soon as that became the priority challenge, then it was, well, what exactly do I need to go buy?

                                    So in this case, I think to Steven's point and yours earlier, is to say the vast majority of our customers, it's incredibly challenging to know what they have. So the way we ultimately helped engage in this particular scenario was we helped that customer through a very specific short timeframe. I mean, we're talking two to three days. It took the customer 20, 30 minutes of some data collections that we ultimately provided them. It's a tool that they can deploy, collects a lot of information regarding the existing assets, 20 to 30 minutes later of work effort on the customer's behalf. Two to three days later, we had all the results of being able to show here's exactly what you have on the floor today, your compute, your storage, your network, and the overall environment. Then secondarily, we can quantify to show exactly what your utilization metrics are. So we can ultimately tell them, "You are 50% over allocated here, and frankly, 50% under allocated in these other categories."

                                    At the end of the day, what we can provide the customer is a very specific, here's what your requirements should look like. Here's the quantifiable improvements you're going to get from it. And they ultimately use this to derive, here's the requirements that I need to provide as an RFP out to the different OEMs so that they can ultimately get bids that shows a very specific, highly efficient environment. So the net result, just if I jump to the end result here with this customer, they roughly had about 2x, or better said differently, roughly 50% of the infrastructure need that they thought they needed. We proved to them that you don't necessarily need that because they overbought in a lot of the categories around network and storage. So it was essentially [inaudible] in the environment, but in a way that we could show the very specific cost savings and of course, here's what your requirements should look like. And it was again, very short turnaround time on the customer's behalf of the work effort involved to size for that stuff.

Robb Boyd:                   Yeah. That's what I was curious about too is what is the customer's engagement specifically? How much do they need to know in advance? How smart do they need to be about certain things to be able to have you in there? Then of course, I think it goes without saying, but I assume this is not a bloody process or a business interrupting type thing that you get in there. But Steve, you were about to say something there.

Steve Gregory:              Yeah. The time on task really is what we care about when we're engaging these types of conversations with the customer. We want to make sure that it's simple and easy, that they understand that they already have the information that we need running in their data center. We just need to extract it. We have rule sets and some things that we do as a business relative to the global engineering team, working with Aaron, to make sure that it's a simple, easy way to extract that information. We can turn that around in a couple of days. And from there, it's just a matter of integrating. How do we make sure that it's a simple story back to the customer? That's the type that we've been involved in.

Robb Boyd:                   Yeah, that's a good point. Go ahead, Aaron.

Aaron Plaza:                 Sorry, Robb. I was just going to kind of add on to that. If I was to describe what makes it unique, because I think that's always the question, because there's always a variety of ways of how you solve the problems. Every customer in the world has dozens of tools, all this information in the data as we described up front. To me, I think the part that we ultimately bring value to our customers is three things when we talk about this approach. One is speed. We've been talking about that, right? Very quick for the customer to get it, not a long professional services engagement, but very, very lean in terms of the work effort, time on task. So speed.

                                    Number two, specificity. Exactly how we go about solving these problems with very specifically prescribed solutions. Then to me, the third, which is the most valuable part, is frankly, the expertise and knowing what to do with the data. Because more often than not, I'll tell you, we work with customers and we show these assessments in the analysis. The first thing I tell every customer is, "Listen, I'm going to show you data that you probably already know, or you've already had a hunch about it." But what we're showing them is two things. One, here's how bad or specifically the severity of those particular issues or where the bottleneck is at. And then of course, the better part is, "Now let me show you exactly how to solve it."

                                    I think to me, if I was to characterize it in a much more generic set of terms that I'd like to just draw an analogy for our customers is it's the same as if when you go see your specialist doctor, right? I think customers come to us as we're the doctor to ultimately help solve those problems. And when you go see your cardiologist, for example, you're not going to go through and get an MRI or whatnot and sit down with them and then he's going to ask you, "Well, what do you think we should do?" No. The cardiologist is going to sit across the table from you and tell you, "Here's exactly what we saw. Here's exactly how bad that problem is. And here's exactly how we're going to solve it." I think that's our responsibility on our behalf of our customers is being able to see the problem, quickly diagnose, and more importantly, prescribe specifically the remediation with, of course, here's the benefits that you're going to get at the end of it.

Robb Boyd:                   Well, I know one of the things you guys are speaking to is not specific to security, although I know that comes up a lot, but when you talk about resource utilization and the accuracy of putting data behind a hunch or validating that someone's right or wrong about something in their own environment with actual data to back that up. Because I think again, we inherently understand the data that's there. But it reminds me of doing security assessments where I would be brought in after someone had received a big book of stuff that was printed out that was not gibberish, I mean, there'd be a certain logic to it, but essentially it was a customer had unknowingly paid for a whole bunch of data assessment that wasn't very actionable because it was missing the next part, which was the whole value of the expert saying based on your goals, based on what you guys want to achieve. Not a generic, this is what we think all customers want, but what you want, plus your actual data.

                                    It sounds like that's what you guys are really trying to say is just going, we have the ability to come in and give you a snapshot of how everything is working to verify that it's what you thought it was, or it's not, and here's what could be done to potentially get it resurrected in the right direction.

Steve Gregory:              Yeah, it really is. It's about understanding that specific customer's data set, [inaudible] state, tying KPIs to that when we can from an interviewing. So it takes both business and technology to come together to solve a problem. One of the interesting points is that we hear a lot of times from the OEMs, they're just throwing things out there, thinking they're solving problems, but without really any data behind it. You know what I mean? They're just putting things out there that says, "Oh, you want to modernize? Okay, do this." Okay. Well, where's the data behind that that tells you that's the right choice? What's the business problem you're trying to solve? So if we can take those two things, like a KPI [inaudible] which is what would help solve from that, and then map it back to that business problem. That's where we see tremendous value.

                                    I think both Aaron and I have been doing this a long time. We have examples of customers who literally just say, "I wouldn't be able to get through this modernization program if it wasn't for understanding my current state. I don't want to make this choice to buy X if I don't really understand what I got going on right now in my environment." I think the value that Aaron brings in the organization that we're putting out there as an example, is to help differentiate to make sure that customers really understand what they're trying to do, and here's the data behind it to make the right choice.

Robb Boyd:                   Yeah. Well, I know you guys have both, and it must be something you guys are all under the gun for at World Wide Technology. But one thing I like is I always encourage anyone I interact with to join your platform at WWT.com. Not just because of the level of interaction of engaging and such. You guys must be told you have to publish at a certain degree or something, but there was a couple of different articles that you guys have pinned on the platform about reducing infrastructure costs, enabling blind spot detection, things that's got to catch people's attention. So it's a good resource just to go on there if nothing else coming out of this conversation. But what other kinds of stories do you like to highlight to kind of prove out the value of what you've discovered through actual customer interactions? Yeah. What else comes up?

Aaron Plaza:                 Yeah. Another, perhaps more specific example of things. Listen, there's a variety of challenges, of course, that customers are looking to solve. I think what makes it more difficult today and increasingly more difficult in the future is that there's more ways to solve it, right? Go back 10 years ago, everybody was more or less doing the same things. As we now look at how cloud ultimately comes into the overall picture, how new technologies like hyper-converged, software defined and all of these new technologies, suddenly there's a dozen ways to solve for that problem now. Before where it used to be, well, what flavor of storage compute and network do I want? Literally just became, what label do you want on solving it? Now there's a variety of ways that ultimately have different strengths and weaknesses.

                                    I think to me, that's the part that continues to make this more and more valuable is as a customer to be real specific says, "Hey, I'm moving from a three tier architecture of compute storage and network. I've heard hyper-converged makes sense, but does it really make sense for me? I've heard that the cloud ultimately seems like it may be more cost effective, but if I was to analyze my workload, does it make sense for me?" I think as that complexity about how we solve these problems, because there's more and more solutions that come to market, suddenly customers have an infinite amount of choices. And that's really where I think the value ultimately comes from World Wide is not only can we show you, number one, what do you currently have on the floor today? Number two, what solutions and products ultimately make the most sense for your workload and for your budget and for your requirements?

                                    But number three, once we go beyond that, it's one thing to talk about it, which I think most partners and OEMs talk about. There's a whole nother thing to show it and ultimately document it. But yet there's a whole nother category, which is now let me prove it. I think that's, at the end of the day, what World Wide can do is we have the expertise, we have the tools, we can do this in a very lightweight kind of quick, rapid insight type of way with our customers. But then beyond that, once we say, "Here's what we believe you're going to get from a benefits standpoint," then we can also bring that into the ATC where we can demonstrate it and prove it. So there's no longer how much risk in this. We as essentially de-risked the entire thought process. But more importantly, as we speed up the decision process through rapid insights, and of course, showing the outcomes through what we can prove in the lab.

Robb Boyd:                   Steve, you were nodding your head there.

Steve Gregory:              Yeah. Just to spell out the Advanced Technology Center is what Aaron speaking about. We have a whole campus of data infrastructure where we spend multi-millions of dollars on making sure that we can help a customer demonstrate these things. So once they start making a decision around, "I'd like to see these types of capabilities fit together. So I want to see an application based on this hardware configuration in these types of storage configurations." We can demonstrate that in our labs so the customer can obviously get to a place where not only do I know my data, I know what I want it to run on. Show me what that looks like. It's very much a show me proof of concept type of environment.

Robb Boyd:                   Proof of concept. Yeah.

Steve Gregory:              Yeah. We're very much heavily invested in that. It's one of our strengths, again, as it relates to not only understanding data, but then taking it to the technology [inaudible] before they make buying [inaudible 00:24:45].

Robb Boyd:                   Yeah. And you're breaking up a little bit there. I know there's nothing you can do about it, and I'll just call it out that we're seeing it as well. But the ATC is amazing. I was there in 2016, we were doing a show for another reason, but I love the multi-vendor approach because you guys truly don't care. I mean, I care, but you're not married to any one vendor. The idea is you're married to a solution for whoever your customer is at that moment and what it is that they want to achieve. But specific to today, which to me, is more revolutionary sounding to me than it really should be, which is the notion of we've always been told that better decisions come from better data. And we all get that we've got the data here.

                                    There's never been more of it than there is now, and here you go, offering. It sounds like a very structured way to come in and analyze well, here's where things are. Then the customer has options to make, but they're making options based on not on hunches or how smooth talking the latest vendor visit was or anything to that effect. It's really about what it is they need. I assume you guys go through a process also of speaking, I've hinted at this, but speaking to customers about what it is they want to achieve or what their objectives are. I mean, it seems straightforward, but yeah, you're not just dumping a big document on them.

Aaron Plaza:                 That's exactly right. As I mentioned earlier, the first set of questions is always the why. Because I think a lot of customers have a fairly good idea of where they want to head and what technologies they're interested in. But again, starting with the why and understanding what exactly it is that they like or dislike about these technologies or OEMs. But when you couple the why as well as what you currently have and then of course, to your last question, which is obviously very important is what you're trying to solve for. Is it cost effectiveness? Is it speed? Is it time to market? A variety of different answers, which usually it's always yes, yes, and yes, but we want to help customers understand the priority. Once we understand that, then we can very quickly prescribe exactly what it is.

                                    So it's the combination of all of these pieces we've talked about that it's never just one silver bullet, like anything else in life. It's a collection of how do we take ideas, art of the possible, coupled with quantitative metrics and data analysis that we can show customers what they really have, coupled with, where do you want to head? And then of course, de-risking the entire thought process. And of course, all this as we speed up the process from a decision making. But de-risking the decision because we can prove it in the lab.

                                    To me, when you can do all of that is I think the key that customers get value from. It's all the way from, here's what I like to do. Here's where I want to head, and let's show you everything in between from ideation to ultimate outcome type of thing that we can prove, which at that point it's like we said earlier. You de-risk the decision, you speed it up, and you can prove those outcomes. That's what I think customers are looking for versus the marketing speak and the promise of things that too often I think just ultimately go unfulfilled.

Robb Boyd:                   Yeah. Go ahead, Steve.

Steve Gregory:              No, [inaudible 00:27:46]. A lot of the narrative coming from OEMs is we can, we can, we can. For us, customers are looking to us to say, "Please help me do that. [inaudible 00:28:00]."

Robb Boyd:                   One wrap up question here, but I'm just curious. As I was doing research on this, to a certain extent, it feels like there are tools out there that I could as a customer purchase myself or engage with and I can run the tool to do some logging of information and get this myself. Obviously, you guys are talking about a service that you're providing. You both represent different parts of the organization that are involved in this. Is that part of the answer? I mean, why would someone come to you guys to do this and not just do it themselves? Where do those lines get drawn, you think, in this?

Aaron Plaza:                 Yeah. To me, it's frankly the expertise, right? Because I would tell you more often than not, especially as we mentioned at the beginning, it's like customers have this data. Customers have the information. Customers have usually the tool sets, and it's usually staring them in the face in terms of the problems. But when you sit there and you look at the same problem day in, day out, year over year type of thing, how do I solve for it usually is the challenge. I think that's what we're uniquely able to do, right? Customers, I think, are so often for the right reasons, their job is to ultimately manage the care and feeding of these existing assets and keep them running. Keep the lights on, if I put it in a simple term.

                                    Our job, what we do day in day out is to look at these problems and figure out how to solve them and run IT environments in a much more efficient state. So that's the difference. It's not that we're going to necessarily bring a very unique set of data set to a customer. In some cases, the answer to that is still true, but it's really more, what do I do with this information and how do I prescribe from this what is the way to solve for it? Because I think at the end of the day, that's usually the challenge most customers have. We ultimately get the luxury of talking with thousands of customers and seeing thousands of diverse environments. We get what works, what doesn't, what people have tried, what success looks like, what good looks like. We get that opportunity to ultimately bring a thousand use cases of examples of learning to say, "Mr. Customer, we can help you avoid those pitfalls. And here's what a data center strategy, a cloud strategy looks like with yeah, of course, avoiding all those pitfalls that many customers have taken in the past."

                                    So it's all that tribal knowledge ultimately that I think it's our expertise as to why leverage us versus, "Hey, run with the data set and run with it yourself," kind of thing.

Robb Boyd:                   Yeah. Forgive me, I probably should know this, but obviously I would encourage people to go to WWT.com and not just visit the website, but actually join the platform because it's been designed... The ATC is available virtually to do a lot of things. You guys run a lot of labs virtually. People do not have to travel. It's physically located in St. Louis, but I know you've got customers to your name, World Wide. So there's a lot of value that can be provided there, but is there something specific? What's the name of the service? Is it assessment service or a workshop or something you guys are offering to make sure everybody's clear on exactly what they should be asking for?

Aaron Plaza:                 You want to take that one, Steve?

Steve Gregory:              No, go ahead. I was just going to say yeah, just inquiring with your team, your account team from a WWT perspective, it's Data Driven Insights. So if you wanted to go up on the WWT site, there's a briefing. It's called Data Driven Insights for Data Center Briefing. What that would be was just kind of like a starter, one hour starting point to talk about engagements, following relationships to storage, compute virtualization, data protection, infrastructure that we can begin to think about what you're trying to solve for and what you want to analyze. Then we would take it from there. But yeah, that's kind of the outcome is to get customers to say, "Hey, I'd like to get engaged. What's the next step?" Go look at Data Driven Insights, Data Center Briefings up on WWT.com.

Aaron Plaza:                 Yeah. The color I'd add to that too, that I think Steve mentioned that it's so important to me to mention is that... He mentioned it. It's an hour long conversation. In many cases, 30 minutes.

Robb Boyd:                   [inaudible 00:32:14]. I like baby steps.

Aaron Plaza:                 Yeah. It's not an army of people. It's not a sign on the dotted line so we can help type of thing.

Robb Boyd:                   That's awesome.

Aaron Plaza:                 It is literally let's talk about what you want to solve for, and in 30 minutes we can derive exactly what that looks like. And more importantly, ultimately prescribe the plan. Here's exactly how we'll go about it. Here's the outcome and deliverables you're going to get. Here's how quickly we can provide it for you. To the engagement model of that, how we do it? Challenge your account teams, right? Talk with your account manager, your CSC, if you will, and say, "Hey, listen, try to solve for my data center strategy, my cloud strategy. Can you help? What are these rapid insights that you guys have mentioned?" And it's as simple as that. At that point, a 30 minute conversation, I'm confident we can figure out here's exactly the next steps and how do we ultimately help you out?

Robb Boyd:                   You know, it's funny because I don't think you guys... I didn't mean to cut you off, Steve, but [inaudible 00:33:06]. What I feel like is, you guys, and I'm just not used to this, at least in my personal experiences, but you want customers to ask you big, broad questions that this kind of thing entails because you have the ability to not make it seem so big and so broad and untouchable.

Steve Gregory:              We don't want it to be [inaudible 00:33:22]. Yes. It's not untouchable. It's not as complex. It sounds complex, but we can make it easier because one, we've done this many times. And two, we have just, like I said, we have the internal skillset as well as the expertise to go make that a light lift for our customers.

Robb Boyd:                   Yeah. And you've been down this road with others before so you can probably avoid a lot of blind alleys and misunderstandings and things like this just based on having probably experienced them before. So you don't have to bring them on to the next customer. I think that's hugely valuable. And I love the fact... Again, personally, I feel like there's some times... Aaron, I think it was you that mentioned a lot of times customers have too many ways of doing the same thing or at least at a certain level, it's the same thing. To me, that sometimes just locks me up because I get caught up in this notion of wanting to do the best thing. Maybe there's five different ways I could do this that many people have recommended, but then I don't make a decision because I get too wrapped around the axle of trying to figure out what the best way is because well, frankly, I don't always have the right data in front of me to be able to then judge it in a quantifiable quantitative manner. And it sounds like I should have called you. Yeah.

Aaron Plaza:                 Yeah. That's exactly right. I'm kind of smiling because there's a joke I like to tell customers every time we engage in this and that more often than not, most customers don't make decisions because of analysis paralysis. Right? I like to tell them that ultimately no decision is a decision is what you're ultimately doing by trying to consider the different options. A joke I like to tell them as a very, very, just general concept is like in today's business world... Well, let me say it differently. The old business world was the mindset of big fish eats small fish, right? That's just kind of a general statement.

                                    But today's business world, I think is fast fish eat slow fish. I think that mindset, time to market, speed to decision-making, and how you can ultimately get time to market for your deployed new applications, how you engage with customers, the speed in which you do that, that's what's valuable today. Time to market is such a critical factor that I think many customers when they look at, "Oh my God, there's 50 different options. And how do I go about solving this?" It's the time on your analysis, if you will, and speed to making that decision really that's the [inaudible] for customers.

Robb Boyd:                   Yeah. I think it was in a Stephen Covey book and we'll end it here, but you reminded me of other points, but I think there was a picture of it that always stuck in my head and it was one of these self-help seminars. But it was like, you're so busy climbing the ladder... It was career advice or something. And then the picture was, but the ladder was on the wrong wall. What you guys are really helping people do is to climb that ladder, you can be fast and agile and do the right things and you can ensure that it's on the right wall. I think that's a good way to look at it. So Data Driven Insights is the briefing that you guys... It's a lightweight briefing anybody should certainly take advantage of now. It's at WWT.com. I'll be your sales person. I encourage everyone to get out there and take a look at that. Two highly smart individuals running some smart organizations here.

                                    This is good because this is stuff I didn't even know you guys were doing. And I think it's an extremely valuable first step and one that everyone should be looking at. Thank you so much for joining us on TEC37 and sharing how this stuff works. I look forward to my briefing here very soon. Thank you, gentlemen.

Steve Gregory:              Thank you.

Aaron Plaza:                 Sounds good.