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THE DATA ECONOMY PODCAST

HOSTED BY MICHAEL KRIGSMAN

THE DATA ECONOMY PODCAST / HOSTED BY MICHAEL KRIGSMAN

Diversify Data to Drive Innovation

Ron Guerrier, Chief Information Officer / HP

“The customer doesn’t just want one cookie cutter view, they want differentiation. So, we have to understand that and provide differentiation in the data we provide and the decisions we make”

Ron Guerrier
Chief Information Officer / HP

Ron Guerrier is the Global CIO of HP Inc. He’s responsible for building out a world-class IT organization to deliver and enable the highest levels of productivity for over 70,000 employees, contractors, and partners around the globe. He develops and oversees a comprehensive approach to digitization across HP, with an emphasis on process automation and improvement while ensuring a positive end-user experience.

In this episode, Ron shares insights on how leaders can create a culture of innovation through diversity of thought and diversity of data. We’ll explore why customer centricity, data diversity, and having a purpose are key ingredients for achieving success with data within an enterprise.

Guerrier has more than 25 years of experience managing technology in both the public and private sectors across various industries. Throughout his career, Guerrier has earned numerous honors and awards, including but not limited to the 2019 & 2020 Crane’s Top50 Award, 2019 & 2020 Top Technology Executive to Watch from HMG Strategy, Gartner’s 2018 CIO Breakaway Leader of the Year, 2018 CIO Digital Edge50 Award, and was included in the Black Enterprise Most Powerful Executives in Corporate America List in 2018.

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Transcript

MICHAEL KRIGSMAN: We’re talking about data and diversity with Ron Guerrier. He is the CIO at HP. The importance of data to innovation can hardly be overstated. 

But to really make use of that data and to make the best possible decisions, we need to weed out systemic bias of every type. That means diversity of thought, diversity of data, and really aligning with what business users need. That’s the formula to be successful with data in the enterprise. 

And that’s the focus of our conversation today. Hey, Ron, how are you today? 

RON GUERRIER: How are you doing, Michael? I’m doing great. Hope you’re doing well as– 

MICHAEL KRIGSMAN: Ron, HP is a company we all know. Tell us about HP, and in particular, describe and tell us about your role as Chief Information Officer. 

RON GUERRIER: Well, thank you, Michael. The opportunity to speak about HP is something that’s always worthwhile for me. HP as everyone knows, is an iconic brand, essentially, one of the founding companies of Silicon Valley. We make printers, PCs, peripherals, and a myriad of other things. 

Company is always reinventing itself, so the people also have to as well. So in my role as the global CIO, my responsibility is to serve and ensure that the employees, roughly 54,000 or so employees of HP, are getting their needs. 

I see things as a value chain. So I want to make sure that I’m delivering for them, but more importantly, doing it at a time of tremendous change and disruption. So pretty exciting, and looking forward to the discussion on HP and other matters within the world of the CIO. 

MICHAEL KRIGSMAN: Ron, we’re focused on the role of data. And I think a good place to begin is discussing innovation, and what does innovation actually mean for a CIO and for IT? 

RON GUERRIER: That’s a great question. And I always want to distill and kind of distinguish two different parts of how I answer that question. Innovation is making marked major improvements to the condition, like see changes. To me, Kaizen, or continuous improvement are incremental changes. 

And I think every CIO, every single day, is doing bits of continuous improvement, Kaizen. We’re constantly improving the condition through introducing new technologies, new process flows, making things frictionless, for example. But innovation is taking that to the next level, is finding new markets, and trying to find totally different ways that we work and how we service our customers. 

So the role of the CIO I see as truly, of course, keeping the lights on– that’s the Kaizen part, improving– but also addressing the bigger challenges of the business that we serve has in front of them. And whether it’s in any one of the industries, I believe that’s one of the most important things. 

How are we with the business, in the room with them? I’m going to quote Hamilton a little. “I want to be in the room when it happens.” But also, I want to be proactive with the business, and say, hey what’s on the pipeline? What’s the next horizon? And let’s IT be in the room with you to start really plotting what that looks like and architecting it with you. 

MICHAEL KRIGSMAN: Would it be fair to say that the foundation of innovation for CIO, for IT, is working closely and understanding the needs of the business? I’m saying that because of the comment you just made, you want to be in the room when it happens. 

RON GUERRIER: Absolutely, and that’s remarkable. I’ve been in the IT game, I’ll say, for 25 years now. And the thing I’ve learned over that time period is we have to be lockstep with the business. We have to understand the business best. 

And a lot of times, we’re the internal consultants to the business as to a world they want to conquer or something they want to address. And the role of the CIO, part of it, of course, is about efficiency, cost optimization, absolutely, which eliminate waste whenever we can. 

But it’s also about how do we get into new markets. And for us to do that well, and be effective, and sustainable, we have to be in the room, in the discussion, in the dialogue, so we could do that. 

And I think the best CIO’s out there, peer groups of mine, are the ones that are really, really close to the business. And the business sees them as an extension of their business team. I think that’s extremely important. 

MICHAEL KRIGSMAN: Yeah, as I talk with really, really good CIOs, there’s no question that is the common denominator. So what is the role of data? And how can data support this kind of innovation? 

RON GUERRIER: That is such a spot on inquiry. And let’s just think back real quick, and I’m just thinking. Like 20 years ago, 15 years ago, data scientists– let’s just think about the role of data science– didn’t exist. 

My son is in his third year at DePaul, here in Chicago, and he’s studying data science. 10 years ago, when I was a CIO, the term didn’t really exist. So the reason I’m bringing this up is that what used to be things that were just throwaway– just think about gasoline back in the day. 

Gasoline was thrown away. No one needed it. They wanted kerosene. And then, all of a sudden, things were modernized, right. The third generation happened and Industrial Revolution. All of a sudden, gas became the commodity everyone wanted. They realized that’s where the value was. 

To me, that’s how I see data. What we want to do in every organization, and HP is definitely front and center on this, is how do we personalize that relationship with the customers? How do we get ahead of what their wants and needs are? 

And the best way to do that is really understand the customer, whether through metadata, or whatever, and really making solutions that are cater to that customer. And I can give you one quick example of that. 

So here at HP we’re working with orthotics. So we want to make sure that we are working to create customized shoes, for example. The best way to do that is really get the information of the customer. Well, Ron is size 9 and 1/2, 10. Ron likes running. Ron wants his name on the side of it or his favorite sports team. 

Let’s customize a shoe or an apparel that meets his need. The best way to do that, the only way to do that, is through personalization. And the last thing I would say is, when it comes to customer experience, everyone has completely expected that you know what I need. 

How do I get ahead of that? But do it in a non-intrusive way, by using the data in a way that is really explained to me what the customer needs from us. And so in IT, for us to create those solutions, we have to have a good command of the data, do the analytics of the data, and get the insights from that data. 

This is now core. Before it was kind of like a nice to have. It is a must at this point. 

MICHAEL KRIGSMAN: So in your role as CIO, how much of your time, or your thought, or your mental space is consumed with looking at data problems, such as the one you just described, trying to be more focused on the customer and customer centric? 

RON GUERRIER: I would say it dominates. It absolutely dominates, and whether it’s directly or indirectly. So quick examples, if I’m doing an upgrade to a new ERP, or a new system, what everyone on this call will know and appreciate is the pain points usually is the integration point. How does it integrate with the old and new? 

But how does the data flow? And making sure that data goes from A to B at the right time frame, whatever that looks like. And then you throw in something we haven’t talked about, but I know we will, is the cyber risk. 

And bad actors, they’re after your data. That’s what they want, they want a piece of. And so you really have to make sure that you’re insulating that data in transport, at rest, or what have you. So data definitely is top of mind in almost every single conversation. 

So it flows, it’s fluid. And I have to make sure that my team upskills ourselves so we understand the value of data. And how do we render it to the business so they make great insights on that data? 

MICHAEL KRIGSMAN: This is really hard to accomplish and do well. For one reason is you’re dealing with multiple sets of talents, right? So when you talk about the data flows, and understanding the data, you have to understand the customer. You have to understand how data works. I mean this is really hard stuff it seems to me. 

RON GUERRIER: It is, but it isn’t. It’s a little bit of both. I mean, when you first kind of look at it, it’s daunting. It’s the forest from the trees discussion, right. And then you start looking at it and you start really taking logical bites of things. Like what do I need? When do I need it? How old is the data? 

Because you don’t want to make decisions on latent data. And you also want to make sure it’s a secure. So it’s the ability to step back from it and really take the tangible bites. And you know, what is the best known information at this time? But most important thing, how do we refresh the data and make sure it still stays relevant? 

Decisions made before our global pandemic were probably good for that time. Today, everything is off the table. And let’s reset, because of how we work, how we play, how we interact has totally changed. So even that data has to be kind of refactored as to what we’re trying to do with it. 

So I think that’s extremely important. But, yes, it is. It could be daunting, totally agree. But with the right tools, the right mindset, right business partnership, I believe it’s something that we could conquer. And you see companies that do really well at this. And I really believe HP is one of those companies. 

MICHAEL KRIGSMAN: Has the composition of your team evolved over time? As well as the cultural mindset to reflect this new way of doing business, which is very data centric, very customer centric, as opposed to the traditional approach of IT, which was all about infrastructure. 

RON GUERRIER: You are absolutely spot on on that, Michael. The mindset has changed. The DNA, the pedigree, of our employee base has changed. And it has to be because it has to evolve, right. 

And I’ve always said that technology is truly the biggest disruptor. When you introduce technology, good or bad, it’s going to change something. So our mindset has to change. How we approach it has to change. 

So the skill sets we’re looking for are individuals who will kind of really attack a problem. What is a problem statement? And what are the things that we could do to render an improvement to that situation? 

So we look for talented people who definitely see things in a different way. So the diversity of how they think, the diversity of their experiences, is very important. And the other thing that we’re really focused on is making sure that the business and IT are lockstep. 

And the word– I was on a to call earlier today and I said, we have to create collaborative teams more and more, cohorts. And we’re all in the foxhole together. So being able to sit with someone in marketing analytics, someone who is in sales, or supply chain analytics, understand their business. 

Say, OK, you need this type of data because you’re trying to solve this problem. And you can’t do that long ways away. You have to be as close as possible to your business to understand what those needs are. 

Old IT was throw it over the fence, wait for a while, get it back and pray that it’s what they wanted. New IT is let’s go to the beach together. Let’s find the rock we really wanted. And let’s try to find the right rock. 

I remember when I started in IT, it was more of the first. Ron, go ahead and we need this, and we need it in about a year and a half, have fun with it. Here’s some money, disappear, come back. 

And I remember I would deliver a project. It was the wrong color, wrong size. The leadership team has changed during that time. And then I’m right back on a hamster wheel. And so the new way we think about IT is more about agile transformation, working with the business and going to that beach together, finding that rock together, and really doing something with that rock. 

So I’ve always seen it’s been a transformation. Even in my 25 years, how they approach IT is a different, but how IT approaches the business has to evolve as well. 

MICHAEL KRIGSMAN: I think your example of going to the beach and sitting on the rock together is so great. Because in the old days, it was all default to no. So yeah, come back in a year and a half, and it’s going to be black, and if it doesn’t really meet your needs, well, it’s going to meet your needs because this is what you’re getting 

RON GUERRIER: Yeah, like the Model T, yes. You can pick any color as long as it’s black, yes. And that does not work, especially in a world where we want to be more personalized. The customer doesn’t want just one cookie cutter view. They want differentiation. 

And so we have to understand that, and provide differentiation in the data we provide and the decisions we make. 

MICHAEL KRIGSMAN: Oh, it totally breaks down when you start talking with customers. It’s one thing internally, and they don’t really have– the users don’t have a choice. 

But when you start talking with customers and they’re paying, then it’s a different matter, and especially as the competitive environment is shifting. Ron, you mentioned the term diversity data. And so when we think about democratizing data, what does that actually involve? And what does that mean? 

RON GUERRIER: That’s a phenomenal question. Democratizing, the way I define it– and I believe the way that we, hopefully, most of us define it– is how do we democratize data and get data to the edge? How do we get it to the people who need to make the decisions quicker, and make sure that data is trusted, and it’s accurate, and it’s secure? 

Those are the things that are very important. And again, a quick anecdote, when I started my first career job was a repo agent. I remember repoing vehicles. That was my job at the time. This was 1985, so mind you, ’96, so technology wasn’t the greatest. 

And I would get the VIN of a car, and I’ll go out and find that vehicle, and there you go. A couple of occasions I would actually pick up the wrong vehicle, because the information that was downloaded was wrong. 

And going back to ’96, I’ve always realized that it’s very important that we democratize the data, get it to the people who have to make decisions off of it as quickly as possible, and refresh it as well. So that’s what I mean by democratizing. 

And the other thing from back in ’96 to today, biggest change– and I guess that’s 25 years– is that we can’t make the assumption that our business colleagues and peers don’t understand how to render the data. They’re far more astute. They understand Python better than anyone else, or whatever tool, or language they are. 

And so we have to have that assumption that they are also a lot more knowledge about how to render the data and use it. So that’s what I mean by democratizing. And when you asked the question about diversity of the data, if you keep on getting the same data points from the same sources over and over again, you can kind of get that same result. 

It’s kind of like NASCAR. You’re going in a constant circle and the only strategy is take a left. Take a left. Pit. Take a left. Take a left. And so if we get diverse data, you can get different insights and different ways of thinking. That wait a second, the customer no longer wants to do NASCAR. 

They don’t want to keep on going left. They want to go Formula One. They want to do left, and right, and there’s different strategies in banking. And so we have to ensure that we’re taking data from different constructs, different locations, bring it together and let’s render the best solution. So that’s how I kind of think of democratizing data and the importance of diversified data. 

MICHAEL KRIGSMAN: Well, we’re definitely going to unpack this concept of diversification and diversity of data. But you mentioned the importance of bringing data to the edge. Can you elaborate on what you mean by that? 

RON GUERRIER: Absolutely. So again, this is where we’ve matured as an IT shop and a business partner. Like back in the day, we all remember we had the batch worlds. We had to wait overnight for something. You call in for your payoff and you had to wait. And it’s good for x date, because it has changed, and we don’t know what it is. 

Our ability to get it to the edge, and our devices today are just absolutely amazing. When you think of, for example, an HP laptop today to a laptop of just five years ago, the compute power, the ability to do things on these laptops are just amazing. 

Then you throw in the capabilities of cloud compute and bringing that to bear. And getting into the hands of a salesperson, who’s out there and trying to give the latest information. Or you’re in a factory floor, and you need to get it to someone to make a decision in real time using a 3D print technology. 

Getting that data to them is most important. So essentially, compute on the edge. And it’s something that we’re trying to do more and more of. But the thing that always challenges is network bandwidth. How do we get the network up to speed with the amount of data? 

But more importantly, the security– our world has completely changed. I think you’ll agree with that. Everyone will agree with that. To make sure while it’s in transit, is it getting in the right hands, and the right people, and the right time. So identity and access management, for example, is more important than ever. 

It was important prior to the pandemic. Now, it is pretty much fundamental to how you work, because your workforce is transient. They’re everywhere. So getting it to the edge is so important, but make sure that you wrap it around the levels of security that you need. 

MICHAEL KRIGSMAN: So if I can summarize our story so far, you’re trying to deliver as much useful data to end users on a variety of different devices using a very wide range of applications. You don’t know where they are physically, geographically, and do this in a very highly secure manner. 

So do you separate out the thought of the data transport, the type of data, from the applications? Because from an end user standpoint, having this firehose of data is of no value unless it’s the right data, and it’s consumed in the right application, so that it solves their particular needs at the time, whether it’s finance, or HR, or marketing, whatever it might be. 

RON GUERRIER: Yes, spot on. And so another thing that I’m just going to throw on top of all this is creating the personas of each person that we’re serving or we’re supporting. So the persona of someone that’s a CSR, answering phone calls, doing a great job supporting HP customers, is different than the persona of someone that’s working in supply chain on sales. 

So we want to make sure that we get the right data to the right person. But based on that persona, what type of data do they need? What needs to be– what could be cache local? And what needs to be refreshed? Right, so we are looking at all realms of that. But again, the personas definitely help us define that. 

And the thing that overlays all of that– and this is something everyone in IT has been talking about for years– architecture. We have to ensure that we have the right architecture in place. But more importantly, that we refresh the architecture. 

The worst thing you could do is have a great data architect, put all this work together, and then let it sit idle. And if this is more than six months, in my opinion, you need a refresh. So I would say every six months we always want to go back and look at our data structure, our architecture, and is this still relevant? 

Are there new technologies that we should probably put in place? Are things that are deprecating? And what are the new emerging tech that we’re looking at? And really understanding that because, again, like I said a little bit earlier, our role in IT is be proactive, and really stay a step ahead, and say, hey, as a consultant to the business, these new technologies hit the market. 

These are things we should probably consider. We’ll put it into our tech stack. In some places we’ll POC it, proof of concept. Some places will say this is not going to work for us. But we’ll put it on hold, because maybe the technology will improve later. 

So your question is spot on. We have to constantly refresh how we render that data and actually distribute that data to those that need it via the personas that we’ve identified. 

MICHAEL KRIGSMAN: It sounds like enterprise architecture is a really crucial component of all this, and being on top of the enterprise architecture, and looking and seeing how it needs to evolve as your business user needs evolve. 

RON GUERRIER: Absolutely, and I think everyone would agree that’s listening in on this. So that your enterprise architecture has to be derived from what your business strategy is. Clearly, your business is going to drive how you need to kind of deliver. But then there’s the foundational data structure that you have to have as well. 

And so how do you bring those together is very important. And the thing I’ve learned over the years is– historically, in IT, we would kind of, in some cases, kind of hold architecture a little like a secret. It’s my precious, right. The world has changed. 

We have to expose what our architecture is to our business colleagues and say, the reason we change this is for this reason. And we want you to understand that. And the reason that’s important is because everything is searchable. Everyone could do their own research. 

And they’re going to question why did you make certain decisions. So the other thing I know that we have to do more of in IT– and I think we’re all getting better at this– is evangelizing the value and why we made certain decisions. It’s no longer, well, I changed this because I can. 

I’ve changed this and this is a value that’s bringing to you. Do you agree? Yes, you do agree. We’ll move forward. If you don’t agree, let’s delitigate it. But this is why we made that decision. So I think that’s something that’s extremely important for IT professionals more than ever before. 

MICHAEL KRIGSMAN: It seems like you’re very aware to respect the users in terms of giving them information to help them understand why you’re making certain decisions. But how do you avoid overwhelming them? Because really the average business doesn’t need to know too much or care too much about the underlying enterprise architecture. They just want it to work. 

RON GUERRIER: That’s a conundrum I’ve been dealing with for years. And I’ve realized that– It’s like, I ride motorcycles. So it’s like a throttle response. If you don’t give it enough, it will not move forward, right. If you don’t give enough information, the bike will not react, and you won’t move or you’ll stall. 

If you overdo it, you might hurt yourself because you gave it too much throttle and you lose it. So I think the true thing we have to do as IT professionals is bringing the organization along like magnets. Like how do you bring it along– so if you go too far, you lose the momentum bringing it forward. If you stay too close, you’re not moving the company. 

So it’s very important that we upskill our peer group outside of IT. And again, 9 out of 10 of them will go ahead and do a search on it or do their own research. And what you don’t want is that you have this misunderstanding of what we’re trying to do. 

So the more I expose and be more transparent, the more they understand, the more we get funding, and the more they see value. But at the end of the day, our conversation has to be of value creation. And if we’re not talking about value creation or cost optimization, what are we talking about. 

So you’re correct. You don’t want to overwhelm. But I think, like I said, in the last 20 years, our business units have become far more astute. And I could tell you this, accounting students in most schools nowadays, Python is a required course for accounting. 

So those that we are recruiting right out of college are already coming with a technical background. They’re digital natives. So we should probably give them a benefit of the doubt that we’re helping them move things forward. 

RON GUERRIER: How do you create this kind of data mentality, or data culture, inside IT with respect both looking at your internal stakeholders users as well as external folks outside the company that you may be interacting with? 

RON GUERRIER: So a couple of things, here at HP, for example, there is a software council. There’s also a data council and data analytics. And so every year, there’s a large council, where people from IT, people from our R&D group and our business, we come together. 

And we really share notes about what’s working best, what tools are the ones that make the most sense, what processes do we need to kind of sunset, potentially, because they’re not working for us. We bring in ML, we bring in AI, we bring on all those different things, and we just have a great 3 day discussion. 

It’s been virtual as of late, but we’re all in the same room trying to talk about how we can improve the condition. So there’s already a mindset of how important data is in the organization. So for me, coming to HP, that was already a win. So my job is how do I continue to fuel that. 

But the other thing is a lot of our individuals in IT, we are on different forums. I’m in different forums because what I don’t want to do is myopically focus on what’s in my shop. I need to understand what’s in my shop, what’s important, what’s going on in the industry, listening to your podcast, listen to other things, understanding what are other people doing. 

Because some of these challenges are not just specific to an industry. It’s across all organizations. So I want to make sure we learn from that. In some places, we’re not competing with what we’re learning from. 

So we can actually pick up the phone, and say, hey, what’s going on in the grocery store business with data, for example. Or what’s going on in noncompete industries? So we do a lot of that as well. And how do you bring that to bear? So I think it’s very important. 

And the last thing I’ll say to this quick topic is that, from Enrique Lores, who’s our CEO, on down, everyone understands the value of data. And they want to make sure that we’re using it wisely and we’re protecting it, which is awesome. 

We’ve already won that part over. Now how do we execute? 

MICHAEL KRIGSMAN: It’s really interesting to see how data is playing this central role at HP, in general, and of course in IT as you’ve been describing. Now, you mentioned earlier about diversity of data, and the diversity needed to create great decisions, the right decisions. 

Can you elaborate more on the importance and why? Why do we need diverse data? 

RON GUERRIER: The diverse data, as I said a little bit earlier, it’s because you have different perspectives so you’re not doing the same thing. You’re learning new ways. You’re actually growing because you’re kind of taking different perspectives. And I think everyone would agree, different perspectives builds your mindset and your thinking. 

But also, it’s the diversity of the data that it provides. And when I say that is, one of the really exciting things is this year HP partnered with MIT and something called removing anti-racism in technology. And when you hear that term, you’re like, what does that mean? 

Well, we all come with our unconscious biases. I have mine. You have yours. We’re human, right. And so when we code something in an AI platform or we work on an algorithm, sometimes those unconscious biases bleed into the work that we’ve programmed. 

And so the work we’re doing at MIT, for example, is we’re awarding scholarships and grants for organizations and startups that are looking to remove a certain biases in how we code, and what we do, and how we create equality throughout. 

So the one thing I truly enjoy about this company, HP, is that there’s truly a very strong social responsibility of the organization. So bringing that diverse thought comes into play. So that’s just diversity and kind of the people element. 

The other diversity that I really want to quickly highlight is that sustainability is very important. At HP we have data showcase how purpose drives our business. For two years in a row, HP sustainable impact drove more than $1 billion in new sales for the company. 

HP launched the world’s first notebook made with ocean-bound plastic sourced from a plastic supply chain in Haiti. Haiti happens to be my parents’ home country. So I have a true sense of pride with that. 

And so we know that we can make an amazing laptop, but use recyclable materials to be sustainable and green. The diversity of the information we get to say we can do this comes from all the data points that we’ve received. 

So diversity for me is not just who you live, where you live, who you love, who you pray to, whatever that is, it’s just bringing it all together to make a better product and a better solution. And I think it’s spot on at HP, we’re definitely doing that. 

And the fact that we are in many countries, we have teams throughout the globe, taking those different thought processes. Because what might work in Austin, may not work in Guadalajara, may not work in Singapore, for example. So really getting their perspective in market, what works for them that may not work here. 

So all those come into play. So that’s really exciting, and that’s why data is so enlightening and exciting for me. Because it really tells you a story, it’s a storyteller. If you’re going to peel back the onion, the insights you get from it could change your business model and change how you interact with your business. 

MICHAEL KRIGSMAN: So you’re very explicit in terms of thinking about the causes and the sources of unconscious bias when it comes to data and the results that will happen if that data is biased. 

RON GUERRIER: No, absolutely. And so I can’t speak for some decisions made in our history, right. Our history being as a society. But we can’t do things to eradicate it. Redlining, for example, things that were done in the past that did not really promote the American ideals of equality. 

So if we bring in data and we do it the right way, but we program it appropriately, we’ll make sure we take those biases out. So I think that’s extremely important that we do. Because I think we owe that to every generation to make sure that we provide equality. And the data will help us do that. 

And the last thing I’ll say to that is the pandemic has proved that data is important. We have to get the data out there, so we can make sure that we are helping the most people in need. So again data is an opportunity to kind of do that more in a better way. 

RON GUERRIER: So bias can come from two sources. Number one, as you just described, the way the data is analyzed. But there’s another underlying source of bias very often, and that is the type of data that we are collecting. 

So it’s not just the algorithms and the analytics that go on with machine learning, but it’s the sources of data. And so are you looking at the source data aspect as well? 

RON GUERRIER: Absolutely. Because if the data is tainted from the source, throughout the process– and I always say this is obvious statement. Bad data in an AI platform renders bad decisions and bad outcomes. 

So we really have to make sure that we have a level of confidence that the data at the source is trusted, it’s accurate, it’s timely, which is very important. So we look at it throughout its journey, so as it’s transported, when it’s sitting at rest, what we need to purge. 

So you’re actually spot on. It’s the human element of who we are as humans when we code. But it’s also where is it derived from. A tainted source will provide tainted information. So we have to make sure we do that better as well. 

MICHAEL KRIGSMAN: And how do you make sure that as an organization, and that as individual teams, that this diversity of data approach and mindset is being followed? Because it’s very easy to let it go and not worry about it. 

RON GUERRIER: Totally agree with that. And so one of the things, like I mentioned the data council that I mentioned earlier, while we meet annually, there are ongoing forums, and discussions, and focus groups that we actually talk about this on a regular basis. 

And not something that you talk about on a Monday, and you forget about it for like six months, and come back to it. It’s got to be conscious of how you’re doing things. But also, when you bring in new hires, for example, here are the principles that we follow and why we follow them. 

Please understand these and how we’re going to move this organization and society forward. So it is a mindset. It’s a culture. And the one thing I’ll say about HP culture, it’s a strong, it’s a very collaborative culture, and everyone wants to move forward together, which is pretty awesome. 

So but, yes, it is a mindset that we have to embed in each and everything we do, each and every day, for the most part. 

RON GUERRIER: And you mentioned hiring and talent management. So that’s an important part of this equation as well. 

RON GUERRIER: Yes, and I see myself, not only as the CIO, but I’m also one of the, I’m a recruiter. I’m out there. And again, I can’t wait to get in front of colleges, and sit in booths, and talk about what it’s like to work at HP, and all those opportunities. But, yes, recruiting is top of mind for us each and every day. 

RON GUERRIER: Do you have advice for business leaders on how to adopt a more diverse data policy, and data mindset, and bring that to a team, and embed it in the team? 

RON GUERRIER: That’s a great question. And what I’ve always done, whether it’s here at HP, but in my past roles is I’ve worked closely with our marketing department. Because the marketing team will always help you build a strong business case. That if our customer base is diverse and change, we have to be diverse and change ready. 

And so it really starts with it’s a good business model, it’s a good business practice. It also works with your HR colleagues and say, hey, this makes sense, because diverse teams, the math tells you that they have better ideas, better outcomes that are more successful. 

And even with my own team, I always ensure, and I say this to my own team is, I need sparring partners. When I go to the meeting and I say something that’s completely left, I need you really to go right. I used to have one person that was always assigned to be the detractor. Like, hey, and whatever Ron says, do the opposite. 

And let’s challenge each other along the way. Because the outcomes can be so much better. But, yes, having the business understand that is very important. And then the beauty about it is this is an easy sell for most people. Like this makes sense. Here are the reasons why. 

And so getting the data to be diverse, getting people to think in a diverse manner, goes a long way. But the business partners have to be along on the journey. It can’t just be IT saying it, and the business saying, well, what are they talking about. So it’s truly a collaboration. 

RON GUERRIER: And on an ongoing basis, as you said 

RON GUERRIER: Oh, yes, yes, it can’t be a one and done. You can’t just check the box and say, I think I got that. It’s ongoing. And then also, how do you hold people accountable? Another thing is people’s behaviors change on how you keep them accountable. 

If you hold them accountable to do certain KPIs, certain things, they will achieve those. It’s the human condition. We want to improve, and get better, and prove that we’re adding value. So that’s part of the dialogue as well. 

RON GUERRIER: What about using data to help drive increased diversity and inclusion? 

RON GUERRIER: Yeah, that’s a great question. So it is another mechanism to do so. One of the things here at HP we’re really focused on is just really addressing the digital divide. I think it’s very, very clear, especially during the pandemic, whether it’s learning, or telehealth, or whatever it is, there’s disparities there. 

So the data exposes that. So the question is, how do we take that and change the world in a better way? So partnering with the business, understanding how the inclusiveness of that goes a long way. The other thing that’s very important is partnering with schools early on. 

So HP partners with HBCUs. We actually just had our first ever HP HBCU tech conference. It’s a mouthful, but HP HBCU tech conference. And it went well. And actually it was a week and a half. It’s actually still going as we speak. 

And what we’re doing is we’re reaching out to the HBCUs, we’re reaching out to universities, and really talking about what are the skill sets that we need to move a company forward, and what we’re seeking when it comes to those skill sets. So that is amazing, a lot of great dialogue. 

And the one thing I’ll say when it comes to diversity is also diversity of skill set. The one thing that I’m seeing over time is we have to do a better job of evangelizing technology. Like we have to be able to be good storytellers to the business. 

Because sometimes we default. It’s like we went with this technology because. Now, we have to explain the back story as to why that decision was made. Because when you tell some of the back story, they’re in the boat with you. They understand that decision was made. It’s for our both benefit, let’s get rowing. 

But if you don’t, and they feel like an outsider, resistance happens. And so we want to make sure that we bring everyone along the way. 

MICHAEL KRIGSMAN: And of course, HBCUs are historically Black colleges and universities. 

RON GUERRIER: Correct. 

MICHAEL KRIGSMAN: So a phrase that we often hear is purpose driven. And how does data support a purpose driven organization rather than just doing business as usual, as we’ve always done it? 

RON GUERRIER: Yeah, so my definition of purpose driven hopefully is, hopefully the norm for most, is truly setting hard goals for yourself. And hard or soft, whatever it is, having very clear goals and really, really being focused on a common vision to move things forward. 

And it might be just your organization, but hopefully it’s the ecosystem around you, and the communities around you. So being purpose driven is very important with that. And the thing that really backs a very strong purpose driven approach is the data. 

And the reason I’m bringing this up is purpose driven approaches, missions, for them to be sustainable, the data and the science does help to support that. Because sometimes we move with our heart, and that’s a good thing. We’re humans, that’s good. 

But the data also helps you bring in the logic as to why that’s also good, right. So we have to make sure we bring the data to support the sentiment and the purpose behind our intent. So I really believe that’s very important. So, yes, it does definitely tie-in to being a purpose driven organization. 

MICHAEL KRIGSMAN: Can you give us any example of using data rather than just relying on our heart, how we feel? It’s like, oh, yeah, I think this or I think that, but relying on the data. 

RON GUERRIER: So diversity, we’ll just talk about that. It’s a big one. So it’s proven through many studies– and again, my sister’s a doctor of psychology, so she hits me with this stuff all the time– the most diverse teams, when they’re in the ideation phase, might take a little longer. 

Because of course, there’s friction, natural friction, different opinions, and different views, but the outcomes are usually 10 to 20 times better because they’ve thought of different ways and different approaches. So the data definitely supports why diversity matters. Not because of something that happened in current events, because this is just the right thing to do. 

And over time it has proven to be the case. But also it brings in different ideas. So quick example, someone sees what we’re doing with 3D prints, the ability to bring in someone else’s mindset, well, maybe 3D print could do something else in the medical field. 

Maybe we’ll start thinking or tinkering about that stuff in the medical field. So the diversity also brings in different approaches to some of the technologies we already have in place. 

MICHAEL KRIGSMAN: And, Ron, as we finish up, what advice do you have for business leaders who want to use data to drive innovation, and data to drive greater diversity? 

RON GUERRIER: So the first thing I’ll say, and this is a selfish plug for my technology friends out there, the business leaders get to know your technology group. Like sit-in, get in the meetings, understand what their challenges are, what their constraints are, and really understand what those strategies are. I’ll say that’s the first thing. 

And of course, my IT friends, understand your business even more. But for the business, the most important thing for me, I would say, is really, really understand the data that you have. But be very conscious and cognizant that there’s data you don’t have. 

And that’s the diversity. That’s bringing in new insights. And really understanding how you can make a better business model by really understanding the data you have and the data you don’t. And really have a strategy, and fund that strategy, make the investments. 

But the biggest thing I would say to my business colleagues, it’s OK to trip up and have a couple of failures from some of your test scenarios. You can fail fast, everyone’s talking about it. Really learn from that, do a couple of proof of concepts, learn from it, set it aside, and just constantly iterating and doing things. 

Because keep in mind, the first prototype is usually not the one that’s amazing. It’s usually a few later, so really invest in those opportunities and those prototypes. Because you may not get an ROI in the first year or two. But if you keep being persistent, there will be an ROI to be found from that, but really invest in the data strategy. 

And the last thing, broadly, is understanding while data is important, as you’re saying, as we’re talking about, make sure you invest in cyber. Because that is what’s going to protect your data. Make sure you invest in architecture because that’s going to be the blueprint for everyone to follow, and the governance. 

If you get those key components right, you could really move mountains and accelerate things. 

RON GUERRIER: So if I can summarize, have an open mind, experiment with the data, don’t worry if it doesn’t meet your needs every time, keep going, make sure that your enterprise architecture can support what you’re trying to do, and never ever forget about security. Does that summarize what you just said correctly? 

RON GUERRIER: I think you hit it spot on, Michael. That’s exactly what I said. 

RON GUERRIER: OK, what an interesting and rich conversation. Ron Guerrier, thank you so much for taking the time to speak with us today. 

RON GUERRIER: Thank you, Michael. It’s been a pleasure as well. Thanks. 

MICHAEL KRIGSMAN: A huge thank you to Redis for making this podcast possible. It’s awesome that Redis is supporting thought leadership and educational efforts like this. So thank you to Redis. I really appreciate it.

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