Episode 2: Value for Money in IT: How to Measure What Matters

Anni Tabagua: Hello and welcome to BizTech Forward, the podcast where we delve into the world of technology and business with some of the brightest minds at DataArt. I'm Anni from the Media Relations team, and I work with these brightest minds daily. So, please think of me as your friendly tour guide as we discuss the past, present, and future of tech. Today, we're going to talk about something quite important for every business leader, I would say. And that is getting the best value from team investments.

In other words, how do companies evaluate whether their IT investments benefit their businesses? To unpack the topic, we are joined by Alexei Miller, Managing Director of DataArt. Alexei, hi, and thank you for being with us.

Alexei Miller: Thank you for having me. I would not miss it. The topic has two of my favorite words: value and money.

Anni Tabagua: Alexei has been with DataArt since its founding more than 25 years ago. He helped build the company into what it is today, from a small team to a large global software engineering firm. He has also overseen business development, client relationships, and the expansion of the finance practice, among many other things. Alexei, again, it’s great to have you with us. Welcome to the show. So, let's get right into it.

We're going to try to break it down into three parts: the past, present, and future. So, let's start by looking back. Alexei, how did companies traditionally approach this? What was the way to measure the value of IT, say, three to five years ago?

Alexei Miller: If you allow me, I would start way earlier, 3 to 5 years, basically yesterday. When I think about the past, sometimes I find it convenient to look 30, 40, 25, or 60 years ago when it actually started or at least started to take the shape it has today and gain the importance it has gained by now. And I think the way it started was kind of right.

And then, in some ways, not all, it was better than now because it started by being helpful, by being a service that makes things simpler, faster, and cheaper, making systems that allowed companies to process things better, make fewer errors, optimize things, and therefore save on costs and so on. So, simply put, it started by being helpful and being a service, being a concierge, if you will, to use a fancier word.

Measurement of value back then was a relatively simple exercise of comparing something before and after. Before IT, you would've had 100 people doing something; after IT, you would have one computer that costs doing something. However you want to, you want to measure it. And because before and after that could be measured in something that is numerical or close to it.

Value was measured fairly straightforwardly, using money, time, people, and so on. Honestly, I think it was healthy. I think it was, for a long time, relatively free of fluff. Today, that's a big part of the technology industry. And it kept this way up until, I'd say, the internet boom of the early 2000s and late 1990s when words like innovation, synergies, and others started to acquire additional meaning to what they are supposed to mean.

I know you asked me about 3 to 5 years ago, which is very recent, but I think looking at this free internet is helpful. It had a very pedestrian, very practical focus, which, like I said before, I appreciate.

Anni Tabagua: So basically, it started with the bottom line to be helpful.

Alexei Miller: That was the purpose. And I think that purpose was the same as every other function in the company. It was not exclusive to IT. You hire an accountant to do something to be helpful to the business. You hire marketing to be useful by helping promote the business. You hire IT to do something and something that is all logical.

In the early days of IT, it was very expensive. It was new, and it was also very expensive. Computers were large and also very expensive. People who knew what to do with them were hard to find and expensive. So it was very attractive because it meaningfully improved things. But it forced this idea that you have to think hard about whether you can afford it and if you can actually drive value from it.

So, the questionable but useful side effect of things being expensive is that unless you have an enormous amount of money, you evaluate whether you really need that thing. So, it was helping itself be helpful by being expensive. I hope that makes sense.

Anni Tabagua: I'm kind of intrigued by the word you used: fluff. So when did all the fluff start to come into play? And what exactly do you mean by that?

Alexei Miller: Well, first, I want to say that fluff is not a bad thing in business. I guess half of business transactions are based on substance and half on fluff. Fluff means promise, and it may translate into excitement. Those are not bad things; they are less material than some measurable, measurable things that have their place. So it's important not to get carried away.

So, I don't want the fluff to be exclusively negative. But let's just say that over the years, starting roughly in the very late 90s and definitely accelerating more recently, I see the value of IT starting to become more nebulous because, of course, it can create new capabilities. You can sell things on the Internet, which you could not do before the Internet.

That's new. Sometimes, you can provide other services on the internet that your customers may or may not need or may or may not be willing to pay for. And that's more nebulous. It's not just about taking your old business and making it run better and more efficiently, which is very material and very measurable. As we discussed before, it's about creating something new.

You're making your hypothesis about the future, and what happened, I think, is that IT people turned out to be amazing marketers and salespeople. I know this goes against the popular logic that IT people are nerds who don't want to sell or know how to sell. They speak in these complicated words.

They get irritated by business people because business people don't know what they're talking about. But there's this enigma about IT, and business people are very willing to believe that there's something behind that enigma. So, IT has been very effective in marketing stuff, some of which businesses did not need.

The business was very willing to spend money on something that needed to be fully measurable, not fully verified, and so on, which is fine. Sometimes, you need to take risks, and maybe for some businesses, that's more relevant than others. But when I say fluff entered this conversation, it's that the business somehow became much more willing to pay for things based on this enigma.

What about we try to bring this technology into the market? Wouldn't this be great? Maybe yes, maybe no. How do we know? Let's just try. This conversation was possible because technology got cheaper. Remember how we discussed it was reassuringly expensive, which forced a long thought. Now, bringing this product is only $1 million, no longer $100 million. Let's just spend it and see how it goes. It's a viable logic, but that logic leads to waste. And the other thing driving a lot of technology investments in the last ten to 15 years is envy. The other guy, the other bank, the other pharma company, the other e-commerce retailer, has this gizmo. We must have that gizmo as well. And then there's this post-fact rationalization of why we need this gizmo. That's not super healthy; that's nebulous. That's ultimately what I talk about when I say fluff.

Anni Tabagua: Okay, that makes sense. And if we, I guess we can spend quite a while discussing the fluff, the past, and how it used to be, but maybe fast track to today. Would you paint us a little picture of how you see today? How has it changed? Where do we stand now? How do businesses measure IT spending and its value now?

Alexei Miller: Businesses have gotten a lot better at understanding technology. That helps have substantive, serious, meaningful conversations about what IT does and, ultimately, the return on investment or value for money. This terrible cliché was so prevalent 25 years ago that the boardroom does not understand technology. The boardroom understands technology now, and that's a good thing.

It's a great thing. So, I'd say those conversations and those calculations have become more meaningful. They've also become multidimensional. If they were fairly simple before and after a single number or a couple of numbers there, those evaluations try to capture multiple factors, obviously financial impact.

Are we going to make more money with this investment in technology? Are we going to spend less money? But there are also less quantifiable things. Are we going to reduce risk? There are many risks: cybersecurity risk, compliance and regulatory risk, business risk, competitive position risk, and key person risk. How do you quantify them? Technology has a very prominent role in that.

You need to find a way to express that value and risk impact in terms that are meaningful to your board, your executive team, and ultimately to your customers. That's different for every company and for many different industries, but it's certainly something that has entered the conversation.

People are trying, and that's a good thing. The other thing that entered the conversation, in my view, was excitement. It's not a word you typically hear in conversations that are supposed to be about cold business calculus. But tech has succeeded in selling this idea that technology creates new capabilities, pushes businesses forward, and opens new doors.

It allows you to engage with new types of customers and so forth. That's exciting—exciting, as in, "Oh, we can make more money." That's one side of excitement, but also excitement as in, "My people are more motivated. They'll love the tools they're using. They are excited to come to work, work from their home office, or whatever it is."

My customers are excited by the stuff we sell to them. That is meaningful. But it's also ultimately excitement. How do you measure that? I've seen attempts to measure the numbers and the crowd, and I don't think they're very successful. So I think in the best case, businesses have come up with this multidimensional model of looking at what value means to them, to their people, to their investors, and their customers, the trio of new business employees, investors, customers, in no particular order, and have learned to map this multidimensional matrix of value onto this trio.

I think there needs to be a unified way to visualize it. Everyone is out for themselves, and that's a much better place than where we were in the early 2000s when there was much excitement but no meaningful conversation. It's more sober. It's not perfect, but it's more sober.

The other thing that is new today, relative to where we were 20 years ago, is that we have data. We have data on thousands of decisions and business decisions that were made. And we know the impact of a collection of those decisions. This is a whole new field of decision science that takes the decisions, how they were made, under which conditions they were made, and the implications or consequences of those decisions.

This can be quite helpful in making better decisions going forward. Businesses have made thousands of IT decisions over the last 25 years. They know how it ends up and can make value decisions based on that data, not just a hunch or not just because it's new anymore.

That's an interesting twist. To what extent are companies willing to consider and trust that data, or is it just informing their thinking? That is individual for every client. We advocate for more data to be brought into those conversations—historical data, any data.

Anni Tabagua: You did mention this, but I want to maybe come back to it or have you talk about this a little more. You did say that there are things that you cannot measure that are more difficult to quantify. I'm thinking of businesses doing business together. That means relationship, trust, strategic alignment, people, and cultural fit.

How do you measure all that since it doesn't really show up on a spreadsheet now? How do you quantify things like cultural fit with an IT partner from your experience?

Alexei Miller: I personally think you don't measure it. You judge it, and that may be the same thing for many people. But it's meaningfully different for me. What you judge is fit and comfort. I'm coming dangerously close to talking about decidedly non-IT things like clothes and shoes, but I think it's a useful analogy for me.

Like when I buy shoes. I don't know about you, but I actually buy quite a few shoes, and I go through a fairly similar process every time. Am I going to use these shoes or this system? Is it too expensive for what I'm going to use it for? What kind of impact is it going to have when I wear it?

Some will be impressed, and I will be impressed, whatever it is, and I have to somehow make this mental equation of whether it's worth it for me. But also, I try them, evaluate, judge comfort, and walk in them. How do they feel? It has nothing to do with their looks, or at least not as much.

But comfort matters a lot. And it's the same thing. And I ascribe certain value to that comfort. They look ugly, but they feel amazing. I'm not going to buy those shoes. They look great, and they feel amazing. I'm more likely to buy those. The same exact thing applies to your IT partners or IT projects; more broadly speaking, you just start.

So, IT projects are long, mostly painful and expensive, and then generally unpleasant in the sense that you know something will go wrong. It's not all bad, but sometimes, in a long and complicated project, there will be problematic moments along the way. And so, your experience while you're wearing those shoes or while you're going through that project and your level of comfort is hugely important.

You can't measure it in money, but you can certainly judge the comfort. Another analogy that is often used in our line of work is that starting a new project, making energy investments, partnering up with a new supplier, and partnering with or onboarding a new platform—whatever it is—is like a taxi ride.

You really, really care about the comfort along the way. And you should and can judge that comfort. But I think folks may be a little too demanding of themselves when they try to measure; just see what it feels like, just like with the shoes.

Anni Tabagua: I love that comparison—both of them, actually—but I definitely did not expect shoes and IT projects to be used in the same sentence. So thank you for that. It makes a lot of sense. It makes me think there are so many shoes, let's say there are so many people doing IT projects, and this is what makes me think of comparing yourself to others.

Where do you think comparison comes into play? Is it ever healthy to compare yourself against your competitor? You know, benchmarking and all that jazz? Is it ever helpful or healthy?

Alexei Miller: Yes, within reason. So, I think comparison, envy, or competitive envy is a very useful way to start many conversations. And it's a terrible way to end conversations. "The other bank or my competitor has this gizmo" is great to know. A very useful thing to say is to start the project or just start the thinking process.

Do I need this gizmo? What advantages does it create for them in the marketplace? What advantages could it give me? So, it's a great source of ideas, intelligence, and something material. If they made an investment, maybe it resonated with them. What logic do they go through?

But it's a terrible way to end the conversation. If I'm going to spend my money just because someone else has the shoes or an IT gizmo, I have not done my work. And that's not a good way to end the conversation. So comparing has its place, for sure. Comparing with the idea of doing better is even better than just comparing. It would be awful if all companies in the same line of business had the same systems and user experience.

It kills innovation, so I love it when our clients come to us and say, "I want a gizmo like my competitors have — just better." Catching up is great. Sometimes, you just have to make defensive moves in business, and I totally get it. But this extra step, compared with the idea of getting one up on your competition, drives the business forward.

It's a risky path, for sure, but that's maybe for another conversation. Maybe we should do another podcast on risks some other day in the room, and we'll talk about the risks associated with that.

Anni Tabagua: Oh, that's for season two. Stay tuned, everybody. We are moving on to, I think, my favorite part now. Okay, so here is a brief recap. We did the past and the present. So Alexei, let's predict the future now, please. No pressure, but what is the future? Specifically, how do you think businesses can make sure they're not just sitting there measuring IT value however they can. Still, they're actually getting the most out of it, especially when working with tech partners like DataArt.

Alexei Miller: Well, I envy you. I knew that the future was your favorite part. I kind of like the past because I know the past. It happened, and I can actually make bold statements about it without being wrong. They're objective. Those things have objectively happened. The future? I have no idea. And therefore, I am very likely to be wrong.

So, the best I can offer is just some speculation about ways that companies, many of our clients, partners, and others in the industry should evolve. I don't know exactly how it will turn out. One thing that comes to mind here is that we all need to get better at dealing with speed.

Speed of change. I mean, it's just dizzying and discomforting to many. And it manifests itself in so many ways. The most banal, obvious example, although it's weird to call banal something that is considered so exciting, is ChatGPT. It came out two years ago, and it went so quickly from being the greatest disruptor to everyone actually having chatbots. Now, why do we need all those chatbots? It's not even two years. It's happening so quickly, and companies have spent a lot of money and time thinking about it. It scrambled a lot of IT investments and projects that had a reasonable idea of value but were about to have it. They had a plan, and then they said no, stop it, stop it. Because AI or ChatGPT or whatever might impact that. So it's happening so fast that it can have this paralyzing effect because everyone now understands that the day after tomorrow is going to change again. Why bother? So that's a bit of a risk.

Today, we don't want the speed of innovation to be so blinding and paralyzing that we don't do anything. We need to carve a reasonably reasonable path forward. Another way the speed of change manifests itself is on the human level. If you look at the average tenure of technology leaders in large corporations, it's getting shorter.

There's this constant speed of change and turnover in the C-suite, starting and restarting projects, and so on. Right now, the best I can describe speed is dizzying to many of us. I certainly am not immune to that. And we need to all get better at dealing with speed.

In my view, keeping a cooler head and ignoring some of the buzz is key. But many might disagree with me here. It's a total cliché to say that IT has become an essential and core part of most businesses. That's not going to change in the future. That's a fairly safe prediction to make.

Anni Tabagua: And if you could comment a bit more on the technology, which you did mention a couple of times, but technology will surely keep playing a huge role. Data, data, data everywhere. Obviously, data will help measure things, but will the human element still be crucial? In other words, Alexei, will they still want us in the future?

Alexei Miller: The question is, who are they? Will they want us, they other humans, or are they these supposedly omnipresent non-humans? I have no idea. But I can tell you that I admire the amazing progress that tech has made over the last ten years. And I say ten years purposely because that's when it really started to accelerate.

Generative AI is a little bit of a sideshow. It's literally a gizmo that a lot of people get excited about. It has utility but is somewhat useless. But overall, the search for intelligence that can feed on prior human experience, make reasonable decisions, and assist in our lives in so many ways, from robots to artificial intelligence, computer vision, and so on, is immensely exciting. And I think it will be helpful. And they, whoever they are, will need us. But our uneasy union will be a pretty exciting thing to see. And is it an unwanted comment? I know, but since we mentioned ChatGPT and generative AI, can I just say I hate the term?

I think Generative AI is just awful because it's so close to "Degenerative AI." I know I said previously that IT people have been good at marketing, but here, I think conversational AI is a better term. But nobody's listening to me on this subject.

So I think, I hope that this generative AI tongue twister kind of goes away.

Anni Tabagua: Since we were talking about measuring the value of IT and maximizing the value you can get from all the spending, maybe just 1 or 2 sentences on a key takeaway that you would give companies to understand. How do they get the most out of IT value today? In today's world, it is like one takeaway.

Alexei Miller: I think because things change so fast, trying to get it right has its limits. Get it somehow. Limit your exposure, get on with it. Prepare to be wrong. Reevaluate. It's okay. We're all wrong about most of these things much of the time. And that's okay. As long as you're not wrong to the tune of a lot of money you cannot afford. And as long as you are right, a little bit more than you were wrong. It's all right. And it's a great way. I was inspired by this. I know you ask for 1 or 2 sentences, but I can't help myself. So, everyone's favorite tennis player, Roger Federer, was giving a commencement speech at Dartmouth College a few months ago. He said, "In my professional career, I won an ungodly percentage of matches, 80% plus percent of matches. But guess how many points I got in those matches I won? 52%, 53%, something like that. Just barely half." His point is that as long as you are right or win more than you lose, you will be all right.

Anni Tabagua: That's great. That's a great note to end on. Alexei, thank you so much for talking to us today. It's been really insightful. Thank you to our listeners for tuning into BizTech Forward. If you enjoyed this episode, please subscribe, rate, share, like, and stay tuned for more. We always want to hear from you—thoughts, questions, insights, anything. Reach out to us at BizTechForward@DataArt.com. Thanks again, and until next time.

Alexei Miller: See you later.