Despite decades of massive investment in technology, most organizations are no more productive or profitable today than they were 30 years ago. In the first episode of a new podcast series from The Technology Economists, Howard Rubin challenges the assumption that new technology automatically creates value—using decades of real-world data to explain why it doesn’t.
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Hello, I’m Howard Rubin. You may be familiar with my work and technology economics, both as an academic and as a practicing professional.
I’m here today to talk about the patterns I’ve observed in the world of technology economics and sort of what I considered to be the crisis of technology and value. A lot of this is stimulated by the ideas that I put forth at the TBM Summit, the Technology Business Management Summit in November.
But let me back up a little bit. See, I truly believe we’re in a technology economy. And you might say, what’s this man talking about? I also believe that the world needs technology economists. I’ll get to that too. But in fact, the key point is we have gone from an industrial economy. And just look at the markets. The markets in the 1800s, none of us are all that. No enough to deal with that, even with mates. But in fact, you know, we’re growing with railroad.The early 1900s were automotive and airplanes, and we got up even to the 1970s, it was oil and energy. But watch the markets every day.
What moves the world’s economy? What’s in the news every day? Right now, it’s AI, it’ll be quantum after that, it’ll be cloud before that and everything else. So I’ve been trying to understand the creation of value through the use of technology. And I have a suitably weird background in that I have a doctor in computer science. And actually it’s called marine microbial ecology and oceanography and stuff like that. And when you’re natural science, you look at patterns.
So, I decided to explore the patterns of the technology economy. And again, when we talk about technology economics, you might say, so what the heck is different between that and classical economics? Well, classical economics looks as the supply and demand and allocation of resources. You go to an it organization that focusing on it finance, which is aptly critical, but who is managing the linkage between technology and how does value manifest itself? And that’s what a technology economist does. They look at the input and technology and implementations and the output in terms of value and value to business might be in terms of margin and that promoter score a whole bunch of other factors. Sharehold of value in the public sector that might be impact on health, educational welfare.
So anyway, stimulated an invitation I had to appear at the Technology Business Management Summit in Miami that was back in November. I was asked to speak about technology and value. So I have 30 years of data at least collected. In my 30 years of data, I cover about 3,000 companies in 20 sectors. So, I decided to look at the for profit sector and look at patterns. They say, so what is all this about? So imagine you draw a timeline and that particular timeline as going back into the 1990s when we have the internet, then we end up having beyond the internet, we start getting into e commerce, then after e commerce, we come into things like cloud and then we’ll come up all the way to jump to AI and jump to quantum. So imagine you draw this big X axis like that and then on top of that you start to take a particular business parameter and my expectation was that I would see inflection. So I would see a big change.
When we started the internet and then e commerce and even cloud, we start to see a change in margin or some of the other business parameters. Well, guess what? When you do that overlay, it’s all flat line. There has been no significant difference across this average large sample size and I use the word average. There are outliers that broke away from this, but very few. An average performance in 2025 was actually worse in most businesses than it was in the early 1990s. So there were no inflection points. So I said that was quite a surprise, although I was looking for something out there in terms of this experiment cause I’m looking at patterns and this is about patterns. It’s not about statistics. That’s what happens in natural science when Darwin did not use statistics in the Galapagos to figure out what’s going on. And I’m trying to figure out what’s going on in the patterns of technology and value production. So digging underneath that, it seemed pretty clear to me cause they also have data on technology implementation and sort of Al Gore, like a whole bunch of inconvenient truths become obvious.
So inconvenient truth number one […0.5s] is really there quite simply that implementing technology does not ensure value implementation.
Number two as putting technology in place, but the inconvenient truth is, is why you putting in place. You doing it cause someone heard about it on the news. You border saying why aren’t you doing this about cloud or stuff like that.
In fact, the other inconvenient truth is that technology is not a fashion show statement. So the real issue really becomes, you know, what do you do to get value and in fact, what are the other inconvenient truths associated with technology and technology economics.
And this is a launch of the series on our website, Tech. Economist. Com. And the series is gonna cover the various inconvenient truths and they’re gonna start exploring this. And if you go to the website, you’ll start to see the whole program. And I’m leaning over here cause there’s a whole list of the inconvenient truths we’re gonna start to deal with in the inconvenient truths, even if just about AI itself and the fact and fiction about layouts of the recording cause of AI or that the ROI of AI is high. This is not about anti-AI. This is about the truth. And there are other interesting things here. Like even tech spent for employee went up, but employee productivity did not go up over this whole period of time. That’s another inconvenient truth about how do you link productivity to your implementation of technologies. And there’s cloud in there and digital transformation and patented measure that I have called technology intensity. But the fundamental theme of the theory is let’s look at technology economics. Let’s look at the inconvenient truths. And in the end, I mean in the end, looking at all this stuff, technology itself is not a fashion statement. You’re implementing it for, there’s a business or social reason for doing it and you’re looking for what the value is. So […0.4s] please take a look at our website. We’re gonna be putting out the series, or at least 8 short programs in the series. I mean, I am told I speak too long and I actually cut this talk right now from 20 minutes down to whatever it turned out to be. And my wife would agree with that too, cause she said I could probably talk if nobody was even in a room or awake or listening. But anyway, these are gonna be short clips, sort of podcast dealing with the inconvenient truth of technology economics. So I invite you to join us. I invite you to look at our website, techEconomist.com and really get under the covers in terms of the technology economy and getting value from technology. Thank you very much and I look forward to having you join me.