How data will transform business

How data will transform business

 

I'll talk a little bit about strategy and its relationship with technology. We tend to think of business strategy as difficult in the economic sense, perhaps somewhat abstract. Business strategy has always been based on assumptions about technology, that these assumptions are always changing dramatically, and therefore, this will lead us to a new, different concept. of what we mean by business strategy. Let me start, if I can, with a little history.

The idea of ​​strategy in business owes its origins to two intellectual giants: BCG founder Bruce Henderson and Michael Porter, a professor at the Harvard Business School. Henderson's central idea was what you might call the Napoleonic idea of ​​concentrating mass against weakness, of crushing the enemy. What Henderson recognized was that in the business world, there are many phenomena that are characterized by what economists would call increasing returns - scale, experience. The more you do something, disproportionately, the better you get. And therefore he found a logic to invest in such types of overwhelming mass in order to gain competitive advantage. And this was the first introduction of essentially a military concept of strategy in the business world. Porter agreed with this premise, but qualified it. He pointed out, correctly, that everything is fine, but companies really do have several steps for them. They have different components and each of these components can be moved by a different type of strategy.

A business or a business can actually have advantages in some activities, but at a disadvantage in others. He formed the concept of the value chain, essentially the sequence of steps with which, say, the raw material, becomes a component, is assembled into a finished product and then distributed, for example, and argued that advantage accrued for each of these components, and that the advantage of the whole was, in a sense, the sum or average of those of its parts. And this idea of ​​the value chain was based on the recognition that what unites a business is the transaction cost, which basically you need to coordinate, organizations are more efficient in coordinating than markets, often and therefore nature , the role and limits of cooperation are defined by transaction costs.

It was in these two ideas, Henderson's idea of ​​increasing returns to scale and experience, and Porter's idea of ​​the value chain, encompassing heterogeneous elements, that the whole edifice of business strategy was later erected. Now, what I will argue is that these premises are, in fact, being invalidated. First of all, let's think about transaction costs. There are actually two components in transaction costs. One is about information processing and the other is about communication. These are the economic aspects of processing and communication as they have evolved over a long period of time. As we all know from so many contexts, they have been radically transformed since the days when Porter and Henderson first formulated their theories. In particular, since the mid-1990s, communication costs have fallen even faster than transaction costs, which is why communication, the Internet, has exploded so dramatically. Now, falling transaction costs have profound consequences because if transaction costs are the glue that holds value chains together and is falling, there is less to save. There is less need for vertically integrated organization and at least value chains can disintegrate.

They do not necessarily need to, but they can. In particular, it then becomes possible for a competitor in a company to use its position at one stage of the value chain to penetrate or attack or deintermedia the competitor in another. This is not just an abstract proposition. There are many very specific stories of how this really happened. An example of child-advertising was the business of the encyclopedia. The business of the encyclopedia in the days of leatherbound books was basically a distribution business. Most of the cost was commission for the sellers. The CD-ROM and then the Internet came, new technologies made the distribution of knowledge much cheaper and the encyclopedia industry collapsed. It is now, of course, a very familiar story. This, in fact, more generally was the story of the first generation of the Internet economy. It was about the fall in transaction costs, breaking down value chains and thus allowing disintermediation, or what we call deconstruction. One of the questions I was asked occasionally was, well, what will replace the encyclopedia when Britannica no longer has a business model? And it was some time before the answer came. ipedia is not your distribution. What's special about Wikipedia isnot its distribution. What's special about the Wikipedia is the way it's produced. The Wikipedia, of course, is an encyclopedia created by its users. And this, in fact, defines what you might call the second decade of the Internet economy, the decade in which the Internet as a noun became the Internet as a verb. It became a set of conversations, the era in which user-generated content and social networks became the dominant phenomenon. Now what that really meant in terms of the Porter-Henderson framework was the collapse of certain kinds of economies of scale. It turned out that tens of thousands of autonomous individuals writing an encyclopedia could do just as good a job, and certainly a much cheaper job, than professionals in a hierarchical organization. So basically what was happening was that one layer of this value chain was becoming fragmented, as individuals could take over where organizations were no longer needed.

But there's another question that obviously this graph poses, which is, okay, we've gone through two decades -- does anything distinguish the third? And what I'm going to argue is that indeed something does distinguish the third, and it maps exactly on to the kind of Porter-Henderson logic that we've been talking about. And that is, about data. If we go back to around 2000, a lot of people were talking about the information revolution, and it was indeed true that the world's stock of data was growing, indeed growing quite fast. but it was still at that point overwhelmingly analog. We go forward to 2007, not only had the world's stock of data exploded, but there'd been this massive substitution of digital for analog. And more important even than that, if you look more carefully at this graph, what you will observe is that about a half of that digital data is information that has an I.P.


Address. It's on a server or it's on a P.C. But having an I.P. address means that it can be connected to any other data that has an I.P. address. It means it becomes possible to put together half of the world's knowledge in order to see patterns, an entirely new thing. If we run the numbers forward to today, it probably looks something like this. We're not really sure. If we run the numbers forward to 2020, we of course have an exact number, courtesy of IDC. It's curious that the future is so much more predictable than the present. And what it implies is a hundredfold multiplication in the stock of information that is connected via an I.P. address. Now, if the number of connections that we can make is proportional to the number of pairs of data points, a hundredfold multiplication in the quantity of data is a ten-thousandfold multiplication in the number of patterns that we can see in that data, this just in the last 10 or 11 years. This, I would submit, is a sea change, a profound change in the economics of the world that we live in.

The first human genome, that of James Watson, was mapped as the culmination of the Human Genome Project in the year 2000, and it took about 200 million dollars and about 10 years of work to map just one person's genomic makeup. Since then, the costs of mapping the genome have come down. In fact, they've come down in recent years very dramatically indeed, to the point where the cost is now below 1,000 dollars, and it's confidently predicted that by the year 2015 it will be below 100 dollars -- a five or six order of magnitude drop in the cost of genomic mapping in just a 15-year period, an extraordinary phenomenon. Now, in the days when mapping a genome cost millions, or even tens of thousands, it was basically a research enterprise. Scientists would gather some representative people, and they would see patterns, and they would try and make generalizations about human nature and disease from the abstract patterns they find from these particular selected individuals. But when the genome can be mapped for 100 bucks, 99 dollars while you wait, then what happens is, it becomes retail.

It becomes above all clinical. You go the doctor with a cold, and if he or she hasn't done it already, the first thing they do is map your genome, at which point what they're now doing is not starting from some abstract knowledge of genomic medicine and trying to work out how it applies to you, but they're starting from your particular genome. Now think of the power of that. Think of where that takes us when we can combine genomic data with clinical data with data about drug interactions with the kind of ambient data that devices like our phone and medical sensors will increasingly be collecting. Think what happens when we collect all of that data and we can put it together in order to find patterns we wouldn't see before. This, I would suggest, perhaps it will take a while, but this will drive a revolution in medicine. Fabulous, lots of people talk about this. But there's one thing that doesn't get much attention. How is that model of colossal sharing across all of those kinds of databases compatible with the business models of institutions and organizations and corporations that are involved in this business today? If your business is based on proprietary data, if your competitive advantage is defined by your data, how on Earth is that company or is that society in fact going to achieve the value that's implicit in the technology? They can't.

So essentially what's happening here, and genomics is merely one example of this, is that technology is driving the natural scaling of the activity beyond the institutional boundaries within which we have been used to thinking about it, and in particular beyond the institutional boundaries in terms of which business strategy as a discipline is formulated. The basic story here is that what used to be vertically integrated, oligopolistic competition among essentially similar kinds of competitors is evolving, by one means or another, from a vertical structure to a horizontal one. Why is that happening? It's happening because transaction costs are plummeting and because scale is polarizing. The plummeting of transaction costs weakens the glue that holds value chains together, and allows them to separate. The polarization of scale economies towards the very small -- small is beautiful -- allows for scalable communities to substitute for conventional corporate production. The scaling in the opposite direction, towards things like big data, drive the structure of business towards the creation of new kinds of institutions that can achieve that scale.

But either way, the typically vertical structure gets driven to becoming more horizontal. The logic isn't just about big data. If we were to look, for example, at the telecommunications industry, you can tell the same story about fiber optics. If we look at the pharmaceutical industry, or, for that matter, university research, you can say exactly the same story about so-called "big science." And in the opposite direction, if we look, say, at the energy sector, where all the talk is about how households will be efficient producers of green energy and efficient conservers of energy, that is, in fact, the reverse phenomenon. That is the fragmentation of scale because the very small can substitute for the traditional corporate scale. Either way, what we are driven to is this horizontalization of the structure of industries, and that implies fundamental changes in how we think about strategy. It means, for example, that we need to think about strategy as the curation of these kinds of horizontal structure, where things like business definition and even industry definition are actually the outcomes of strategy, not something that the strategy presupposes.

It means, for example, we need to work out how to accommodate collaboration and competition simultaneously. Think about the genome. We need to accommodate the very large and the very small simultaneously. And we need industry structures that will accommodate very, very different motivations, from the amateur motivations of people in communities to maybe the social motivations of infrastructure built by governments, or, for that matter, cooperative institutions built by companies that are otherwise competing, because that is the only way that they can get to scale. These kinds of transformations render the traditional premises of business strategy obsolete. They drive us into a completely new world. They require us, whether we are in the public sector or the private sector, to think very fundamentally differently about the structure of business, and, at last, it makes strategy interesting again.