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[It's important to understand just how much the theory has evolved in the last 10 years. Much more perhaps than in its first eight.]

Doug Kaye: Hello, and welcome to IT Conversations, a series of interviews recording and transcripts on the hot topics of information technology. I am your host, Doug Kaye, and in today’s program, I am pleased to bring you this special presentation from the Open Source Business Conference held in San Francisco on March 16 and 17, 2004.

Mike Dutton: My name is Mike Dutton, and it is my pleasure to introduce to you today Clayton Christensen. Professor Christensen hardly needs an introduction. His first bestseller, “The Innovator’s Dilemma,” has sold over half a million copies and has added the terms “disruptive innovation” to our corporate lexicon. His sequel -- and you have to have a sequel to be a management guru -- is entitled “The Innovator’s Solution” and is currently Business Week’s bestseller’s list. Professor Christensen began his career at the Boston Consulting Group and served as a White House fellow in the Reagan administration. In 1984, he cofounded and served as chairman of Ceramics Process Systems Cooperation. Then, as he was approaching his 40th birthday, he took the logical step of quitting his job and going back to school, where he earned a doctorate in Business Administration from Harvard Business School. So, today he is a professor of Business Administration at Harvard Business School where teaches and researches technology commercialization innovation. Professor Christensen is also a practicing entrepreneur. In 2000 he founded Innosight, a consulting firm focused on helping firms set their innovative strategies. And according to a recent article in Newsweek, “Innosight’s phones ring off the hook, and the firm cannot handle all the demand,” very similar to all the startups in open source here today. So, please join me in welcoming Clayton Christensen.

Clayton Christensen: Thank you, Mike! I’m 6 feet 8, so if it’s okay, I’ll just…the mic picks up okay. I’m sure delighted to be with you, especially because there is blizzard in Boston today; my kids have to shovel the snow!

As Mike mentioned, I came in to academia late in life, and the first chunk of research that I was engaged in was trying to understand what it is that could kill a successful, well -- run company. And those of you who are familiar with it, probably know that the odd conclusion that I got of that was that it was actually good management that kills these companies. And subsequent then to the publishing of the book that summarized that work, “The Innovator’s Dilemma,” I’ve been trying to understand the flip side of that, which is if I want to start a new business that has the potential to kill a successful, well -- run competitor, how would I do it? And that’s what we tried summarize in the book, “The Innovator’s solution.” It’s really quite a different book than the “Dilemma” was, because the “Dilemma” built a theory of what is it that caused these companies to fail. And then in the writing of this solution, I’ll just give you analogy for where we came out on how to successfully start new growth businesses.

I remember when I first got out of business school and had my first job. I was taught the methods of total quality management as they existed in the 1970’s, and we had this tool that was called a “statistical process control chart.” (Do they still teach that around here?) Basically you made a piece, you measured the critical performance parameter and you plotted it on this chart, and there was a target parameter that you were always trying to make the piece to hit, but you had this pesky scatter around that target. And I remember being taught at the time that the reason for the scatter is that there is just intrinsic variability and unpredictability in manufacturing processes.

So, the methods that were taught about manufacturing quality control in the ‘70’s were all oriented to helping you figure out how to deal with that randomness. And then the quality movement came of age, and what they taught us is, “No, there’s not randomness in manufacturing processes.” Every time you got a result that was bad, it actually had a cause, but it just appeared to be random because you didn’t know what caused it. And so the quality movement then gave us tools to understand what are all the different variables that can affect the consistency of output in a manufacturing operation. And once we could understand what those variables were and then develop methods to control them, manufacturing became not a random process, but something that was highly predictable and controllable.

Well, I think that today the creation of new growth businesses is where the quality movement was 30 years ago, and that is that there’s just a widespread belief that it’s random and unpredictable. So, for example, every time venture capitalists invest in a new company, they invest in the belief that it will be successful, but the odds are that two out of ten really become successful, and the whole industry is structured to help them deal with the alleged variability in creating new growth businesses. And for established companies who launch new products, every time they invest in a new product, they think it will be successful, but actually 75% fail. And so a lot of the methods that are taught for how to manage innovation are really structured around how to deal with the alleged unpredictability. We think that it is not intrinsically unpredictable. If we can actually understand the variables that affect the success of new businesses that we’re trying to start, that we can succeed with a much higher probability than has historically been the case.

And so that’s what I want to talk about is, “What are these variables that we have to control?” And in kind of an unabashed way, I’m going to structure this around theories of strategy and management. And the word “theory” gets a bum rap amongst some managers because it’s associated with the word “theoretical,” which connotes “impractical.” But a theory is actually a very practical thing because it’s a statement of causality, a statement of what causes what and why.

And so, like gravity is a theory; it allows to predict that if you jumped out of a window on the top floor of this hotel, you’re going to fall, and you don't have to collect experimental evidence on that question. And what this means is that every time a manager takes an action, it’s actually predicated upon a theory in her head that, “If I do this, I’m going get the result that I need.” And every time you put a business plan into place, you’re actually employing theories in your mind that if you do these things, you will be successful. It’s just you don’t know quite often what the theories are that you’re employing and aren’t aware whether they’re good or bad. So, I just want to try to discuss with you some of the theories that we’ve tried to draw upon to put together this work, especially as they relate to how you would create a successful open source software business and how the companies that might be disruptable or threatened by open source software create new ways of growth that will keep them healthy.

So, I’m going to… move to the next slide please. These are the questions that you’ve got to get a lot of things right, but 10 questions that you need to get right in building a new growth business are, “How do we beat the competitors?” “How do we know what customers we ought to focus on with our first product?” “When we are focusing on a set of customers, how do we know whether they’re going to want to buy the product that we have in mind?” “How do we distribute to them, and how do we build a brand that communicates what we want to communicate to them?” “Of all of the things that have to be in place for the customers to benefit from the product, which should we do ourselves and what can we rely upon partners and suppliers to provide?” “How do we keep our product from getting commoditized?” “Who should we hire to run this new business, and what kind of person if we hired to run it would kill the business?” “How do we structure the organization, and if it’s within an established company, where is the right home for the new growth business to live?” “How do we know when we’ve got the right strategy, and how do we know when the strategy that has been working will not work in the future?” And finally, “Whose money should we take to fund the business and whose money, if we took it, would kill the business?” turns out to be quite an important question.

And so I want to just walk through the models that we propose you can use to think your way through these questions as far as we can go in the time that we have. And then we’ve got some time at the end for you to call all of this into question or send barbs or criticisms, or ask other questions as you see fit.

So, lets start at the top one, and it turned out that this one was really quite readily answerable by the model of disruption that we summarized in “The Innovators Dilemma,” and for those of you aren’t familiar with it, I’d like to just walk through that as quickly as we can. There are three parts to this model.

The first one is represented by that line, and what it suggests is that in every market, there is a trajectory of improvement that customers are able to utilize over time. And a good way to visualize that is in the car industry. Every year the car companies give us new and improved engines, and yet we can’t utilize all the improvement that they give us because you’ve got nuisances like police that put a crimp on how much of the engine we can use.

Now to keep the diagram simple, I’ll just depict that ability to utilize improvement as a single line representing the median customers in a market. But if you can remember that there’s really a distribution of customers in every market, and so at the high end, really demanding applications that are never satisfied with the best they can find, and at the low end, pretty unsophisticated folks that are overserved by very little. So, that’s the first piece of the model is there’s an ability to utilize improvement.

And then the second one is that in each market there’s a trajectory of improvement that the innovating companies provide as they introduce new and improved products. And the most important finding on this is that this trajectory of technological progress almost always outstrips the ability of customers to use that improvement. And so it means that a company whose products aren’t good enough to be used by customers in the mainstream of a market at one point can improve its products at such a rapid rate that it overshoots what they’re able to use at a later point in time. Now they may keep buying that product out here; they just can’t utilize all the improvement that’s made available within it.

And a good way to visualize this one is, if you go back to the early years of the personal computer industry when we were first learning how to do word processing. Do you remember how often you had to stop your fingers and let the Intel 286 chip inside catch up to you because it wasn’t good enough even for a simple application like word processing? But as Intel has introduced faster and faster chips that it can sell for more attractive profits to demanding customers in higher tiers of the market, now that they’re at a 3 -- gigahertz Pentium IV processor up here, they’ve way overshot the speed that mainstream business users are able to use.

Now at the same time, there’re still some freaky people at the high end that need even faster chips, but they’ve overshot what the mainstream can use. Now some of the innovations that allow a company to move up this performance trajectory are simple incremental year -- to -- year engineering improvements, and others are this sort of dramatic breakthrough technologies. Like in telecommunications, the change from analog to digital and from digital to optical were very complicated technological tour de force. But they had the same effect on the industry as the simple ones, and that is they sustained this trajectory of performance improvement.

And what we found, as you may know in that study, is that it actually doesn’t matter technologically how difficult or radical that innovation is, that almost always the incumbents win these battles of sustaining innovations. Again, it just doesn't matter technologically how hard it is. It just seems like, if it helps them make a better product that they can sell for more attractive margins to their best customers, they figure out a way to get it done.

But then there was this other kind that we call the Disruptive Technology that comes into the market every once in a while, and open source clearly is one of these. And we called it “disruptive” not because it was a dramatic breakthrough improvement, but instead of sustaining the trajectory of improvement, it disrupted and redefined it and brought to the market a product that was crummier than those that historically had been available. In fact, it performed so poorly that it couldn’t be used by customers in the mainstream. But it brought to the market a simpler and more affordable product that allowed a whole new population of people now to begin owning and using it, and then, because trajectory is so steep, what takes route in a simple application then can intersect with the mainstream. And so that’s the basic model of disruption.

One the companies that has tried to use this a lot in the last few years in managing their strategy and new product development has been Intel because, as I mentioned, they’ve gone from a point of having a product that wasn’t good enough to now overshooting the volume of the market. I got invited to go out to a meeting there because, through the late 1990’s, Intel, they were coming into the low end of the processor market in entry -- level computer systems.

Much cheaper processors were made by Cyrix and AMD, and they were just killing Intel at the low end; in fact, their market share in entry -- level systems dropped from 90% to 30% in 18 months. And it felt great actually to get driven out of the low end, because as they were losing the volume in the most price -- sensitive tiers of the market, they were replacing the volume at the high end with much more attractive margins, and so overall their reported gross profits were improving, and Wall Street just loves gross margins! And so it felt good until they saw this dumb model, and then it helped them see, “My gosh! If we lose the low end today, we may lose the mainstream tomorrow!”

So they I got to come out and have this meeting with their executive staff and their chairman, Andy Grove, who is in the audience. And I was going through this, and he had a real puzzled look on his face, and then it was like a teacher’s dream and the light bulb turned on, and he raised his hand, and he said, “I see what’s wrong with your idea.” He went up and he crossed out the word “technologies” there and he said, “Clay, if you frame this as a technological problem, you’re going to mislead the world.”

And unfortunately, “The Innovators Dilemma” had just been published and I couldn’t get it out. But he said, “If I get the idea, I would characterize it as just straightforward technology that disrupts the business model of the leaders, and that’s what makes it so hard.” And he then went on to give his view of the puzzle that had been in my mind that it kind of triggered the whole line of research, and that was living in the Boston area, how can digital equipment get killed?

I remember watching digital equipment grow up through the ‘70’s and ‘80’s. It was probably the most widely admired of all the companies in the world economy. And when you read articles in the business press about why they were so successful, it was always attributed to the brilliance of the management team. Then about 1988, they just fell off a cliff and began to unravel very quickly, and when you then read articles in the business press about why they had stumbled so badly, it was always attributed to the ineptitude of the management team. They were the same folks running the company.

And so for a while, I scratched my head and wondered, “How could good managers get that dumb and that fast?” That really is the bad management hypothesis, is the most ready explanation that we can offer for the failure of most companies. But the reason it didn’t quite fit right in this case is that every minicomputer company in the world collapsed in unison. Is was not just digital, it was Data General, Prime, Wang, NEXT, Hewlett Packard, and you might expect them to collude on pricing, but to collude to collapse was a bit of a stretch, and this had to be something more fundamental going on.

And that’s what really precipitated this question. And so Andy then went on to give his view (let’s go to the next slide) of what happened to digital equipment. And he said, “In the first place, if we are able to line up in this room the sequence of mini computers that Digital introduced to its markets, they didn’t skip a beat.” If you peeled the covers off and looked at the technologies that were required to make a good mini computer better, anything that helped them make a better product that they could sell for higher margins to their best customers, they got it done.

But he reminded me, “Do you remember how crummy those early personal computers were?” They were toys. In fact, Apple sold the Apple II primarily as a toy to children. It wasn’t good enough to be used by customers in the main stream market as it existed in the late ’70’s and early ‘80’s, and that meant that the more carefully Digital listened to its customers and tried to reflect their unmet needs in the properties of their next generation product, they got no signal that the personal computer mattered because, in fact, their customers couldn’t use it. And so it took root as a toy, and then because this trajectory improves at such a rapid rate, within a few years it intersected with the main stream needs, and it wasn’t just digital, it was the whole population that got blown out of the water.

And he said to his earlier point, “This wasn’t a technology problem. Digital’s engineers could have designed a PC with their eyes shut.” But they had a business model, and the minicomputers were quite expensive and complicated, and in order to sell them, they had to be sold direct to the customer, and the selling process involved the lot of training and support and service. You just had to have costs like that in the business in order to play in that game.

Given that kind of a business model, Digital had to make about 45% gross profit margins, and a typical computer sold for about $250,000. Now, in that environment, as in most companies environments, people are walking in to senior management all of the time with proposals to make better products. Well, some of the proposals that management was entertaining entailed making a better computer than Digital had ever made before. If you look at those proposals, they typically promise gross margins of 60% and the machines could easily be sold for half a million dollars.

But at that same time that management was trying decide if they should invest in those things, other people were walking in with proposals to invest in personal computers because it was quite obvious by the early ‘80’s, that this was going to be a big market. But if you look at those business plans, in the very best of years they promise gross margins of 40% and they were headed down to 20%, and these machines could only be sold for $2000.

And so Andy said, “So really, the decision the management had to make was, “Should we invest our money to make better products that our best customers could use that would improve our profit margins, or should we invest our money to make worse products that none of our customers could use that would ruin our profit margins? What should we do?” And I’m pretty quick, and so what I said was, “Andy, since you’re in this situation, my advice is to bale out and become a professor.” But then I realized that the very same thing is happening to the Harvard and Stanford business schools. We have become very good and very expensive, and we’re getting disrupted by crummy, low -- end, on -- the --job learning experiences like you’re having today! A little bit later I want to talk about that because it really is quite frightening for us!

But anyway, this is kind of my answer for the first of these questions that you need to get right, which is, “How do you beat the competitors?” And the answer is, that if you come into an existing market with a better product, the odds are that the competitors will get you because you’ve taken a piece of real estate up there that is financially attractive for them to pursue. If you come into the market with a disruptive product, the odds are that the entrant will win because you set up a situation where they’re motivated to flee rather than fight. And if you pick a fight like that where they don’t want to fight you because it’s in their interest to move in some other direction, it’s a great way for a little company to beat a big company. And so that’s the answer to the first question of why disruption is a great tool to beat the competition.

Now, I want to skip down. If you look at the stodgy companies today, and really crawl back inside of their history, most of them started out as disruptive innovators. It’s interesting in Japan. I had a student who went back to Japan and became a senior official in their Ministry of International Trade and Industry a few years ago, and he, poor guy, got sentenced to having to write plan for the resurrection of Japan’s economy.

And he worked on this thing for about two years and then called up and said, “I don’t think there’s any hope for Japan.” And he was looking at it from a macroeconomic policy perspective and came over and we talked about it for a couple of days. And then what hit us is that every one of the industries that constituted a fundamental engine of Japan’s economic miracle in the ‘60’s, ‘70’s and ‘80’s did this.

And so, those of you who have gray hair may remember that Toyota came into our market in the ‘60’s with a crummy, rusty, subcompact model called the Corona that no self -- respecting non -- college student would think of owning, and now they make Lexuses. And Sony came in with crummy transistor radios, and now they’re the best consumer electronics maker in the world. Their steel industry came in with the lowest quality steel in the world, and now they’re the highest quality steel companies. Canon did it in photocopiers, and Seiko did it in watches, and over and over.

And just like it happens in our economy, now those companies have become huge global giants, making the highest quality products, serving the most demanding tiers, and there is no growth up there. If they had tried to somehow cobble together the computer from outsourced subsystems or modules that fit together according to some industry standard, they couldn’t have done it because the establishment of the interface standards takes so many degrees of freedom away from the design engineers that they would have to back away from the frontier of what’s possible. And when the product isn’t good enough, competitively you can’t back off the frontier. And so that meant that in order to play in that game, you had to do everything in order to do anything. There is a huge advantage to being integrated and having a proprietary architecture in this era when the functionality isn’t good enough.

And so in the early years of that industry, IBM just dominated its world. And in the similar period of the automobile industry, General Motors and Ford just dominated their world. And the question comes, “What happens once the functionality and reliability become more than good enough for what customers in the less demanding tiers of the market can use? What do you do to get traction with these kinds of customers if you want to build a new business serving them?”

And the answer is that what’s not good enough now changes, and what begins to matter to these customers is, “I can’t get what I need fast enough, and I can’t get exactly what I need as fast as possible.” And so improvements in speed to market and the ability responsively to give every customer exactly what they need, that constitutes a new trajectory of innovation along which improvements are rewarded with attractive prices and increases in market share.

And in order to compete in this way to be fast and flexible and responsive, the architecture of the product has to evolve towards a modular architecture, because modularity enables you to upgrade one piece of the system without having to redesign everything, and you can mix and match and plug and play best of breed components to give every customer exactly what they need. And because there are clean interface standards here, when that happens, the industry disintegrates. (And this is just the chart that I put together with Andy Grove a few years ago to illustrate the rough concept.)

So here the rough stages of value added in the computer industry, and during the first two decades, it was essentially dominated by vertically integrated companies because they had to be integrated given the way you had to compete at the time. We could actually insert right in here “Apple Computer.” (Let me go back to the prior slide.) Do you remember in the early years of the PC industry Apple with its proprietary architecture? Those Macs were so much better than the IBM’s. They were so much more convenient to use, they rarely crashed, and the IBM’s were kludgy machines that crashed a lot, because in a sense, that open architecture was prematurely modular.

But then as the functionality got more than good enough, then there was scope, and you could back off of the frontier of what was technologically possible, and the PC industry flipped to a modular architecture. And the vendor of the proprietary system, Apple continues probably to make the neatest computers in the world, but they become a niche player because as the industry disintegrates like this, it’s kind of like you ran the whole industry through a baloney slicer, and it became dominated by a horizontally stratified population of independent companies who could work together at arm’s length interfacing by industry standards.

One of the things is that to us was most interesting is that where the money is made flips on both sides of this equation. We wrote an article about this that we published in the Harvard Business Review called “Skate to Where the Money Will Be” in honor of the ice hockey star, Wayne Gretzky. Somebody asked him, “How come you’re so good?” and he said, “Well, I never skate to where the puck is; I always skate to where the puck is going to be.”

And the notion here is that if you create a new business that tries to position itself at the point in a value chain where really attractive money is being made, by the time you get there it probably will have gone, and you can tell where it’s gone in a very predictable way, and that’s what I want to try to get at here. Over on this side of the world, the money tends to be made by the company that designs the architecture, the system, that solves what is not good enough. Because it’s functionality and reliability that’s not good enough, the company that makes this systems that is proprietary and optimized tends to be at the place where most of the profit in the industry is made. Because the performance of that kind of a product isn’t dictated by the individual components, of which it is comprised; this is determined at the level of the architecture of the system, and that is where the money is made.

So in the early years of computing, IBM had a 70% market share; they made 95% of the industry’s profit. In the similar era in automobiles, General Motors had a 55% market share; they made 80% of the industry’s profit. And if you were a supplier to General Motors or IBM, you just lived a miserable, profit -- free existence year after year because the components did not solve the problem of what was not good enough; the system solved the problem.

But on this side, when it becomes more than good enough and the architecture becomes modular, where the money is made flips to the inside of the product. And a good way to visualize this is just imagine that you were working as a computer designer for Compac, and your boss said, “I want you to go design a better computer than Dell.” How are you going to do this? Put in a faster microprocessor, more gigapixels on the screen, higher capacity disk drive, or anything you can do, the competitors can just copy instantly because in a nonintegrated word, you’re outsourcing from a common supplier base, and when the architecture of the system is modular, and it fits together according to industry standards, the better products are not created through clever architectural design; the performance of the product is driven by what’s inside.

And so the ability to make money migrates from the system to the subsystems that define the performance and allow these guys to keep moving up market. And so that’s the answer for why in the computer world IBM in the design and assembly of computers made all of the money, and it was not in the components. And so when they got into the personal computer business, they thought that the same formula would hold here, and so they outsourced the components and stayed in the design and assembly of the computer, and they did just what Wayne Gretzky said don’t do. They skated to where the money used to be and outsourced where the money would be.

You can see the very same thing happening in the automobile industry today. Automobiles have become more than good enough for what all but the most demanding customers are able to use. Our family is a great example. We just sold our Toyota Corolla after about 180,000 miles of loyal problem -- free service. Just a beautiful car! but my kids hadn’t been willing to ride in it for about the last four years because it went out of style about five years before it wore out.

And so, do I need Toyota to give me an even more reliable car next year? I can’t absorb more reliability. And so this very same thing is happening in the automobile industry. Over here, when the architectures were like that, it took six years to design a new car; now it takes two years. You can walk into a Toyota dealership today and custom order a car assembled exactly to your spec, and it will be delivered in five days, about as fast as Dell can deliver a computer assembled to your spec.

And the way they’re becoming this way, fast and responsibly flexible, is the architecture of the automobiles have evolved from a proprietary and interdependent architecture to a modular architecture. Over here, they source components from hundreds of suppliers, no one of which made a difference. On this side, they source components from a few suppliers that they call “tier -- one suppliers.”

On the left hand side, for example, Dana Corporation supplied axles. On the right hand side, Dana Corporation supplies a complete rolling chassis with all of the suspension system and everything. And the smoothness of the ride, or the feel of the ride, isn’t dictated by Ford anymore, it’s dictated by Dana because that problem is solved in the rolling chassis. Similarly, Johnson Controls on the left hand side supplied seats; on the right hand side they supplied the entire interior cockpit subsystem and Delco supplies the electrical system and Bosch, the breaking system, and so on.

And true to form, the industry has had to disintegrate. And so the integrated giants that dominated over here, General Motors, packaged up all of its components operations and sold them off in a company called Delphi Automotive, and Ford packaged its components operations off and sold them off as Visteon. But you can see that the car companies did exactly what IBM did when it put Microsoft and Intel into business, and that is, they sold off the pieces of value added, the subsystems, where in the future the money would be made in order to stay at the level of value added, which is the assembly of a car, where in the past the money was made.

This also highlights, for me, a process of what you would call “commoditization.” And what commoditization means is a company’s product getting better and better and better and better, and you reach a point where these folks aren’t benefited by an even better product, and so their willingness to pay a better price for an improved product diminishes to the point that you can’t get pricing to stick for an improvement.

And that’s one dimension of selling a commodity is, you just can’t get a premium price for a better product. The other dimension of commoditization is that your ability to differentiate your product disappears. Here, this is highly differentiable; here, it’s not at all differentiable. And so the process of a company’s products becoming commoditized is just a very natural result of the interaction of the technological progress in customers’ ability to utilize that progress.

Even a brand can become commoditized. And most companies think that, “Well, if our product is really not differentiable, at least we take refuge in having a brand.” If you think about it in these terms, a brand has value when you’re marketing upward to customers who are not yet satisfied with the best they can find, because the brand serves to close as much as is possible the emotional gap. But once the product is manifestly more than adequate and you’re marketing down to overserve customers, the brand really does not create value, and the brand itself can become commoditized.

Now, I want to try to walk into how you can use this way of thinking in a concept that’s called the “law of conservation of modularity.” And I want to illustrate this in a view of what I think is going to happen on the hardware side, in particular in the semiconductor industry, and then try to use that to think about what open source software could mean.

And the core concept of the law of conservation of modularity is that -- if you can just visualize -- if you are writing a software application to run on Windows, you might go to Redmond and knock on the door and say, “Would you please just let me into Windows? And if I could just change these 25 lines of code, the application would run so much better!” But Windows doesn’t dare open the door, do they? because it has an interdependent architecture, and if you change a couple of lines, who knows what else would get screwed up!

And so the application has to be suboptimized and conform itself to Windows so that Windows could be optimized. And the reason is, according to (I’ll go back a slide) this model, historically in order to fuel Dell moving up market so that it could keep competing against Sun Microsystems at the margin there, the fuel that allows Dell to move up is the microprocessor inside and the operating system inside.

That’s what constrains its up -- market progress. And so the microprocessor and the operating systems have a proprietary and interdependent architecture even while Dell’s product has a modular architecture. And so, back to the software analogy. The application has to be suboptimized so that Windows could be optimized. But if you’re writing an application to run on Linux, because Linux has a modular architecture, you don’t even have to knock on the door. You just walk in, change what needs to be changed as long as you don’t screw up the interfaces, and the modularity and conformability of Linux allows the application to be optimized.

And so one side or the other needs to be modular and conformable to allow what’s not good enough to be optimized. If you think about it in a hardware context, because historically the microprocessor had not been good enough, then its architecture inside was proprietary and optimized and that meant that the computers architecture had to modular and conformable to allow the microprocessor to be optimized. But in a little hand held device like the RIM BlackBerry, it’s the device itself that’s not good enough, and you therefore cannot have a one -- size -- fits -- all Intel processor inside of a BlackBerry, but instead, the processor itself has to be modular and conformable so that it has on it only the functionality that the BlackBerry needs and none of the functionality that it doesn't need. So again, one side or the other needs to be modular and conformable to optimize what’s not good enough.

Now, there was a guy at Bell Labs a few years ago who published an article about Moore’s Law, and what he showed is that in pursuit of Moore’s Law – now the vertical axis here is the complexity of the circuit, which may roughly equate to the speed of the circuit. In the pursuit of Moore’s Law every year, the fabs and applied materials make 60% more transistors available on an area of silicon than were available the prior year.

But if you look at the ability of circuit designers to utilize transistors year on year, they’re are only able to utilize 20% more transistors than they were the year before for any given level of complexity of circuit, and the reason is they just have design budgets; they don’t have enough money or time to design circuits that are complex enough to utilize all the transistors that Moore’s Law makes available.

What that means is, for most of the volume applications in the world, circuit designers are actually awash in transistors. Even while at the very high end, they still need even finer line widths and demand that Moore’s Law take the next step to that next node of technology, but they’ve overshot what most circuit designers are able to utilize. And so, what this would then predict is that circuits which on this side had to be proprietary and interdependent in their architecture, over here, now the way you compete to win the business of those people is going to change and you’re going to need to be very fast and flexible and responsive and be able to deliver systems on chips that offer every application exactly the functionality that they need and none of the functionality that they don’t need.

And so, how the law of conservation will play itself out is, this is kind of my sense of how the industry was structured in the past. So the microprocessor wasn’t good enough. That meant that the desktop computer had to have a modular architecture to conform itself in order to allow this to be optimized because the line widths on the circuit were not good enough.

The equipment that was made by companies like Applied Materials and Tokyo Electron, each piece of equipment was optimized. It had its own proprietary architecture, and in the sequence of steps that a wafer has to go through, there was no attempt, nor could you make an attempt, to synchronize the flow of material across those machines. Each piece of equipment had to be optimized for itself. That meant that the fabs had to be laid out in a modular way bay by bay, and the sequential steps in the process had to be buffered or modularized by having gobs of working process inventory in those fabs. And that made the fabs very slow, but they actually had to optimize this rather than vice versa because this wasn’t good enough, and then the components that comprise applied materials equipment did not matter at all. So the money was made here and the money was made here, and these guys, these guys and these guys lived a miserable, profit -- free existence.

Now in the future, in handheld devices, I’m just talking about this little piece of the world, but I think it applies to almost any situation where logic gets embedded in a system. But, I’ll talk about a handheld device like the RIM BlackBerry. It’s the device itself that is not yet good enough and, therefore, you cannot back off the frontier of what’s technologically possible. It has to be optimized with a proprietary interdependent architecture. That means that the processor inside of a BlackBerry has to be modular and conformable to allow that to be optimized.

Now you think about this, where these chips are now customized chips delivered to every customer’s application, and the design cycle out there in the customer’s end is measured in months rather than years. The fabs up here would take three months often to work an order through all of that inventory in the fab. And for a fab to take three months to deliver an order in a world down here where these are really fast -- cycle custom designed products, is just intolerable.

And so the fabs are going to need to figure out how to deliver products really fast, and that means that over the next few years rather than being laid out in bay structure, a fab is going to need to reconfigure itself in a single wafer process so that they can process silicon like Toyota makes cars, with very little inventory in the process, and that’s what make them really fast.

And nobody has figured out how to do that yet, but the pressure from the market will mean that it’s the fab that is not good enough on this critical performance dimension, which is, get every customer exactly the circuit they need as quickly as they can do it. That then means that the manufacturing equipment from companies like Applied Materials needs to be modular and conformable so that the fab can optimize the flow of product through itself.

And this is possible now because Moore’s Law has overshot what most circuit designers can utilize, and this is possible because these products don’t need a Pentium IV processor, and so you can back away from the frontier. And so what it means is that the places in the value chain where attractive profits can be earned are going to migrate from where they are today in a very predictable way.

So, I’m not a software engineer or designer, but this is what I think Linux does, or MySQL or Apache, whatever it is, is that because of the open source character of it, the architecture is modular. And what that means is -- let me back off from this. What this really tells me is that, like the microprocessor is going through a process of commoditization as it overshoots and becomes modular and undifferentiable. But, whenever that happens at one layer of value added that there is a process of commoditization, it initiates a reciprocal process of decommoditization at the next level of value added.

So, whereas the device up here was a commodity, this is not a commodity. Whereas a fab was commodity, this is a proprietary architecture that’s not a commodity and so on. So -- and I’ll come back to the software world -- there’s a fellow named Tim O’Reilly who’s done a lot of thinking about this that some of you may know. (Is that you? We just emailed. Stand up. He’s a lot smarter than he looks actually!) And another guy who runs a company in Santa Clara called Tensilica, who has thought a lot about this law of conservation of modularity. Tensilica makes these modular integrated circuits.

So the operating system is going, because of Linux, from a proprietary to a commoditized modular architecture, and what you’ll see happen then, because the very modularity of the open source architecture allows it to conform itself to allow the application to be optimized. And the operating system in many ways just folds itself in to the application and disappears.

And so my sense is if you look at how Red Hat lives, ostensibly they’re an operating system vendor, but really what the value that they create is at the next layer, the software that keeps the operating system from ever crashing and keeps maintaining itself, and that’s what is not good enough. And the conformability of Linux allows them to sell what you might call an application that is just extraordinarily optimized, and that’s becoming an noncommodity.

And similarly, in the Oracle world, the database software is proprietary and optimized, and a lot of money was made there, but MySQL allows to you to just fold the database into whatever the next layer of value added is so that it can be optimized, the application can be. And Google runs on Linux, and the operating system disappears into the search engine.

And so I don’t think that you could say that open source is a movement and nobody has figured how to make money in it, it is just where the money is made migrates to a different layer in the value -- added chain and, in fact, it facilitates the decommoditization of the next layer because what’s not good enough can now be optimized. And so that’s my rough…Tim, do you want to clarify any of that gibberish? Or did I get your argument right?

Tim O’Reilly: I’m actually talking about it tomorrow, but actually I’m really struck by something else that you are saying here, and actually I’m going to disagree with you about Red Hat because what I think Red Hat is much more analogous to is your fab. I look at Apple with Mac OS X has done something that’s much more analogous to folding the value into an application layer on top, but what Red Hat does, and what I think really all Linux vendors do, and actually somebody else in the audience, Ian Murdoch, is really a leading thinker on this.

He’s right over here. It’s really that the critical competency of open source distributions is actually the active assembly. I think that’s really an interesting thing, and we were starting to see that what Ian’s new company does is really focus on really custom distributions and that ability to be responsive, to be faster. So I think there’s a lot of different elements in the story. You did actually correctly characterize my argument that we’re driving value up to things like Google on top of Linux.

There are many, many instances of that, but there is a lot of other pieces of the story. I think there is another one, too. I’m jumping into things that we’re going to ask you in the questions, but I think that your whole fabrinology here, you’re starting to have a lot of people starting to play with FPGAs, for example, where you’re actually literally doing a lot of the processor work in a quick responsive way, and then some.

Clayton Christensen: Okay! Thanks, Tim. I had a student write an article about cellphones and where the value migrates there because, in many ways, a Nokia and a Motorola phone have been over on the left hand side where the proprietary architectures, then they do their own processors, they do their own operating system optimized, but now those cellphones have so many features that the limitations on the system are not in the handset themselves, it’s elsewhere in the system.

And so we wrote a couple of things that forecast that the handsets are going to become modular, and because of that then, where the money is made in that value chain is going to migrate to the back end. And it’ll become a disintegrated industry, and the way to make money would be for Motorola to sell its chip sets to a thousand Chinese assemblers and for Nokia to sell its operating system to a thousand Chinese assemblers, and all of those guys colliding against each other in commodities would then drive the pricing of those things down and so on, and that’s the way the world would work.

And sure enough, Motorola subsequently announced that they were opening up their system and selling chip sets to anybody who wanted to buy. And then, according to this student, Nokia announced that it would make its operating system available to anybody who wanted to buy, and so I’m thinking, “Boy, these guys are brilliant because they followed Clay’s advice.” But then Nokia announced that it was almost giving its operating system away, and I thought, “Those idiots! That’s where the money is going to be made,” but then my student said, “No, they’re a lot smarter than you, Clay, because of the law of conservation of modularity.

By opening up their operating system and making it essentially free,” he asserted, “what that then allows is the operating system becomes modular and conformable so that Nokia could keep optimizing hardware and keep the hardware part of the system proprietary.” Had they let it became a truly modular world, then Microsoft was there sitting with its own operating system ready to move in and make all the money in the assembly of a modular handset, and maybe the strategy that Nokia followed, it is actually kind of clever to essentially wipe out the value that is created at the operating system layer in order to keep playing the game where they had an advantage over Microsoft.

(Okay, now I want to click ahead.) They’re just one other set of concepts that I wanted to go over, and then we could just have some questions. This last one was the question, I think, number two on our list of, “How do I know who are the right customers to target with my new technology?”

And I think from what little I know about open source, there are a lot of wrong customers that have been targeted that have caused a lot of expense in brief. Now, where this idea came from is actually in one of our MBA classrooms. And I had written an article about the disruption of the Harvard Business School, and what it asserts is that our MBA’s have become extremely expensive.

I would never criticize Stanford in public, so I’ll just talk about Harvard. They cost about $130,000 to hire. And if you look at who recruits on our campus, operating companies have a very hard time recruiting because they’re so expensive and they can’t fit our expensive graduates into their salary structures. So who recruits increasingly are venture capitalists, private equity investors, Mackenzie and Goldman Sachs.

Now, the operating companies aren’t getting lower quality talent; they’re just going into undergraduate programs and raking out the best engineers and others that they can find, putting them to work, and then two years later at the time when many of them would leave to get an MBA, the companies are saying, “Nope, you don’t need an MBA!” “We have GE Crotonville or we have Motorola University or Intel University. IBM spends $500 million dollars a year in management training. We’ll train you right here!”

So anyway, I wrote a case about how on -- the -- job training is disrupting the Harvard Business School, and one of the students raised her hand and, in a very polite way, she said, Well, excuse me, but I think you can only be disrupted if you have overshot what the market needs, and frankly I am not overserved by your teaching.” So I was convinced that Harvard was getting it, and yet it was very clear that she wasn’t overserved. And so it helped me think through that there are actually two different kinds of disruption, and I want to just talk that through.

So, one type of disruption, we’ll plot on this chart, and what we showed before is that if a company’s entry strategy is to bring a better product into an established market, the probability that it will build a successful growth business is zero because of these asymmetries of motivation that exist. Now, incidentally, if a venture capitalist funds a venture that tries to do this, and they actually do come into an established market with a better product, if their strategy is to turn around quick and sell out to the incumbent leader, they can actually turn in a nice piece of money, but it’s not a strategy to create a new growth business.

Now, one type of disruption we called a “low -- end disruption,” it just takes root in the very same market where the incumbent leaders are, but it just picks it off at the low end, and they build a business model that can make money at the discount prices that’s required to steal the business down here. So it doesn't create a new growth market, but it does create a new growth business. And the examples I’ve used in my writings of steel mini -- mills, they did this. Discount department stores did that. They didn't create a new market; they just had a lower cost business model, and the incumbents were motivated to flee rather that fight.

But the other type of disruption, and this is what corporate education is, we called the “new market disruption,” and it comes out in a new context, and so it’s almost like you have a third plane of competition out here. And by bringing a product that is so simple and inexpensive, a whole new population of people can now afford to own and use a product who historically couldn’t do it because they didn't have the money or the skill, and it creates a booming new market out in this new plane of competition and doesn't effect the business of the original players at all for a very long time.

The personal computer was one of these, right? So I remember when I got out of grad school, when I had to compute, I had to take my punched cards to the corporate mainframe center, and the expert ran the job for me. Because it was so expensive and inconvenient, we didn't compute very much. But when the personal computer was introduced, it was so inexpensive and so idiot simple that an idiot like me could now begin to compute for himself in the convenience of my own office.

And at the beginning, out here in this new plane of competition, those early PC’s could barely do word processing. But because I hadn’t been able to do anything myself, I was delighted to have something that wasn’t very good. And then as the PC and the software associated with it got better and better and better out in this third plane of competition, ultimately it got good enough that it started to then suck applications out of the back plane into the new plane, and little by little the customers left the established players. And so the effect of the disruption was the same in that the established leaders got killed; it just is kind of a different animal bringing something that is so much more affordable and simple that a whole new group of people can now begin to do it for themselves.

I want to just illustrate this with a couple of examples from history, and then think through how open source software might be affected by this principle. This is the historical example: The transistor was a disruptive innovation relative to the vacuum tube because when it emerged in the late 40s and early 50s, it simply couldn’t handle the power that was required to be used in the markets that existed at the time, the big tabletop radios and floor standing televisions and so on.

Every one of the vacuum tube companies took a license to the transistor, but they carried the license into their laboratories and they framed it as a technological deficiency. In other words, the transistor isn’t enough yet to be used in the market. And if you could go back and get all of the expenses out of these companies, they probably in aggregate spent $2 billion in today’s dollars, investing, trying to make solid state electronics good enough that you could make big products out of them.

And while they were trying to do that, over here -- now I’m going collapse this back into two dimensions, but when you see green, I really mean that that’s taking root out here in the third plane of competition. The first application was a germanium transistor hearing aid in 1952. A tiny little market, but it valued it for the very attributes that it made it useless in the mainstream, and that was low power consumption. And then in 1955, Sony introduced its first pocket radio. And those of you with gray hair remember how crummy those things were, just static laced, very low fidelity, wouldn’t get a signal from much of a distance.

But Sony chose to sell the pocket radio to the rebar of humanity, people we call teenagers. And the teenagers were delighted to have a product that was not very good because their alternative was no radio at all, and it allowed them to do something that they had wanted to do, but never could do, and that is listen to Rock -- n -- Roll out of the earshot of their parents.

So a booming new market emerged in this third plane of competition, and these guys back here felt no pain because they were all new customers. Had Sony tried to sell its pocket radio to the parents, a crummy product would have been judged to be crummy because they had the alternative of a high quality vacuum tube radio. Then in 1959, Sony introduced its first portable television, and again, they competed against nonconsumption. They made it so affordable and simple that a whole new population of households who didn’t have a big enough apartment to have a big floor standing TV or didn't have enough money to buy one, now they could own one, and because the alternative was no TV at all, they were delighted with the crummy product.

And again, a booming new market emerged in this third plane of competition until the mid 1960’s. And now solid state electronics was good enough that it could handle the power required to be used in making these big devices. And bam! within three years, all of the applications got sucked out into the solid state world, and the vacuum tube companies were just dead, and these are venerable institutions like RCA. And the punishing thing is that it’s not that they didn't see the technology coming. They saw it before Sony did.

It was not that they weren’t aggressive and visionary. They invested far more money trying to make the technology good enough than did Sony as they were building these growth businesses. The punishing thing is that they targeted the wrong customers. They targeted consumers, and the only way the customers here would have adopted the new technology is if it were better than the old technology and more cost effective. That was a very demanding technical hurdle for the vacuum tubes companies to surmount. As they came out and competed against nonconsumption in contrast, Sony had a much more modest performance hurdle because they just had to make the product that was better that nothing, and the customers were delighted.

Now, where you see this happening today is voice recognition software. So, the next time you go to a computer superstore, go to the voice recognition software shelf and pick up a box there that’s called the IBM ViaVoice. Now don’t buy it, but just look at it! They have a picture of the customer on the box, and it’s an administrative assistant who is sitting in front of her computer wearing a headset speaking rather than word processing.

You think about the value proposition that IBM has to be making to this woman. She types 90 words a minute. She is 99% accurate. If she needs to capitalize something, she just instinctively presses shift and cruises through. And IBM has to say, “No, don’t do that anymore. I want you to put this headset on and teach yourself to speak in a slow and distinct and consistent manner in complete sentences. If you must capitalize, you must pause, speak the command “capitalize,” pause, speak the word you want to capitalize, pause, speak the command “uncapitalize,” pause, please be patient, we are 70% accurate, this will get better we promise.”

This is not an attractive proposition to this customer. And IBM has -- I’ve not worked with them at all, but as I understand it -- they’ve spent maybe $700 million trying to make voice recognition technology good enough that it can be used in that market. This is a very difficult technical hurdle to surmount. Meanwhile, while they are investing that aggressively, Lego comes up with these robots that recognize “stop,” “go,” “left,” “right,” and the kids are thrilled with the four word vocabulary, and then press -- or -- say -- one kinds of applications take root, and now directory assistants ask you to say the city and state and so on, and much simpler, and an interesting market is emerging.

I bet maybe the next place it takes route is in chatrooms because the kids don’t spellcheck or capitalize anyway, and they would rather speak than type. And maybe then the next application would be, when you see these stubby fingered executives with their BlackBerrys trying to peck out emails, and their fingers are four times the diameter of the keys, they’re only 70% accurate. If somebody gave them a voice recognition algorithm that really didn't have to be very good so that they could speak their wireless email rather than peck it out, I bet they’d be thrilled with the crummy product. And ultimately, as it takes route in these new applications, it may get good enough that we can do word processing with it, but it’ll be a long time.

I’ve asked myself, “Why would the IBM engineers have picked off the most demanding application conceivable for this technology,” and it probably resides in the resource allocation process of the company, because it’s not just IBM, everybody does it. You got to rule out stupidity because they’re at least as smart as us, but in order to get funded, the people who had the idea knew that they just couldn’t stand up in front of senior management without PowerPoint and just say, “I’m sure there’s going to be a lot of ‘press or say’ when stuff happens some time.

They never get funded. But they have to do a PowerPoint presentation that has financial projections, and they have to be able to say that we hired a consulting firm and they did a market study and, there are 37.9 million administrative assistants who spend this many hours a day word processing, and this is how big the market is, and in order to get funded it forces the company to target the market that ultimately causes them to fail.

And the digital camera people like Kodak fell victim to the same process. These digital cameras are potentially disruptive, and so in order to make a digital camera good enough that people would opt to take a digital rather than a film image, they have to cram it full of charge couple devices, and that drives the price point up so high that the only people who can afford to buy a digital camera are the people who own film cameras, and so then the reward for success once they got a good enough digital cameras is they don’t sell film.

So a massive investment and no growth. And meanwhile, we see taking root out in a third plane of competition, credit -- card -- thickness cameras that have just dirt -- cheap CEMA sensors, and now CEMA sensor -- based imagers in cellphones that take crummy images, but they’re so much better than nothing at all, that a booming new market is emerging. And whether a disruption creates new growth or threat to the core business in many ways is driven by this very same thing.

Our daughter just finished a mission for our church in Mongolia where she had been for a couple of years, and we went over to get her in August when she finished her service. And I’d always wondered whether solar energy was ever going to be commercially viable because the European and American governments have probably invested $15 billion trying to make solar energy good enough that we could use it in our markets.

If you think about it, this a very difficult technical hurdle because our homes are filled with air conditioners and power sucking computers and microwave ovens. And you got minor problems like nights and clouds that get in the way and, it is a very difficult problem! And so the technology making solar cells with this as the core market that they invasion is very expensive and optimized to try to wring the most power possible out of the materials and technology that are available.

Anyway, when we were in Mongolia, our daughter took us to this big open -- air market in the capital city Ulaan Baatar. There was this big line of stalls in this market where the vendors are selling dirt -- cheap solar cells shrink wrapped with 6” televisions and rabbit ears antennas, and they’re just walking out of marketplace! Because half the population of Mongolia doesn’t have access to power over a grid. And it doesn't really matter if it was cloudy today; I couldn’t watch TV yesterday.

And there are about two billion people in South Asia and Africa who don't have access to electric power at all, and it turns they don't have air conditioners and microwave ovens in their homes, and they’re delighted with something that won’t be very good. Now whether solar energy ever takes root as a viable commercial technology, I don’t think it’ll ever get driven in the sophisticated engineering labs of North America and Europe. It will be by folks out there in the third plane of competition competing against nonconsumption and get better and better all the time.

So as I look at how different companies have tried to deploy Linux. What this would suggest is that if IBM tries to shove Linux down Merrill Lynch’s throat in its core internal mainframe computer system, there are just so many complicated interdependencies when you insert a new technology into an existing system of use, that you’re running into all kinds of problems.

But I think at that end of the world where you see open source taking root is in web servers, which is a totally new application taking root out here in Internet -- based computing. And as it gets better and better and sucks applications out of an internal system to a web -- based model, then gradually Linux disrupts, as a new market disruption UNIX, in those tiers of the market. But it does it not by a direct attack, but by taking root in a new application.

And similarly what it would forecast, and again I say this is just what the model says, is that any attempt to deploy Linux right onto a desktop, there are just so many complicated and unforeseeable interdependencies when you insert a new technology into an existing system of use. So many other subtle things would have to change, and it would have to become better than the existing thing in the ways that the consumer measures goodness, I wouldn’t expect it to take root.

But because of the law of conservation of modularity, as it takes root out in the new plane of competition with wireless handheld devices, because the modularity of Linux allows the device to become optimized. And then as it gets better and better, applications get sucked off the desktop into the handheld device, and that would be the mechanism by which the Microsoft proprietary operating system would get disrupted by Linux. I mean, I don’t know if that’s true, but that’s what the model would predict.

Well, there are a bunch of other questions that we didn’t answer, but I hope this gives you a flavor of at least the way we’ve been trying to think our way through some of these problems. And this book that we wrote about it, “The Innovator’s Solution” gives the models that address the other questions. If you have any interest, they’re there, or I just work at our business school, it won’t get finished off for another 20 years. Disruption is a process, not an event. So you could contact me at Harvard if you have any other questions.

Anyway, criticisms or barbs or…. Yes?

(Question by a speaker too distant to be heard clearly.)

Yes, that would work, kind of, in that it’s so much better than nothing and it’s a new system of use to an extent. The problem is if, in fact, they bump into existing systems of use, and that is application software that just don’t run well on that, then you would expect them to run into problems, but China is a much easier place to deploy it then existing markets. Yes?

(Question by another speaker too distant to be heard clearly.)

Well, that’s a great question. Can I give you a longer answer than you asked for? When we were having this case discussion about the disruption of Harvard Business School, I walked into the classroom and took a vote of the students, and there were 100 students in the class. “How many of you think Harvard’s in trouble?” Three students raised their hand; 97 -- there were no abstentions -- voted that, “Don’t worry, be happy, this could never happen to our school.”

And so I asked if one of the three who was worried why he was worried and he said, “Well, there’s a real pattern here,” and he lists out the elements of the pattern and then he said, “Now look in the case and everything that happened to all of these other people is happening to us. That’s why I am worried.” So then I turned to the don’t -- worry -- be -- happy crowd and said, “So why aren’t you worried because it fits the pattern so closely?”

And everything that they cited related to the data, that more people are applying to Harvard then ever before, our students are getting more money than ever before, and the more money they get paid, the higher…we’re much further ahead of Stanford on the rankings, and so on. And so we had this argument back and forth.

So then I asked one of the students who was the most vociferous defender of Harvard’s invincibility, “So imagine you were dean of the school, what evidence would you need to see to become convinced that this is a problem that we need to address?” And he said, “Well, I would look at Harvard’s market share amongst the CEO’s of the global 1000 corporations, and if it starts to dip, then I’d worry.”

And I said, “Well, when you saw that data, would it signal that the problem needs to be addressed, or that the game is over?” He said, “Oh, yeah, the game would be over!” And so I turned to the rest of the don’t -- worry -- be -- happy crowd and said, “So any of the rest of you, imagine you were dean. Could you give me data that would convince you that it was time to take action?” And actually, every piece of data that they could come up with was evidence that the game was over.

And the idiot -- simple insight that we got is that data is only available about the past. And yet, the way we teach our students, at our school we teach by the case method and if the student makes a comment in a case discussion that can’t be backed up by his analysis of the data in the case, the instructors are trained to crucify the student on the spot. And so we enshrine the virtues of data -- driven analytical decision making in the way we teach at our business schools, and the our students go to work for McKinsey and they carry data driven analytics to the nth degree, but in many ways the very ways we teach them condemns our managers to take action when the game is over.

But the scary thing for Harvard is that this means that we need to take action based upon a theory, not evidence. And that’s how I got into this thing that, well crum, we’re always using a theory anyway, because a theory is a statements of cause and effect. We just hope we have better theories.

So at the time IBM made the decision, there was no theory to guide them; there was only evidence of the past, and the evidence of the past was that the money was made at the system, not in the components. And now, as you have a theory, hopefully it’s a good theory, then it allows companies who face this transition to make a decision about whether they ought to create an interdependent or a modular architecture, and when it’s going to flip.

For example, what’s going on right now with wireless access to the Internet; it’s not good enough, it needs a proprietary system. And so companies that have tried to cobble together a system around WAP standards, for example, it’s prematurely modular. And the companies that have an interdependent system like DoCoMo and J -- phone in Japan, they’re making bundles of money, and they’re also out competing against nonconsumption for the business of teenagers. So that’s what I hope to accomplish, is that we can look into the future and make statements about what will happen before the data is clear, but in the past that hasn’t been possible. Yes, Tim?

Tim O’Reilly: I have a question about the theory of conservation of modularity. (The rest of the question is obscured due to the distance of the speaker).

Clayton Christensen: Yeah, I think it would be, Tim. In other words…but you have to think of it in relative terms. So, what is it in that system in the value chain of the system that gets delivered to the customer is not good enough, and that tells you then what has to be optimized, and you’ve got to be integrated across that interface that optimizes it, and what is next to it that needs to be broken up. And you’re thinking about it, I think, in a healthy way. Yes?

(Question by another speaker too distant to be heard clearly.)

Yes, his question is. “Does the theory predict that the profits will disappear in every market or that they will just be made by different parties?” And it’s very much the latter. In fact, for marketing purposes, we called this concept the “law of conservation of modularity.” In the book, we called that “law of conversation of attractive profits.”

And again, at one layer as it moves towards commoditization by overshooting and becoming modular, the adjacent layers move towards decommoditization, and so the ability to make money will shift. So like in the car industry, the subsystems, the tier -- one suppliers are not yet manifestly more profitable than the car assemblers, but we should see that transition occurring over the next few years as the power in that industry shifts and so on. Yes?

(Question by another speaker too distant to be heard clearly.)

Well, I don’t think I can repeat your statement, but I hope everybody heard it. I think the concept is that when you have a modular architecture, it truly is undifferentiable because the pieces fit together in a pattern that everybody follows, and so the product is not differentiable. And in a disintegrated industry structure, the cost structure of the company is heavily variable because you outsource the components.

And so a variable cost structure means that the scale curve is flat, so small companies and large companies have the same cost, and the product is undifferentiable, and that’s why it’s very hard to make money as an assembler of a modular system. In a proprietary system, it’s just the opposite, that the proprietary architecture yields a highly differentiable product, and it’s a heavy fixed cost because the design of a proprietary product is expensive, and so that creates steep scale economics, meaning that the big players sell -- that’s a recipe for minting money versus not making money.

And so whether MySQL gets folded in to optimize some other application, or Linux gets folded in to some other application, or they try to fold an application into the operating system, where the money will be made is where you’re optimizing the performance of something that is not yet good enough, and that’s really all I can say, because then that creates a condition in which a proprietary architecture will win, and that’s where money gets made. So, I got to believe that a lot of money stays in the system, that it just gets made at a different level.

(Comment by another speaker too distant to be heard clearly.)

This merits a microphone here.

Member of audience #1: I’m the guy from MySQL and I think that the value is being produced in the layer above the infrastructure, so in web services specifically. So look at Amazon, Yahoo, Google, who all use standardized open source modular components that they pay virtually nothing for, and then they create a highly interdependent system with a very high value that they can sell out the customers, and they make much more money than the open source players, so I guess that’s part of an answer.

Clayton Christensen: Great! Thank you. There, in the middle…?

(Question by another speaker too distant to be heard clearly.)

Northeast. Yeah. Microsoft is in the Northwest.

(Continuation of speaker too distant to be heard clearly.)

I will just conjecture because I do not consult for them or anything like that, but that NT is a disruption relative to UNIX, and that system has just been moving up market and squeezing the UNIX and the risk world up to the high end of the market. And then Linux on web servers has inserted itself there. It’s an interesting question whether, Microsoft…in the absence of Linux, I think Microsoft would’ve had a really exhilarating…there was a lot of headroom above them.

Whether Linux limits the further up market march as applications move to a web -- based system, I don't know. I also think that it’s just very hard for me to imagine the core franchise of an operating system on a desktop as being threatened in the foreseeable future because of the reasons that we’ve talked about. Now, the growth markets they may very well have a difficult time catching.

I also see them launching their own disruptions against other folks, which is really a great idea, and so they’ve got database software coming up against Oracle, and they have got Great Plains, but SAP needs to be disrupted. There are a very complicated, high -- end, overshot interdependent system, and there’s a lot of growth there, and so they’re doing a lot of interesting and useful things.

But I think the critical thing as per what he said is if they want it keep being profitable, there’s a mindset that while we milk the operating system business over here, in the future, operating system is not where the money will be made, and so don't somehow try to make money off of Linux. Use Linux to somehow optimize the next layer up and shift how we make money there. But they’re a tough company, and a good company.

Member of audience #2: My question is about switching costs. Not certainly the one we stopped the new line of business, but in the one where a lower cost comes in and attacks. In that, case switching costs seems to me to have effect of the diagram of moving the curves further apart, and that, for instance defends Office against Open Office, is attempts to tie it in and keeping the switching costs very high.

Clayton Christensen: Yeah, it’s a very good point, and that’s why the cramming it into the blue space so often is expensive and fails whereas if you take root in a whole new plane of competition, you don’t run into the switching cost problem out there. It’s like this: The shortest distance between two points is not a straight line. Yes?

(Question by another speaker too distant to be heard clearly.)

Well, of course I think it’s a perfect theory or I would’ve changed it, right? The only way you can develop a better theory is to find anomalies that the theory won’t explain. And so I’ll tell you what I do think is that these pressures…are you familiar with the story of the minimill? So in the new book I understood that a lot better and told the deeper story that as that the minimills hit the rebar market, because they had a 20% cost advantage, they made tons of money.

And, of course, the integrated mills, because they were more profitable investments up, they got out of that business. And it felt great until 1979 when the minimills finally had the whole market to themselves, and then the price collapsed by 20% because, the insight I got was that a low -- cost strategy is only viable as long as there’s a high -- cost competitor around, and so they had to move up because that’s where the high -- cost competitor was.

And that’s why Dell has to race up market because it gives them the privilege of competing against Sun Microsystems. So I would say that those pressures to move up exist on everybody. Now, some companies, like in the pharmaceutical industry, they haven’t yet overshot very much, and so the forces are there, it just hasn’t played itself out.

In other industries, there are anomalies that I think you can explain, so let me tell about this and then there are some that I don't understand yet. Airlines. Southwest Airlines was a new market disruption. It’s that when they started out, they were competing against buses and cars, not against United, and so just like WalMart locked up the little cities, Southwest locked up the point -- to -- point routes between the little cities, and they’ve done okay.

But all of the other discount airlines have come in as a low -- end disrupter, not a new market disrupter, hitting the low end of the main market. The latest is Jet Blue, and they’re flying in and out of mainstream airports. And it’s easy for a discount airline to create a low cost structure; you just buy fully depreciated jets and higher nonunion people and so on. And you notice how many discount airlines have started over the last 20 years, and their average life expectancy is about four years.

As they hit the low end of the market, and it looks like a classic disruption, the problem is for the major airlines. Their cost structure is such that they cannot live without the volume at the low end of the market. And so the discounters can gain a little share, and then the major airlines just have set up shuttle by United or (Song) and swat them down, and then as soon as the discounter is gone out of business, then they shut down shuttle by United and go back up. And so it’s an eminently disruptable business, but the incumbents cannot flee; they have to fight. And so it makes it miserable for everybody except Southwest; they’re kind of in their own little world. So that's an anomaly which I actually think the theory can explain.

I can’t explain, for example, why EMC beat IBM. It wasn’t a disruptive technology, it was a better product, and yet they cleaned them out. And there are a couple like that, but I think it's a pretty pervasive phenomenon. Religion? I haven’t applied it to churches yet, but…

It’s a great question. How does this apply to Intel? So they were getting killed at the lower end, and they then developed what they call the Celeron chip and tried to sell it through the sales force. The problem was the sales force had a problem, because when they were trying to get a design win, say, at Dell, they had to choose, “Should we spend our energy trying to get a design win for a $300 Pentium processor that gives us 80% margins? Or should we get a design win for a $50 or $70 processor that yields 30% margins?”

So they set up a separate marketing organization out of Israel and gave it the responsibility to sell the Celeron chip and gave it a cost structure so that a $70 price point was attractive, and as soon as they put good technology in a business model that found the disruption attractive, bam! and they got the low end of the market back again. Cyrix was gone, AMD was nailed to the wall, and now the Celeron is the highest volume of all of the products in the line.

And now the next thing that is happening is the system on a chip, the modular custom -- configured processor that needs to be delivered very rapidly. And they have got a fab in Marlboro, Mass. with their StrongARM technology trying to do that. And I think this disruption it is a new market disruption here is a bigger deal.

(Question by another speaker too distant to be heard clearly.)

Yeah, they’re really…and that’s the evidence that the incumbents actually don't need to get killed, but they actually they’ve got to set up their separate organization that can focus on the new thing. And the reason you have to set it up separately is that the new game begins before the old game ends, and if you try to do the new thing within the established when you take your off the old game, and there’s still a lot of money to be made there.

There’s a company in Santa Clara called Tensilica that I think is very interesting. In the new market disruption, what happens…I’ll give you an analogy of how this works because I think it’s a big deal for the software industry. If you go back 30 or 50 years ago in organic chemistry, if you wanted a new molecule, you had to go to the labs at Dupont, and they employed the finest organic chemists in the world. And one of them would mix up a few atoms in a beaker and heat it up and draw a fiber out and look at it under a microscope, and then go down and talk to a colleague and say, “What do you think this is?” and the colleague would say, “I have no idea, but heat it up for ten more minutes and let us see what happens.”

And the miracle molecules that we know as nylon and polyester and Kevlar emerged from an unstructured trial -- and -- error problem -- solving process in the labs at Dupont. And nobody could do this like Dupont or like the engineers who were at Dupont; you just had to be the best experts in the world. But as they kept doing this over and over, they began to recognize patterns of cause and effect.

And when that realm of knowledge migrated out of an unstructured experimental problem solving mode down into pattern recognition, then you didn’t have to be nearly the world’s experts in order to make molecules. And so other companies like Dow and Union Carbide and so on could get into the plastics business. And then quantum theory took over, and quantum theory allows you -- I’m going to overstate the case a little bit -- it allows you to predict that if you put the atoms together in this structure in the molecule, these will be the properties of the material, and that then allows you to write a piece of software to reverse engineer, so if you need these properties, this is what the molecule has to be structured like.

And so now you really just need a BS in Chemical Engineering from Montana State and a good piece of software, and you can design better molecules faster and at lower cost than the world’s experts could a generation ago because it’s gone from unstructured problem solving to pattern recognition down to a rules base.

And in many ways the progression from interdependence to modular follows that same thing, so in a world of interdependence, you just need the best experts in the world and through trial and error and working things out, they create great systems. And modularity that defines how the pieces snap together is only possible when it’s down more of in a rules -- based world, and that allows now people with much less skill to do very sophisticated things because the technology is more rules based.

So what Tensilica is doing is the software that allows their customers to create custom -- configured processors tailored exactly to each situation, their target is to make it so idiot -- simple to design a custom configured processor that even a software engineer could design a processor to optimize the application. I think that is kind of slick, but now that the functionality is more than good enough and you can back off the frontier and the rules are not yet there but they are emerging, it could really change a lot of the world for somebody like Intel.

And another thing is that as the law of conservation and modularity works its way through, Intel needs to be an integrated company because at the high end, there’s not a clean design and manufacturing interface. But at the low end there are much better defined rules for design and manufacture, and so the fabulous companies and the focussed fabs are kind of taking over. It would be crazy if, as that disintegrated industry structure works its way up market, it would be crazy for Intel to sell off its fabs. And its finance people are going to want to sell them off because they’re so capital intensive, but the fab is the place where the money will be made if they are fast. Yes?

(Question by another speaker too distant to be heard clearly.)

Her question is. “What happens if these market disruptors get bought by big players and by the incumbents?” It actually is a great strategy. I want to say two things. Companies like Johnson & Johnson as the healthcare industry is getting disrupted in a pretty big way -- we don't have time to talk about it -- but they’ve decided, “We’re not good at getting these things off the ground,” but they’ve got a team of people that have these lenses on going around the healthcare industry, identifying little companies that are new market disruptors.

And so a company that has a technology that will allow you to do in the home what today you have do in an office, or will allow you do in an office what today you have to do in a hospital, that’s a new market disruption, and they’re actively trying to buy them. And then if they keep it separate and let them have their own processes and create their own business model and just give them their money, it’s a great way to generate growth. And J&J has generated…now every year they get about $9 billion of revenue from disruptive companies that they bought a decade ago. If they try to fold the company into the parent, then it destroys what they bought because it has to conform to the business model of the parent.

(Question by another speaker too distant to be heard clearly.)

Can I fit the University of Phoenix into the Harvard Business School’s picture? Yes, it is exactly one of those things. Not good enough, but there are 160,000 students at the University of Phoenix getting management degrees of one sort or another online, and it is getting better and better every year, and the students that they cater to are not people who would have had gone to a leading MBA program anyway, and therefore they’re really quite happy to able to do something that’s online and ostensibly not as good, but, geez! they’re getting good.

(Comment by the same speaker too distant to be heard clearly.)

Well, it is a good question. So the University of Phoenix is not something that Harvard should go after. If you go back to the model of skating to where the money will be, in the past…see Harvard is an integrated institution. We do the research. The research gets embodied in components that we call “cases and articles.” We assemble the components into courses. We produce the courses, we market the courses, we soak our students for money to finance the courses and everything.

And the architecture of the MBA program is interdependent, and so you can’t study marketing if you don't study product development, and you can’t study product development if you don’t study manufacturing, and you can’t study manufacturing if you don’t study cost accounting, and you can’t study cost accounting if you don't study organization design, because management is a big hairball, and you’ve got to study all of it in order to understand any of it.

But online or corporate education is modular, and so somebody will call up corporate training and say. “Geez, we got to give a strategy presentation to the board in June? Can you give us a week of strategy?” And it's not good as Michael Porters’ course, but it does a job. And then they learn a little strategy and go practice it, and then they call up and say, “We got to get better in product development? Can you find us two weeks of product development?” and so on.

And on that side, in a modular world where the money is made is not in the teaching of the courses, the assembly of the course. In our world, that’s where the money has been made. In that world, if Harvard could become the Intel inside of every corporate university -- and I’ll put my tongue in my cheek -- if we could make it foolproof for all of these unwashed instructors in corporate training programs to teach great stuff in compelling ways, we will create so much growth in education and we would still make all the money in the industry. But it is a very different business model than what we have now, but that would be the right play, but we do not have any data to support that.

Should we do just one more question? Well, we better not. Talk to you afterwards.

Guys, thanks for wasting the end of your day with me! You’re very helpful.

Doug Kaye: Thank you for listening to this special edition of IT Conversations. This edition was recorded at the Open Source Business Conference held in San Francisco on in March 2004. For more information regarding this and future OSBC conferences, please visit www.osbc.com. IT Conversations is a production of RDS Strategies LLC. This program is copyright 2004 by the presenter, Open Source Business Conference, and RDS Strategies LLC. My name is Doug Kaye, and I hope you will join me the next time for anther edition of IT Conversations.

In Part 1 of a look at Google's future I showed that Google's revenues have been highly correlated with the population of Internet users in the markets it serves. If there were a causal relationship between population of users and revenue growth then the company would face a growth inflection point when that population becomes half penetrated.

In Significant Digits Episode 1 (Part 1) I showed data which suggests that the inflection point will come in 2016. Essentially the argument is that Google's growth is ultimately limited by the population of users and that itself is a predictable number. I also used the example of the PC and smartphone penetration curves to show how the perception of the fortunes of companies whose revenues are based on those technologies were affected by inflections in their respective adoptions.

However, correlation is not causation. These users we count are not the customers who pay for Google's services. Users (or usage) is therefore only a proxy. It may be a good proxy and intuitively it makes sense that it's a driver of growth but fundamentally the company lives on a stream of revenues paid by advertisers ((This is true to date and certainly it could change but hints of how that might change are still not visible to me)). In order to really evaluate the opportunity we need to "follow the money" and track down where it comes from.

We don't have visibility into the exact sources of these revenues but we have a top-level geographic segmentation (shown below.)

The data shows that in the most recent quarter 53% of Google's revenues came from the US and UK. Five years ago the proportion was 61%.  Clearly then about 10% of the mix shifted to non US/UK.

If we exclude China, US and UK, in 2009 there were 1.07 billion Internet consumers. By 2012 there were 1.59 billion users in those same territories. The growth is therefore almost 50%, and this excludes 2013. The corresponding growth in the US/UK was 15%. We should also note that in the same time frame, there were almost a billion Android activations but the number of new users in the US ((as measured in comScore)) was only about 70 million (or 7%).

It's therefore clear that whereas the population of Internet users and the ways they might access Google exploded in the last five years, Google revenues have come disproportionately from US/UK consumers. Or, at least from US/UK advertisers, which we are assuming are primarily targeting local users.

The result is the following revenue per user per year based on where the users reside:

The disproportionate weight of US/UK income and the low growth of income from rest-of-world vs. the far faster growth of usage outside the US/UK means that the toughest nut for Google to crack is not penetration but emerging market monetization.

The disparity is enormous. US/UK revenue is on average $86/user/yr (2012) and rising. The rest of the world only manages $12/user/yr. That Rest Of World includes many wealthy countries such as all of Europe and Japan. So the problem for Google is that it has an order of magnitude less income per user in the part of the internet which remains unpenetrated and the trends show that they are not narrowing the gap. ((The ratio between average US/UK and RoW revenue per user/yr was 6 in 2009, 7 in 2010, 7 in 2011 and 7 in 2012))

Google's R&D efforts seem to be oriented around creating consumption (Making it Rain) but the problem is that the quality of that consumption and the indigenous sources of income are unaddressed. These problems are structural and based on social constructs which don't change at the pace of technology adoption.

 

Show #1: The Future of the Internet and Everything

Part 1: The Internet is dead, long live the Internet
The data shows the Internet growth will go through an inflection point. Should we panic or celebrate?

 

In this inaugural episode we open with the biggest question facing the biggest technological innovation of our time: the limit to growth of the Internet. The Internet is the backbone of our post-industrial society as much as the railroad was the backbone of the industrial revolution. Even more so, the diffusion of internet consumption is the fundamental engine of growth at a time when industrial economies are all mired in syndromes of underinvestment and misallocation of resources.

And so it matters greatly if and when the Internet will "inflect" in growth, going from acceleration to deceleration. Mobile computing sustained this acceleration, bringing computing and connectivity to the billions for whom the PC would always be beyond reach. But even with the expansion of device-based usage limits are in sight.

The implications could be profound. Frothy valuations and optimism could evaporate. Venture Capital could find few exits and the "second Internet Bubble" could burst. On the other hand, maybe the data shows that opportunity is largely unmet. Quantity of users is but one proxy. How can growth and business model innovation continue?

To help us think this through I have as my guest Marko Anderson, cofounder of Random  ((Run out of Internet to read? Random’s new iOS app is for you )) and a former colleague at Nokia.

Stay tuned for four more parts:

• Part 2: Browsing vs. Apps The HTML5 vs. Native debate and the jobs the Internet is hired to do.
• Part 3: Monetize This The problem with business model innovation. When the ad dollars run out, what will take their place?
• Part 4: Random How discovery is changing and the value of irrationality.
• Part 5: Glass is half full How can we screw this up? Privacy, Surveillance and The Internet Citizen's Bill of Rights.

Significant Digits is a talk show where we take time to recognize patterns in the lives of technologies.

From 2005 through 2012 Google site revenues ((Google revenues are reported as "Google.com", "Network", "Motorola" and "Other". For this analysis I am including only the Google.com revenues)) have risen at a rate consistent  with the growth in global Internet population excluding China ((Internet population is calculated as a combination of penetration as reported by the ITU and population data from the World Bank)). The Internet population and Google.com revenues for the period 2005-2012 are shown in the following graph.

The correlation is shown in the following graph:

Taking into account costs and expenses, on a per-user basis profitability per user (assuming all non-Chinese internet users are Google users) is shown below:

The simple conclusion is that Google earns approximately $1.2 per user per quarter (net income is the blue area above). This figure is relatively constant with a slight increase (~20%) over 3 years.

If the company does not alter its business model then the future potential of the business could be measured as a function of Internet (ex. China) population growth.

How hard can that be?

The next post will answer this question.

On a recent podcast I noted that Google was perceived as invulnerable. In contrast, Apple is seen as temporarily enjoying a stay of execution. ((The list of Apple Achilles' Heels is so long and creatively composed that it would take ages to compile, but here are just a few: the Mac (vs. Windows), Digital Rights Management (which kept the iPod alive), dozens of lawsuits (including from The Beatles), the Mac (when it ran Windows), PlaysForSure, Music Labels retaliation, the Zune, Android and clones, the Kindle and Amazon in general, more Mac, iTunes, iPod and iPhone and iPad killers than can be counted; Steve Jobs is ill, Jony Ive will quit, Tony Fadell quit, Rubinstein quit, Forstall was fired, etc. Feel free to add more through comments. See also Apple Death Knell Counter.)) This is not necessarily a bad thing for Apple. The more gushing the loathing or scorn, the more likely it's a reaction to love and attraction. A brand dies not from hate but from apathy.

But nor is it necessarily a good thing for Google be be seen as invulnerable. There might be no "Google death knell counter". There might not be a "Google is doomed" trope. If an executive from Google quits or is fired there is no investor panic. If a product is withdrawn there is no mourning. There are no journalists pursuing Pulitzer prizes by describing some seamy underside of Google. But there are no overt displays of affection either. Google is seen, on balance, as benevolent and hopeful. The discussion on business robustness is simply missing.

I suspect the absence of scrutiny comes from Google being seen as an analogy of the Internet itself. We don't question the survival of the Internet so we don't question the survival of Google -- its backbone, its index, and its pervasive ads which, somehow, keep the lights on. We believe Google is infrastructure. We don't dwell on whether electric grids are vulnerable, or supplies of fuel, or the weather(!)

Too complex, too pervasive. These are systems, not things. And people are not designed to contemplate systems. We leave that to experts, or better yet, computers.

The reason Apple is contemplated at all is that it's not seen as a system. Even the suggestion that Apple is a system is implicitly treated as an impossibility. Because it's not a system it's fragile. It's a person, or an idea, or a product or a singular "key" to something. It is, ultimately, mortal. The only debate is when it will die and points are earned for calling it sooner rather than later.

But what if Apple were a system? And what if Google were a person (or three?)

 

According to ITU data, Internet usage reached about 2.2% penetration in the US (2.2 users per 100 residents) in 1993. The figure in 2012 was 81%. The history of penetration is shown in the following graphs.

Similar graphs can be drawn for other countries (data is available for 193 countries/territories.) I chose the following set of countries arbitrarily:

When looking at all countries, the patterns are fairly self-evident. They nearly all behave the same way with respect to the impulse to move online. The pattern is approximately logistic (observed as linearity in the right-side graphs). ((Those that don't are anomalies which should be inspected individually and might provide insights into the constraints for systemic state health.)) The main difference is one of timing.

The global picture should therefore not be surprising. In absolute terms, the penetration was 35% at the end of 2012 or 2.5 billion individuals. The graph of global population divided into Internet consumers and Internet non-consumers is shown below followed by penetration.

The linearity in the blue line above is consistent after 9% penetration is reached (P/(1-P) ~= 0.1) suggesting logistic growth (far more smoothly than individual country data). Note that I also took the step of projecting the logistic curve that describes the internet's growth forward a few years.

Based on this history, it becomes possible to project that 2013 penetration reached around 39% or 2.78 billion individual users.

It also suggests that "saturation" could come between 2030 and 2035. ((The curve is defined as having a half-period of 19.7 years from 1996))

If we look at growth, ((Derivative of logistic curve)) the inflection point comes in 2016. Thereafter internet user growth will slow.

Overall, the growth pulse of the Internet will be approximately 40 years long. ((More likely 35 years as saturation dynamics will be erratic.)) We are therefore nearly half-way through.

It might seem an interesting but benign fact, however I must caution that as we've seen with smartphones, once the point of inflection is reached, investors tend to flee the sector. That in itself may not be a bad thing but investment flight has deep effects on "ecosystem" participants.

Venture investments tend to feed entrants disproportionately and they are remarkably sensitive to the valuations of public companies (and IPOs). These investment might therefore be in danger in two years. Plan accordingly.

My thanks to Eric Jackson for his thoughtful questions and post on Forbes.com. You can read full interview here but I repeat a few non-biographical questions and answers here for discussion:

An Interview With Horace Dediu: On Blogging, Apple And What's Next

Q: Turning to Apple, where is it at right now as a company in this post-Steve Jobs period?

A: Still too early to tell. They seem to be cooking a lot of things and the great experiment of whether a company can be Jobsian without Jobs is still going on. I have been trying to put together a picture of how it operates. It’s hard because that’s their biggest secret. It’s also a picture that few people have ever seen, even those who worked there a long time. The glimpses so far are tantalizing but there is so much we don’t know and thus can’t assess how robust it is. One thing that is clear to me is that there is no absorption by mainstream observers of what makes Apple tick. It’s hiding in plain sight because what it is isn’t anything anyone can recognize. Case in point is the functional and integrated dimensions. It’s the largest functional organization outside the US Army and more integrated than Henry Ford’s production system. Just describing it sounds medieval and it’s so far outside convention that it’s not something reasonable people are willing to believe actually exists.

Q: Is Tim Cook the right CEO for the company at this time?

A: I hold the belief that he’s been CEO for much longer than it seems. Jobs was not a CEO in any traditional sense. He was head of product and culture and all-around micromanager. He left the operational side of the company to Cook who actually built it into a colossus. Think along the lines of the pairing of Howard Hughes and Frank William Gay. What people look for in Cook is the qualities that Jobs had but those qualities and duties are now dispersed among a large team. The question isn’t whether Cook can be the “Chief Magical Officer” but rather whether the functional team that’s around Cook can do the things Jobs used to do.

Look at it another way: I subscribe to the idea that any sufficiently large company is a system and needs to be analyzed using a lost art called “Systems Analysis”. This is a complete review of all parts and the way they inter-relate. However, since for most of its life Apple was personified as an individual, what came to pass for Apple analysis was actually the psychoanalysis of that individual. It makes for great journalism and best selling books. It’s also banal and almost certainly wrong. The proof is in the vastness of complexity and number of people involved. Engineers tend to think about constraints and the constraints on companies are innumerable.

Q: You’ve written extensively on the post-PC period, when will we come to the post-phone period – if ever?

A: I think less than 10 years. Maybe even five. A wristband today can have more processing power than the original iPhone. An iPhone has more power than a desktop did 4 years ago. The speed of change is incredible.

Q: What’s going to be the “next big thing” for Apple? Watches, TVs, something else?

A: I segment along “jobs to be done” which are basically unstated and unmet needs. Unstated because they are usually so deep and so pervasive that they’re taken for granted. We have the need to feel good about our lives, to be healthy and to be connected in meaningful ways to others. These jobs are very poorly served by technology today and there are many non-technology products that are hired as poor proxies to help. The speed with which technology changes means that the trajectory of improvement will undoubtedly intersect that of the job. Even a small job like losing weight and eating well is probably worth as much as half the mobile phone market. Imagine if someone gives us a magic tool that does that for us. How much would you pay? How many of us would pay? There are so many next big things that I cannot choose. (By the way think of the job Facebook is hired to do: make me feel good about myself because I can show others how good I am. Boom!)

Q: What’s your take on how they’re handling their expansion into China, India, and other emerging markets?

A: It’s depressing how slow things are moving on that front. We can draw lines on a graph but we don’t know the constraints. Again, the issue with adoption is that the timing is so damn hard. I was expecting smartphones to take off in mid 2004 and was disappointed over and over again. And then suddenly a catalyst took hold and the adoption skyrocketed. Cook calls this “cracking the nut”. I don’t know what they can do to move faster but I suspect it has to do with placement (distribution) and with networks which both depend on (corrupt) entities.

Q: As you look at the rest of the mobile internet competitive landscape, do you expect any big surprises from other players (good or bad) in the next 5 years?

A: The big question in my mind is the sustainability of the arbitrage models which underpin pretty much every internet business plan. Essentially we have two markets: one where everybody consumes but pays in metadata and another where everybody consumes aggregated analytics but pays in cash. An internet business is the arbitrageur who takes advantage of the inability of each market to price the other. History shows that arbitrage markets tend not be stable as information begins to leak across markets. Therefore what would blow the internet up is if consumers could become wiser about what they are giving up and advertisers would become wiser about aggregating consumer data. I imagine a system where each individual would allow bids on their consumption and a market mechanism where bidders competed for that data. This of course depends on users taking control and ownership of their own data. What might help is the realization of what mass state surveillance can do and the realization that internet giants have more information about us than the government could ever hope to possess.

It would create a new era which will have political dimensions. I imagine we’ll need an internet citizen’s bill of rights or some such movement which will reset expectations. Economically, could bode well for those who position themselves as protectors of the individuals and be a crisis for those who take advantage of consumer ignorance.

 

One of the enduring mysteries of the iPhone has been its lack of a portfolio. After six years it seems that Apple has finally acquiesced that there should be one, albeit currently limited to two items. The second enigma is related to the price, namely why does Apple ask so much for its phones? At an average sales price of $600 it's a shocking premium to the average phone, and with a six year run, a shocking resistance to the corrosive effects of competition.

The obvious answer to why Apple asks so much is because it can. Anybody would if they could. That's a poor question. So the right question should be: why does anybody pay this much? One could answer that few do and it's not a mystery that some feel better paying more simply because they can. But those who pay Apple's prices are, mainly, not consumers. They are operators. Exactly 270 of them.

So then let's re-ask the question: Why do so many operators pay so much for Apple's phones? We can't answer that with the psychological slurs usually directed at the brand. Surely Operators aren't competing in beauty contests or need to soothe their collective egos. The decisions operators make on whether to range a phone are driven by hard economic realities: ARPU, churn, network costs, depreciation, ROI, etc. Some clearly can't make the iPhone fit their economic models and indeed about two thirds of them don't. But the most prominent ((Arguably the most important)) do. DoCoMo, the largest in Japan just did after holding out for five years. Verizon held out for years, as did T-Mobile. China Mobile's acceptance also seems imminent.

But that still leaves the question of why are those operators who do carry the iPhone willing to pay so much for it? I only assume that their decision process is likely to be rational. Mainly because we have a large enough sample but also because there is a lot of money at stake requiring quite a bit of internal consensus and vetting before committment. We have to conclude that operators place the orders because they obtain value from the iPhone even when it's priced at a premium to the average alternative.

The question which follows then is how do they obtain value? I've argued that this follow-the-money process leads one to conclude that the iPhone helps in moving users to higher revenue data services. These are more profitable services for operators and the subsidy model creates more loyalty and thus reduces churn and creates a stable cash flow which can then be leveraged through debt to upgrade networks and attract yet more loyal iPhone users.

Therefore the iPhone is "a data service salesperson" receiving a large commission (in the form of a price- and hence margin premium) for doing what few others can do. In that sense the iPhone is hired by the operator to do a unique and valuable job and is paid well for doing it.

This answers the question of why Apple can get away with charging so much for its phone: because operators love it. The entire product depends on a reward system and for years we've heard fears that it's going to end. But it hasn't. Operators love subsidies and they've been honing them for long before the iPhone showed up. ((Recall that the first iPhone was sold without subsidy and with a separate, secret revenue sharing plan. It did not last because it was cumbersome and because operators convinced Steve Jobs that their way was better.))

But this is not the end of the money trail. The premium is initially paid by the operator but they tend to get most of that payment back from the consumer. In other words the subsidy that inflates the iPhone price is at least partly if not mostly paid by the consumer in the form of a higher phone bill.

You won't see it itemized on your bill, but it's likely that $10 to $15/month from a subsidized phone service plan goes toward paying for your phone.

So in a way, Apple has managed to place itself on many people's monthly phone bills. It's a nice place to be. It's nice for the same reasons operators like post-paid customers: predictability. It's also nice because recurring services are a better business model than products; they have higher levels of loyalty and are more "sticky".

But this placement is not transparent. It smacks of misdirection. The link is not made in the mind of the consumer that they are paying for a phone through their service plan and many see it as a thinly veiled con. The value of the iPhone to the user may be evident through its use but the payment for that value is not.

But in many ways this is similar to how many services are valued: through bundling. We pay for the value of a great retail experience through a higher price on items purchased. But we still associate that price with the good sold not with the place where it was bought. We get great value from Google's services but don't know how to quantify the cost of their peering into our minds. In fact the whole Internet and all business plans that are built on it depend on a subtle "something for nothing" type of misdirection. The Internet runs on the arbitrage between a consumer service market where everybody consumes but nobody pays and a separate data market where nobody consumes and everybody pays.

The iPhone could thus be finally understood as a complex service business. It captures value through the phone bill but delivers value through a screen. A misdirection magic trick which many have tried to pull off. It's essentially tapping into the $1.3 trillion communications market, skimming profits by delivering the "content" which lights up the wires.

It's great except it does not work everywhere. Not yet at least. The complexity of services means that they are usually found in more advanced so-called service economies and rare in less developed so-called goods economies.

Economists have observed this process and even have a name for it: servitization: The process whereby almost all sufficiently advanced products are indistinguishable from services.

As a service, the iPhone's strengths are easier to understand. Its weaknesses as well. Services simply don't work in economies which don't have robust institutions of credit, capital intensive infrastructure and distribution networks.

It's also the reason why Apple is so slow to penetrate all markets. It's not in the business of selling phones. It's in the business of enabling and creating services.

The following is a slightly edited transcript of a portion of the Critical Path podcast #79. I am reproducing it here for the sake of brevity and focus of discussion.

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I'm going to try to put together an analogy together here that maybe will help us think through the Facebook Home and the Google Fiber issue.

I've been thinking a lot about how to illustrate Google's business model. The problem is that discussion has been polarized: Two camps have formed. One camp suggests that Google is a benevolent entity that does great things and only asks that we indulge their hobby of a business model called advertising. Fundamentally they are about pushing the envelope on technology, making wonderful things happen.

That is one camp. I call them the utopians. It may not be a nice thing to call them but I frame it as being exceedingly idealistic.

The anti-utopian camp is one that suggests that Google is an advertising company primarily, and fundamentally and overwhelmingly. And anything they do technologically is in support of that. The implication is that Google is sinister and manipulative, bent on getting away with as much privacy extraction as possible.

I believe that the anti-utopians dismissing Google as an advertising company sounds a bit incomplete. It's not incorrect. It's not erroneous. It's just not a complete story.

And also the utopian view that they do everything for us out of the goodness of their hearts and that advertising is something that they are reluctant to do, saying in effect, "We only do it because it earns us enough money so that we can do good deeds." That too is not an accurate picture. Google is a business and its business management team is hard nosed and knows what they're doing and they are not purely idealistic in that sense.

And so the question could be where across this spectrum does Google lie? Possibly it moves around between these points. Where they are becomes a question of motivation and what they want to become.

But this is only one dimension. It does not help us answer the question of Home, or Fiber or Reader or Blink. Their actions seem contradictory. Holistic or selfless in one case, greedy and capricious in another.

Let's step out of this spectrum and try to think of different ways which can describe the situation.

I propose a way to think about it as: Google tries to make a business succeed through having a huge amount of _flow_ in terms of data, traffic, queries and information that is indexed. So think about this idea of them tapping into a vast stream. The more volume that is flowing through the system the more revenue they generate.

As so given this very rough analogy I try to sharpen it up by saying: imagine it more as a river. And even more than a river, as a watershed, a river basin. Perhaps a giant basin the size of a continent. The business is, let's say, capturing fish at the mouth of the biggest river, before it exits into the ocean at its delta.

And so your job (as Google) is to catch fish mostly at one point. It's the most efficient way to catch fish because you have the most flow of water at that point and building nets is not trivial.

But in order for you to improve your business, to create more opportunity, presumably, you want to essentially have more water flowing.

And so how would you do that? Think of the Mississippi river. If you've got a net down at the bottom of the river, the question is how would you engineer, through civil engineering, or shaping the earth itself, a way of catching more fish.

The answer I think, in terms of the way Google might be thinking, is that they want to create more sources of water. So they would look to connect tributaries and lakes. "How about having another river join our river?" Let's make sure that we have "everything east of the Rockies" flow into our river system.

Now, think of it this way: After you've gotten all the tributaries, what are the remaining sources?

First, you'll want to make sure that no-one can dam or stop the flow of water into your main channels. And so you become extremely anxious about people building dams. That's the number one concern.

So your strategy becomes one of "how do we avoid dam building"?

That's one part of your strategy.

The other thing you could do to improve your business would be to make it rain more. So there's the question in your mind of: If we had more rainfall, then everything will flow more rapidly and we'll get many more tiny rivers forming and joining together into our main river.

Android and the Fiber business and even Facebook fit into this analogy rather well. In this context more rainfall means more people using the Internet. If you have more people you'll have more rivers and you'll have more water and hopefully more fish. Fiber means the water will flow more rapidly: you're essentially dredging the riverbed.

But the two are very disconnected (rain, dredging and fish). So your strategy amounts to not really worrying about the ratio. You don't create incentives to people who make rain in the form of fish catch quotas next quarter.

In other words, your performance as a manager of cloud seeding efforts should not be measured in fish.

Leadership should instead simply put out the mandate of "Go out and make it rain".

So that's the notion of Google going out on these projects and doing all these "great things" for us. They make it rain. The Internet expands. There is minimal censorship.

By the way, censorship is a dam. Being blocked out of a country is a huge dam. It's actually more like building a mountain range that diverts water flow away from your watershed.

And so they have these notions of how to prevent these things from happening.

So it sounds like they are doing good things. It sounds like asking for it to rain; they want to make sure that people don't divert resources; they want to make sure that there are no barriers between the raindrop and getting access to the channel to the ocean.

So it sounds like they're doing all the good things like a good civil engineer. Like the US Army Corps of Engineers who developed the irrigation, flood control, energy generation and waterway transportation of the United States.

Google seems to be the world's "internet civil engineer". They are building all these things to make sure that we have good water (i.e internet) supply. That we have plenty of navigable channels. That's the analogy.

But let's not forget that the only reasons those things are happening is because they are catching fish at some point down the Mississippi.

From that point of view you have to ask yourself: do they deserve this concession? Because they are ultimately affecting the environment to such a degree; and the environment is the internet; and the whole scope is how the world operates.

That is where people have to step back and ask themselves: Even a group of civil engineers that have all the best intentions may realize that they didn't think of all the consequences of their actions. A lot of the criticisms may come decades later. From people who'll note an effect on the environment. Dams get silted, a lack of floods reduces nutrients to crops which then need fertilizer, which has a whole other set of problems.

That is when you have to reflect more deeply on what is right and what is wrong. So saying, as the City Council of Austin might: thank you for coming and paying for installing broadband for us. Fine, but we just don't know what the unintended consequences might be. It all _sounds_ good but we don't know if it _is_ good.

And similarly, in the case of Facebook, there is a subtle hijacking going on where Android creates more rain, and Facebook and Amazon are essentially putting down nets and catching fish upstream. They're not damming the tributaries. They're not putting up mountain ranges and saying they'll make sure the water flows away from the Mississippi. But rather they are putting nets and saying "Thanks for the rain". They took advantage of what amounts to a public resource. Here the failure of anticipating consequences falls on Google. But they could not have possibly foreseen all that? Or could they?

Then there is the question of measuring success. It's complicated and hard to measure performance. Even Google's own performance. We don't really know if the cloud projects work. We don't get to run this as an experiment that can be tweaked as data comes in.

Google does not report performance. When they go off on these rain making projects, it's natural to ask how many fish were caught as a result. Is that incremental new rainfall causing more fish to get caught. And Google won't say anything about the profitability of rain making. They will never give you a profit and loss statement for all these projects: the dam eradication project, the project dredge a channel, the project to seed clouds. They will say that these are projects that will result in only one thing, which we do measure, which is the number of fish we catch in the delta of the Mississippi down by New Orleans. But so far although rainfall seems to be increasing exponentially there are not that many new fish.

So that's where we struggle as analysts: is rainmaking good? Is the dam destruction process working? We can't answer these question. And we don't even know if Google themselves can. They might think of it as a strategic thing: it's always better to have more rain than less and more water flowing. End of discussion.

To borrow a phrase from Zuckerberg, it's above my pay grade to know what all the consequences are. I have opinions as environmentalists have opinions and sometimes they have some data to back up those opinions. For instance whether a dam project is a good thing on balance. But they are bound to have partial answers because the cost/benefit analysis is definitely missing a lot of the costs and missing a lot of the benefits as well. You can't put a number on a lot of these things.

That's where we are today. Google and Android are forces which are are very powerful but which are, to a large degree, uncontrolled, even by their own managers.

 

The following article is published in Filmmaker Magazine. Fall 2012, Vol. 21 #1.

There is a saying I once heard: "Once you change the method of distribution, the product has to change."

This itself is a take on the idea that distribution defines the product. You see this around you every day in the products you buy. Cars are influenced by the dealership networks that sell them. Phones by the mobile network operators and the choice of computer you use at work by whatever the IT department or value added reseller prefers to work with. Mass market restaurants offer what can be sold by wholesalers--typically frozen, long shelf-life staples. Almost every product category is shaped more by what can be distributed than what can be produced. That's simply because in mature economies distribution is harder than production. In consumer products it requires access to wholesalers who then require access to shops who themselves have access to prime real estate which attracts foot traffic. Production only requires capital. Distribution requires relationships, often exclusive ones.

This pattern is even more pronounced when looking at media products. Production is arguably easier since it's constrained by talent, which is fungible. But distribution is even harder as it is addressing bigger audiences in shorter time frames. You see this lopsided balance of power in the abundance of books being written relative to those being published. There are thousands of films produced and hundreds get distributed.

But the saying suggests that if distribution were to change then the product itself would change. Indeed, if you can sell ebooks direct, then they tend to evolve into new genres (e.g. Fifty Shades of Grey). If you can sell cheap adult video online it tends to evolve into new genres as well (I'll leave examples to the imagination.) YouTube videos quickly cluster around "Fail" or "Win" compilations which evolved from America's Funniest Home Videos. They get millions of views. Even before the Internet, the availability of cable created the genre of music video, which created the first music broadcast alternative to radio. And of course, cinema itself redefined theater once it could get shown to millions rather than thousands. The new methods of distribution of media affected what gets produced rather than the other way around. Consider the converse: innovative filmmakers who try new storytelling methods are stymied by a lack of acceptance by existing distributors and find their material languishing in festivals or perpetual cult status.

So we can re-state the saying to a new "Law of new media": Once you change the method of distribution, the medium itself has to change.

I gave examples of how Internet distribution changed some media formats. However, the Internet itself has not had any effect on long-form cinema so far. In fact, you would be able to tell if Internet distribution did work by watching if the product would change. So far, it seems, at least to me, that the commercially successful product has not changed. One reason has been that film is still a very difficult product to distribute digitally as most of the world does not have the capacity to buy, consume and enjoy films digitally. Another is that the current distributors have had an allergic reaction to the option. As existing products have been crammed into the new distribution chain (e.g. Netflix) the established distributors are experiencing channel conflict and are raising the costs of digital distribution rights. Netflix has seen its costs triple as it ate into Cable market share. Fundamentally, the incumbent distributors are reluctant to open a channel of distribution which conflicts with or reduces margins of the existing channels.

This brings up another corollary: fundamentally, you can’t move an existing media to a new network. You have to think of it as a deeply rooted-in system, and it's just not going to like moving to another environment. You have to uproot this huge tree, and it just won’t come out and if it did it will not take root in a new place.

The only way to create this new value network around new distribution is to plant a new tree.

This is the problem for the technology industry today. The only way technology companies can solve the “content is king” dilemma (which, by the way, is an euphemism for "Hollywood is king and Silicon Valley isn't"), is by allowing new content to flourish on top of new platforms. It’s not about moving the old content to the new platform. It’s about allowing new content to be created exclusively on the new platforms. This new content will therefore, by our law, be a new medium.

For me, apps are that new medium. Apps offered a new way to package entertainment for “niche time”. The early fart apps evolved into a whole new genre of games which are now challenging the established game studios. The result is that a generation of developers has moved from building PC or web software to apps with cloud back-ends. The first to switch to this new medium were those with the least to lose and with the most modest of goals. Apps have now a more valuable industry than digital music with over 55 billion installs between the iPhone and Android ecosystems. Consumers are increasingly spending their spare time in front of apps. In the US “app consumption” increased from 43 min/day in 2010 to 94 min/day at the end of 2011. This number already exceeds the time spent in web consumption. I find it difficult to doubt that app time will exceed TV time, especially as TV time is increasingly a dual screen experience.

(Feels like it needs one sentence explaining why. Is it because of their accessibility to small developers, or their ability to reach mobile handsets natively, or because of consumer trend?) If it’s absolutely impossible to move long-form video or long-form cinema to this new medium in such a way that everyone in the world can consume it on every device, then the app ecosystems will take up that challenge and say, “There’s a job to be done, and that’s to enertain people for an hour-and-a-half with characters, plots and wonderful stories, and we will make that happen, and we’ll call this thing an app.”

And that app will solve that job for that person. It's what's happening to the game console business. The new game apps are distributed differently, priced differently and produced differently. As a result they are used differently and make a different set of developers thrive.

The new app media will mean that we’ll just have to live in app universes, and go eat popcorn somewhere else. Microsoft and Google and Apple and Amazon and anybody else whose belly is at the bar has been scratching their heads wondering "How do we move that content over to us?" They've been barking up the wrong tree. The fundamental question isn't how to cram old media into a new shiny screen. It is how do you let developers and artists and creative people create stuff that is new and compatible with this new way of living.

Think also about the history of media -- movies haven't been around forever; music hasn't existed as a recorded medium forever. Not even books. What did people do before these forms of expression? We think of the use cases of going to the movies, or the use cases of sitting in front of a TV on Sunday night, or playing a console game. These things didn’t get done at some point in time. Nor will they be done at some future point in time.

In a few years we’ll move on and we won’t do those things. Each person will probably have his own screen in front of them--many already do--and whatever we do together we’ll do through a shared screen. We won’t have communal experiences that we associate with the old media. Certainly not in a theater. Maybe not even in a living room. And that is how we will move into a new value network.

It is inevitable. As a technology provider, you shouldn’t try to squeeze a 19th-century model into a 21st-century model. Just let it go. Create a platform and give people the freedom to create on it. As a media creator, you should try to learn what the new model demands. New forms of interaction, new story telling opportunities, new ways to communicate with audiences. Create experiments and learn. It's the only way.

Apple's recent margins are nothing short of spectacular. It's hard to convey just how remarkable 47% gross margin and 39% operating margins are. For a company that sells hardware these are simply unheard-of numbers.

The best way I can illustrate this is by comparing Apple's operating margins with those of two other platform-based companies, Google and Microsoft.

Microsoft invented the software-as-a-business model and, as software is easily reproduced, their margins are phenomenal. The gross margins are typically in the 80% range for software. Overall, the company had higher R&D and SG&A expenses so their operating margins are a more modest 37% on average. However, Apple managed to exceed this value even though it has the disadvantage of actually having to build things made of atoms.

Google also has led a charmed life free of inventory and factories. Its operating margins have been however hurt by investments needed to sustain the infrastructure for indexing the internet. That means that their margins have hovered around 33%.

As the chart above shows, Apple has been creeping up on both these benchmark companies with exceptional operational leverage and, as of this last quarter, overtaken them.

The reason Apple is able to do this is that its iOS businesses are extremely profitable and, as those businesses grow in absolute terms and relative to its other businesses, the overall margins are reaching into the stratosphere.

The impact of iOS on Apple is shown in the right-most two charts below. The difference in growth relative to these other great companies makes Apple all the more impressive.

But the temptation is to compare the "core" business models and ask which is best: hardware, software or internet services. It would seem that hardware is winning, suddenly getting the best margin and best growth--a dramatic reversal with prior technology business dogma.

However, it would be a mis-reading of what allows Apple to succeed. Apple is the most valuable company in technology (and indeed in the world) because it integrates hardware, software and services. It's the first, and only, company to do all these three well in service of jobs that the vast majority of consumers want done.