Friday, December 6, 2019

The Source of Genius

The guy at the next table looks out at the amber sunset, puffs up with gravitas, and announces to his wide-eyed friend “soon all things will be connected seamlessly to a ubiquitous network." Time to change tables. I grab my drink and set off to find an area outside of Houdini’s vocal range. The bar at the Rosewood is cursed by its reputation as the place where VCs from Sand Hill Road meet, so it attracts posers playing the prophet like LA attracts actors.

Coincidentally, on my way over to the Rosewood, I saw along El Camino Real a hand-painted sign saying “clairvoyant conference” with an arrow pointing to a hotel. Imagine a conference for clairvoyants! You would not need to have sessions on “future trends,” since they would already know. But wait: Why the sign giving directions, for that matter?

Since time began, it seems people want to believe that some of us have a special knowledge of what is to come. So we’re vulnerable to those who claim such knowledge - albeit that different people fall for different images of the prophet. You might mock the trappings of the village shaman, the tarot reader, and the astrologist – but I bet you’d clear your calendar to hear the latest word from the valley’s richest VCs.

I’m not just waxing cynical. It turns out that venture capitalists typically are bad at telling the future. As an industry, VCs don’t perform that well financially. To find VCs who outperform the market, you have to selectively sample only the most successful ones - but that is true for slot machines, too. OK, a minority of VCs do tend to appear repeatedly on the winning side, so perhaps they are the real Houdinis. Maybe. Or maybe having been successful they end up getting preferential access to things that continue to make them successful. (I appreciate that advantage, working at Stanford.)

Whatever the reason, the fact that at least some VCs are repeatedly successful has created the mystique that there does exist, somewhere along Sand Hill Road, somebody who does know what’s next. Hence all the puffery at the Rosewood. How are we to know that he’s not really a visionary?

Professor Elizabeth Pontikes and I took a careful look at this question. We collected data on thousands of firms in the software business and looked at their fates over time – including both successes and failures in the data. We found that firms herd into “hot” markets that have been blessed by the VCs. But we also found that the VCs herd into markets too, following each other in financing frenzies. The resulting hype cycles lead to bad outcomes for companies; firms getting funded in these waves are the least likely to ultimately succeed by going public. So much for Houdini.

Perhaps even more interesting, the VCs themselves seem to be aware of this problem. While VCs herd into hot markets, at the same time they try to avoid investing in firms that do so. The VCs prefer instead to invest in those who pioneered what is now a hot market (and survived). As a kid I had a precocious classmate who would jump to the front when he saw a trend, pointing resolutely forward in Napoleonic fashion, proclaiming “follow me!” I’ll have to check; perhaps he grew up to be a VC.

Remember, the most remarkable changes are not predicted by our experts. These acts of genius are pioneered by those foolish enough to ignore the consensus. Be skeptical of those who claim to know what's next.

Then What's the Fuss About "Unicorns"?

OK, Barnett, if we're so bad at predicting genius, then why does everyone make such a fuss about spotting "unicorns"? I ran into this question recently from three very different groups: some top executives of a large American manufacturing firm, a roomful of Russians, and several thousand Chinese entrepreneurs in Shanghai. Very different groups. Very different topics. But one question was asked in every venue: "What business is the next 'unicorn'?"

If you can read then by now you are tired of hearing about unicorns. The internet tells me that the trope refers to startups valued at $1 billion. Most pundits talk about them only after they are valuable, but anybody can look in the rear view mirror. What my audiences worldwide want to know is how to see them coming.

First let's get something straight: Statistics tells us that amazing exceptions will happen, every now and then, at random. In fact, amazing exceptions will even come in bunches every now and then at random, in the same way that my music player will randomly serve up three straight "Steely Dan" songs in a row. Call them what you want; black swans, unicorns, whatever. Unusual exceptions happen at random.

But with unicorn businesses there is a pattern we can see in advance. This pattern won't tell you who is the next unicorn. It will tell you where not to look, however.

Let me explain. Research shows that waves of exuberance about businesses tend to be biased. Since we're all looking to each other to find the next new thing, once a market space starts trending it's bound to get hyped beyond its real potential; that's what the "hype cycle" is all about.  All that buzz makes it much easier to start companies in a hyped space. Ironically, this makes it so that many of the least competitive firms are the ones that herd into the hot markets where everyone wants to invest.

Want to find the next unicorn? Listen to where the buzz is coming from and run the other way. I can't tell you who will be the next unicorn, but I can tell you it will come from where we least expect it.

Then How Do We Organize to Create Genius?

If we cannot predict genius very well, what is a business leader to do if she wants her firm to innovate?

One way to answer this question is to recall an old debate in the management of innovation. Mid-20th century economists, most notably John Kenneth Galbraith, predicted that large companies would be responsible for most of the groundbreaking innovations in our future. History has proved them dead wrong.

In fact, the opposite has turned out to be true. Startups – entrepreneurial companies – are the engine of innovation in the modern economy, and as a result they grow disproportionately faster than large, established firms. And this is true both in terms of their average growth rates and in terms of which companies are more likely to be super-high-growth outliers.

Big firm fans: Before you argue by naming your favorite big-firm innovator, review the quality research on this subject. A large academic literature has thoroughly looked at “Gibrat’s Law of Proportionate Effect” in firm growth rates. That's a baseline model where small, new companies and large, established ones innovate and grow proportionate to their size. If that were true, then entrepreneurship and intrapreneurship would be equally effective. But this literature consistently finds disproportionate growth rates (and more dispersed growth rates) among smaller, newer organizations. We can debate nuances, such as whether large organizations help by investing in R&D that later appears in the innovations of startups, or that there are some exceptional big-company innovators, but there is no doubt of the main finding: Entrepreneurs outperform intrapreneurs.

But what about the studies showing that innovation helps big firms improve? Two problems here. First, when innovation does help large firms, the improvements typically don't kick in until after a difficult and painful period of adjustment. In fact, often large companies fail outright while trying to adjust to innovation. Second, this is a false comparison anyway. Sure, compared to its tired, old self, an innovative big firm is improving. But the correct comparison is to the entrepreneur.

Now you may be wondering, don’t new companies also fail at a higher rate? Yes, they do, but the growth created by the high-growth survivors more than compensates for the economic losses due to failure. Plus, failures fuel future entrepreneurship; the “creative destruction” described by Schumpeter. In any case, if you’re looking for big success, look to entrepreneurs – not to the intrapreneurs funded by large, established companies.

But why?

To understand why entrepreneurs outperform intrapreneurs, you first have to understand how great new innovations take hold. The process happens in two steps:

Step 1: Variation.

Groundbreaking new innovations are typically "nonconsensus" ideas when they start out. That is, some think they are a good idea, but many disagree because (by definition) groundbreaking innovations defy conventional wisdom. I recall when the consensus said that internet search was not a good business. After all, we had seen the failure of Lycos, Excite, Alta Vista, and a bunch of other search firms. So when Google came along few people wanted to fund them. Now, my marketing colleagues tell me that search is the greatest business in the history of humankind. In this way, we're often very bad at predicting which innovations will succeed. But we're so good at retrospectively rationalizing, we forget how bad we are at predicting.

Of course, not all nonconsensus ideas are brilliant. In fact, often they are really bad ideas. We won't know for sure until an entrepreneur proves their genius (or folly) by experimentation. Nonconsensus ideas are not necessarily better, they are just higher variance.

To see what I mean, Consider these two distributions:

Let's say these are plots of the number of innovations produced, ranging from really foolish (far left) to really genius (far right). The top distribution is a high-variance distribution, while the bottom distribution is low variance. Both have the same average, but the top distribution has much more genius (and folly) than the one on the bottom. Nonconsensus ideas are high variance ideas, like the top distribution. If what we want are some really great innovations, we want to generate high-variance distributions like the one on the top.

Entrepreneurs are unpredictable, and uncontrollable. So they are very high variance, looked at as a group. Many are complete fools, and some of the fools will turn out to have been geniuses once we see how history develops. By contrast, intrapreneurs operate within a corporation. They need to justify their expenses. And, even if they are given a great deal of latitude, they must at some point explain themselves. The need to answer to a big, established firm renders intrapreneurship low variance.

For instance, I remember when Hewlett Packard was the model of big-firm intrapreneurship back in the 1990s. I was studying their venture into video networking, a very entrepreneurial move. Jim Olson ran their video division just like a startup, even imitating the physical surroundings and culture of a start-up company. But every year he would have to attend the budget meetings, where the meager returns of the video division were dwarfed by the billions being earned in other parts of the company. So it was that the division began to market a printer that would sit atop your TV, since corporate understood printers. This move helped them in the budgetary negotiations, but in so doing it moved them from high-variance entrepreneurship to the safely low-variance world of intrapreneurship.

Step 2: Selection.

Once an idea is surfaced, the innovation process has just begun. The process of "selection" involves testing the idea in the market. You've probably heard a lot about this process: The innovative firm quickly gets its idea into the market in an effort to improve by failing fast and cheap. This process improves the idea by iterating through trial and error. What you may not realize is that the real beauty of the selection process is when the market test leads to unexpected outcomes - discovery. The most innovative applications of ideas are not the anticipated applications, but rather those that materialize along they way. There is a long list of innovative companies that became raging successes after discovering their unexpected brilliance, including Airbnb, NetApp, and Apple (to name just a few).

Image result for apple lemmingsWhen it comes to discovery, entrepreneurship again has an advantage over intrapreneurship. The intrapreneur's iterative tests are seen through the lens of the parent organization. Imagine when Airbnb was first discovering itself. Had its model been tested by the folks at Hilton or Sheraton, odds are they would not have recognized the very different logic at work. Similarly, NetApp's innovative file servers would have made no sense to IBM - nor would have Apple's odd experiment with iTunes. All these experiments were based on logics that made no sense to the establishment.

Now you may be thinking: Intrapreneurs also engage in discovery. Yes, but they do so through the lens of the status quo. When it comes to discovery, the lens of the status quo creates blinders. By contrast, the entrepreneur can see things in ways that the intrapreneur cannot.

Implications for startups: If you're getting push-back because your idea is nonconsensus, that's a good thing. If the big-company people like your idea, it is time to worry. And if your plans are not working out as planned, that's a good thing; you're discovering.

Implications for big, established companies: Don't reward good innovation. Reward high-variance innovation, good or bad. Evaluate your innovation processes in terms of how they affect variation and selection. Stamping out foolishness? Then you're eliminating any chance of genius.

The Price of Genius

On this note, I am often approached by company executives who read all this and then say something along the lines of "But, Bill, I want innovation - but I want 'good' innovation."

Well, there's your problem. 

Searching for "good" innovation means you want creativity, but without any of the foolish errors. But creativity is not about eliminating error. Creativity's payoff is the occasional burst of genius - and you don't get that by eliminating error. If you were, for example, to start telling the musicians how to look, sound, and act, you'll never get the next Bob Dylan. Systems that sometimes give us the rare genius also give us a lot of foolishness along the way.

Creative systems should be judged, but not by their "average output." Instead, you should judge creative systems by their variance - their ability to produce extreme outcomes whether good or bad. As Professor James March explains, high-variance systems are the most creative. They produce lots of foolishness and, every now and then, a moment of brilliance. If you plan away the foolishness you might improve the "average" result. But planning away foolishness will also reduce variance - which means you eliminate any chance of genius. 

In short, foolishness is the price of genius.

You probably accept this idea when it comes to artistic creativity. But what about in business? Well-meaning business leaders plan away variance all the time. Sometimes that makes sense, of course. I don't want a lot of creative experimentation when we're operating an airport. But when leaders want innovation, they typically put systems in place that reduce variance and raise the average. They ask for "intelligent" innovation, for creativity without foolishness. Don't look to leaders like this for the next breakthrough innovation. They are unwilling to pay the price of genius.


Barnett, William P. and Elizabeth G. Pontikes. 2017. "The Nonconsensus Entrepreneur: Organizational Responses to Vital Events." Administrative Science Quarterly. 

March, James G. 1991. "Exploration and Exploitation in Organizational Learning." Organization Science.

Thursday, November 21, 2019

Strategic Advantage

Once when I was lecturing in Moscow, French chess grand master Joel Lautier was in the audience and he asked me about strategic advantage: “There may be many possible business strategies," he said. "How do we know which strategy is best?” I replied that Mr. Lautier himself illustrated the key to strategic advantage by his own example. The best strategy depends on you, because it is the strategy that plays to your strengths.

Let me explain: Several years earlier, Lautier had been brought onto a team advising Vladimir Kramnik as he prepared for his tournament against chess icon Garry Kasparov. The team were all wiz kids, each a chess master in his own right. No one person could fully prepare alone for the many possibilities of a match at this level. So Kramnik had advisors each assigned to work out the best solution to a particular situation that might arise. Lautier was on the team because he is one of the few to ever beat Kasparov.

Lautier’s job was key: Formulate Kramnik’s best “black” opening. Many readers will know about the most well-known chess openings. But, in fact, there are many more possible openings than the common ones, and Lautier was tasked to find a way to improve Kramnik's chances in the games where he started as “black”- second - since those games would favor Kasparov’s famous attacking ability.

Lautier formulated an unusual approach for Kramnik, one rarely used at that time. The opening was not ideal, but it might work given Kasparov’s strengths relative to Kramnik. It involved an odd series of moves quickly leading to the trading of queens, an approach known as the "Berlin" defense. The opening would leave Kasparov with his players in slightly better places on the board. But it would hurt Kasparov too, by skipping the complicated “mid game” where he had an advantage. The strategy worked. The opening shifted the edge enough for Kramnik to draw games that he would have otherwise lost, and nicely illustrates how strategic advantage results from pursuing a strategy that plays to your strengths.

Strategic Alignment

Barnett says "do what you are good at." That may sound obvious, but then why do so many companies seek to imitate "best business practice"? Here in Silicon Valley, executives come from far and wide to tour the campuses of Google, Facebook, and Apple. They come to Stanford and ask "what is the Silicon Valley's secret to success?" These efforts are premised on the idea that there exists an ideal strategy. But in fact the ideal strategy depends on the company. Some businesses are well suited to take a low-cost strategy, while others are adept at marketing products and services with greater perceived quality. Still other companies are good at a time-to-market strategy, and some thrive at technological innovation. In short, don't seek out "best business practice." Instead, follow a strategy that plays to your strengths.

Of course, doing what you are good at is only half of the strategic advantage story. The other half is your company's environment: the markets (including customers, suppliers, labor, and financial markets) as well as the political and social forces that affect your company. A company good at low-cost manufacturing will thrive only if it operates in an industry where low-cost products and services are valued by customers. The same goes for high quality producers, those who are good at time to market, and innovators. Strategic advantage happens when you do what you are good at - in an environment that rewards what you do. This happy outcome is sometimes called strategic alignment: when a company's strategy, organization, and environment are all aligned with what the company does well.

The Basis of Advantage

To align with the environment, you need to understand what is rewarded in that environment. Otherwise, you could excel at execution but still under-perform because you are playing the wrong game, like a well-run cab company losing to competition from ride-sharing services. In short, what it takes to have a strategic advantage depends on the basis of advantage.

For instance, early on the computer storage company Seagate excelled at low cost manufacturing, but had trouble turning a profit. When Steve Luczo took over as CEO in the late 1990s, he shifted the company to compete on the basis of time-to-market rather than purely on manufacturing costs. The consequence of this shift was a dramatic increase in financial performance, since Seagate's customers were willing to pay a premium to get better storage devices sooner. Luczo's transformation of Seagate changed many things, but the most important change was to align Seagate's strategy and organization to compete on the basis of advantage favored in their markets. To paraphrase leadership sage Peter Drucker, strategic advantage is not about doing things right, it is about doing the right things.

Straightforward though it seems, there is a great deal of muddled thinking when it comes to  the basis of advantage. Perhaps the biggest source of confusion comes from denying that trade offs must be made. For example, there is a trade off between cost and quality. If a company does everything possible to minimize costs, it is the extreme low-cost producer. Of course, it should also produce at the highest quality possible given its low costs, but the extreme low-cost producer makes no cost trade offs to increase quality. By definition, if it now chooses to increase quality, this will have to come at the expense of greater costs. Similarly, the extreme high-quality producer makes no quality trade offs to lower costs. It wants to minimize costs, but only if this does not come at the expense of quality.

These two strategies - the extreme low cost producer and the extreme high quality producer - can be thought of as the extreme points on the cost-quality "frontier". The cost-quality frontier illustrates the various combinations of low cost and quality that are possible. At any point along the frontier, you can improve your costs, but only if you are willing to make a trade off against quality (and vice versa). 

Now enter muddled thinking. Often you will here pundits say that "quality is free", or that making trade offs comes from the "tyranny of the or." These experts will give you examples of where a company increased quality and lowered costs at the same time. Well, this just means that the company in question was inefficient. It was inside the frontier - meaning that it was producing at a lower quality than it should have, given its costs. By improving the way it organizes, the company is able to improve both quality and costs. If it keeps improving, at some point it will reach the frontier. Once on the frontier, any further improvements in quality will require greater costs (and vice versa).

Low cost and perceived quality are just two bases of advantage. In practice, a variety of bases determine strategic advantage across the many markets that exist in the world: authenticity is the basis of advantage for ethnic restaurants; innovativeness determines strategic advantage in pharmaceuticals; responsiveness to market trends is the basis of advantage for popular music producers; and the list goes on. Strategic advantage is evaluated according to different criteria, depending on what markets you operate in.

What's more, in most markets companies face multiple bases of advantage, and different companies will compete on different combinations of criteria. Hotels are evaluated according to service quality and price, with different companies competing with many distinct combinations of service and price. And in some markets, companies must first satisfy a basic entry criterion, after which they may compete on various dimensions. Airlines, for instance, must all be seen as safe to fly at all, after which they can then balance service, route access, and cost. Because different bases of advantage often matter in a given market, business leaders must be very clear about the bases of advantage on which they are trying to compete.

Positional Advantage vs. Capability Advantage

Speaking of strategic advantage, what university would you say has the best geography department in the world?

If you answered "Harvard," you are not alone. Harvard often ranks well when people are asked this question. But Harvard does not have a geography department.

In fact, the field of geography is still reeling from Harvard's decision, decades ago, to disband its geography department, since this decision led to similar abandonments at Yale and elsewhere. To find classes in geography at Harvard today, you have to find courses that sneak into the curriculum masquerading as Earth Sciences, Environmental Studies, Anthropology, and the like.

The success of Harvard's nonexistent geography department is an example of positional advantage. An advantage is positional when it is based on who or where you are, not what you do. By contrast, a capability advantage is based on what you do. Brand reputation - essentially status - is at the heart of Harvard's advantage. But there are many other forms of positional advantage besides reputation.

One of the most common positional advantages is the incumbent scale advantage, where an existing firm ("incumbent") enjoys economies of scale - making it difficult for new rivals to enter the market. New rivals might enter even though an incumbent enjoys scale advantages, of course, but the newcomer will not immediately attain scale, putting them at a competitive disadvantage. 

The incumbent scale advantage is especially strong when the minimum efficient scale in an industry is about the same size as the market. (Minimum efficient scale is the smallest size one can be and still enjoy economies of scale.) In those cases, the incumbent firm will probably end up a monopoly.

Note that incumbent scale economies might be either supply side scale economies or demand side economies. Either way they give the incumbent a positional advantage. On the supply side, increasing scale leads to decreasing average costs - typically because of a large fixed cost such as a factory or refinery. On the demand side, scale economies exist where increasing the number of users makes a product or service more valuable, as with the so-called "network effect." But either way, scale economies give an incumbent a positional advantage over newcomers.

The first-mover advantage is also positional, because it depends only on your order of entry to a market. Research demonstrates that first-mover advantages are not common, but they do exist in some cases. For instance, a firm that owns intellectual property, such as a critical patent, may enjoy strategic advantage (at least until the patent expires). Similarly, if a firm's product or service becomes a de facto standard before others can get established, this will serve as an advantage. This was the advantage that kept Microsoft dominant in the computer industry for a number of years.

Strategy professors and investors love positional advantage. They wax metaphorical about not needing to compete, preferring for companies to find "blue oceans" and "moats" where position alone is enough. The problem here is that no positional advantage is forever. If there is money to be made, somebody else will find a way across the moat. Once that happens, you will wish you had been improving your capabilities.

By contrast, capability advantage continues to improve as your company continues to learn. A company that is good at getting products to market, or at delivering great customer service, or at last-mile logistics - or at whatever capability - can continue to reinforce its source of advantage by continuing to improve that capability. As a result, capability-based advantages remain strong when a competitor shows up. By comparison, a positional advantage may feel safe, but by its nature it depends on avoiding competition.

Ideally, your strategic advantage will result from both capabilities and position, but this need not be the case. When companies enjoy positional advantage, they continue to attract business regardless of whether their capabilities measure up. This fact often leads to the problem of the "lazy monopolist," where leadership of a dominant firm allows its capabilities to lapse (because they can).

Friday, November 15, 2019

Discovery Beats Planning, so Plan to Discover

Heard at an outdoor cafĂ© along University Avenue in Palo Alto: “The strategy was clear. You can’t start as a platform. You start as an application and then, when the user base is large enough to get a network effect, you can pivot into a platform.” Knowing nods around the table; wisdom understood by the cognoscenti.

I was hunkered down with a Super Tuscan at the last sidewalk table, eavesdropping on the ideas circulating among the start-up crowd. This one is a lesson from my course at Stanford. Not to imply that I’m the headwaters. To the contrary, I’ve waded into a stream of ideas cascading around the valley, ideas that change with each new, unexpected development. Even the subject of the debate I overheard, Facebook’s platform strategy, was discovered along the way. Originally, Facebook’s leaders saw it as a social network application. Only once Facebook grew large did the idea materialize to become a platform. So in 2007 the website’s APIs were opened to a world of developers who could independently create Facebook applications. Since then, a litany of reversals and changes have fueled debate among developers and users, as Facebook has tried to exert control over the platform. Some have criticized Facebook for this haphazard evolution. Turns out, that is how most strategies emerge: Discovery beats planning.

For more evidence, go back and look at the strategic plan from years ago at your favorite successful company. There is a good chance that the company’s winning strategy won’t appear in that old plan. Examples abound: Trader Joe’s, a boutique specialty retailer in the U.S., once made its money selling cigarettes and ammunition – a far cry from the microwavable organic meals and fancy cheeses one can get there today. Honda Motors, famously, planned to sell big motorcycles – “choppers” – in the U.S., and ended up discovering the market for small “minibikes.” The list of examples goes on, including many entrepreneurial firms that discover a strategy better than the plan their founders once pitched.

So how do we deal with the fact that discovery beats planning?

One common reaction is to pretend that the success was planned. Of course, after a discovery we naturally try to make sense of what we see working so well. And there is nothing wrong with retrospective rationalization; we do it all the time in business school “case studies” in an effort to learn. The problem is allowing retrospective rationalization to masquerade as a well-planned strategy, as in the young folks talking about Facebook (“The strategy was clear…”) Such a misunderstanding leads observers to think (wrongly) that great businesses result from a great plan.

Another bad reaction is to wax cynical, surmising that success really just comes down to luck. This conclusion denies the fact that some people are better than others at spotting the opportunities that (luckily) come along. There is much more to discovery than the flip of a coin. When plans produce unanticipated consequences, these look like failures.  If you think that leadership means waiting to get lucky, you’ll conclude from such failure that your luck has run out – a self-fulfilling prophecy.

A better reaction is to lead your organization through the process of discovery. After all, there is information in those unanticipated consequences for those who know to seek it out. Scott Cook, Intuit’s founder, coaches his people to “savor surprises” – to see deviations from plan as the fountainhead of opportunity. Seen this way, the strategic plan is just the start of the discovery process. This process happens differently at different companies - and often happens unintentionally. But research on how companies evolve has revealed two key steps in the discovery process that are worth highlighting.

Step 1: Failed Execution

It may surprise you that the discovery process often starts with failed execution. But think it through. When execution of a strategy goes smoothly, we simply enjoy the success. It often requires failure for companies and their leaders to stop and reconsider their strategy.

In fact, rather than think in terms of "strategy execution", many prefer instead to describe the process as a hypothesis test. This approach draws from the ideas of Professor James March, who conceived of organizations as "learning" much like people do. Seen this way, a company's strategy is a theory - one that develops over time as the organization and its leaders learn. Taking this approach, the execution of strategy is really just a test of the strategy's logic. Our strategy guides and coordinates, but in the process it allows us to treat the underlying logic as a hypothesis to be tested. So it is that you will hear people advise you to "fail fast and cheap." They don't really want you to fail; they want you to learn - to develop your strategy during the process of execution.

Some readers will now be thinking of the modern approach to entrepreneurship, as summarized in the work of Eric Ries in The Lean Startup or Steve Blank in The Four Steps to the Epiphany. Understanding that an entrepreneur must learn by doing, these authors nicely outline an iterative approach to creating the start-up's strategy: Starting with a "minimum viable product," using it to fail fast and cheap in a test of the "value hypothesis," and then adapting to the market's response (the "pivot"). The process of creating start-ups has been dramatically improved by this approach, since it explicitly allows the strategies of start-ups to learn from the failures so common during execution.

But adapting strategy through failure applies far beyond the world of the start-up, to established companies and even global giants. Siemens - the German technology giant - initially failed when it attempted to enter China with its medical diagnostic imaging machines. Only over time would that company succeed in China, after adapting its approach to the very different health care markets and institutions it encountered there. More generally, whenever a company attempts to do something novel, from new product launches to internationalization, initial failure can trigger the process of strategic discovery.

Step 2: Diagnosis and Learning

Learning from failure is difficult. It requires considerable effort by leadership to correctly diagnose, to interpret and make sense of what has happened. Sometimes in the process leadership may even discover possibilities they might otherwise not have imagined. But this learning process is fraught with difficulties.

To illustrate, consider the example of music subscription. After Napster was shut down in 2001, the brand was reborn in 2003 as a subscription online-music service run by Roxio’s Chris Gorog. Chris and his team quickly amassed a large catalog of songs, enabled radio streaming, established partnerships with online platforms like yahoo, built an entrepreneurial organization, and expanded internationally. As record stores became history, Apple’s iTunes, illegal music downloads, and a few subscription services like Napster offered different visions of the future. But by 2005 the verdict was in. Illegal downloads continued apace, iTunes was a clear success, and subscription services were not. As one Washington Post writer put it (in 2005), Napster’s subscription model was not a viable alternative to music ownership: “When music is good, you want to know that it can’t be taken away from you.” The final nail was Steve Jobs' declaration: "Nobody wants to rent their music." The experiment had been run, and the music ownership model beat subscription services.

But wait. With the explosive growth of services like Spotify and Apple Music, the pundits are now saying that subscription models are the winning logic in that business. What about the lesson we learned from the failures of just a few years ago?

The problem here is that a failure is a datum, not a logical argument. Data do not speak for themselves. Failures can have various causes, and so it takes logical reasoning to explain why failures happen. Perhaps the early subscription services were ahead of their time, such that limited bandwidth might have made them less attractive than they are today. Or maybe the smartphone is a necessary complement to such services. Whatever the diagnosis, logic is required to sort out why firms succeed and fail.

Unfortunately, most observers skip the logic part. It is mentally easier to jump to the “obvious” conclusion: If the business failed, the business model must be wrong. Full stop. You can easily tell when this skip happens. The person will name an example as if it were a reason. Is online grocery delivery a viable model? No: Webvan. Is internet search a viable business? No: Alta Vista. These examples are data, not logical reasoning. But it is hard to rebut those who argue by citing examples, because you look the fool trying to say that a failure somehow might have made sense. Like Gerald Grow’s cartoon, we replace reasoning with dueling examples: I shout “Napster!” you reply “Spotify!”

The result? We often “learn” without logic, and so we often walk away from great ideas. The Apple Newton failed, leading many to say that there was no market for smart handheld devices - yet now we all own them. Early attempts at remote alarm systems failed, leading many to conclude that such services could not be profitable; now they are commonplace. Even internet search, possibly the most lucrative business in history, was initially panned after a spate of failures among early movers – Lycos, Alta Vista, Excite, and others. Often firms fail. But that may not mean, logically, that we should abandon their business models entirely.

To diagnose well, we need to systematically contrast failures and successes - as is done in good academic research. Popular techniques such as A/B testing, agile development, root-cause analysis and similar approaches are designed to show us successes and failures without destroying the firm. These techniques routinely are used in Silicon Valley firms these days, and are making their way into the global business lexicon. Sometimes such techniques are very effective for learning. But keep in mind that these techniques simply provide us with data. It is up to us to explain the data, and that requires logic.

False Results

The music subscription example highlights a problem in learning known as the "false negative." The possibility of false results needs to be understood if you are to successfully lead strategy. No doubt you've heard insanity defined as "doing the same thing over and over and expecting different results." And yet we know from science that advances often come when experiments fail to replicate a result. Einstein himself, said to be the aphorism's author, often repeated experiments. After all, experiments sometimes produce false results. You don't have to be Einstein to know it is a good idea to run the test again.

Yet if you are in business, you probably live by the insanity aphorism - insisting that no test be repeated. How often have you said "But we already tried that, and look how it turned out!" Calling others insane is an effective way to shut down further experimentation (and thinking).

Fortunately for us all, the world re-runs experiments all the time, and often gets different results. Webvan failed. Now Amazon, Google, and others are delivering to your door. EachNet (and its acquirer, eBay) failed to make cash-on-delivery work in Chinese C-to-C e-commerce. Now Taobao's cash-on-delivery system is thriving. The failures of Alta Vista, Excite, Lycos, and others led many to conclude that internet search could not be a business. Now, well, you know.

You're probably already trying to explain the differences in all these examples. Slow down; the broader issue here is the problem of false results.

Sometimes experiments generate false negatives - they tell you "no" when the real answer is "yes." And sometimes experiments generate false positives, telling you "yes" when the real answer is "no." You of course know about false positives and false negatives in medicine. We worry about them a lot, which is why we often go back for a re-test when things get medically serious. But for whatever reason, we don't think about false results nearly enough in business.

For instance, I recall one of the early movers in digital medical diagnostic imaging. Their system was rapidly adopted by several hospitals, leading to a lot of excitement, including executives quitting their jobs and joining the company. Then growth abruptly ended. It turns out the early wins were a false positive. (Many more examples of false positives can be found in Geoffrey Moore's "Crossing the Chasm" books, enough to have created a consulting juggernaut.)

False negatives in business are common too, as in the examples of search, delivery, and Chinese COD - but they are often harder to spot. The problem is that false positives are self-correcting, but false negatives are not. When you get a positive result from a business experiment, typically you'll keep at it. If it turns out to have been a false result, the world will make that clear enough. But if you get a false negative, you'll be inclined to "pivot." And you'll never know that you were on to something good - unless somebody else tries it again.

Perhaps you are thinking: "Hey, in all your examples, there were some variables that changed. A good test would take into account all the variables that matter." Sure, Amazon and Google now know about some things that Webvan did not, and they have adjusted those variables accordingly and that's why their experiments are working when Webvan's did not.

Here's the problem: Often we don't know all the variables that matter. This problem is well understood in science. Good scientists know that two seemingly identical experiments can produce different results, since often there are variables operating that are unknown to the scientist at the time. In fact, even random chance can produce odd results. That's why a good scientist knows that there is a lot she does not know; so she runs the test again.

The lesson: Insane though it may seem, don't just pivot. Run the test again.

Are the Dogs Eating the Dog Food?

The ultimate aim of the discovery process is to find "product market fit," that situation where customers are clearly engaged with your product or service. When I get to know a business leader, I typically ask "do you have product-market fit?" Normally she will say "yes," and then I'll ask "how do you know?" Then the hand-waving begins, featuring a lot of talk about "value propositions" and such. I listen for the evidence of product-market fit. Are the dogs eating the dog food? If so, can we be sure about why? Or are we misreading the signal?

There are many ways of misreading a signal. For instance, just recently a software entrepreneur in Santa Clara told me, "Alibaba is a potential customer, and they want to invest!" OK, this remark raises the obvious problem that customers and investors have very different motivations. But the real problem is the executive. He's getting excited for the wrong reason. An offer to invest is not a purchase order. It is not evidence of product market fit. It is not "the signal."

What's more, an investment like this not only gets misread as the signal, it also buys the firm more time to keep doing what they are doing - even though the dogs are not eating the dog food. Investments often kill firms by cushioning their management teams, allowing them to feel like they are doing a good job even when they should be desperately reconsidering their strategy.

Ultimately, strategic discovery is about finding out what it takes to achieve product-market fit. We start with a strategy and test that theory by going to market, all the while trying to find our way to product-market fit. If all goes well, we may end up discovering a strategy much more valuable than what we could have imagined when the process began.

Friday, November 8, 2019

Dead Revolutionaries: A Call for Nominations

Russian revolutionary Leon Trotsky survived for decades, sometimes imprisoned, often in exile. Ultimately, in 1940, he was assassinated while in exile in Mexico - not by an agent of the former Czar, but by another revolutionary likely connected to Stalin.

So it often goes: The fiercest rivalry takes place not between the old guard and the new, but among those who vie to be called the "real" revolutionaries.

Revolutionaries assassinate each other in business, too.

Think Overture, the long-gone innovator of the space Google owns today.

Got a favorite dead, revolutionary firm? Click here to vote, or to nominate your own candidate.

Thursday, October 31, 2019

What is Strategy?

"I may be wrong, but at least I am not confused."

Jeff Miller, former CEO of Documentum, repeats this point whenever he has a chance. He strikes a chord. A leader, above all, must point the way. Better to be pointed the wrong way than to be left aimless. After all, clearly going the wrong way, your error will eventually become evident. Aimlessness is probably wrong too, but is harder to correct. If leadership is anything, it is about pointing the way.

But pointing the way is difficult. Organizations face conflicting demands: marketing reports on a new competitor with a dramatically different product; R&D has created a breakthrough technology, but it is behind schedule and needs more funding; legal compliance is at odds with the company's China country head, whose "entrepreneurial" actions are ramping up sales there. Leadership can seem so simple when portrayed as pointing to the top of a hill. In practice, leadership is about deciding amid sharply conflicting priorities. For that you need a strategy.

"Bill says you need a strategy." Obvious. But you would be surprised at how many companies I see that do not have direction. The problem? Let's call it strategy neglect. Meaningful strategy gives direction; you know you suffer from strategy neglect when people in your organization don't know how to resolve conflicting priorities. I'm not talking grand mission statements about changing the world, nor lengthy strategic plans packed with detail. I'm talking about strategy: the logic that explains why we might win.

And to be useful, your strategy’s logic must be specific enough to guide action. This means that a useful strategy includes a working definition of the company's goal, what it does, and how it does it - a logic that a rank-and-file employee can put into action. Maybe I finish my project a day late because our strategy is about completing work to perfection. Or maybe I cut some corners to be on time because we're about time-to-market. Whatever the strategy, it needs to be alive in the day-to-day actions of employees. Otherwise, as in so many companies, we are left confused.

Strategies Emerge

Of course, you not only want your strategy to be logical, but you want your logic to be sound. Logics can be wrong when they are based on assumptions that turn out to be wrong. So it is that often strategies change because we question, and then correct, the underlying assumptions behind our strategy. This kind of strategic change is sometimes called "emergence."

For example, today NetApp is known as a well-established player in the data services space, pulling in revenue in the billions of dollars annually and running complex hybrid cloud services for the world’s largest companies. But when it started in the 1990s, the company’s strategy targeted small firms with simple low-cost file servers. This strategy was based on the assumption that only small firms, which lack IT infrastructure, would value the simplicity of NetApp file servers. That strategy failed, but in the process leadership noticed that large companies loved their file servers – unexpectedly for the dramatic increase in data speed these servers offered. Taking advantage of this discovery, the company pivoted to target large firms – as Tom Mendoza and his team built out a direct sales force and an organization to support it. In this way, we often see winning strategies emerge as, with experience, we revise the assumptions on which they are based.

Since winning strategies need to be based on correct assumptions, all strategies are a work in progress - because the world keeps changing. Moreover, companies are also learning every day about what they are capable of, in much the same way that a person learns about her strengths by trial and error. Remarkably, research tracking companies over time shows that many of the world’s greatest organizations discovered their strategies, winning for reasons they did not understand initially.

Take, for instance, the fintech powerhouse Alipay. Today it has over half a billion users, continues to grow, and is extremely profitable. Yet the service was created originally back in 2004 to help the then-new Taobao C-to-C ecommerce platform compete with eBay. Neither Taobao nor Alipay was initially intended to be money makers. Rather, they were meant to deter eBay from growing as a competitor to Alibaba. Yet by banking the unbanked, and enabling those without other credit options to enter the ecommerce world, Alipay discovered an entirely new and hugely profitable strategy. Today, leadership at Alipay is entirely clear on their strategy - even though the logic of that strategy emerged through experience.

So it is that strategy emerges from experience. Leaders play an important role in this process, because they help their people understand what is happening to the company. As Steve Jobs put it during his commencement address at Stanford in 2005: “You can’t connect the dots looking forward; you can only connect them looking backwards.” Because strategies emerge, one of the primary responsibilities of leadership is to make sense out of why their firm wins. That "sense-making", when formalized and explicitly stated, is strategy.

Creating and Capturing Value

I've talked about winning, but business leaders often succeed at their strategy only to end up losing money. The problem is that a business can produce a valuable product or service, only to find that some other business gets to keep that value. For instance, one of the most hard-working entrepreneurs I know runs a vending machine company here in Silicon Valley, devoting endless hours to keeping the machines stocked and well functioning. But every time his revenues increase, his host clients increase his rents - the fees he pays to have his machines on good properties. So although he creates a great deal of value, this entrepreneur keeps very little of it. Winning in business requires that we both create and capture value.

Effective strategies constantly grapple with the need to both create and capture value. For example, the video entertainment industry has recently seen tremendous changes, with viewership moving from traditional television broadcasters to online and streaming services. How do we understand the various strategies emerging in this context? Why is Netflix, a streaming service, spending so much on original content creation? Why is Disney, the storied king of content creation, now moving aggressively into direct-to-consumer streaming?

The answer, in both cases, comes down to creating and capturing value. Video production studios create value when they produce content that people really want to watch, like the comedy series Seinfeld produced by Warner Brothers. Video distribution services, such as Netflix, also create value when they enable consumers to conveniently view such content. Taken together, the content producers and distribution services create and deliver entertainment - the "value" that the consumers are willing to pay for.

But who gets to keep that value? Consumers pay Netflix billions of dollars in revenue every year, but Netflix, in turn, pays billions of dollars in license fees to the studios that create much of the content that they distribute. Netflix does get to capture some of the value, but the studios that produce content also capture a great deal of that value.

The struggle to both create and capture value has led these companies to change their strategies. If Netflix can produce original content, it will reduce the amount of value it pays out to the studios; that is, it will capture more value. If Disney can stream its content directly to consumers, it will reduce the amount of value it leaves with distribution services like Netflix; it will capture more value. Companies in this industry today are following a strategic logic that includes both the production and distribution of content, in the hope that they can create and capture the most value possible.

But there is a catch: Value is created only if the costs of doing so are less than the amount consumers are willing to pay. Netflix is paying a great deal to create original content. Some pundits speculate that they may not recoup their investment. Similarly, Disney is paying a great deal to create a direct-to-consumer streaming service. Each of these companies is following a strategic logic - one built on the assumption that it can create value greater than the costs involved. Whether this assumption turns out to be correct, only time will tell. No matter how this particular example works out in the end, the lesson is clear: A winning strategy lays out the logic of how a company will both create and capture value.

What About Planning?

If strategies emerge, then what about planning? After all, If you say “strategy” to most people, they will think of the annual “strategic planning” (budget-and-goal) process at their place of work. Even though strategies emerge from experience, we must of course plan because we must create budgets and goals to guide action over the year to come. But that budget-and-goal process, in and of itself, is not strategy, since such planning can and often does take place without any guiding logic.

The best example of planning without logic is historical: The Soviet Union. Business school professors miss the Soviet Union. The nemesis of old used to provide us with a stream of cautionary tales.

Take nails, for instance. Socialist economist Alec Nove wrote of this example: In an effort to increase the production of nails, the Soviet planning authorities created production incentives based on numbers of nails produced. In response, the Soviets enjoyed the following year a plentiful supply of many many very small nails. 

To correct the problem, the authorities cleverly switched to incentives based on weight, and the producers responded by manufacturing very large nails. The travesty was parodied in this cartoon from the satirical magazine Krokodil. Ah yes, better to use the market. But the real lesson of the Soviet experiment is about planning: Unless it is guided by a strategic logic, planning doesn't work.

Corporations must and do plan, of course. Their leaders often call these plans "strategic" to give them gravitas. But typically strategic plans are just budgets and goals. Budgets and goals are important, but they are not "strategy" if by strategy we mean the logic that drives action.

For planning to be strategic, it needs to be guided by a clear logic that links the actions of people throughout the organization to the success of the firm. In this way, planning is a way to go from sense-making - "connecting the dots" - to giving direction. Planning guided by strategy builds on what we have learned about our organization's successes and failures, turning those lessons into guidance for future action.