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.