STRATEGY IS BASED ON ASSUMPTIONS

 

Every business plan begins with a set of assumptions. It lays out a strategy that takes those assumptions as a given and proceeds to show how to achieve the company’s vision. Because the assumptions haven’t been proved to be true (they are assumptions, after all) and in fact are often erroneous, the goal of a startup’s early efforts should be to test them as quickly as possible.

What traditional business strategy excels at is helping managers identify clearly what assumptions are being made in a particular business. The first challenge for an entrepreneur is to build an organization that can test these assumptions systematically. The second challenge, as in all entrepreneurial situations, is to perform that rigorous testing without losing sight of the company’s overall vision.

Many assumptions in a typical business plan are unexceptional. These are well-established facts drawn from past industry experience or straightforward deductions. In Facebook’s case, it was clear that advertisers would pay for customers’ attention. Hidden among these mundane details are a handful of assumptions that require more courage to state—in the present tense—with a straight face: we assume that customers have a significant desire to use a product like ours, or we assume that supermarkets will carry our product. Acting as if these assumptions are true is a classic entrepreneur superpower. They are called leaps of faith precisely because the success of the entire venture rests on them. If they are true, tremendous opportunity awaits. If they are false, the startup risks total failure.

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Most leaps of faith take the form of an argument by analogy. For example, one business plan I remember argued as follows: “Just as the development of progressive image loading allowed the widespread use of the World Wide Web over dial-up, so too our progressive rendering technology will allow our product to run on low-end personal computers.” You probably have no idea what progressive image loading or rendering is, and it doesn’t much matter. But you know the argument (perhaps you’ve even used it):

Previous technology X was used to win market Y because of attribute Z. We have a new technology X2 that will enable us to win market Y2 because we too have attribute Z.

 

The problem with analogies like this is that they obscure the true leap of faith. That is their goal: to make the business seem less risky. They are used to persuade investors, employees, or partners to sign on. Most entrepreneurs would cringe to see their leap of faith written this way:

Large numbers of people already wanted access to the World Wide Web. They knew what it was, they could afford it, but they could not get access to it because the time it took to load images was too long. When progressive image loading was introduced, it allowed people to get onto the World Wide Web and tell their friends about it. Thus, company X won market Y.

Similarly, there is already a large number of potential customers who want access to our product right now. They know they want it, they can afford it, but they cannot access it because the rendering is too slow. When we debut our product with progressive rendering technology, they will flock to our software and tell their friends, and we will win market Y2.

 

There are several things to notice in this revised statement. First, it’s important to identify the facts clearly. Is it really true that progressive image loading caused the adoption of the World Wide Web, or was this just one factor among many? More important, is it really true that there are large numbers of potential customers out there who want our solution right now? The earlier analogy was designed to convince stakeholders that a reasonable first step is to build the new startup’s technology and see if customers will use it. The restated approach should make clear that what is needed is to do some empirical testing first: let’s make sure that there really are hungry customers out there eager to embrace our new technology.

Analogs and Antilogs

 

There is nothing intrinsically wrong with basing strategy on comparisons to other companies and industries. In fact, that approach can help you discover assumptions that are not really leaps of faith. For example, the venture capitalist Randy Komisar, whose book Getting to Plan B discussed the concept of leaps of faith in great detail, uses a framework of “analogs” and “antilogs” to plot strategy.

He explains the analog-antilog concept by using the iPod as an example. “If you were looking for analogs, you would have to look at the Walkman,” he says. “It solved a critical question that Steve Jobs never had to ask himself: Will people listen to music in a public place using earphones? We think of that as a nonsense question today, but it is fundamental. When Sony asked the question, they did not have the answer. Steve Jobs had [the answer] in the analog [version]” Sony’s Walkman was the analog. Jobs then had to face the fact that although people were willing to download music, they were not willing to pay for it. “Napster was an antilog. That antilog had to lead him to address his business in a particular way,” Komisar says. “Out of these analogs and antilogs come a series of unique, unanswered questions. Those are leaps of faith that I, as an entrepreneur, am taking if I go through with this business venture. They are going to make or break my business. In the iPod business, one of those leaps of faith was that people would pay for music.” Of course that leap of faith turned out to be correct.4

Beyond “The Right Place at the Right Time”

 

There are any number of famous entrepreneurs who made millions because they seemed to be in the right place at the right time. However, for every successful entrepreneur who was in the right place in the right time, there are many more who were there, too, in that right place at the right time but still managed to fail. Henry Ford was joined by nearly five hundred other entrepreneurs in the early twentieth century. Imagine being an automobile entrepreneur, trained in state-of-the-art engineering, on the ground floor of one of the biggest market opportunities in history. Yet the vast majority managed to make no money at all.5 We saw the same phenomenon with Facebook, which faced early competition from other college-based social networks whose head start proved irrelevant.

What differentiates the success stories from the failures is that the successful entrepreneurs had the foresight, the ability, and the tools to discover which parts of their plans were working brilliantly and which were misguided, and adapt their strategies accordingly.

Value and Growth

 

As we saw in the Facebook story, two leaps of faith stand above all others: the value creation hypothesis and the growth hypothesis. The first step in understanding a new product or service is to figure out if it is fundamentally value-creating or value-destroying. I use the language of economics in referring to value rather than profit, because entrepreneurs include people who start not-for-profit social ventures, those in public sector startups, and internal change agents who do not judge their success by profit alone. Even more confusing, there are many organizations that are wildly profitable in the short term but ultimately value-destroying, such as the organizers of Ponzi schemes, and fraudulent or misguided companies (e.g., Enron and Lehman Brothers).

A similar thing is true for growth. As with value, it’s essential that entrepreneurs understand the reasons behind a startup’s growth. There are many value-destroying kinds of growth that should be avoided. An example would be a business that grows through continuous fund-raising from investors and lots of paid advertising but does not develop a value-creating product.

Such businesses are engaged in what I call success theater, using the appearance of growth to make it seem that they are successful. One of the goals of innovation accounting, which is discussed in depth in Chapter 7, is to help differentiate these false startups from true innovators. Traditional accounting judges new ventures by the same standards it uses for established companies, but these indications are not reliable predictors of a startup’s future prospects. Consider companies such as Amazon.com that racked up huge losses on their way to breakthrough success.

Like its traditional counterpart, innovation accounting requires that a startup have and maintain a quantitative financial model that can be used to evaluate progress rigorously. However, in a startup’s earliest days, there is not enough data to make an informed guess about what this model might look like. A startup’s earliest strategic plans are likely to be hunch- or intuition-guided, and that is a good thing. To translate those instincts into data, entrepreneurs must, in Steve Blank’s famous phrase, “get out of the building” and start learning.