To close out National Entrepreneurship Month, we're celebrating with an excerpt from our 2017 book Innovating: A Doer's Manifesto for Starting from a Hunch, Prototyping Problems, Scaling Up, and Learning to Be Productively Wrong by Luis Perez-Brava.
An aspiring entrepreneur or innovator lives at N = 1. The merits of her or his innovation or organization will be measured relative to adoption, not by comparison with other innovators or entrepreneurs. The one problem that gives her or him purpose has to be solved with the resources at hand and at scale—it all needs to work. It does not really matter whether the way the problem is ultimately solved falls at the center of some graphical distribution of entrepreneurial performance or at the graph’s tail end.
The statistics pertaining to who entrepreneurs are or how they perform do not really apply. That is a limitation of statistics as the chosen method, not a problem with the underlying research. The keywords and concepts used to map entrepreneurial ideas are indexed by the final outcome—a successful startup, a product, an innovation, an enterprise, or more generally the establishment of any kind of organization—not by the initial premise, knowledge, and resources of the entrepreneurs studied.
Keywords and highly specialized concepts such as need, product, distribution, value chain, users, lead users, competitive forces, value creation, and value capture do not have meanings set in stone. At the beginning of an innovator’s inquiry, they are largely undefined and ambiguous; they acquire their precise meanings and their analytical strength only over time through the inquiry of the innovator, from the organization that emerges, and in the context of the problem that organization ultimately solves. It’s like thermodynamics: We don’t need to understand the science to enjoy an iced beverage, but if we ever need to maintain temperature constant for a brief while, the knowledge that temperature remains constant during the transition from liquid to solid may be critical.
It is easy for aspiring entrepreneurs to characterize their ideas using their best understanding of those concepts in the abstract. It is more difficult for them to realize that whatever they end up with may walk and quack like a startup but not yet be a startup. The business concept they may produce re-mains a good aspirational destination to guide their inquiry, but that’s all. I encounter this time and again in class: Incipient entrepreneurs confuse their initial guess of a destination with an actual plan of action.
Unfortunately, it’s easy to fall in love with the craft that goes into articulating a concept using precise technical management terms while losing sight of the job ahead. It’s the same as burying yourself in technical jargon from whatever field you’ve been working in. Both are excellent examples of over-engineering—something every engineer is strongly encouraged to avoid.
This is not a shortcoming of the literature of management or that of product design. It is a sign that other fields of inquiry—particularly those concerned with engineering, with high technology, with science, with tinkering, and more generally with the synthesis of new ideas—have yet to offer viable strategies for you to engage in entrepreneurship and innovation that are compatible with that world view. In a way, entrepreneurship and innovation emerged first as a scientific and management field, but they still lack an experimental and engineering footing. Chemistry went through this same process before chemical engineering emerged. A symptom of this lack is that we see more people concerned with idea selection than we see people con-cerned with actually producing innovations.
The real impact of this shortcoming is that more and more aspiring entrepreneurs and innovators focus on new consumer products and on leveraging reasonably commoditized technologies (e.g., the Web and apps). Mean-while, fewer pay attention to opportunities in more complex systems and new technologies or use either to conceive entirely new categories of activity. They also fail to address meaningfully how to scale up their ideas until they become viable business concepts to which they could then apply what they have learned (or can learn) about management and entrepreneurship.
This situation persists because the literature and the lessons aspiring entrepreneurs and innovators are applying are intrinsically analytical and statis-tical and so are most conducive to identifying arbitrage opportunities in well-outlined industries centered on well-identified markets or users. The “toolbox” is biased toward the analysis of what already exists. If an aspiring entrepreneur wants to use the same tools to conceive a new market, to discover an actual real-world problem, or to untangle the complexity of an industry to reveal new opportunities, he or she may discover that the tools demand a significant dose of creativity just to overcome that “bias.” That’s creativity that is not directly applied to innovating but to make recipes work for something other than what they were intended. We might as well equip aspiring entrepreneurs with broader knowledge about producing innovations so they can channel that same creativity more effectively.
Again, an aspiring entrepreneur or innovator lives at N=1, and where he or she lands in a distribution of innovators is immaterial. That isn’t the objective. What an aspiring entrepreneur or innovator needs to do is synthesize one robust idea—a space of opportunity—and make that work.