Innovation & Design

Take a Chance on Experimenting


Disruptive innovation can be filled with unknowns and assumptions, but it's still important. Innosight's Julie Toscano Sequeira explains how to manage the process

Disruptive innovation is often fraught with unknowns and assumptions. But that doesn't mean it has to be risky business. By using an approach that systematically attacks the most critical unknowns with tailored, low-cost experiments, innovators can "de-risk" their strategies and thereby increase their chances of success—while lowering the associated costs.

When working in high-assumption, low-knowledge environments, it is prudent to take a disruptive path to market by systematically testing assumptions and shifting the path forward as necessary. The goal is to run early experiments to gain critical pieces of information that can enable flexibility and increase the odds of success at a lower price tag.

The further from the core an idea ventures, the more critical it becomes to follow an emergent strategy. "Test and learn" is the mantra. "Invest a little and learn a lot" is the approach.

Test Your Assumptions

Not sure of where to begin? A good first step involves detailing the inherent assumptions. The key question: "What would have to be true in order to make this innovation a success?" Think expansively about the different categories of assumptions involved—consumer, solution, profit system, channel. Be willing to get down to details, but don't worry about perfection as this process will naturally involve iteration. If you get stuck, pull in others to get their perspectives.

Once you have a list of assumptions that you feel pretty good about, the second step is to prioritize. Ask three questions of each assumption:

How important is it for this assumption to be true?

How confident are we in this assumption?

How easy would it be to test this assumption?

The goal in this exercise is to identify the top two to four "killer assumptions," or the most critical assumptions to which both these statements apply: "This assumption would have to be true for success to happen" (a high-risk assumption) and "This is an assumption in which we have the least confidence" (a low-knowledge assumption).

Let the Experimentation Begin

In many ways, devising effective experiments is a matter of thinking like an entrepreneur. The goal is to come up with low-cost approaches to getting the needed information.

While experiments will clearly vary depending on the context, here are a few helpful guidelines:

As with high school chemistry lab, the best experiments isolate the variables being tested. Without such control, it will be impossible to interpret which factors led to success or failure and to adapt accordingly. For example, a large consumer packaged goods company considering a new product concept while simultaneously toying with alternative distribution channels might be tempted to test both elements at once. However, such a test might lead to confusing results—was a lower-than-expected response due to inexperience with a new channel or to lackluster consumer reaction to the product? By splitting the experiments and testing each element separately, the company would be better able to systematize their testing process and improve the solution on both dimensions.

Second, embrace scarcity. One of the biggest hurdles that large corporations encounter when innovating is actually the lack of constraints on resources (people, time, or money). Experiments should be low-cost, imperfect, and designed to get the maximum learning in the shortest time possible for the minimum investment.

A large electronics retailer used such an approach to test a new help desk. A typical corporate test-market process would have taken months, if not a year. Instead, the innovation team simply put up a folding table in one store and manned it with a knowledgeable floor salesperson. They then monitored who stopped by, at what time of day, and with what questions. For just a few hundred dollars, they were able to test the demand for the concept and tweak it to increase the odds of success before rolling it out more broadly.

Third, get into the real world. When working in large corporations, there is a natural tendency to spend a lot of time in conference rooms with data-rich spreadsheets and detailed market research reports. But there is often no substitute for interacting with customers directly. As A.G. Lafley has described, Procter & Gamble (PG) brings consumers into their offices: "We run nurseries in the baby care business, so right there in the research center every morning young mothers bring their sons and daughters, and so we have a chance to run ongoing labs, but we do it in virtually all the businesses. I just want to get our people in touch."

Step Back, Assess, and Determine Your Next Move

After running the experiment, you have one of three immediate choices: double down and continue to the next assumption; adapt the experiment and reassess the killer assumptions involved; or determine that it is time to cut your losses and fold.

All three scenarios can be equally good. Option No. 1, doubling down, is what we are all seeking as innovators in the field—a small victory in an uphill battle. Option No. 2, reassessing, indicates that learning has provided the key to a different strategy. Option No. 3, folding, in essence curbs investment costs, thereby enabling future experiments for additional ideas. Of course, folding can at times be devastating, given the amount of nurturing, time, and emotional energy that are poured into new concepts. However, knowing when to move on vs. hold on is one of the most important disciplines to maintain as an innovator.

The lesson overall? When experimenting, all information is good information. It is the information—and the speed and capital efficiency that it can deliver—that we are seeking. As such, we celebrate the failures as much as the victories, and move on to the next assumption and experiment.


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