"We never see any good ideas,” lamented a senior executive. “People bring us ideas. But they just don’t have any . . . magic".
The problem with the company wasn’t that its employees were lacking creativity. In his Harvard Business Review article, Innosight’s Scott Anthony identified that the company suffered from a deep case of “iteration-itis” – every idea was to go through multiple rounds of iterations before it made it onto the agenda of top management. By the time the idea generators had gone through the onslaught of iterations from numerous gate-keepers, their ideas became watered down and wafer thin – acceptable to everyone, exciting to no one.
There are a few techniques a company can use to treat a case of iteration-itis. Our favorite technique is to switch innovation from academic to active – that is, encouraging idea generators to test their critical assumptions early. Instead of having idea generators get the opinions of multiple gate-keepers, they would generate data from active experimentation. This is especially critical in situations with high levels of uncertainty, for example, if the idea is a non-core (new) innovation.
The focus of this technique is to test assumptions in the idea’s early stages, the metrics are learning-based, and the data is not available or difficult to access. How, then, do you go about managing this uncertainty? Which uncertainties should you test first? What does success look like and how do you measure it? What constitutes a deal-killer? The four-step DEFT process can help you think about these questions:
The Document phase helps to detail an idea to an adequate level that allows it to be tested. The Evaluate phase examines the business plan to determine how they can be improved, prior to testing. The Focus step identifies critical uncertainties in the business plan. The final step, Test, discusses how to design experiments and get into the market to validate assumptions.
For a pipeline of “magical” ideas in your company, instead of having idea generators go through rounds of multiple iterations from dozens of gate-keepers, have them generate data from active experimentation.
If you're looking to help your organization approach innovation efforts more systematically, learn more about the Experiment sprint.