We talk a lot of talk about creating ‘fail fast’ culture. However, the goal is not failure, it is rapid learning. When you learn you can make faster, more informed decisions, that’s what allows the startup to go faster. It is not speed, it is agility. Eager corporate executives may not always appreciate this subtly. They get restless, worrying that waiting for more evidence just risks letting the competition in and missing the market window
They get restless, worrying that waiting for more evidence just risks letting the competition in and missing the market window. This impatience drives them to make an ‘all or nothing’ bets rather than wait for the outcome of the learning experiments. As a result, they invest ahead of learning, making commitments that can become serious liabilities for the Corporate Explorer down the line.
However, getting that decision wrong means wasting resources on pivots or failed projects. The secret is to progressively de-risk an investment through a series of rapid experiments. This contains the cost of innovation and links it directly to learning. Spending levels only increase as risk is reduced and confidence builds.
Here’s how it works:
- Project team identifies an important customer problem or underserved need in the market
- An Innovation Board (comprised of senior executive sponsors) chooses the most promising opportunities and approves a small amount of funding so the team can validate the problem and ideate a proposed solution
- Team identifies most important, highest risk assumptions on which solution or new business model is based
- Team runs experiments with measurable evidence thresholds to validate or invalidate the highest risk assumptions
- Team reports back to the Innovation Board with a pursue, pivot, or cancel decision, and a plan for investing in the next set of experiments
The Innovation Board makes small investments on short timescales at first and then as evidence reduces uncertainty, that commitment becomes longer and more financially significant.
Innovation Boards use a simple scoring model to evaluate progress, so that they can judge the quality of evidence an experiment generates. This helps them know that they have learned enough to know an innovation is desirable to customers, feasible to build, viable commercially, and can get adoption in the market. That helps them invest at the speed of learning.
Read more about how to invest ahead of learning here.