Managing Uncertainty Through Experiment-Based Validation

Abstract

Two types of mistakes can often be observed in strategy design processes. The first is, executives believing that they know their customers better than customers do know themselves. This leads to offerings being developed that nobody wants, or nobody is willing to pay for. The second big mistake often observed, on the opposite end of the scale, is decision takers only being willing to decide if they are 100% convinced that change will be successful. A key feature of design thinking for strategy to address these mistakes is experiment based validation with real customers. During designing the detailed business model, choices are made based on sound assumptions. Although strategy designers believe in the assumptions they make, that does not necessarily mean that these assumptions are true. Assumptions must be validated. To do so validation experiments are designed. They primarily focus on trying to invalidate the made assumptions rather than confirm the already known, in line with the credo fail fast, to succeed faster. Experiments are prioritized based on their probability to fail and significance for the validity of the prototyped business models. The outcome of the validation phase is one or more business model prototypes that are desirable, feasible, and economically viable.

Our success at Amazon is a function of how many experiments we do per year, per month, per week, per day—Jeff Bezos