How are our recently launched innovations performing in market?
Innovation portfolio reviews are exercises in uncertainty. We spend hours discussing technical feasibility, revenue forecasts, launch date projections, estimated costs to complete, and customer uptake rates. In most cases, the only number that is certain is how much we have already spent on a particular initiative – and we are trained to ignore this information as irrelevant to the decisions before us. So we are left to do our work based on estimates and projections.
To set the proper context, my suggestion is to begin each portfolio review session with a look at the in-market performance of an innovation initiative that has launched within the past year. Ask the innovation initiative leader, the product manager, and others responsible for the program to present a case study that includes prelaunch projections versus actual performance in-market with a thorough analysis of what went according to plan and where the team’s estimates were off.
This presentation serves two purposes. First, it should inject some humility into the innovation portfolio review and put the flurry of numbers in their proper light. Too often, portfolio analysis is presented as a set of facts that executives should be able to crunch through an algorithm to make trade-off decisions. The role of the portfolio review committee is to get behind the numbers, challenge the assumptions underlying the forecasts, and apply sound management judgment to the portfolio management process.
The second benefit of this exercise is that it teaches us to be better innovators. The path to in-market success is filled with obstacles. Making the product work is just the beginning. Learning from experience and exposing these lessons to the executives on the portfolio review committee can have a powerful affect. Taking a good hard look in the rearview mirror at launches past and the causes behind the variances will enable improvements in the future.
We all love certainty, but there is precious little of it when it comes to predicting innovation success.