The metrics we have been discussing over the past couple of weeks were designed to be either predictive or to measure historical effectiveness of investments in innovation. Today we look at tracking a set of numbers that should help us improve the ability of the organization to predict the financial impact of individual initiatives. The constant and consistent degradation of forecast revenue and margin as a new concept works its way through the development cycle and into market is a common problem.
You know how this works. The $100 million idea becomes a $75 million concept that turns into a $50 million product just prior to launch. We then end up with $25 million in first year revenues and that is deemed insufficient to warrant further investment and the product gets pulled from the market. This degradation is not just a function of a better understanding of the market opportunity. The financial forecasts should become more accurate as we learn more, not just smaller.
It is not surprising that our forecasts prove to be wrong when we are estimating financials at the early stages of development. We are dealing with assumptions built upon assumptions about events that will happen months or years in the future. If the idea is truly innovative then there are no benchmarks or analogs to use as comparisons. That makes the job even harder. What is surprising is that we are almost always wrong on the upside. The bias to overestimate financial results is pervasive and persistent.
We can tackle this problem by tracking risk-adjusted forecasts at each stage of development and comparing them to actual results in market. Combine this disciplined measurement system with a process of post-launch review that forces the team to identify the sources of variance in the original forecast. This will create a learning organization that gets better at predicting the future.