Foresite SPA endorses The Harvard Business School’s views on driver-based rolling forecasts which form the core of the Foresite SPA methodology.

Make rolling forecasts the primary management tool
Most CFOs want to spend more time managing the future rather than dwelling on the past. So the ability to help managers to prepare quality forecasts is fast becoming a core competence. But most finance teams have much to learn. The mistake that most of them make is assuming that forecasts are about predicting and controlling future outcomes. The purpose of forecasting is to inform decision making (to help shape future outcomes), not to predict the future. In reality, forecasting is necessary only because organizations cannot react instantly to changing events. That’s why fast reaction is more important than (even accurate) prediction—because accuracy is rarely achieved. Indeed, the only certainty about a forecast is that it will be wrong. The question is by how much. Narrowing that variation comes from learning, experience, decent information systems, and ultimately, judgment.

The more practice managers have at preparing short term forecasts, the better they will become. That’s why adaptive organizations focus less on annual budgets or long-term views and more on rolling views—usually rolling forecasts that always look twelve to eighteen months ahead. Rolling forecasts, if well prepared, form the backbone of a new and much more useful information system that connects all the pieces of the organization and gives senior management a continuous picture both of the current position and the short term outlook. In effect they are the aggregate of business as usual forecasts (extrapolations of existing trends), all the action plans in progress, and all plans in the pipeline. In other words, forecasts should be “baseline plus anticipated events,” with the effort being focused on “events.” An honest view has no bias, so managers should expect to see half of their forecasts to be on the high side of actual outcomes and half on the low side. The ideal forecast has clean data that enables managers to improve decision making. Forecasts must not be seen as commitments, otherwise bias and distortion will be inevitable—that’s why implementing rolling forecasts under the umbrella of fixed targets (usually focused on “closing the gap”) rarely works. If managers at any level interfere with the forecasting process on the basis of giving it “more stretch” or “bridging the gap,” the outcome is almost guaranteed to be a dangerous distortion of reality.