The benefits of measuring seasonality of accuracy are that users can plan high/low scenarios for each prediction based on the season-specific range of possibilities.  Departments can adjust how much capacity, safety stock, or cash reserves are needed based on their own worst case.  And it's easier to determine missing factors for model improvement when you focus on adding predictors to the high noise areas of the model.

Traditional FP&A systems are typically focused on one aspect of the management process.  For example, setting a budget, collecting a forecast, or delivering results in the form of a report pack.

Over the past 20 years, there have been concerted efforts to combine these processes into a single system – after all, what’s the point of a budget if you can’t report against it or collect a forecast to see if year-end goals are going to be achieved?

The main criticism of the traditional budget is that it does not react to what is actually happening in the business during the year. But a Rolling Forecast solves that problem, helping companies to continuously plan (forecast) over a set time horizon.

Cultural change on FP&A is inevitable. As the world evolves, our cultural norms on business evolve too. The best way is to catch up with the speed of this daily evolving change is through scientific thinking. Now for our profession, data is the lowest meaningful element, such as an atom in a living organism. The advantage will favour the teams who will understand that indisputable fact and, we will witness the process closely in the future.