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.

Michael gives an insightful presentation on FP&A Scenario Planning: Forecasting in the Uncertainty.

Corporate Performance Management (CPM) has long consisted in breaking the company’s strategy down into operational objectives and indicators, measuring the achievement of these objectives against operational entities' budget or forecast and take action on that basis. This approach was effective in a stable business environment, with slow and controlled changes.

The New Normal means that planning is no longer an extrapolation of the past. Similarly, business drivers that worked last year may no longer be relevant for the future. The reality is that organizations face multiple possible futures. Each one can be triggered by a crisis or an unforeseen event that will require the company to adjust or even change course.

So how should FP&A adapt to this New Normal?

There has never been greater uncertainty and a faster pace of change than over the past months.

And yet, at a time that requires speed and agility, and in a function that needs these qualities more than others, we cleave to our traditional management accounting methods and adhere to our longstanding processes.

The result is this paper that covers the elements crucial for any organisation approaching AI or ML for the first time including challenges, methods and key success factors.