For many organisations, the Strategy Gap is a major obstacle, preventing them from truly maximizing their Strategic Planning efforts and sustainably creating value.

Join the face-to-face Toronto FP&A Board on October 17th to discuss and learn the FP&A Storytelling best practices.

We decided to devote one of our digital circles to the subject of the Power of Driver-Based Planning and Forecasting and how organisations should implement it.

FP&A Storytelling has been one of the biggest trends in FP&A over the last few years as executives and C-level leaders want to know how their company is performing, what segments are performing well or not so well, and why so.

Is planning a routine annual exercise or a flexible and dynamic FP&A process that drives value and supports decision-making under uncertainty? How to achieve the latter?

This article looks at the key concepts and definitions of both integrated and agile FP&A. Through the two case studies, we explore how to connect integrated FP&A from a finance view to deliver continuous and real-time planning through an operational and technology view.

To deal with the resulting uncertainty, FP&A teams have had to demonstrate agility and analytical rigour, as well as flexibility. The organisational disruption, impact on business performance and changing supply chain demands have required FP&A teams to respond with rapidly changing forecasts, budgets and investment plans.

In this environment of ‘unknown unknowns’, the future is becoming more and more difficult to predict. Traditional management accounting methods based on historical data alone are no longer sufficient for planning and forecasting. Scenario Planning can help us overcome this challenge. 

Budgets were invented in the Industrial Age as an efficient management tool. So why in this day and age of VUCA, most of the organisations around the world are still so hung up on traditional budgeting?

Technology is beginning to impact profoundly on forecast accuracy. We are moving now to Digital FP&A: Predictive, Prescriptive Analytics (PA) and AI/ML. There is no doubt that this will revolutionise the forecasting process.