At the third meeting of the AI/ML FP&A Committee, Xena Ugrinsky, Principal and Founder at GenreX, talked about the future of FP&A and some ways of incorporating AI into the financial forecasting process. Also, Xena provided an example explaining how Stanley Black & Decker improved financial forecasting by 60%.

When I first came across the term driver based planning and forecasting I was confused. As an ex-investment banker having joined a Finance team the concept of drivers when talking about a forecast or plan was simply assumptions. Why was it not called just that? Assumptions! Investment bankers have been building models with assumptions ever since the first model was built and a corporate transaction was negotiated.

The strength of those working in FP&A often comes when they worked in different industries or with BU’s from different countries. They learned a little bit more about the impact management can have on the numbers under different circumstances. To develop a long-range forecast, financials need to look beyond current events and steer away from business plans based on extrapolation.

Sometimes, what you forecast needs to change dramatically, due to e.g. market disruption or internal changes. You also might not monitor every business the same way, because each might be in different development stage or ´situation´. By looking at the company itself, but also possible (management) crises, you can determine what the focus of the forecast should be. 

Forecasting new product launches are a tricky business with plenty of emotional baggage. They are also often, inevitably, wrong. This blog argues that when commercial finance or FP&A professionals are involved they should focus equally on model flexibly as well as the outcome.

Being critical of one’s own work, is even more important for the financial doing the forecast. A forecaster will undoubtedly have his or her bias and blind spots. However, some can be avoided by looking at the forecast itself, and some by looking at person doing the forecast. The aim here is to create deeper awareness of ‘forecasting’ by presenting some structural elements.