There is evidence that FP&A interest is growing fast. Each and every day, CFOs feel the pressure building on the finance function to contribute more to business success. Within the CFO’s organization, the responsibility for tracking, assessing and reporting corporate performance normally falls to the Financial Planning and Analysis (FP&A) group.

As most forecasting methods require data, a forecaster analyzes the availability of data from both external and internal sources. The availability of external data is improving rapidly. With the explosion of Internet websites, potential sources of valuable data are becoming limitless. With unstructured data, the need for data mining tools has become a necessity for exploring potential sources of data for consumer analyses and predictive modelling purposes.

In an uncertain and fast-changing world, line managers need to be made aware of the uncertainties and risk inherent in the financial forecasts provided to them. Uncertainty is difficult to manage but uncertainties can be converted into known risk as forecasting capabilities and data management improve.

Although it is becoming commonplace to refer to financial planning and analysis as FP&A, this is actually an American term and one that is still not widely used outside of the US. It is true that around the world, FP&A goes by many names.

Planners and managers in supply chain organizations are accustomed to using the Mean Absolute Percentage Error (MAPE) as their best (and sometimes only) answer to measuring forecast accuracy. It is so ubiquitous that it is hardly questioned.

Future coordination is a brainer - not a no-brainer. Combining the Now and the Future requires a well-prepared FP&A team. AI as Robotic Process Automation (RPA) can support with the “no-brainers”. Looking ahead requires diligence and thinking time, which RPA can provide space for. Also, computer algorithms prescribe to keep exploring for future gains. This includes looking to the Arts and the Artificial Intelligence developments.