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.

How can an FP&A practitioner assess the effectiveness of financial reporting processes?  This article describes five tips that could be used in order to establish a starting point in the process.

There is no point on aimlessly analysing data in the hope that something will jump out at you.  It won’t and all that you will do is waste vast quantities of time and effort.  Like any search, there must be an objective and a plan to reach that objective.  This is where a mature approach to analytics comes in. The author reveals a mature approach to data analysis that includes 4 stages.