The fourth meeting of the Frankfurt FP&A Board meeting will take place on Wednesday, 9th May 2018. The Board will interactively discuss Why Driver-Based Planning (DBP) Matters for Modern FP&A. 

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.

FP&A does not work in the finance silo of providing backward looking analysis of what has happened. They arm themselves and their operational and departmental leaders with the “why” of the performances and develop insights on trends. In the leading state of the FP&A Business Partnering Maturity model, FP&A is a credible partner that the business leaders can rely on when developing a sound strategy.

The statistics reveal that 60%-90% of strategy implementations fail and only 14% of executives are satisfied with the execution of a strategy. Why do companies systematically fail to set meaningful and achievable targets that can help close the strategy gap? What should be the role of the FP&A in Strategic Planning?

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.