Considering forecasting as an exercise to assess future financial performance as accurately as possible through a bottom-up approach based on actual facts, it appears necessary for an Organisation to become conscious of its own culture.

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.

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.

During the recent years, the level of detail and precision which financial modeling in the business world has pursued has been elevated. Learning Excel, a widely used and accepted computer application is one essential skill required of a strong financial modeler. But these days, the business world requires more. This article addresses those needs.

Are FP&A teams empowered to deliver strategic value across the enterprise? I partnered with FP&A thought leaders Larysa Melnychuk, and James Myers to develop the FP&A Empowerment: The Evolution of Technology & Trends survey in part to find out if this perception is a reality. More than 300 global FP&A leaders took part at the survey.This article shares the key findings and conclusions.