Traditional FP&A systems are typically focused on one aspect of the management process.  For example, setting a budget, collecting a forecast, or delivering results in the form of a report pack.

Over the past 20 years, there have been concerted efforts to combine these processes into a single system – after all, what’s the point of a budget if you can’t report against it or collect a forecast to see if year-end goals are going to be achieved?

It is unrealistic to link every activity. In some cases, you may only be able to present the work that has been done with no obvious mathematical link to the outcome or the performance measure it supports. However, there is still value in presenting a goal and the supporting work being done along with its cost, so at least management can make an informed judgment as to whether they are linked.

There are many terms connected with FP&A, such as “unstructured analysis,” “predictive analytics,” and “machine learning". Often very little detail on how they can be used in everyday life. Sure, there is an odd example such as how the sales of one product in a supermarket are related to another based on their location. But what do these technologies actually do, and how can they help management in today’s fast-moving, complex business environment?

The volume of data is so large and complex that forecasts are often unpredictable: the world is changing faster than managers can anticipate. Managers can no longer rely on traditional monthly reporting of internally generated data to navigate the future. This is where iFP&A comes in.