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?

Many companies measure their progress against annual objectives through profit and loss (P&L) reporting and a business performance measurement (BPM) tool. In many cases, this tool is a scorecard summarising the key P&L and balance sheet numbers. Is this enough?

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.

When your financial planning and analysis (FP&A) becomes data-driven using automation and an intuitive platform with the right tools, then there's a fundamental shift. The data flows freely, it's trustworthy, and it starts to work for you. In fact, it can lead to a transformation, especially with decision-making around your organisation's finances and business strategy. But how can you reach this point? 

Data today is being created and consumed at an unprecedented scale. Data science is progressing even faster, further speeding up the rate of data creation and consumption. The companies that are the first to adopt the best practices will gain a significant advantage. The rest might just perish. 

One of the most important aspects of the FP&A role is to be able to provide insights by analysing the P&L. On the surface, P&Ls measure the profitability of the whole business and a lot of times FP&A professionals will look at P&Ls for the overall health of the organisation.