Forecasting with ML and deep learning allows you to justify budget allocations based on company performance, understand reasons for growth or decline, and plan for future growth. But how do we make sure we achieve these outcomes?

In this uncertain, technology-driven world, surveys conducted by the FP&A Trends Group and not only have identified three trends shaping FP&A Technology in 2022: Predictive and Prescriptive Analytics, Driver Based Planning (DBP) and Integrated Analytic Platforms.

Budgeting and planning activities within companies are often time-consuming and quickly outdated in their significance. Methods like driver-based planning or even Beyond Budgeting represent attempts to increase efficiency, but the approach remains old-fashioned. However, the developments in the field of AI/ML are now opening up completely new possibilities. In the near future, it will be possible to calculate and compare a wide variety of planning scenarios within minutes.

In my day-to-day job, I interact with many Financial Planning and Analysis (FP&A) organisations implementing predictive planning to improve their budgeting and forecasting processes. 

Today’s uncertain times mean that it is no longer good enough for organizations to have one fixed plan and forecast. Historic data by itself cannot help predict the future, nor can classical planning methods and standard variance analysis provide sufficient information to manage a business. It is time to change and adopt a fact-based mindset towards business decisions.

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