In this short video, the Head of FP&A and M&A at Lonza, Patric Somlo, shares how his organisation transformed its planning process by using Predictive Analytics.

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?

With technology developing at breakneck speed, it is no wonder that FP&A teams around the world are beginning to capitalise on innovative modern tools. In particular, planning processes have been transformed by the implementation of Artificial Intelligence (AI), Machine Learning (ML) and Predictive Analytics.

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Budgeting and planning activities within companies are often time-consuming and quickly outdated in their significance.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.