Budgeting and planning activities within companies are often time-consuming and quickly outdated in their significance.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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Watch the full recording of the FP&A Trends Webinar to look at the examples of Predictive Analytics in FP&A and understand how we can implement the process for the benefit of the whole organisation.
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?
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