Weathering the Storm Part 12: Data Analytics & AI: Machine Learning

  |  June 4, 2020

two people looking over data

In this post on Data Analytics & AI, we introduce the use of machine learning (ML) in forecasting.

Traditionally, forecasting techniques like linear regression, moving average and trends have been used to understand and predict business performance using limited sets of (primarily) internal business metrics which are often based on lagging indicators. However, today’s climate of economic uncertainty creates an urgency for organizations to create greater precision around forecasting and model decisions to better predict business performance.

Machine learning algorithms provide a means to better identify the unknowns that can impact results. Using adequately sized datasets to “train” ML algorithms, previously unidentified, complex patterns in the data can be identified. For example, machine learning applied in an FP&A context can analyze weather, macro-economic indicators and historical sales data to quickly discern their impact on sales. This information can then be used to help finance create more precise and continuous forecasts. Simply put, this provides leaders with better business insights.