Predictive analytics for FMCG business strategies and tactics

In today’s increasingly globalized and liberalized markets, traditional values like stability and predictability have gradually been phased out. Food and agricultural markets have always been affected by unpredictable weather. Due to global interdependency of food supply chains, food raw material prices have become as volatile as ever. In October 2017, to mention but one example, the EU butter market price dropped 30% within one month.

In companies, the new normal of price volatility should not lead to resignation. Volatility should rather be seen as opportunity—the opportunity to outperform competition by better predictive analytics of future raw material market prices. Erik Elgersma details how a global food company uses multiple sources of monthly actualized data and smart algorithms to predict future commodity prices, describing the journey of discovery to develop a data-based dairy product forecasting model that predicts prices up to nine months forward and the steps taken to implement the model’s outputs in the company’s commercial policies.