Additional data signals, such as downstream POS and data from syndicated scanners, boost statistical capabilities. Causal variables – sales promotions, pricing, epidemiological data, Google trends, and local or regional economic data – increase forecast accuracy. Data scientists work alongside demand planners, helping them extract more insight and therefore more decision-making value from predictive analytics models. If the answer is yes, then it’s time to talk to SAS about evolving your forecasting maturity – at your own pace! Make a friend of uncertainty with agile