Four P's in a Pod: e-Commerce Forecasting and Planning for Supply Chain Practitioners

Four P's in a Pod: e-Commerce Forecasting and Planning for Supply Chain Practitioners

Best-in-class practices for achieving credible and sustainable forecasting performance in an e-commerce environment? Opportunities for making quantitatively-challenging processes more accessible and useful to supply chain practitioners. . For a general demand forecasting needs , it stresses adherence to a four-stage PEER process involving (1) ‘big data’ issues of data quality, outlier resistance, data exploration and predictive visualization, (2) predictive analytics suitable for automating useful forecast modeling solutions in a relational and databased F orecast D ecision S upport P latform ( FDSP ), (3) an objective approach to forecast profile accuracy measurement and (4) challenges in reconciling statistical models and forecasts to support a synchronized, I ntegrated B usiness Planning ( IBP ) process.