Mature data analytics are a key performance driver in strategic logistics operations. Many supply chain organizations employ data analytics in areas such as spend analysis, demand forecasting, inventory optimization, transportation optimization, supplier performance tracking, and cost modeling. When used properly, analytics can help organizations synthesize information in real time from disparate sources to glean insights, make predictions, and even offer courses of action. However, analytics is a highly data-dependent process that requires systems to aggregate vast quantities of internal and external data and analysts with powerful tools to make sense of the results. Read this performance driver from APQC’s Blueprint for Success: Logistics.