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The Big Data revolution is enabling pioneers such as Amazon, UPS, Dell, and Wal-Mart to gain unprecedented mastery over their supply chains. These companies are gaining greater visibility into inventory levels, order fulfillment rates, material and product delivery, and much more. As they use predictive data analytics to match supply with demand, they are also leveraging new strengths in sales and operations planning to optimize their sales channel strategies. Beyond these improvements, predictive data analytics can inform supply chain strategy and competitive priorities, and support the creation of new business ventures. Despite these powerful strategic opportunities, many companies have yet to fully leverage Big Data in their supply chain operations. Some don't know where to start; others are engaging in fragmented utilization, rather than a systematic and coordinated effort. The results are isolated benefits, inadequate insight and competitiveness, and unnecessary inefficiencies.
This reference presents a systematic five-step framework for using Big Data in supply chains. You'll learn best practices for segmenting and analyzing customers, defining competitive priorities for each segment, aligning functions behind strategy, dissolving organizational boundaries to more effectively sense demand and make decisions, and choose the right metrics. Using these techniques, you can overcome the widespread obstacles to making the most of Big Data in your supply chain - and gain powerful competitive advantage from the data you're already generating.
