Not that long ago, supply chain visibility tended to be an internally-focused process, one that allowed manufacturers to know when exactly they could expect to receive inbound goods and materials from their suppliers so they could plan and adjust their production schedules. While that's still an important capability for companies to have, the Age of the Consumer has shifted the focus of visibility initiatives in the direction of the customers.
Manufacturers still need a complete view of their supply chain as it exists now, of course, but just as crucial is being able to know where their supply chain needs to be. And that's where predictive analytics come into play.
"Predictive analytics are changing consumer buying behavior," notes Bill Abernathy, head of North America product supply logistics excellence, Bayer CropScience, "and supply chain professionals need to be able to satisfy the increasing demands of consumers who expect products delivered exactly when promised." Abernathy was one of a panel of supply chain experts speaking at ProMat 2015 in Chicago, in conjuction with the release of a new industry report compiled by MHI, a supply chain trade association, and global consulting firm Deloitte.
Customer demands for lower delivered costs and pricing are seen as the top challenge facing supply chains today, the report indicates. However, by applying advanced statistical analysis of structured and unstructured data sources (i.e., Big Data) to identify patterns and predict future events, manufacturers using predictive analytics gain the ability to make better decisions that anticipate what their customers are asking for now, and will be asking for in the future, according to a new industry report compiled
"The speed at which supply chain innovation is being adopted—coupled with rising consumer expectations for anytime, anywhere service—is stressing traditional supply chains to near-breaking points," says George Prest, CEO of MHI.