Over the last three decades we’ve moved from maximizing resource utilization to operating demand-driven supply chains. So you can imagine my surprise when I heard a leading process manufacturer in a supply constrained environment, one that sells to large businesses, was considering returning to a fixed production schedule. The justification for the change – high demand variability and poor forecast accuracy – only furthered my disbelief.
Innovative companies are cutting supply chain complexity and accelerating responsiveness using artificial intelligence. By applying AI and machine learning against vast sets of supply chain data to unearth insights into problems and performance, enterprises are augmenting knowledge-intensive areas such as supply chain planning to be more dynamic, flexible, and efficient.
By now, it is a shared understanding that we are on the cusp of an industrial revolution led by AI, data and digitization. Industry 4.0 is a revolution that can pay off handsomely: A 2016 study by McKinsey revealed that the data-driven supply chain could gain up to 6 percent in additional revenue.
Customer demand for categories in grocery, drug and general merchandise changes constantly. Ten years ago, retail store shelves were stacked with CDs and DVDs. Supermarkets sold many cases of standard lager. Drug stores had photo processing departments. Today, subscription streaming is king, craft beer is mainstream and online photo printing services dominate.
Computerization, the Internet and automation ushered in Industry 3.0, revolutionizing the way we work. Now there’s IoT, cloud computing, 3D printing, autonomous vehicles, mobile, social and Big Data. Welcome, Industry 4.0. In the not-to-distant future supply chain planners will sit in control rooms with a real-time view of inventory at all nodes of the supply chain.