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.
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.
Undoubtedly, “blockchain” is one of the key technology buzzwords of 2017. While there is still considerable hype around this topic, we’re starting to see real projects using blockchain, and real value emerging in certain markets. In this blog, I’ll look at several recent examples that highlight the drive for innovation behind blockchain’s adoption—but first, let’s cover some definitions.
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