Improving decision-making by applying advanced analytics (including machine-learning techniques) to analyze second-, third-, and even fourth-order implications of potential responses to disruption.Sensing upcoming shocks earlier and deeper across the supply chain by applying digital technologies and the Internet of Things (IoT).Extending the ends in end-to-end planning by interconnecting historically isolated functions, such as supply-response planning and logistics execution, as well as upstream and downstream channel partners.
More recently, some companies with leading-edge supply chains have started to experiment in creating “supply-chain nerve centers”-digital, end-to-end control towers that span functional silos. While today’s control towers can significantly improve supply-chain performance, especially for the short term, they have limitations in their functional scope, ability to sense upcoming shocks, and capacity to compute globally optimal responses. That’s despite the fact that many organizations now operate a version of the supply-chain control tower. The production team therefore reallocated capacity to other products-but never communicated the decision and rationale back to the planning and sales teams.įor many companies, the current state of their supply chain means situations like this one, while completely avoidable, remain all too common. Upon digging deeper, the planning team discovers that the logistics manager had asked manufacturing to stop producing the item two weeks previously, citing constraints in storage and transportation even though adequate manufacturing capacity was available.
This article was a collaborative effort by Jaafar Beydoun, Elise Cruel, Scott McArthur, Ali Sankur, and Ketan Shah, reflecting views of McKinsey’s Operations Practice.
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