A recent study conducted by network and cloud-based supply chain management company E2open reveals that the use of artificial intelligence and real-time data during the pandemic cut supply chain forecast error by 32%.
E2open’s annual Forecasting and Inventory Benchmark Study captured the state of supply chain performance during this unparalleled timeframe, offering a fact-based analysis of just how much business has been impacted.
The study found that the pandemic made business structurally harder than ever, with service levels (i.e., a supplier’s ability to fulfill demand) dropping to an all-time low of 83% during the onset of the pandemic and stabilizing to a new normal of 86% in June 2020. Ironically, it is also during this time that demand for goods increased, creating vast unrealized revenue opportunities for businesses that could not keep up with demand.
These results indicate that the new normal going into 2021 is a business environment where it is now harder than ever to forecast, and 36% of volume is exposed to the most costly and disruptive error — 33% higher than before the pandemic.
As business became structurally harder to forecast in the face of strong and unpredictable demand, businesses that used artificial intelligence and real-time data were able to successfully cut supply chain forecast error by 32%. This is important because every business decision, and every win or loss, starts with a prediction of what customers will buy.
In a world of globalized just-in-time manufacturing, these are the types of ripple effects we can expect to experience during future disruptions. Understanding what happened during the pandemic helps leaders prepare for other large-scale disruptions in the future.
E2open conducted a study, directly from its platform, of over $200 billion of fast-moving consumer goods from some of the world’s largest manufacturers to measure supply chain forecasting performance before, during, and after the height of the pandemic.
Read the full report by E2open.
