Given this unprecedented level of volatility levied upon supply chains, KPMG established a set of machine learning algorithms to help gain insight into the new behaviors that companies are taking to adjust to the new norm.
Fueling these algorithms is 14 years of data representing nearly 30 variables and key performance indicators (KPIs) that characterize end-to-end performance of U.S. supply chains. These are variables that describe service level, cost, working capital, and labor performance.
The resulting output of this advanced analytics initiative is the Supply Chain Stability Index.ii Stability is defined as the ability for a supply chain to achieve key performance targets on a consistent basis. It measures how well a supply chain deals with the ups and downs of market volatility. In the figure shown, the less erratic the line, the more stable the supply chain.
The index not only visualizes stability, but it also quantifies it by providing data- driven insights that substantiate the evolving behavior of supply chains. In this report, we share these insights, which include:
The root of all stress. Logistics is the predominant cause of stress in the supply chain, accounting for 71 percent of variability, followed by Capacity (19 percent) and Supply (10 percent).
The driver in the driver’s seat. Freight cost has become a top driver of customer service level, increasing its strength to affect order fill rate by more than 100 percent.
People make the difference. Availability of skilled logistics and manufacturing professionals is a critical enabler of stability, driven by the need to mitigate supply constraints and adapt to volatile consumer demands.
ii KPMG Supply Chain Stability Index, in association with ASCM. All percentage references in this report are derived from this source unless otherwise noted.