There’s an old business adage that says, “You can’t manage what you don’t measure.” Updating that aphorism for the supply chains of the 2020s, it might read, “You can’t improve what you don’t measure.”

Metrics have long been crucial to many aspects of supply chain management. But there’s reason to believe their use has become more widespread in recent years, migrating from strategy sessions at the upper echelons of large corporations to operational decision-making in supply chain organizations large and small.

As supply chain metrics evolve, they are becoming more sophisticated by recognizing the interplay among multiple metrics and using that to drive not only strategy, but day-to-day operations as well. The tradeoffs among general warehouse statistics — such as warehouse capacity usage, order-picking accuracy, and on-time delivery percentages —with labor productivity numbers are also increasingly receiving recognition. 

For example, warehouse managers might want to examine how an increase in capacity usage affects the time it takes for pickers to complete orders. That’s similar to the experience many people have in their cluttered garages. The more you have crammed in there, the less likely you are to know where any given item resides. And even if you do know, the longer it will take for you to retrieve it when you need it.

“In general, once you start to get above about 80% of facility spatialization, you start to see a negative trend in labor efficiency,” explains John Reichert, senior director for SCE Solutions at Tecsys. That’s a good thing to know if you’re a warehouse manager.

Tecsys, a global provider of supply chain solutions, has noticed what it calls the democratization of supply chain metrics. That means these performance measures are increasingly being used lower down in corporate hierarchies. Managers and supervisors are interested in knowing how their facilities and teams are performing — against their own expectations, against industry benchmarks and against former versions of themselves.

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