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Big Data Prevents Accidents in the Distribution Center

In just one year, Cummins Rocky Mountain’s lost-time injuries decreased by 88 percent, lost work days fell by 97 percent, and property damage cases dropped by 22 percent.

(Boonton, NJ, March 6, 2014) — Before applying a data-mining technique known as predictive analysis to its operations, engine distributor Cummins Rocky Mountain struggled to prevent accidents at its Denver distribution center.

The company would manage to cut injuries one year, only to see them spike the next.

Cummins turned the corner after it began using a new software package from Predictive Solutions. Within a year, Cummins’ recordable incidents plunged by 76 percent.

Predictive analysis has taken off in recent years as companies increasingly mine data to improve their marketing and cut their costs. Netflix famously has used predictive analysis to recommend movies based on titles customers have enjoyed in the past.

For Griffin Schultz, general manager of Predictive Solutions, using data to recommend flicks is small potatoes. His goal is nothing short of saving lives.

“What we can do today is predict and prevent workplace injuries," he says. “What safety managers could not see, the computer could.”

Details on Cummins’ sophisticated data collection and hazard modeling appear in the March issue of Distribution Center Management.

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For more than 40 years, Distribution Group publications have helped distribution center and warehouse managers increase productivity, cut costs, and meet increasing customer demands. Distribution Group publishes Distribution Center Management newsletter, books and reports, and a free e-newsletter.

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