Scott Sullivan, Pitt Ohio Express

Two years ago, Randy Black discovered that one particular lane in the Shaw Industries transportation division was performing significantly worse than average. Black, e-business manager for Shaw, was looking specifically at a 55-truck operation that delivers flooring to locations in Georgia. The Dalton, Ga.-based flooring giant also operates more than 900 total vehicles in interplant, regional and over-the-road divisions.

As part of a Six Sigma effort – a data-driven approach to improving business processes – Black had begun looking at lane, driver and vehicle metrics for the 55-truck operation on a per-pound basis. Viewing performance in terms of weight of product hauled made it easier to compare loads of varying volumes – carpet versus hardwood, for example.

After Black found that the labor cost per pound was higher than average in this one lane, he looked for the reason and found that drivers were making a daily 50-mile roundtrip simply to drop off bills of lading at the company’s headquarters in Dalton. Shaw easily fixed this problem by placing a drop box for BOLs at the truck leasing facility where drivers picked up and dropped off their trucks each day, Black says.

Through numerous small changes like this, Shaw realized savings of 6.5 percent in labor costs per pound in its Georgia delivery fleet. Shaw achieved this improvement not only by ferreting out bad habits and processes but also by identifying top performers and modeling their best practices.

“That is the fun thing – to not only see what is bad, but to know what the top performers are, and what are they doing right,” Black says. “Without running the data tools or a pro-rate chart on costs, you are really just guessing to see where you are inefficient.”

With varying degrees of sophistication, many fleet owners mine their operational and financial data to unearth hidden poor performers and unheralded best practices. Data mining helps executives get answers – often without even knowing the questions – and may help managers break out of conventional thinking and assumptions that hamper improvement.