October 5, 2012

New software benchmarks lift truck fleet performance against peers

I.D. Systems says its I.D. Systems Analytics product is the first to allow users to compare performance not only across their own sites but also against other lift truck fleets nationwide.

By Toby Gooley

Shippers have long had the ability to compare their freight rates to those of other shippers on similar lanes. To get that information, they rely on freight payment services that aggregate and analyze invoices for thousands of customers, and then produce reports on the average rates being paid for various lanes, commodities, and types of service. Now a similar benchmarking opportunity is available for the performance of industrial truck fleets.

I.D. Systems Inc.'s new I.D. Systems Analytics product allows users to benchmark industrial truck performance not only across multiple sites within their own companies but also against all of the lift truck fleets tracked by the Woodcliff Lake, N.J.-based provider of wireless vehicle management systems. The benchmarks are derived from the company's database of asset activity, which encompasses more than 250,000 industrial vehicles, 50 million man-days of operations, and more than 1,000 manufacturing and distribution sites in a wide range of industries. According to the company, this is the first time such information has been made available in a formal product offering.

I.D. Systems Analytics builds on the company's vehicle management system for lift trucks, pallet jacks, tow tractors, and other material handling equipment. Vehicle management systems track and measure lift trucks' and drivers' activities. They then produce reports on safety, vehicle utilization, and vehicle and driver productivity. Many users analyze that information separately for each warehouse or DC, and some also create reports comparing performance at multiple facilities. But the Analytics package goes beyond that, the vendor says, by quantifying best-practice benchmarks for vehicle utilization and safety; identifying and measuring variations and inefficiencies across sites and geographic regions; and providing comparisons to benchmarks by industry, facility type, or vehicle type.

Users can view such measures as paid time, actual operator log-in time, equipment utilization, overtime, and vehicle impacts per motion hour, to name just a few. The measures are available in real time and for multiple sites in a graphic format. The charts also show current data or trends by site, as well as the enterprise average and the average for specified peers (industry, type of facility, or type of truck) so users can compare all three at a glance. The industry averages are constantly updated with fresh information from I.D. Systems' customers, said President Ken Ehrman.

Technology has only recently progressed to the point where it could aggregate and analyze this kind of benchmark data, according to Ehrman. "We are leveraging off of a lot of innovation in analytics," he said. "The technology needed to reach the point where we could collect, store, and analyze huge amounts of data on multiple levels. Because of the evolution of the technology that underlies the database and the communication of data to customers, this all can now be done cost-effectively."

In addition, he said, it is now easier to integrate industrial vehicle analysis with information from warehouse management systems (WMS), labor management systems (LMS), and timecard software.

About the Author

Toby Gooley
Contributing Editor
Contributing Editor Toby Gooley is a freelance writer and editor specializing in supply chain, logistics, material handling, and international trade. She previously was Senior Editor at DC VELOCITY and Editor of DCV's sister publication, CSCMP's Supply Chain Quarterly. Prior to joining AGiLE Business Media in 2007, she spent 20 years at Logistics Management magazine as Managing Editor and Senior Editor covering international trade and transportation. Prior to that she was an export traffic manager for 10 years. She holds a B.A. in Asian Studies from Cornell University.

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