August 21, 2018 /

Turn Data into Dollars with Forklift Analytics

By The Industrial Truck Management Team at I.D. Systems

Material handing is a major cost center, so companies are always looking for new ways to cut costs. And these days, data is the key. But how do you actually turn data into dollars in your material handling operations?

forklift analytics turn data into dollars - cost savings

There are many technical solutions to track and manage different aspects of material handling. So how can you choose the right set of data you need to make cost-saving decisions? (And how can you avoid data overload?)

One proven way is with forklift analytics, which can tie industrial truck usage data to data from other systems. Like time cards and WMS (warehouse management systems).

For example, take our PowerFleet IQ™ analytics platform. A leading global food & beverage producer used PowerFleet IQ to integrate data across multiple systems. Specifically, it blended data from our PowerFleet® forklift telematics system, a Kronos® time-card system, and an SAP® WMS.

Blend Data Across Systems to Turn Data into Dollars

The overlapping data from these three systems created a unique data set that included:

  • Lift truck operator paid-time vs. seat-time, deadhead-time, and time-in-motion-with-load
  • Pallets moved by each lift truck vs. damage-causing forklift impacts

This data enabled the food & beverage firm to set new standards across its entire enterprise, using Key Performance Indicator (KPI) scorecards.

For example, the KPI scorecard at right shows the following.

forklift analytics turn data into dollars - site comparison

Of all the company’s sites, “Demarest” makes the most efficient use of industrial trucks [1]. It has the highest ratio of forklift motion to driver login time. However, compared to other sites, “Demarest” is only average in its total hours of lift truck usage [2].

On the other hand, “Montvale” [3] looks like one of the busiest sites, in terms of total hours of forklift usage. But measured by vehicle motion time vs. driver login time, it is actually the least efficient site [4].

Overlaying timecard and WMS data with this forklift telematics data produced even deeper metrics on operator activity.

To learn more about how these metrics helped the food & beverage company achieve 100% of target pallet moves with 85% less forklift damage, download the full case study.