This Company has a long history of using cutting-edge supply chain technology. For example, it is a leader in blockchain technology for sharing data securely across the food supply chain to help ensure food safety. The Company’s Center of Excellence (CoE) focuses on continuous improvement in manufacturing and distribution, with data as its life blood.

To find new ways to reduce material handling costs, one of the key data sets the CoE wanted to understand better was the relationship between lift truck safety and productivity.

With Powerfleet forklift telematics already in place across the Company’s entire fleet of lift trucks, the CoE didn’t have to look far to find the data-driven solution it needed.

To gain deeper insight into the cost of lift truck safety vs. operator efficiency vs. material handling velocity, the Company licensed Powerfleet IQ Analytics, a Powerfleet software option, to link data from multiple sources.

Specifically, the Company wanted to use Powerfleet IQ to blend these data ingredients:

• Number of damage-causing impacts recorded by forklift operators
• Time forklift operators spent actively working
• Number of pallets moved by lift truck operators

Before launching a new technology for its material handling workforce, the Company knew from experience it needed to plan carefully and be proactive about the way it would use the data.

One of the pitfalls of data-driven technology, like Powerfleet IQ Analytics, is that the data can be overwhelming. Another challenge is translating the data into action. All too often, a flood of data is received passively, without a clear vision of what to look for or how to react.

For any new system to succeed, the people who will get the data need to know ahead of time what they will be looking for—and exactly what they are supposed to do with it.

The Company knew that for Powerfleet IQ to be most effective, key employees—lift truck operators, line supervisors, facility managers, and corporate management—needed to care about the outcome. The Company had to make more than a financial investment; it had to engage and motivate these stakeholders.

The key to making workers care is accountability. So the Company devised a “carrot-and-stick” plan with both incentives for “good” behaviors and consequences for “bad” behaviors. Using Powerfleet IQ Analytics data, the Company:

• Developed a consistent set of metrics for material handling productivity and safety, regardless of the type and size of a facility, or the makeup of a site’s lift truck fleet.
• Established new benchmarks for pallet moves vs. lift truck motion time and impact events.
• Set up key performance indicator (KPI) scorecards for drivers, supervisors, and warehouse managers.
• Awarded cash bonuses and other incentives for meeting target KPIs.
• Retrained or reassigned forklift operators who failed to meet the benchmarks for safe productivity.

The next KPI scorecard excerpt ranks sites by forklift fleet efficiency, based on the amount of time vehicles spend in motion compared to the time vehicle operators are logged into the equipment. The “Demarest” site makes the most efficient use of its equipment—it has the highest ratio of motion (time vehicles are moving) to login (time drivers are logged in)—even though the site is average in its total hours of equipment usage. Conversely, although “Montvale” seems to be among the busiest sites, in terms of total hours of equipment usage, it is actually the lowest-performing in its ratio of vehicle motion time to driver login time.

The first key role of Powerfleet IQ was to validate data accuracy. One KPI scorecard monitored the health of system components—particularly to confirm that the Powerfleet vehicle-mounted hardware was collecting data normally and attributing it to identified operators. With validated data flowing smoothly, the Company went through a period of analysis over several months, without acting on the data. This enabled the Company to set expected benchmarks without rushing to judgment about individual operator performance. Importantly, the established benchmarks were ratios (not absolute numbers) to normalize performance across operators, vehicle types, and sites with different operating patterns.

• Pallets moved to severe forklift impacts (which have a high correlation to damage) and to medium forklift impacts (an indicator of excess wear and tear over time)
• Vehicle motion time to operator login time to Kronos® shift time

Also significantly, Powerfleet IQ enabled different standards to be set for different vehicle types, and accounted for drivers who operated different types of vehicles in same shift or day.

Based on these benchmark ratios, the Company set up multiple KPI scorecards for different stakeholders: individual drivers (with daily, weekly, and monthly metrics); supervisors (focused on all drivers each shift); warehouse managers (with a view of the entire facility); and corporate management (with stack-ranking of all sites in a single view).

This data hierarchy enabled a rapid, logical flow of information and decisions. Corporate management identified high- and low-performing sites. Facility managers saw where they ranked compared to other sites, and where they stood in relation to the target benchmarks. Line supervisors drilled down to understand which forklift operators were high achievers—and which needed refresher training. And forklift operators could see in black-and-white where they stood.

In the end, the food & beverage Company was able to drive much safer lift truck operations while maintaining high material velocity through its distribution system. The result was an 85% reduction in forklift damage costs with 100% achievement of target pallet moves.

Using Powerfleet IQ forklift analytics, this food and beverage Company was able to change the way it measured and balanced productivity (pallets moved) with safety (forklift collisions) and efficiency (active time on equipment vs. paid time). This data enabled a new approach to material handling discipline, with high-performers rewarded with financial and other incentives, and low-performers trained to improve. The bottom line was a stronger safety culture, with a new way to measure and manage productivity.

• Compliance with key safety metrics increased to essentially 100%
• Accidents and damage decreased more than 85%, while pallet moves remained at target levels
• Company-wide, Powerfleet IQ Forklift Analytics helped add more than $2 million in cost savings to the bottom line

In Long Beach, CA, a Knight Transportation driver reported that his truck and trailer were missing. The security department immediately enabled Emergency Track on its Powerfleet for Logistics system to begin the trailer location process. It was discovered that the trailer traveled throughout the previous night ending its journey in Rialto, CA at 8:51 a.m. The authorities were notified of the stolen trailer and were told exactly where it was parked, based on the last location delivered by the Powerfleet system. Surveillancewas immediately established across from a large warehouse facility.

Mission Success– The missing trailer came out of the warehouse hooked to a different tractor. The rig was followed by police and the driver was arrested. The authorities recovered all 111 televisions valued at over $100,000, as well as the tractor. Interestingly, a container was also retrieved containing fabric worth over $250,000 that wasn’t yet reported stolen. Several more arrests were made at the scene.