In a warehouse, time and space are valuable assets. The process of tracking, analysing and improving those assets is a constant cycle, but without the right data is impossible. Data blind spots take a toll on efficiency, but one of the most obvious remains the most untapped: the time during a pallet move.
Visibility is valuable
Motorway speed checks used to suffer from a similar lack of visibility. To track a vehicle’s speed, law enforcement would record a vehicle’s speed at one checkpoint and measure it again at a following checkpoint. Theoretically, a driver could pass the checkpoint at the legal limit, accelerate once they had passed and decelerate before the next checkpoint. From the – inevitably limited – point of view of law enforcement, that driver would not have breached the speed limit. There was simply no way to know the driver’s actions between those two checkpoints. The same is true of pallet management. If you only monitor the point of pickup and deposit, you are blind to what happens in between.
Modern speed cameras have changed this process. So-called ‘average speed’ cameras spaced along a road monitor each vehicle’s licence plate before calculating the average speed and determining if a driver has broken the legal limit. The data exists, the visibility is there. For law enforcement, average speed cameras have become a critical part of road safety infrastructure. For warehouse managers, this level of visibility holds substantial potential for performance improvements, but only a few have recognised its prospects.
The cost of driver inefficiencies
For example, in a medium sized warehouse it could take one driver one minute to pick up a pallet, drive across the floor and deposit the pallet in a racking shelf. You can’t be certain of optimal performance because there is no data from the driver’s activities in that time; you can only be sure the pallet has been picked up and put down.
In that minute, any number of scenarios could have affected the driver’s efficiency. They could have:
taken a scenic route
had to manoeuvre around something that was blocking them
had to wait for barcodes to scan properly
incorrectly placed pallet in wrong shelf and had to move
stopped to speak to a colleague
Without data about that minute, one or all of the above could have happened. And there would be no way to know. If that driver goes on to shift 160 pallets a day, you might face around 2.7 hours where performance improvements are possible, but unknown. Multiply that by just three drivers and that’s a shift’s worth of time to optimise.
Add in the Impossible Triangle, the truly ‘lost’ hours, and you face a wealth of performance improvement possibilities.
How to track performance
Collecting data in the gap between pallet pick up and deposit needs more than just location data from warehouse vehicles. By placing nodes around the warehouse, on the forks of trucks, racking shelves, and drivers themselves, a central system can monitor not only where each vehicle is, but also whether the driver is where they should be, if they are prohibited by anything else, and monitor where exactly pallets are placed. The data, fed back to a system integrated tightly with the Warehouse Management System, can help you identify where and when performance is affected.
For example, if drivers are routinely held up in one location, you might discover some issues with your warehouse layout. If pallets are routinely placed in the wrong racking shelf, you might investigate whether you need additional signage or more driver training. Problem areas can be fixed quickly and with a constant feed of real-time data, you can quickly see which changes have worked and which have not. Consider using the metrics of the Impossible Triangle to track the reduction of lost hours as you close the data gaps and break open blind spots.