The Human Factor in Slotting

The following article is from Waukesha, WI-based logistics solutions provider Red Prairie

Optimizing warehouse slotting can be a full-time job. For most distribution centers, the mix of items is constantly in flux. Items change packaging, and therefore handling characteristics. New items replace old or are simply added to the mix. Seasonality, promotions, demand, and other factors beyond anyone’s control change an item’s velocity with predictable unpredictability.

Many DCs are faced with physical constraints that limit the amount of forward pick locations. When the number of active items outnumbers the forward pick face slots, this real estate becomes a scarce resource, to be allocated wisely only to the most deserving items. Every other item must be given the “next best thing.”

Many slotting applications have been developed to address this challenging issue. Most, though, consider only inventory pick velocity and travel distance when making slotting decisions. They ignore the human side of the equation, which takes into account what effect any changes might have on work processes.

Creating slotting plans
Most slotting plans are created from a macro view of the facility and the items stored within it at any given time. For instance, a section of case flow rack is the forward pick area, and within that, the first three bays of every aisle are reserved for the fastest-moving items. Any primary items that cannot fit in that zone should get as close as possible in the next five bays, intermingling with the items of secondary importance.

The bigger challenge requires considering less obvious variables. Does placing an item on the top shelf of the forward pick face really produce faster pick times than placing it in the secondary pick area in the chest-high “golden” pick zone? How does changing pick location affect put-away and replenishment times? What would be the impact on picking efficiency of a forward pick area layout change? These and many more questions affecting slotting decisions require understanding each job in the facility at the task level.

When slotting is done manually, it is unrealistic to assume that you can do a thorough job, evaluating all factors, on a regular basis. With a system in place to do the number crunching, frequent evaluation should become the norm, with major reslots the exception. But to be truly effective at executing and enforcing the slotting policy, the slotting application must be integrated to DC operational systems such as warehouse management and labor management systems. This enables the slotting plan to be a natural complement to normal DC operations such as replenishment and put-away. Inventory managers would then be less likely to delay reslotting, since the onerous task of shutting down the DC to execute the reslot could be avoided and incremental ROI could be achieved on a regular basis.

Measuring effectiveness
One measure of effective slotting is a predictable reduction in cost, as a result of ongoing optimization. The cost per unit shipped should not trend upward over time and then dip due to a reslot, only to drift upward again. With a good slotting system “watchdog,” the overall throughput cost should stabilize as moves are made on a regular basis. Thus, the goal of the slotting plan is to maintain or continually improve on overall cost per unit shipped.

With a plan duly represented in the system, a watchdog looking for opportunities, and metrics keeping everyone honest, the inventory manager can focus on continuous improvement. What if a wider variety of items was allowed into a given zone? What if the slots were smaller? What if pick error rate played more into the decision process? There are a plethora of options the inventory manager could consider.

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