Survey Says: DC Slotting Pays

Though efficient slotting practices have been shown to reduce labor hours and operating costs in the distribution center, a recent survey from Raleigh, NC-based Tompkins’ Associates’ Supply Chain Consortium reveals that less than a quarter of surveyed firms use slotting optimization software.

“Few operations can afford to ignore slotting,” says Tom Singer, Tompkins Associates Principal and author of the DC Slotting survey report. “Product location is the key to optimizing warehouse operations. Furthermore, participants who use slotting software packages report an average 16% reduction in labor hours by using an automated tool over a manual approach.”

Labor costs are a large factor in optimizing DC slotting. A typical warehouse spends around half of its operating expenditures on direct labor. Proper slotting will significantly reduce travel time, which accounts for up to 60% of these costs.

There are a wide variety of slotting approaches and methodologies, but they can be summarized according to four basic categories (Primary Slotting Methods Figure):

The fixed assignment method is the simplest slotting approach. Stock keeping units (SKUs) are assigned to locations based on physical characteristics and unit of measure without any attempt to minimize labor, improve flow, or meet other operational requirements.

The manual assignment approach designates SKUs based on physical characteristics, unit of measure, and inherent knowledge of the impact of slotting an individual SKU in a particular location.

The manual assignment approach, assisted by spreadsheet or other database tool, assigns SKUs in a similar manner as manual assignment, but with an internally developed spreadsheet or database tool to identify key characteristics that are used to make slotting decisions.

The slotting software approach assigns SKUs based on a software package that analyzes relevant data against user-defined objectives and produces a best fit or optimal slotting plan.

“Many operations do not need sophisticated tools or packaged software to slot product,” Singer notes. “A manual approach may provide similar results. Generally, the larger or more complex an organization is, the more sophisticated its slotting approach should be.”

Other key survey findings include:

Only 31% of survey participants said that their slotting plan was efficient or near optimal in terms of minimizing picking travel times.

51% of operations use an internally developed spreadsheet, database tool or slotting software package to develop slotting plans.

The majority of respondents do not use sales forecast data to support slotting plans.

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