But there have been practical issues as well.

Early generations of the tools were hard to use. More importantly, even when the tools were giving managers the right answers in terms of the optimal slotting plans, the effort to actually making the slotting moves required proved too much for many operations.

Adoption Rates are Increasing

There are signs, however, that this is starting to change. The combination of DC operational pressures and substantial improvements in Slotting Optimization software tools is leading to increased adoption rates.

At a recent Manhattan Associates user conference, a diverse array of companies supported that view.

A panel discussion there on slotting included Chris Smith of pharmaceutical wholesaler McKesson, Justin Daugherty of purse and accessories manufacturer Vera Bradley, and Kenny Dugger of O’Reilly Auto Parts. Each of these companies were using Slotting Optimization to solve unique challenges.

McKesson has more than 80,000 SKUs in most of its 30 DC network, with many very small products and primarily “eaches” picking. It has been using Manhattan’s slotting application for five years, and seen significant benefits, including double-digit productivity gains and reduction of “emergency replenishments from as high as 20% of all replenishments in some facilities to the low single digits today.

Vera Bradley primarily uses the tool-in-planning mode. As a fashion manufacturer and distributor, the company’s product line turns over frequently, with new styles and colors. It uses the slotting tool primarily to optimize slotting plans for each new season.

With as many as a 100,000 SKUs in each DC, multiple pick areas and storage modes, and wildly different velocity profiles across that SKU base, O’Reilly’s has a huge and classic slotting challenge. The company has used spreadsheets and more legacy slotting solutions in the past, but found it just couldn’t meet its level of requirements. It is in the final phases of implementation of Manhattan’s slotting solution.

One key trend in all three cases is the use of more disciplined—and pragmatic— approaches to getting the slotting moves made. The tools increasingly today can calculate and estimate the cost and benefit from making a particular move. Those that fall under a given threshold may be ignored. Companies may also simply ask for the top 100 or 200 moves that will deliver the largest productivity gains, and act on those suggestions from the tool.

There is also a trend, as illustrated by McKesson and O’Reilly’s, of having dedicated slotting teams that manage set-up and data maintenance within the slotting application on a centralized basis—and then working with local DCs to ensure the slotting changes are enacted on the DC floor.

The bottom line: Slotting Optimization tools themselves are getting much easier to deploy and use, and leaders are developing the internal skill sets and disciplines to maintain slotting data and to ensure the most beneficial slotting recommendations are consistently made.

Are distribution management trends causing you to look more closely at slotting optimization tools? What are the software and operational barriers? Let us know your thoughts at the feedback button below.