Through a special arrangement, what follows is an excerpt of a current article from CPGmatters, a monthly e-zine, presented here for discussion.
A set of recommendations for reducing retail out of stocks (OOS) is outlined in a new comprehensive study. The research grouped the root causes of OOS into three areas: data accuracy, measurement and shelf merchandising practices.
"Data accuracy must be addressed first, as it is the foundation for ordering and forecasting," said Thomas Gruen, Ph.D. of the University of Colorado. "We found major problems with retailers' product item data accuracy."
Mr. Gruen conducted the research along with Dr. Daniel Corstein, IE Business School Madrid. It was funded by a grant from Procter & Gamble.
The study identified a variety of store issues that create perpetual inventory system inaccuracy.
"The level of PI (Perpetual Inventory) inaccuracy was stunning, as PI accuracy (where the PI exactly matched the on-hands) ranged from 32 to 45 percent in the four studies we conducted or examined," said Mr. Gruen. "Improvements in PI accuracy cut OOS in half."
The study found that manual audits and PI measurement of OOS levels are inaccurate, do not focus on the lost sales associated with an OOS item, and do not adequately point to solutions.
In shelf merchandising, the study found that most OOS sales losses are due to a relatively small number of items, and few of these items have adequate shelf space relative to their demand.
"Reworking planograms to account for the demand of the faster moving (and high OOS) items can reduce the level of OOS and the store labor necessary to continually restock these items," said Mr. Gruen. "Second, basic retail practices that encourage three well-known links to OOS need to be enforced: one, don't cover holes; two, don't hide product, and three, shelf tag accuracy. We found that simple adherence to these practices had a huge effect on out of stocks, reducing OOS levels by about 40 percent."
The study outlined a three-step approach to address OOS:
- Create Ranking: Create both a product ranking and a store ranking when assessing OOS; in other words, which products have the highest level of lost sales and which stores have the highest level of lost sales due to OOS.
- Target Reduction Desired: Determine the amount of OOS reduction desired and then allocate the amount of gain to be achieved from "product-based" OOS reductions (store or ordering types of solutions) and from "store-based" OOS reductions (shelf or operations types of solutions).
"For example," the study states, "if a goal of $500,000 lost sales reduction has been established, determine how much of the goal will be obtained from ordering-type solutions such as PI data accuracy and how much should be gained from store-type solutions such as demand-based planograms. In this example, it may mean focusing on the top 300 products and the worst 24 stores to get them to their target rate."
- Apply Solutions: Apply the solutions in the assessment to those products (across all stores) and those stores (across all products). This will provide an estimate of the resources needed to achieve the goal.
Discussion Questions: What do you think are the root causes of out of stocks (OOS)? What do you make of some of the recommendations in the study to reduce OOS? What solutions did they miss?