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    EXPERT COLUMN: The True Cost of Stockouts

    It’s far more than just one lost purchase

    By Matt Waller

    Julie Crimson shops weekly at FemMart, generating about 25 dollars in margin for the retailer each trip. She makes a special trip to the store to get Kotex, but for the third consecutive month her favorite Kotex SKU is out-of-stock. That’s the last straw for Julie! She declares she will never shop at FemMart again. The present value of that shelf-out is about $11,250.

    Cheri Smith routinely purchases Doughberry frozen piecrusts. One day she finds no Doughberry frozen piecrusts so she decides to try Pillsbury refrigerated piecrusts. At dinner on Sunday afternoon, everyone comments that the piecrust tastes better than usual. Cheri decides to switch to Pillsbury refrigerated piecrusts, costing Doughberry about 240 units of frozen piecrusts over the next year.

    Even when these are rare events, the result is extremely expensive. This strategic impact is why on-shelf availability has become such a buzzword in the retail and CPG industry. But yet the challenge has created a perfect scenario for collaboration between retailers and suppliers: a common opportunity with interdependent solutions. The two scenarios have strategic implications, and it takes strategy, process and technology to solve the problem.

    Suppliers are occasionally the cause of such issues by developing product packaging that complicates handling, case packs that don’t fit on the shelf, and promotions that are not backed by sufficient inventory.

    On the other hand, retailers can contribute to the challenge as well and allow SKU proliferation to the point that retail shelves lack sufficient holding power; don’t set store replenishment parameters scientifically; or they have inaccurate perpetual inventory.

    On most days, a SKU that sells about one unit per week will have zero demand (Table 1), but there may be multiple days in a year with a demand of four or even five. If a typical forecasting approach like exponential smoothing is used, then forecasting error will be 195 percent or higher. Ironically, setting forecast to zero would reduce error to about 30 percent. It rarely works at the store level to use typical forecasting methods and the resulting forecasting-based means of setting reorder points.

    Table 1: Point of sale data.

    There are several approaches that can be taken to improve on-shelf availability, and they are worth pursuing. However, remember to consider the fundamentals of managing the whole supply chain (Table 2). Don’t improve on-shelf availability by excessively increasing costs at some other point in the chain.

    Table 2: Back to supply chain fundamentals.

    Here are a few ways retailers and suppliers can collaborate to improve on-shelf availability:

    • Agree clearly on defining availability, including what is ‘off shelf.’ What if it is on the shelf but in the wrong place or hidden from sight?
    • Agree on how to measure off-shelf events. What if the store is out? Which type of availability most worries you, the supplier?
    • Agree on how stores will be audited to assess the problem.
    • Jointly create a cause and effect analysis of shelf out-of-stocks in your category.

    Some technologies, such as forecasting, bring pitfalls for on-shelf availability.

    • Don’t rely on the store perpetual inventory system to assess on-shelf availability; they are notoriously in error.
    • Avoid purely rules based analyses to identify shelf stockouts.
    • Don’t use static probability distributions blindly; most POS is non-stationary.

    On the other hand, keeping up-to-date POS data in the system can enable great improvements:

    • Keep a demand signal repository that can handle daily, not just weekly, POS data.
    • Install a demand signal repository across as many accounts as possible

    With collaborative effort and the help of current POS data management, both suppliers and retailers can greatly improve on-shelf availability, making this area one of the great current opportunities for mutually beneficial collaboration.

    Dr. Matt Waller is currently the chief data scientist at Orchestro, Garrison Endowed Chair of Supply Chain Management at the University of Arkansas' Sam Walton College of Business and co-editor of the Journal of Business Logistics. He can be reached at [email protected]


    By Matt Waller
    • About Matt Waller

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