The idea of aligning category space, product assortment, product space, shelf location, facings and section “flow” with store sales, loyalty data and demographic profiling has been around for a number of years.
The benefits are customer satisfaction, inventory reduction, lower out of stocks, increased sales, freed up space, lower restocking costs and others. Store specific planograms done in lab circumstances almost always yield impressive results, particularly in the sales, inventory reduction and OOS reduction areas.
The adoption of this practice has picked up by both retailers and manufacturers. This comes at no small cost as special software, additional data and in many cases additional labor is necessary to accomplish this effort . . . and that effort is ongoing and expanding.
However, it turns out that store specific planograms are subject to the same pitfalls and challenges as the category planograms.
We reviewed Snapograms collected by ShelfSnap across a number of categories from three or the top four grocers in the U.S. as well as from some small format stores (gas and convenience). These Snapograms are the actual shelf sets based on digital images of the planograms from scores of stores. ShelfSnap then used their proprietary image recognition and spatial analytic engine to identify products, locations, shelves, facings and OOS from those pictures. ShelfSnap has developed a planogram compare production facility it calls King Compare, and it used that facility to compare the Snapograms against the store specific planograms for those stores.
Results:
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Not one store complied with it’s POG. Not one. Orientations, positions, flow, facings and assortment all had substantial variences in virtually every case.
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Products that were in the POG but not in the Snapogram accounted for up to thirty percent of the intended range.
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Unexpected assortment ran to upwards of 25% of the total range.
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By and large the number of SKU’s underfaced (vs. the plan) ran about equal in number to the SKU’s with the correct facings.
We talked to one company who spent a great deal of time and money developing store specific planograms for a variety of top accounts. We asked how they measured compliance. They mentioned that they had not started to measure compliance, but hoped that the reset teams would take the expensive store specific POGs as more than “suggestions.” Turns out this is not the case.
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