Pensa_Facings_Optimization.pdf

Facings Optimization

Driving Sales by Capturing True Demand

SITUATION

Many Consumer Packaged Goods (CPG) manufacturers lack visibility into how their categories actually look on the retail shelf regardless of whether or not they write the planogram (POG) for the retailer. Even when they do write the POG, current POG data inputs are often limited to sales velocity based upon point of sale data and shelf capacity based upon case pack-out requirements. What's missing is a view of "true demand" from the shelf; in other words, what products were missing at the point of purchase leading to shopper substitution.

FACINGS OPTIMIZATION

Pensa's Facings Optimization solution is like a pricing elasticity model for your shelf to help you understand the point of diminishing returns for incremental facings. Pensa's highly-accurate shelf intelligence data provides category management and sales teams a fact-based ability to sell more space with real shelf data that shows the number of facings required by SKU to optimize on-shelf availability (OSA) and increase sales and profits.

HOW IT WORKS

First, real shelf conditions are analyzed at scale
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FACINGS OPTIMIZATION BENEFITS

Then, the value of a facing is quantified
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Top 20 Items All Other Items
Facings OSA % Pt Change OSA % Pt Change
0 0 - 0 -
1 74% 74% 86% 86%
2 91% 17% 96% 10%
3 95% 4% 96.6% 1%
4 96.1% 1.1% 98.3% 1.7%
5 96.8% 0.7% 100% 1.7%
10 97.7% 0.9% - -
20 98.0% 0.3% - -

2 facings yield +17% in OSA and ~8% in expected sales
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For 95% OSA, 3 Top 20 and 2 Other facings recommended
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