Retail Planogram Optimization via Space Elasticity Modeling
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Solution Overview
Problem
Existing computer models for generating electronic planograms in retail environments are inefficient and inaccurate, failing to effectively correlate space and sales relationships to maximize profit, leading to suboptimal shelf space allocation.
Innovation Solution
A method and system that calculate space elasticity and cross-space elasticity using constrained linear regression and multiple regression models, followed by a non-linear multiple-constraint mixed integer optimization model to determine optimal horizontal facings for items, thereby generating an electronic planogram that maximizes revenue.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing computer models are used for generating electronic planograms, then the process is simple, but the accuracy and efficiency are insufficient
Solution Approach 1:
The patent segments the space-sales relationship analysis into distinct components: space elasticity calculation for individual items and cross-space elasticity calculation for item interactions. This segmentation allows each component to be modeled with appropriate regression techniques, improving overall accuracy while maintaining manageable system complexity.
Solution Approach 2:
The patent introduces elasticity coefficients as intermediary variables that mediate between physical shelf space allocation and sales outcomes. These elasticity parameters serve as bridges in the regression models, enabling accurate prediction of sales responses to space changes without requiring direct complex modeling of all underlying factors.
2Productivity
If shelf space is allocated without accurate space-sales correlation, then allocation is simple, but total profit is not maximized
Solution Approach 1:
The patent implements feedback mechanisms through regression models that continuously analyze the relationship between space allocation and sales performance. The calculated elasticity coefficients provide feedback on how changes in facings affect sales, enabling profit maximization by adjusting space allocation based on quantified relationships rather than simple heuristics.
Solution Approach 2:
The patent transforms the space allocation problem into a parameter optimization problem by introducing elasticity parameters that quantify the relationship between facings and sales. By changing and optimizing these parameters through regression analysis, the system maximizes total profit while managing the complexity of space planning decisions.
3Reliability
If traditional planogram generation methods are used, then implementation is straightforward, but revenue optimization is limited
Solution Approach 1:
The patent performs preliminary analysis by calculating space elasticity and cross-space elasticity coefficients before generating the optimized planogram. This preliminary regression analysis establishes the quantitative relationships needed for revenue optimization, separating the complex analysis phase from the simpler planogram generation phase.
Solution Approach 2:
The patent adds the dimension of elasticity analysis to traditional space planning, moving from direct space-allocation decisions to decisions based on quantified elasticity relationships. This dimensional addition enables more reliable revenue maximization by incorporating the intermediate layer of elasticity measurement and analysis.
Data Source
AI summary
A method for computer modeling a retail environment includes: calculating a space elasticity for an item of an item category in a retail store, using a constrained linear regression model; calculating a cross-space elasticity for the item of the item category in the retail store, using a multiple regression model; generating a number for horizontal facings for the item of the item category in the retail store, using a non-linear multiple-constraint mixed integer optimization model, based on the space elasticity of the item and the cross-space elasticity of the item; and generating an electronic planogram of the item category for the retail store, based on the number of the horizontal facings of the item.