Merchandizing Fixture Assortment Optimization

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Solution Overview

Problem

Developing an efficient planogram for retail spaces with multiple items is complex due to spatial constraints, varying item dimensions, profitability differences, and legal and aesthetic considerations, making it difficult to optimize item placement and assortment while maximizing profit and customer satisfaction.

Innovation Solution

A computer system that receives spatial, financial, and interaction data for items, groups them into choice sets, and uses linear programming and simulation techniques to generate optimal assortment and layout, considering business rules and historical data to maximize profit and improve shoppability.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If manual methods are used to develop planograms for multiple items, then simplicity of implementation is maintained, but optimization effectiveness deteriorates due to the complexity of considering multiple parameters and constraints

Engineering Contradiction:

Improveease of planogram developmentVSAvoidoptimization effectiveness

Core Design Contradiction:

Ease of manufactureVSProductivity

Solution Approach 1:

The patent replaces manual mechanical planning methods with an automated computer-based optimization system that uses algorithms to evaluate multiple parameters and constraints simultaneously, transforming the planogram development process from a manual iterative approach to an automated computational optimization process

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system changes the approach from considering single parameters manually to simultaneously evaluating multiple parameters (profitability, spatial constraints, customer behavior, legal requirements) through computational algorithms, enabling comprehensive optimization that was previously infeasible

Inventive Principle:

Principle #35Parameter changes

2Productivity

If more items are placed on shelves to increase profit, then revenue increases, but spatial constraints are violated and customer accessibility deteriorates

Engineering Contradiction:

Improveprofit generationVSAvoidshelf space availability

Core Design Contradiction:

ProductivityVSArea of stationary object

Solution Approach 1:

The system transforms the approach from simple item counting to multi-parameter optimization, evaluating profitability metrics alongside spatial constraints, customer accessibility, and behavioral patterns to determine optimal item placement and quantity that maximizes profit without violating space limitations

Inventive Principle:

Principle #35Parameter changes

3Reliability

If items are arranged to satisfy all legal and business rules, then compliance is achieved, but flexibility in optimization is reduced

Engineering Contradiction:

Improvecompliance with rulesVSAvoidoptimization flexibility

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The system incorporates legal and business rules as predefined constraints in the optimization algorithm before execution, allowing the system to automatically evaluate and satisfy compliance requirements while still exploring the full range of feasible optimization solutions within those constraints

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The optimization system dynamically adjusts item placement and assortment recommendations based on the interplay between fixed constraints (legal and business rules) and variable parameters (profitability, customer behavior, spatial availability), maintaining compliance while achieving adaptability in the optimization outcomes

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS9805333B1Generating a maximum-profit solution for a merchandizing fixture

Publication Date: 2017.10.31 WALGREEN CO

AI summary

A method in a computer system for selecting an efficient combination of items for placement on a merchandizing fixture, wherein each item has a respective size, and wherein each combination of items has a respective profitability metric; including electronically receiving an indication of a size of the merchandizing fixture; electronically receiving a business rule indicative of whether gaps on the merchandizing fixture are allowed; when gaps on the merchandizing fixture are allowed, automatically selecting via a computer processor a combination of items that has a highest profitability metric and that fits on the merchandizing fixture without occupying the entire merchandizing fixture; and when gaps on the merchandizing fixture are not allowed, automatically selecting via a computer processor a combination of items that has a highest profitability and occupies the entire merchandizing fixture without exceeding the size of the merchandizing fixture.