Retail Pack Size Optimization Under Shelf Capacity Constraints
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Determining the optimal pack size and customer-facing quantity for retail products is a complex, labor-intensive, and costly task for large retailers, impacting operation costs and sales efficiency.
Innovation Solution
A computer-implemented system and method that utilizes a computing device with a simulator and optimizer engine to analyze inventory, cost, and optimization factors, simulating sales and handling costs to determine the pack size and customer-facing quantity that maximizes net profit, considering shelf capacity and supply chain dynamics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual determination of optimal pack size and customer-facing quantity is performed for every product, then accuracy of inventory optimization is improved, but labor intensity and operational costs increase significantly
Solution Approach 1:
The patent replaces manual mechanical determination methods with an automated computer-implemented system that uses simulation engines and optimization algorithms to calculate optimal pack sizes and customer-facing quantities, eliminating labor-intensive manual processes while maintaining or improving accuracy
Solution Approach 2:
The system enables self-service optimization by automatically processing product data, running simulations, and generating optimization recommendations without requiring manual intervention for each product, allowing the system to serve itself in determining optimal inventory parameters
2Reliability
If comprehensive simulation and optimization analysis is conducted for all products, then net profit maximization is improved, but computational complexity and processing time increase
Solution Approach 1:
The patent segments the optimization process into distinct functional modules including data processing components, simulation engines that model different scenarios, and optimization algorithms that analyze results, allowing each component to be developed and executed independently while contributing to the overall profit optimization goal
Solution Approach 2:
The system performs preliminary actions by pre-processing product data, pre-configuring simulation parameters, and pre-establishing optimization criteria before executing the full analysis, reducing the complexity and processing time of the main optimization computation
3Loss of energy
If detailed cost analysis including handling costs and storing costs is performed, then operational cost reduction is improved, but data processing requirements increase
Solution Approach 1:
The patent merges multiple cost analysis functions into a unified simulation and optimization framework that simultaneously processes handling costs, storing costs, and other operational expenses, reducing redundant data processing while achieving comprehensive cost reduction analysis
Data Source
AI summary
Described are methods and systems for estimating an optimal product pack size and on-shelf customer facing quantity of the products in view of shelf capacity limitations of the shelves at a given retail store/product distribution center, with the aim of maximizing the total net profit of the store/distribution center. The systems and methods obtain inventory-related, retail facility product storage capacity-related, and product storage/handling-related data from one or more databases and estimate the net profit of multiple variations of pack size and customer-facing quantity for each product. Then, these results are processed via various inventory optimization algorithms obtained from one or more databases to estimate the pack size and customer-facing quantity for each of the products to be stocked at the retail facility that would be estimated to result in maximum net profit for the retail facility within a given period of time.