Product Assortment Recommender System Using Demand Transference

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Solution Overview

Problem

Existing methods for determining product assortments in retail environments are inefficient and fail to account for complex interactions between products and changing demand, leading to suboptimal business strategies and increased costs.

Innovation Solution

A product assortment recommender system that uses a computing device to optimize product assortment recommendations based on sales forecasts, demand transference, and replenishment costs, incorporating strategic business considerations and clustering similar stores for optimized product placement and inventory management.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional manual methods are used to determine product assortments, then decisions can be made with simple historical information, but the accuracy and optimization of business strategies deteriorate due to failure to account for complex product interactions and demand transference

Engineering Contradiction:

Improveaccuracy of product assortment decisionsVSAvoidcomplexity of decision-making system

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent replaces manual human decision-making processes with an automated computing system that uses algorithms to analyze product interactions, demand transference, and forecast sales. The system substitutes human judgment with computational analysis of complex relationships between products, enabling accurate optimization without manual intervention.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces a computing device as an intermediary between historical data and product assortment decisions. This intermediary processes complex relationships, demand transference patterns, and forecast data to generate optimized recommendations, bridging the gap between raw data and strategic decisions.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If product assortment changes are implemented frequently to optimize business strategies, then sales and profit can be maximized, but the cost and time required for implementation increases significantly

Engineering Contradiction:

Improvebusiness strategy optimizationVSAvoidtime for assortment changes

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The patent performs preliminary analysis and optimization calculations before actual assortment changes are implemented. The system forecasts sales, analyzes demand transference, and determines optimal assortments in advance, allowing retailers to plan changes strategically and minimize implementation time and costs.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent enables dynamic adjustment of product assortments by continuously analyzing forecast data, demand transference, and sales performance. The system can rapidly reconfigure assortments in response to changing conditions without the delays of traditional manual processes, optimizing business strategies while reducing implementation time.

Inventive Principle:

Principle #15Dynamics

3Measurement precision

If comprehensive data analysis is performed to account for demand transference and product interactions, then product assortment accuracy improves, but the computational resources and processing time increase

Engineering Contradiction:

Improveproduct assortment recommendation accuracyVSAvoidcomputational resources required

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The patent segments the complex analysis into manageable components: forecast data analysis, demand transference calculation, product interaction modeling, and optimization algorithms. This segmentation allows the system to process comprehensive data efficiently by breaking down the computational task into discrete, optimized steps.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS20230245148A1Methods and apparatuses for determining product assortment

Publication Date: 2023.08.03 WALMART APOLLO LLC

AI summary

A system for determining recommended product assortments for a retail environment includes at least one computing device that obtains store layout data, product data and forecast data. The forecast data characterizes projected sales information for the products described in the product data. The computing device also obtains demand transference data characterizing changes in demand for one or more products when a different product is unavailable and obtains product replenishment data characterizing a cost to re-stock products. The computing device also determines a recommended product assortment for the products described in the product data for each store described in the store layout data based on the forecast data, the demand transference data, and the product replenishment data and then displays the recommended product assortment.