Mobile device based inventory management and sales trends analysis in a retail environment
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Solution Overview
Problem
Retailers and consumer packaged goods companies face challenges with frequent out-of-shelf and out-of-stock conditions due to poor demand forecasts, leading to inefficient production, excessive inventory, and lost sales, largely because current technologies lack real-time visibility into customer demand and shelf conditions.
Innovation Solution
A method using mobile devices and image processing to calculate sales trends and velocity by identifying products on shelves through tags, transmitting data to the supply chain, and generating optimized replenishment routes to minimize out-of-shelf occurrences, which includes receiving availability data in the form of pictures, identifying products using tags and image processing, and calculating sales velocity and trends to predict and prevent out-of-stock situations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual shelf monitoring is performed by employees, then product availability can be tracked, but labor costs and time consumption increase significantly
Solution Approach 1:
The system enables automatic self-monitoring of shelf inventory through mobile devices captured by consumers. The mobile application automatically detects product availability, captures images of shelves, and transmits data to the server without requiring manual intervention from store employees, thus eliminating labor costs and time consumption while maintaining tracking accuracy.
Solution Approach 2:
The patent replaces the mechanical manual monitoring system with an automated optical recognition system. Mobile devices use camera imaging and image processing algorithms to automatically identify products on shelves, replacing the need for human employees to physically check and record inventory status.
2Reliability
If real-time shelf monitoring is implemented, then out-of-stock situations can be prevented, but system complexity and implementation costs increase
Solution Approach 1:
The system leverages the universal mobile devices already possessed by consumers, eliminating the need for specialized monitoring equipment. The mobile application serves multiple functions: capturing shelf images, processing images to identify products, determining availability status, and transmitting data to the server, thereby reducing system complexity through multi-functionality.
Solution Approach 2:
The patent introduces a server as an intermediary that centralizes data processing and analysis. Mobile devices transmit raw image data and basic information to the server, which performs sophisticated image processing, product identification, and generates actionable insights. This distribution of computational tasks reduces the complexity burden on individual mobile devices.
3Productivity
If traditional demand forecasting models are used, then production planning can be performed, but forecast accuracy deteriorates due to lack of real-time shelf data
Solution Approach 1:
The system establishes a continuous feedback loop where real-time shelf monitoring data is collected from multiple sources, transmitted to the server, analyzed to determine actual product availability and consumption patterns, and then fed back into demand forecasting models. This feedback mechanism ensures that production planning is based on accurate, up-to-date information rather than outdated estimates.
Solution Approach 2:
The system performs preliminary detection and recording of product availability status continuously before actual stockouts occur. By monitoring shelves in real-time and identifying declining inventory levels early, the system enables proactive production and replenishment planning, preventing out-of-stock situations before they impact demand forecasting accuracy.
4Ease of operation
If consumers verify product availability online, then purchasing decisions can be made, but sales are lost when products are out-of-stock at physical shelves
Solution Approach 1:
The system provides real-time feedback to both retailers and consumers about actual product availability at physical shelves. Retailers receive immediate notifications when products are out-of-stock or misplaced, enabling rapid replenishment. Consumers receive accurate availability information through the mobile application, preventing futile store visits and ensuring they can make informed purchasing decisions based on current shelf status.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution provides real-time data on product availability and consumption trends, enabling better demand forecasting, reducing out-of-shelf times, and optimizing inventory management, thereby minimizing sales losses and improving supply chain efficiency.
Implementation Method 1
A method using mobile devices and image processing to calculate sales trends and velocity by identifying products on shelves through tags
Data Source
AI summary
A method for calculating sales trend of a product at a store shelf based on crowdsourcing, includes receiving, by a retail store server, availability data of a product measured on a shelf in the retail store from a portable device, where the availability data is in the form of a picture acquired of the product on the shelf, identifying products on the shelf using tags attached to the shelves, calculating sales velocity and sales trends of the product from the identified products, and transmitting the sales velocity and sales trend of the product to one or more third parties' systems in a supply chain of said retail store. Products and their locations on retail store shelves have been cataloged in a product database.