Facility Management Support for Opportunity Loss Analysis
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Solution Overview
Problem
Current facility management systems struggle to efficiently understand and address opportunity loss in large-scale store management, as existing technologies can only determine the status of opportunity loss at individual sales floors and not the entire store, leading to reduced operational efficiency and difficulty in identifying areas for improvement.
Innovation Solution
A facility management support apparatus and system that integrates video capture, statistical information generation, and display output to provide a comprehensive view of opportunity loss across multiple facilities, allowing for detailed analysis and identification of attention timeslots and areas for improvement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the supervisor checks display contents for each sales floor individually to understand opportunity loss status, then detailed understanding of each sales floor is achieved, but operational efficiency significantly reduces
Solution Approach 1:
The system segments the store into multiple sales floors and evaluates opportunity loss status for each sales floor independently. The evaluation unit calculates opportunity loss for each sales floor based on customer count and purchase count data, allowing detailed analysis of each segment while aggregating results for overall store assessment
Solution Approach 2:
The system introduces an evaluation unit as an intermediary that automatically calculates and evaluates opportunity loss status. This intermediary processes raw data (customer counts, purchase counts) and generates evaluated results (opportunity loss status, attention determination), eliminating the need for supervisors to manually check each sales floor while providing precise evaluation
2Ease of operation
If simple comparison of sales status among chain stores is performed, then ease of operation is improved, but comprehensive understanding of opportunity loss status is insufficient
Solution Approach 1:
The system changes the evaluation parameters from simple sales status comparison to multi-dimensional opportunity loss evaluation. It calculates opportunity loss based on customer count, purchase count, and their relationship, providing comprehensive insights into why sales may be suboptimal rather than just comparing sales figures
Solution Approach 2:
The system adds another dimension to the analysis by evaluating not just sales status but also the relationship between customer count and purchase count. This dimensional expansion allows identification of opportunity loss patterns that simple comparison would miss, such as high customer traffic but low purchase conversion
3Measurement precision
If the supervisor manually evaluates opportunity loss status for each store in a large management system, then detailed assessment is achieved, but the burden increases significantly with large scale
Solution Approach 1:
The system enables self-service evaluation where the evaluation unit automatically assesses opportunity loss status without supervisor intervention. The unit retrieves data from storage, performs evaluation calculations, and determines attention requirements autonomously, reducing supervisor burden while maintaining assessment precision across large numbers of stores
Solution Approach 2:
The system replaces the mechanical manual evaluation process with an automated information processing system. Instead of supervisors manually checking each store, the evaluation unit automatically processes data using predetermined evaluation criteria, substituting human effort with automated computation while handling large-scale management
Data Source
AI summary
The number of entering customers and number of paying customers in a store are obtained, statistical information indicating temporal change in status of the number of entering customers and the number of paying customers in a store is generated, the statistical information is displayed along a time axis, the number of a timeslot which is a selection point is displayed on the time axis, and the video of the inside of the store corresponding to the selected timeslot is displayed in response to the user's operation to select the timeslot.