Dynamic Workforce Assignment Using Privacy-Preserving Activity Maps
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In retail environments, optimizing employee distribution based on customer concentration is challenging due to privacy concerns and legal restrictions on tracking employees, which can impact sales and customer perception.
Innovation Solution
A dynamic workforce assignment system that uses activity sensors to create raw activity maps, which mobile clients alter based on their positioning information as a damping factor, generating altered maps that are aggregated without revealing employee positions, allowing employees to self-determine optimal positioning without compromising privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If employee position tracking is implemented to optimize workforce distribution, then productivity and customer service quality improve, but privacy protection and legal compliance deteriorate
Solution Approach 1:
The patent introduces activity maps as an intermediary representation that indirectly reflects employee presence without exposing precise position data. Instead of directly tracking and using employee coordinates, the system uses activity maps that show general activity levels, allowing workforce optimization while maintaining privacy through this mediating layer of information.
Solution Approach 2:
The system creates copies of activity information in the form of activity maps that represent employee presence patterns without containing actual position data. These maps are generated from position information but serve as anonymized representations that can be used for optimization purposes without revealing sensitive location data.
2Ease of operation
If real-time employee position monitoring is used to dynamically assign employees to high-traffic areas, then customer service quality improves, but device complexity and system requirements increase
Solution Approach 1:
The system enables employees to automatically receive updated activity maps on their mobile devices that reflect current store conditions and their own positions. This self-service approach allows employees to independently make informed decisions about where to position themselves without requiring complex centralized assignment algorithms or constant system intervention.
Solution Approach 2:
The activity maps are dynamically updated as employees move and as customer activity patterns change. The system continuously regenerates activity maps based on current position information and activity data, allowing real-time adaptation without requiring complex reassignment protocols. This dynamic updating simplifies the operational process while maintaining responsiveness.
Data Source
AI summary
In one embodiment, a method includes receiving a first activity map. A first mobile client determines first positioning information based on a first position of the first mobile client. The first mobile client generates a second activity map using the first positioning information of the first mobile client as a damping factor for activity in the first activity map. The first mobile client sends the second activity map to a balancing manager. A third activity map is received from the balancing manager. The third activity map is based on the second activity map from the first mobile client and a second activity map from a second mobile client. The second activity map from the second mobile client is generated using second positioning information for a second position of the second mobile client as the damping factor.