Resource Allocation Engine Using Occupancy Data Across Locations
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Solution Overview
Problem
Management of resources across multiple locations in an organization is time-consuming, costly, and largely ineffective due to discrepancies in employee presence and duty allocation, leading to resource wastage and inefficiency.
Innovation Solution
A resource engine collects and analyzes data from various sources to determine resource utilization and occupancy density, providing recommendations for optimal resource allocation through alerts, reports, or user interfaces, which can be automatically applied or manually implemented.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If resources are allocated based on location capacity rather than actual employee presence, then resource allocation is simplified, but resource waste increases
Solution Approach 1:
The system implements continuous monitoring of employee presence data and automatically feeds this information back to the resource allocation system. This feedback loop enables dynamic adjustment of resource allocation based on actual occupancy levels, eliminating waste while maintaining operational simplicity through automated decision-making
Solution Approach 2:
The resource allocation system serves itself by automatically detecting occupancy changes and reallocating resources without human intervention. The system monitors its own performance metrics and adjusts allocations autonomously, reducing both manual effort and resource waste simultaneously
2Adaptability or versatility
If manual resource management is used across multiple locations, then flexibility in decision-making is maintained, but time consumption and costs increase
Solution Approach 1:
An automated resource management system acts as an intermediary between occupancy data and resource allocation decisions. This intermediary processes data automatically and provides actionable insights to managers, maintaining human flexibility in final decisions while eliminating time-consuming manual tracking and analysis
Solution Approach 2:
The patent replaces manual mechanical processes of resource tracking and allocation with automated electronic systems. Sensors, software platforms, and algorithms substitute for manual counting and spreadsheet management, dramatically reducing time consumption while preserving strategic decision-making flexibility
3Ease of operation
If personnel are scheduled without considering actual occupancy patterns, then scheduling simplicity is maintained, but productivity decreases
Solution Approach 1:
The system performs preliminary analysis of occupancy patterns and automatically generates optimized scheduling recommendations before personnel are assigned. By pre-processing data and identifying optimal schedules in advance, the system maintains scheduling simplicity while significantly improving productivity through data-driven decisions
Data Source
AI summary
Embodiments of the present disclosure relate to systems, methods, and user interfaces for optimizing resource allocation for an organization. More particularly, embodiments of the present disclosure utilize multiple data sets to enable organizations to make intuitive business decisions and plan resources accordingly. To do so, various data is collected at a resource engine that utilizes the data to determine resource utilization, occupancy density, and a recommendation. In various embodiments, the resource utilization, occupancy density, and a recommendation may be provided to a user as an alert, a report, or a user interface. The user interface may additionally enable the user to apply the recommendation. In some embodiments, the recommendation may be automatically applied or the user may be directed to perform the recommendation. The alert, report, or user interface may additionally inform the user of the impact of performing or not performing the recommendation.