Weighted Work-Item Prioritization Under Resource Constraints
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Solution Overview
Problem
Current software development tools struggle to associate computerized work-items with organizational objectives, prioritize them based on weighted rules, and measure progress effectively, lacking decomposition of contributions and expenses into sub-components and considering different resource categories.
Innovation Solution
A system and method that processes a master list of computerized work-items to generate a prioritized list using weighted computer-executable rules, assigning scores to contribution and expense sub-components, sorting, and traversing the list to ensure resource limits are not exceeded, while tracking progress using bucket values and telemetry.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If traditional ad hoc priority setting is used for work-items, then implementation simplicity is maintained, but the ability to quantify impact towards organizational objectives deteriorates
Solution Approach 1:
The patent segments the impact of work-items into distinct contribution sub-components (e.g., revenue impact, adoption impact, product quality improvement, customer satisfaction impact) and expense sub-components. This segmentation allows each aspect to be measured and weighted separately, transforming the ad hoc priority setting into a structured evaluation system that quantifies impact towards organizational objectives while maintaining implementation feasibility through modular assessment.
2Measurement precision
If weighted scoring based on organizational objectives is implemented, then work-item prioritization accuracy improves, but computational complexity increases
Solution Approach 1:
The patent divides the prioritization process into segmented steps: (1) assigning weights to contribution and expense sub-components based on organizational objectives, (2) scoring individual work-items against these weighted criteria, and (3) aggregating scores to determine priority. This segmentation transforms a potentially complex computational problem into a series of manageable steps that can be implemented systematically.
Solution Approach 2:
The patent introduces configurable parameters including weights for different contribution and expense sub-components, which can be adjusted based on organizational priorities. This parameter-based approach allows the system to adapt to different organizational objectives without requiring fundamental changes to the computational structure, thereby managing complexity while maintaining prioritization accuracy.
3Productivity
If resource constraints are enforced during work-item selection, then resource utilization efficiency improves, but the number of selectable work-items decreases
Solution Approach 1:
The patent incorporates resource constraints as adjustable parameters in the work-item selection process. By defining resource categories (e.g., engineering resources, hardware/software expenses, legal expenses) and setting maximum resource unit limits for each, the system can enforce resource efficiency while allowing flexible adjustment of constraints based on organizational capacity and priorities.
Solution Approach 2:
The patent generates a prioritized list of work-items that may include more items than can be immediately executed, allowing organizations to plan and prepare for future execution. This approach enables resource-efficient selection for immediate work while maintaining a pipeline of prioritized items for future resource availability, effectively managing the trade-off between current resource utilization and future work capacity.
Data Source
AI summary
Generating an output prioritized list of computerized work-items for prioritizing work based on a set of weighted computer-executable rules includes a structured way of associating contributions and expenses with computerized work-items and enhancing current technological processes of selecting computerized work-items to meet weighted computer-executable rules. The method includes assigning a weighted score to the contribution and expense sub-components based on a weighted computer-executable rule associated with those sub-components, determining a value score for each computerized work-item using the weighted scores, sorting the computerized work-items of the input master list in descending order of the value score to obtain a sorted list of computerized work-items, and traversing the sorted list of computerized work-items to generate the output prioritized list of computerized work-items for prioritizing work based on weighted computer-executable rules.