Group Performance Attribution via Factor Segmentation
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Solution Overview
Problem
Conventional tools fail to accurately represent the performance of a group of entities, such as machines, as they do not indicate the sources of performance changes, leading to unreasonable management decisions and inability to distinguish between intrinsic group properties, agent skill, and luck.
Innovation Solution
A computer-implemented method and system that analyzes group performance by generating historical group factor performance data, static factor performance data, and dynamic factor performance data, providing values that represent the factor timing performance associated with the group, and attributing performance to agents to assess their skill in managing the group.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional tools measure group performance based on whether a particular property has increased or decreased, then the measurement is simple, but the tools do not indicate why the value changed or identify the sources of performance
Solution Approach 1:
The patent segments group performance measurement into multiple dimensions including factor timing performance, factor selection performance, and intrinsic group performance. This segmentation allows the system to not only measure whether performance changed but also to identify the specific sources and drivers of the change, resolving the contradiction between measurement simplicity and information completeness.
2Device complexity
If conventional tools do not identify whether performance increase is due to intrinsic property, agent skill, or luck, then the analysis is straightforward, but agents may take unreasonable actions to manage group value
Solution Approach 1:
The patent introduces an intermediary attribution model that acts as a mediator between raw performance data and management decisions. This model decomposes performance into components attributable to intrinsic group properties, agent skills, and luck, providing a reliable foundation for decision-making while maintaining manageable analysis complexity through structured attribution frameworks.
3Ease of manufacture
If conventional tools measure only the change in group property value, then the measurement process is simple, but the tools fail to accurately represent the performance of the group
Solution Approach 1:
The patent adds another dimension to performance measurement by incorporating factor exposures and factor timing analysis. Instead of measuring only the change in group property value, the system measures performance across multiple dimensions including exposure to various factors, timing of factor bets, and attribution to specific drivers, thereby achieving accurate group performance representation while maintaining a systematic measurement process.
Data Source
AI summary
A method for quantifying performance of a group includes generating historical group factor performance data for a plurality of predefined factors in accordance with historical performance data and historical group factor exposure data for the plurality of predefined factors; generating historical group static factor performance data for the plurality of predefined factors in accordance with the historical performance data for the plurality of predefined factors and one or more representative values of the historical group factor exposure data for the plurality of predefined factors; generating historical group dynamic factor performance data for the plurality of predefined factors in accordance with the historical group factor performance data for the plurality of predefined factors and the historical group static factor performance data for the plurality of predefined factors; and providing one or more values that represent the historical group dynamic factor performance data.