Worker Activity Categorization for Granular Productivity Measurement
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Solution Overview
Problem
Existing systems lack effective methods to categorize electronic monitoring data for measuring productivity, particularly distinguishing between time and inputs focused on work-product and non-work-product activities.
Innovation Solution
A computer-implemented method and system for categorizing worker activities by classifying files, URLs, and software applications into categories such as Work-Product, contributor, maintainer, and distractor, using a graphical user interface to track and analyze time spent on these categories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If electronic monitoring data is collected to measure worker productivity, then productivity measurement capability is improved, but the ability to effectively categorize and utilize the data deteriorates
Solution Approach 1:
The patent segments worker activity data into distinct categories (Work-Product, non-work-product, and intermediate categories) based on the relationship to value creation. This segmentation allows the system to handle complex monitoring data by dividing it into manageable, analyzable segments that can be processed and measured effectively.
Solution Approach 2:
The patent introduces an intermediary classification layer between raw electronic monitoring data and productivity measurement. This intermediary system categorizes activities based on their relationship to Work-Product, acting as a mediator that transforms raw data into meaningful productivity metrics without requiring direct complex analysis of all monitoring data.
2Quantity of substance
If all worker activities are tracked in detail, then data completeness is improved, but the difficulty of detecting and measuring productivity deteriorates
Solution Approach 1:
The patent extracts and isolates the critical element of productivity measurement by focusing specifically on Work-Product activities. Rather than attempting to measure all activities equally, the system extracts and prioritizes data related to value creation, making productivity detection more straightforward despite comprehensive data collection.
Solution Approach 2:
The patent applies local quality by treating different types of worker activities with different measurement approaches. Work-Product activities receive focused, detailed measurement while other activities are categorized more broadly, allowing the system to maintain data completeness while simplifying the detection and measurement process for productivity-critical activities.
Data Source
AI summary
According to an aspect of the present invention, there is provided a computer-implemented method for measuring the productivity of a user, comprising: measuring, at a user computer terminal, the duration of time a worker is focused on specific work-product files, URLs or software applications; and measuring the inputs of the worker over that duration of time.