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Deriving an adjusted rate of human analysis by factoring in performance as the sum of weighted accuracy rates

IP.com Disclosure Number: IPCOM000237525D
Publication Date: 2014-Jun-19
Document File: 2 page(s) / 86K

Publishing Venue

The IP.com Prior Art Database

Related People

Josh Gordon: AUTHOR [+3]

Abstract

When a team of individuals is tasked with completing an eyes ­on analysis of a large set of data, metrics relating to the speed and accuracy of the team are often desired to assess overall team effectiveness in data analysis, forecast required resources for project completion, and track data analysis trends and progress.

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Deriving an adjusted rate of human analysis by factoring in performance as the sum of  weighted accuracy rates 
 

Authors: Josh Gordon, Linda Nguyen, and Khanh Trieu 
 
When a team of individuals is tasked with completing an eyes­on analysis of a large set of data,  metrics relating to the speed and accuracy of the team are often desired to assess overall team  effectiveness in data analysis, forecast required resources for project completion, and track data  analysis trends and progress. 
 
These metrics are typically measured through various means, including tracking changes to  analysis­based categorizations through Quality Control (QC) review, and tracking the number of  records analyzed per team and team member in a given quantity of time.  
 
Low analysis rates and accuracy rates can increase the overall amount of time necessary to  complete review and QC of a data set. Tracking these rates can help to identify issues with a  team's progress; however, understanding a team's performance using this data can become  increasingly difficult with higher numbers of categorizations being performed per record.  
 
This calculation incorporates accuracy across several different analysis categories to provide an  adjusted analysis rate. To arrive at this adjusted rate, accuracy rates are counted as deductions  applied to base rates of analysis. The rates can be weighted to reflect the impact or importance  of each analysis category, with higher weights translating into bigger deductions.  
 

Variables: 
 
a.  Individual's base rate of data analysis.  Calculated by dividing the total number of records  analyzed by hours worked, per team member. 
 
b.  Weights of analysis categories.  Each catego...