Re-Evaluating Performance Measurement: New Mathematical Methods to Address Common Performance Measurement Challenges

<p>Performance Measurement is an essential discipline for any business. Robust and reliable performance metrics for people, processes, and technologies enable a business to identify and address deficiencies to improve performance and profitability. The complexity of modern operating environments presents real challenges to developing equitable and accurate performance metrics. This thesis explores and develops two new methods to address common challenges encountered in businesses across the world. The first method addresses the challenge of estimating the relative complexity of various tasks by utilizing the Pearson Correlation Coefficient to identify potentially over weighted and under weighted tasks. The second method addresses the challenge of determining performers' influence on a metric by treating performance rankings as vectors and evaluating the change of the vector over multiple performance periods.</p>

Name thesis:degree_name

MS

Level thesis:degree_level

Immediate Access

Discipline thesis:degree_discipline

Computational Mathematics

Year dc:date.available

2018

Author dc:creator

• Benis, Jordan David

Contributors dc:contributor

• John Kern
• Frank D'Amico

• Performance Management
• Performance Measurement
• Performance Metrics
• Performance
• Employee Performance
• Computational Engineering
• Mathematics
• Operations and Supply Chain Management
• Statistics and Probability

Language dc:language

English

Repository record dc:identifier

https://dsc.duq.edu/etd/1427

OAI identifier oai:identifier

oai:dsc.duq.edu:etd-2452