Date of Award

8-2011

Degree Type

Thesis

Degree Name

Master of Science

Major

Industrial Engineering

Major Professor

Rupy Sawhney

Committee Members

Joseph Wilck, Gregory A. Sedrick

Abstract

Every organization has to deal with planning of the appropriate level of human resources over time. The workforce is not always aligned with the requirements of the organization and it increases an organization’s budget. A literature review reveals that there is no model that can systematically predict accurate human resource required within a complex organization. To address this gap, a human resource predictive model was developed based on material requirements planning (MRP). This approach accounts for complexity in workforce planning and generalized it with a logistic regression model. The model estimates the employee turnover number and forecasts the expected remaining headcount for the next time period based on employee information such as; age, working year, salary, etc. Moreover, external variables and economic data can be utilized to adjust the estimated turnover probability. This model also suggests the possible internal workforce movement in case of in-house manpower imbalance.

Files over 3MB may be slow to open. For best results, right-click and select "save as..."

Share

COinS