Tejas Pawar

ORCID Identifier(s)


Graduation Semester and Year




Document Type


Degree Name

Doctor of Philosophy in Industrial Engineering


Industrial and Manufacturing Systems Engineering

First Advisor

Donald Liles

Second Advisor

Royce James Lummus


The field of Program Management is subject to high program failures. The Project Management Institute (PMI) states that 74% of programs are executed unsuccessfully (Mulcahy, Rita). The high rate of program failures is primarily due to inadequate planning before a program begins and inadequate management of a program when it is being executed. To avoid these high failure rates, a Program Manager needs a tool to help him assess the Probability of Success (POS) of fully accomplishing the objectives of his program from the initial planning phase and throughout all phases of program execution. Purpose: The purpose of this research is to define and demonstrate a methodology for assessing the Probability of Success of achieving the program cost and schedule objectives of the program during all phases of the program. Methodology: Monte Carlo Methods, Oracle Crystal Ball, and Risk Management methods were used to develop this methodology. Findings: The findings indicate that the application of Risk Management combined with Monte Carlo Methods and Simulations into a Probability of Success Evaluator (POSE) tool can significantly improve the Probability of Success of a program achieving the desired program cost and schedule objectives. POSE can also be used to test various risk mitigation plans for a program to drive to a program plan the meets the program objectives. This dissertation further demonstrates how POSE can be used to effectively perform trades between various variables like risk mitigation and management reserves to derive the best value program solution for the required organizational program Probability of Success. Practical Implication: This dissertation is aimed at delivering solutions to the problems in the field of Program Management. A formal user-friendly risk management process has been defined to help program managers accommodate risk and prepare for uncertainty. This dissertation has defined the POSE tool that utilizes a clear process for applying statistics and simulation to validate program plans before beginning and while managing program execution to determine the likelihood that the program will succeed in achieving the organization's requirements. The POSE tool and process helps the Program Manger significantly better understand and manage the critical success and failure factors of the program and serves as a constant means to study and mange how to bring a program to completion successfully throughout the program.


Probability of success, Project management, Program management, Project schedule, Project cost, Risk analysis, Monte Carlo simulation, Crystal ball, Risk management


Engineering | Operations Research, Systems Engineering and Industrial Engineering


Degree granted by The University of Texas at Arlington