Modeling, Evaluating, and Predicting IT Human Resources Performance

This book addresses the critical role of human factors in IT risk assessment, offering methods to evaluate IT personnel performance, analyze psychological traits, and enhance software engineering processes through statistical principles.

Modeling, Evaluating, and Predicting IT Human Resources Performance addresses the critical need to incorporate the human element in assessing risks associated with information technology (IT) personnel. While many existing methodologies focus on the roles and responsibilities of IT staff, they often overlook the impact of human errors and the inherent risks they pose. This book seeks to bridge that gap by emphasizing the importance of understanding human factors in the software engineering process.

The author presents a comprehensive evaluation approach rooted in established research, enhancing traditional methods through rigorous application of software measurement and statistical principles. By examining IT human factors from a risk assessment perspective, the book delves into the fundamentals of IT human performance. It identifies key factors necessary for predicting human performance outcomes and provides a thorough investigation of existing evaluation methods, including the Big Five personality traits and advanced statistical techniques like failure mode and effect analysis (FMEA) and design of experiments (DoE).

In addition to discussing established human factors methods, the book introduces three models designed to analyze psychological characteristics relevant to IT roles. It offers in-depth insights into human resources across various software processes, such as development, maintenance, and application, while considering the Capability Maturity Model Integration (CMMI) process level five. Overall, this book serves as a vital resource for understanding and improving the human aspects of IT performance, ultimately contributing to more effective risk management in software engineering.