|Ph.D Student||Eilat Harel|
|Subject||Evaluation, Selection and Control of Projects in|
a Multi-Project R&D Environment
|Department||Department of Industrial Engineering and Management||Supervisors||Professor Boaz Golany|
|Professor Avraham Shtub|
|Full Thesis text|
Research and development (R&D) management in multi-project organizations is concerned with doing the projects which best meet the strategic objectives of the organization, and with assuring that projects are executed efficiently. In this thesis we provide methodologies that can improve the R&D management in multi-project organizations and that address the evaluation and selection process, as well as the control process.
The thesis is composed of three articles. In the first article we provide a multi-criteria approach for the relative evaluation of R&D projects in different stages of their lifecycle, based on a performance measurement model that is derived from and supports the organization's strategy. The evaluation model recognizes that the information available in R&D decision-making is uncertain, incomplete, and partially qualitative, and addresses the three common goals that organizations are trying to accomplish: 1) Effectiveness: achieve the strategic objectives 2) Efficiency: optimize the usage of resources in generating desired outputs, and 3) Balance: obtain balance in the use of inputs and the production of outputs. In the second article, we developed a methodological process for the construction and analysis of portfolios for R&D projects with interactions. The process includes the following parts: a procedure to allocate resources to project categories; a procedure to evaluate and screen projects based on their relative value and on the portfolio requirements; a procedure to construct candidate portfolios; and, finally, a procedure to evaluate these portfolios. In the third article we adapted the earned value method (EVM), which is used as a control method during project execution in many industries and organizations, to R&D projects. We developed an analytical model of an R&D project with the essential elements of EVM, and used it to analyze the factors affecting the EVM measures and to compare different forecasting models of the final cost of the project.
In this thesis we used and studied well established managerial methodologies, including the data envelopment analysis (DEA) and its weight restrictions expansions, balanced scorecard (BSC), and the earned value method. New models and solutions approaches were developed, including an extended DEA model, which quantifies some of the qualitative concepts embedded in the BSC approach, and an R&D project model that uses elements of EVM. The proposed approaches are illustrated though case studies and numerical experiments, and new insights are provided from the analysis.