Team performance and information system implementation

Although the Earned Value Method (EVM), a multi-dimensional project control system, has been widely used since 1960, there has been little research focused specifically on its application in IS implementation. The management of IS projects—including the accurate forecasting of project duration—is complicated by the strong impact of the learning curve on the effectiveness of EVM. This study makes new contributions by advancing formulas for the accurate prediction of project duration, and by developing a decision support model in which the learning curve is fully integrated with EVM, and performance changes due to learning are isolated from other factors affecting project duration. The study makes three contributions to the understanding and use of EVM in IS implementation: (1) It provides an extended version of EVM, (2) it provides an illustration of the application of EVM to a real project situation based on empirical data from an ERP implementation project, and (3) it provides a theoretical basis for empirical studies of IS project control techniques. The decision support model can be used to determine both the learning curve coefficient and the project completion date during the early stages of a project, and it thus offers a significant practical contribution to the management of IS projects.

Malgorzata PlazaEmail:

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Dr. Margaret Plaza   is an Associate Professor of Information Technology Management at Ryerson University and a Senior Research Scientist in IITM. She holds an M.Sc. in Mechanical Engineering and a Ph.D. in Production Engineering from Politechnika Krakowska (Cracow University of Technology) where she specialized in flexible manufacturing systems. Dr. Plaza is also a PEng. (Ontario), PMP, and CIA and has over 20 years’ industry experience working with consulting and manufacturing firms in both private and public sectors. She managed or provided consulting for ERP and supply chain implementations. Her current research focuses on organizational learning, technology management and the supply chain. She has developed decision models and decision support technologies to assist managers with problems in new technology implementations.