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Shiv Nadar University

Decision Sciences, Operations Management, and Information Systems

In recent years concurrent, overlapping development activities of engineering tasks have proved to be a cost-effective and time-efficient way to build products geared toward meeting the demands of a competitive and quality-conscious market. In this study, we examine the structure and dynamics of a software project in information technology industrial research and development that has this methodology as its foundation. We first describe a number of software engineering aspects of the project that elucidate how various development activities in its concurrently unfolding component projects are overlapped and integrated to gradually build the product over time. Using the mathematical tools of dynamic systems analysis, we next derive a number of results that characterize the long-term, stable behavior of the project. These results are then used in a numerical simulation to illustrate a procedure by which relevant resources can be distributed across the components in a way that maintains continued stability of the project over time. Our modeling approach is flexible enough to allow the theoretical results and the simulation techniques to be easily generalized to study, in real time, the stability, maintenance, and management of similar concurrent projects. The usefulness of the method lies in motivating and refining managerial decisions that drive overlapping development activities of such projects. © 2010 IEEE.

(SME) School of Management and Entrepreneurship

IEEE Transactions on Engineering Management

Concurrent, overlapping development and the dynamic system analysis of a software project

Adopting the framework of a multicomponent, distributed outsourced project in information technology research and development, the present paper introduces a quantitative model of the asymptotic stability of development output in the outsourced project components. Empirical production functions are employed to formulate stochastic distributions of the parameters in the model Observational data from actual industrial projects are compared with prediction results from Monte Carlo simulations of the underlying project dynamics to determine the span of the linear regime of development progress. Simulation-based analysis further provides domain maps of parameter stability. These are valuable tools for project managers and management practitioners to control and sustain the long-term evolution of the project. The points of departure from linearity as well as some of their probable causes are also indicated and discussed. © 2009 Taylor & Francis Group, LLC.