A Simulation-Based Decision Support System for Managing Information Technology Project Portfolios

The complicatedness in conducting software development derives from the probabilistic assessment of future conditions or unclear requirements and project implications. Information technology project portfolio management is more complex and presents program managers with the challenge of dynamic decision-making in the context of target revisions and project selection (continuation of active projects at various budgeting levels, termination of other active projects and launching new projects). The authors propose a simulation-based decision support system for managing information technology project portfolios. At each control (decision) point, this data support system enables 'optimizing' each project planning subject to alternative determinations of time and cost chance constraints, and evaluating the up-to-date chance of alternative project selections being within the project portfolio budget. These 'optimizations' and evaluations are provided by a stochastic procedure based on Monte Carlo simulations. In contrast with deterministic procedures that are highly inadequate since they mostly provide erroneous results, the stochastic procedure is appropriate since it analyses a higher level of information and provides more accurate results. The proposed system enables the program manager to decipher highly complex simulation results and make decisions based on up-to-date data. It can be easily implemented even by non-experts.