Knowledge-based portfolio analysis for project evaluation
Information and Management
Resource-constrained project scheduling: a survey of recent developments
Computers and Operations Research
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
A Case for Using Real Options Pricing Analysis to Evaluate Information Technology Project Investment
Information Systems Research
Understanding software project risk: a cluster analysis
Information and Management
Optimizing an IT Project Portfolio with Time-Wise Interdependencies
HICSS '06 Proceedings of the 39th Annual Hawaii International Conference on System Sciences - Volume 08
Project Assignments When Budget Padding Taints Resource Allocation
Management Science
Contingent Portfolio Programming for the Management of Risky Projects
Operations Research
Risk management in ERP project introduction: Review of the literature
Information and Management
Research on Multi-project Scheduling Problem Based on Hybrid Genetic Algorithm
CSSE '08 Proceedings of the 2008 International Conference on Computer Science and Software Engineering - Volume 01
It portfolio management step-by-step: unlocking the business value of technology
It portfolio management step-by-step: unlocking the business value of technology
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Managing project portfolios has been a challenge to many IT organizations due to the size and complexity of their initiatives that are often cross-functional, fast changing, and transformational in nature. A governance process on project solicitation, evaluation, and monitoring is thus essential to ensure the resulting portfolio creates tangible values, balances across priorities, and supports business objectives. An optimization model to streamline the decision processes for IT portfolios and programs is proposed. We consider project characteristics such as the extent of strategic alignment, expected benefit, development cost, and cross-project synergy to maximize the portfolio value. We also consider team proficiency and resource availability to determine a project portfolio that could be implemented within the overall development time. The multi-objective model identifies the optimal mix among project types and the solution procedure efficiently produces recommendations that are superior to those found with current empirical techniques. We also describe an evolutionary algorithm to find approximate solutions to the optimization model. Possible extensions on how the optimization procedure can go beyond projects to also streamline decisions such as the renewal or replacement of in-flight applications is discussed.