A review of analytical models, approaches and decision support tools in project monitoring and control

• We explore problems, analytical models, and algorithms on project monitoring and control.
• We summarize DSS tools and emphasize integration to project management.
• This review differs from the previous ones on project management; the scope is narrower.
• We discuss the possible research extensions.
• Our conclusion serves as a basis to develop efficient decision support systems.

This paper reviews the problems, approaches and analytical models on project control systems and discusses the possible research extensions. We focused on literature in Earned Value Analysis (EVA), optimization tools, and the design of decision support systems (DSS) that will contribute to helping project managers in planning and controlling under uncertain project environments. The review reveals that further research is essential to develop analytical models using EVA metrics to forecast project performance. It also suggests that DSS should be model driven, function as early warning systems and should be integrated to commercial project management software.