Developing a dataset of real projects for portfolio, program and project control management research

Area of Science:

• Project Management
• Operations Research
• Data Science

Background:

• Complex project environments often involve inter-related resources and multi-dimensional constraints.
• Standardized estimation techniques are crucial for establishing reliable project baselines.
• Accurate tracking of time-phased costs and progress is essential for effective project control.

Purpose of the Study:

• To introduce a novel, comprehensive dataset for research in managing multiple, resource-constrained projects.
• To provide a standardized dataset for analyzing portfolio, program, and project (PPP) management strategies.
• To facilitate research on the complex inter-relationships between resources, costs, and progress in project portfolios.

Main Methods:

• Development of a dataset from six projects with budgets based on first-principles, bottom-up estimation.
• Inclusion of homogeneous, complexly inter-related consumable and non-consumable resources.
• Standardized collection and attribution of 12,139 actual costs and progress measurements over 109 weeks.

Main Results:

• A unique dataset featuring time-phased actual costs and claimed revenue for each project.
• Detailed, standardized progress and cost data across six projects, ensuring consistency.
• Data captures complex resource correlations, productivity rates, and cost rates.

Conclusions:

• The dataset is valuable for research in portfolio, program, and project (PPP) management.
• It enables studies on the collective control of multiple, resource-constrained projects.
• The standardized nature of the data offers a unique advantage for comparative analysis in project management research.