Real project data

We are currently working hard on collecting real data and classifying it into a new commercial project database. The database will contain baseline scheduling data (network, resources, ...), risk analysis data (for Monte-Carlo simulations) and project control data (using EVM and ES metrics). This website is continuously under construction (see history at the bottom of this page) and new data will be added upon availability. 

Empirical project data

The collection of empirical project data started in 2008 (with the first projects finished in 2011) and the data and interesting references are as follows:

Classification: The original database, consisting of 52 empirical projects, has been proposed in the study of Batselier and Vanhoucke (2015). The data is classified using two criteria (completeness and authenticity) using a colour code (green, yellow, red). This classification model is presented in this paper.

Batselier, J. and Vanhoucke, M., 2015, "Construction and evaluation framework for a real-life project database", International Journal of Project Management, 33(3), 697–710 (doi:10.1016/j.ijproman.2014.09.004).

More data: In 2016, we started to provide the literature with an overview of both artificial and empirical project databases, as summarised in Vanhoucke et al. (2016). Things changed to quickly that the paper was out of date after one year. A recent update, with more references, is available at our project data website. 

Vanhoucke, M., Coelho, J. and Batselier, J., 2016, "An overview of project data for integrated project management and control", Journal of Modern Project Management, 3(2), 6–21 (download).

Full summary: In 2023, the database has been updated and consists now of 181 empirical projects. The update is described in the book "The Illusion of Control" by Vanhoucke (2023).

Vanhoucke, M., 2023, "The illusion of control: Project data, computer algorithms and human intuition for project management and control", Springer, In Press (coming soon)

The data: The projects are available as the DSLIB dataset and accompanied by an MS Excel file providing a summary. Visit our project data website for more information.

Download the dynamic scheduling library (DSLIB) from the OR&S project data webpage

Download our data

History

• Last update (April 2023): The database now consists of 181 projects as described in "The Illusion of Control" by Mario Vanhoucke.
• August, 2019: 8 projects added (C2019-01 to C2019-08) with corrective actions for the paper "Integrating corrective actions in project time forecasting using exponential smoothing" (Journal of Management in Engineering, 2020, doi: 10.1061/(ASCE)ME.1943-5479.0000806)
• October 19, 2016: 34 new projects added (ProTrack and MS Excel file format)
• December 10, 2015: 32 new projects added (ProTrack and MS Excel file format)
• On March 15, 2015, I promised to put some excel files online with data for 10 projects. While all projects above can be downloaded in ProTrack format, 10 of them are available in MS Excel format and can be downloaded here. 
• January 21, 2015: 5 new projects added.
• July 9, 2014: Project cards for 16 remaining projects added.
• June 2, 2014: ProTrack files for C2013-05, C2014-01, C2014-02 and C2014-03 added.
• April 23, 2014: 51 projects added (some still to be completed).
• Update: March 14, 2014: Website constructed and documents to add your data added

Submit your own data

• Guideline for project data input: Description of the data we need, classified in necessary and additional data points.
  • Data points that are “necessary” refer to inputs we really need since otherwise we cannot analyse the data.
  • Data points that are “additional” refer to inputs we really like to have to support our research, but if you don’t have them, it’s not a major problem.
• Project data input sheet: Excel sheet where the data can be plugged in. Alternative formats such as txt formats are also welcome but the excel file can be used as a guideline for the way data should be formatted.
• Project card: Summary card we will make for each project you deliver.