Data-driven project management with Python

OR&S' Project Management book #8 has arrived! The book "Data-Driven Project Management with Python: Optimizing Schedules, Simulating Risk and Analyzing Project Performance through 10 Example Experiments" is now published by Springer Nature as part of the "Management for Professionals* series. 

This time, the book is meant for doing, not just reading.

Indeed, it has become a hands-on book by design, as it contains 10 Python experiments that let you learn by doing, testing project scheduling, risk analysis, and control yourself rather than just reading about them. It bridges academic research with practical experimentation, connecting what we study with what actually happens on projects.

This book explores how project scheduling, risk analysis, and control can be understood, tested, and taught through data-driven experimentation that guide readers from fundamental scheduling techniques to advanced project control methods, with all data and code provided for readers to reproduce, modify, and extend. It moves through three parts: the first builds on the Critical Path Method and extends it to time/cost optimization and resource-constrained scheduling via heuristics and integer programming; the second uses Monte Carlo simulation to capture schedule uncertainty and measure activity sensitivity for both unconstrained and resource-limited projects; and the third turns to project control, using Earned Value Management to replicate forecasting accuracy studies from the academic literature. Its distinctive contribution is linking theoretical scheduling principles with executable Python models, offering a transparent way to explore how data can drive project decisions while raising questions about data adequacy, the measurement of uncertainty, and the balance between simplicity and realism.

The book takes an educational approach, linking clear explanations with ten reproducible experiments that encourage readers not just to understand the models but to test and extend them. By bridging theory and practice, it offers a hands-on framework for exploring how data shapes scheduling, risk analysis, and project control, making it well suited for courses in project management, operations research, or decision analytics, as well as for self-learners looking to build data-driven project management skills in a structured way

A slightly more personal note

I happened to be in Lisbon (where else?) when the book finally arrived in my mailbox. It was also the day of the solar eclipse (August 12, 2026), so naturally I took the opportunity to make a funny and slightly ridiculous picture with the book and posted it on LinkedIn. With a bit of AI displaying the sunset in the North, I could proudly announce the news of the new publication, extremely happy to see this new release.

As a matter of fact, writing a book is both a rewarding and lonely journey. But sharing it with the world is something different. It becomes a collective effort. Promoting it to an unknown audience is not something you can do alone. It takes a community, and you can be part of it.

If you find value in data-driven project management, I kindly ask you to share this page on LinkedIn and help bring it to people who might be interested.