Better project management thanks to better data
The Illusion of Control: Project Data, Computer Algorithms and Human Intuition for Project Management and Control - new book by Mario Vanhoucke
By Mario Vanhoucke
Professor of Decision Sciences
“Anything that can go wrong, will go wrong. Daily life in project management is exciting – I don’t need to convince anyone of that,” says Professor Mario Vanhoucke. “But people are much less aware of the more academic side of the story, the facts and figures.” Statistics can be incredibly exciting too, as he demonstrates in The Illusion of Control: Project Data, Computer Algorithms and Human Intuition for Project Management and Control. And although data plays the starring role in this book, it is a story about people too.
Taking stock
Mario is a man with a mission: to convince as large an audience as possible of the importance and possibilities of data-driven project management – the quantitative tools and techniques to support projects. He has considerable experience under his belt: this is his sixth book on the subject. His previous publication, The Data-Driven Project Manager, focused on the practice of project management, and it was written in the form of a novel. The Illusion of Control takes a different tack. “Everyone has their own way of understanding things. That’s why each time I take a different approach to tackling the same subject.” This time, he approaches the role of data from an academic perspective. During a lecture at a conference for professionals, he had noticed that they were also genuinely interested in academic research.
As it happened, that conference was almost exactly twenty years after he completed his doctorate. “And after twenty years, you do take stock of your career now and then,” Mario smiles. “I realised I’d come a long way with my academic colleagues, students and people in the field. They have helped to shape my career and research, and I wanted to thank them for that – not with a traditional acknowledgements page, but by interweaving the stories of our work together through the entire book.”
Three to remember if you want to get to grips with data
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From research to practice in five parts
The Illusion of Control is in five parts. After a first, introductory part on the basic principles of data-driven project management, the data you need and the various methods you find in the literature, the next three parts form the lion’s share of the book. Part two describes how academics use project data to test new ideas and methods. It considers the existing techniques and increases understanding of why this data is usable for certain projects but not for others. Then it discusses the various new statistical techniques that may deliver considerably better results. Finally, it elucidates a few advanced techniques, such as machine learning. Mario reveals a glimpse of this part: “Machine learning surely has potential, but it is still too early for practical applications in project management.”
Academic research must be practically relevant, Mario believes. In his leisure time, he paints – his paintings give shape to his creative imagination. He feels that he is an artist in his field of research as well. “That is where I give my academic imagination free rein, but ultimately it needs to culminate in something concrete.” Part three is illustrated with case studies, and it recounts what researchers do to bridge the gap between theory and practice. The fourth and most substantial part focuses on project data. “Where do we get project data from? How do we generate it? Where do we save it? What do we do with it – or, in other words, how do we analyse it?” In the fifth and final part, Mario sketches the four characteristics that he believes define the perfect researcher.
Artificial and empirical data
So the emphasis is on data, but what data? “On the one hand, you have data that describes the characteristics of a project, such as the construction of a bridge, which means the activities, the relationships between those activities, the run time, cost estimates and so on,” Mario explains. “On the other hand, you have progress data, which is data about the work done on a project. Now, there are three ways to obtain this data. You can generate artificial project data. That seems simple, but it isn’t; you need to get it just right, so that you can do relevant research with it. So it's more complex than just throwing a few figures into a spreadsheet. You can also collect empirical data: data from real projects. Once again, that isn’t as easy as it seems. Everyone has project data, except the data that's really needed. Last but not least, you can derive artificial data from the empirical data using statistical techniques.
Data calibration
The trouble is that empirical data contains errors, falsehoods and biases: the project was delayed by three weeks, but the reports say it was on time. Project data is sometimes also interpreted incorrectly: say an activity took four days, but reporting is weekly, those four days may become five. So it is crucial to calibrate data in such a way that you obtain the truth, that you filter out the human errors, as it were, until what is left is the real data for academic research. In fact, the book devotes an entire chapter to data calibration.
“By using real data from past projects in research, we gain useful insights that help to predict budgets and run times better in practice, and to trace losses of control or deviations,” Mario explains. “You see,” he enthuses, “that is the ultimate goal of our research: to manage projects better thanks to better planning, better risk management and better monitoring during implementation, based on data and statistical methods.”
Accessible and original
The Illusion of Control is the story of twenty years’ research and experience, brought together in an accessibly written book that is so comprehensive that both beginners and readers with experience will have something to gain from it. It is aimed at both theoreticians and practitioners. Researchers familiar with the academic literature will find context in this work: the bigger picture that is missing if you only read individual studies. Professionals in the field will gain a unique glimpse behind the scenes of scientific research, insight into the theoretical substantiation of practical tools and techniques, and a foretaste of what will be possible in the near or distant future as better data becomes available.
Furthermore, besides being an in-depth work about the academic background of data-driven project management and the unceasing search for practical relevance, The Illusion of Control is the story of Mario’s collaboration with people who have gone from being professional contacts to becoming friends. That is precisely what makes this book so original.
Want to read more?
The Illusion of Control: Project Data, Computer Algorithms and Human Intuition for Project Management and Control is published by Springer and available from good bookshops. You can also order the book on Amazon.