The Illusion Of Control: Project Data, Computer Algorithms and Human Intuition for Project Management and Control

• Title: The Illusion of Control: Project Data, Computer Algorithms and Human Intuition for Project Management and Control
• Author: Professor Mario Vanhoucke
• Published by: Springer
• Where to find it: https://link.springer.com/book/10.1007/978-3-031-31785-9

More and more our lives revolve around data – how to collect it, where to store it, how to understand, read and analyse it and, increasingly, how to use those understanding to make better decisions. For those that are computer and data literate these exists the opportunity to gain an inside track or an advantage against the competition, a sense of assurance in the choices they make and even a window to the future.

It’s a shame then that, even now, so few senior-level professionals are able to tap into such a super power effectively.

Enter Mario Vanhoucke, a Professor of Decision Sciences at Vlerick Business School in Belgium.

Mario is described by the School as passionate – something backed up by his CV. Not only is a Professor at Vlerick, he also acts as Head of both Operations Management and the School’s Information Science Centre, and teaches across its MBA, Masters and Beijing International MBA programmes. Vlerick isn’t the only institution to benefit from his expertise as he also holds a faculty position at the UCL School of Management in the UK

He’s also a prolific author, with research published across academic journals and several books to his name.

With a solidly established background in project scheduling, risk analysis and project control, his research expertise focus on how to fine more effective ways to measure, improve and optimise resource efficiency and performance – guiding industry in doing so. Data analysis and data management is now a natural part of such endeavours and Mario has turned this passion to focus on exactly this topic. His latest offering to the world “The The Illusion of Control: Project Data, Computer Algorithms and Human Intuition for Project Management and Control” seeks to asses the growing importance and relevance of project data for professionals across industry and fellow researchers alike.

Data collection, analysis and implication is not as straightforward as people might think, Mario suggests. Nor should it be a skill solely left in the hands of the tech team or the CIO. Mario’s book offer insight, advice and guidance for those management professionals seeking to gain a better understanding of how to utilise data to best effect, and also reminds us of the power of human intellect and intuition.

We sat down with him to find out more…

Can you tell us about the inspiration behind your new book? What motivated you to write it?

Since I have been investigating the use of data-driven methods to better manage projects for years now and have seen the growing interest from practitioners in this field in recent years, I got the idea to tell this academic research journey into relevant themes around project planning, project risk analysis, and project control.

I did not just want to provide a mere overview of existing methods but to contextualize them in a complete narrative to convince practitioners that some methods are easy to implement (so there is no reason not to do it). In contrast, others may require more experience and affinity with statistics and may be a bit more challenging to implement.

This book is written for academics who want to know the latest research and for practitioners who need and are willing to implement some existing, improved, and even completely new methodologies for managing their projects.

Since the book’s topic fits within the growing interest of project managers in data and methodologies using statistics and artificial intelligence, I decided to write the book right now.

What are the key takeaways or main ideas readers can expect to find in your book?

The main takeaway is that there are few reasons not to transition to data-driven methods for project management because there is something available for everyone. For this reason, I divided a specific part of the book into three parts.

In the first part, I discuss the research using an existing technique for project monitoring (Earned Value Management). I compared different versions of this method to better understand why this technique sometimes works very well for some projects but can also fail for others.

While many project managers already use the methods of the first part, in the second section, I proposed statistical extensions of these methods to convince the project manager to take the next step towards improvements. Implementing them is a bit more challenging but not impossible and leads to better results.

Finally, in the third section, I presented very advanced methods that are not yet widely used in practice but which, I believe, represent the future. I wrote this part mainly to demonstrate that academic research can sometimes dream of a further future by proposing totally new methods, hoping that some major companies will adopt them one day (after which smaller companies may follow suit).

Who is the target audience for your book, and how do you believe it will benefit them?

As I mentioned, the target audience includes both academics and practitioners with experience in small or large projects.

For this latter group, I mainly aim at the growing number of practitioners who are open to a research perspective on their world. The book does not offer practical software tools but instead presents the results of experiments that can be translated into usable methodologies. If so, the project manager who wants to implement some of the discussed techniques needs project data (extensively discussed in many chapters of the book) and knowledge of various methods, ranging from simple spreadsheets to more advanced statistical methodologies and simulation techniques.

My main aim is to convince project managers that making decisions in project management should not solely rely on experience or intuition but should also be supported by data analysis. Hence, the title ‘The Illusion of Control’ suggests that combining intuition and data analysis is the safest way to break through that illusion.

Using data and statistics might be a small step for a project manager, but it is a huge step for project management.

What do you think makes this topic particularly relevant or timely in today’s business world or for the years ahead?

The relevance for today’s project management lies mainly in the growing importance of high-quality project data, which was undoubtedly fuelled by the big data hype and the increasing interest in artificial intelligence. I also want to mention that my book is not about artificial intelligence but rather about the correct use of data as the primary and most important factor in eventually transitioning to artificial intelligence.

I also want to demonstrate that many AI methods are heavily based on old and existing statistical methods and are not as new as they seem. So, it is essential to understand this foundation to not blindly jump on the hype without understanding the underlying workings.

I am convinced that the importance of data-driven decision-making in projects will continue to increase. In recent years, I have noticed an evolution in research interest, shifting from ‘very theoretical and too difficult to apply’, to ‘challenging but with practical relevance’.

Please share some practical tips or strategies from your book that readers can immediately apply to improve their business or career

I believe there are two important tips that I want to convey in the book.

Firstly, I firmly believe that practice should not be blind to what is happening in academic research. It is easy to describe research as theoretical and out of touch with reality, and initially, it may sometimes be. Still, it seeks foundations and insights that can be relevant to practice. Therefore, research is best stimulated by people with practical experience but who are interested in academia because this interaction leads to the most beautiful and often most relevant results. Many practitioners have contributed to this book; some are mentioned, others had no idea they did.

Secondly, I also want to emphasise that it does not have to be as tricky as it seems. I admit that I presented some methodologies many project managers will not easily implement. Still, nobody learned to ride a bike on a racing bike (you better start first with the support of extra wheels). Therefore, a step-by-step process towards a more data-driven approach, starting with the easy methods, is the only correct way to take that inevitable step in a quality manner. The book tells this story.

Can you discuss any specific case studies or real-world examples from your book that illustrate its principles in action?

Many case studies are available in both research and specialised literature, although they are not addressed in my book.

Instead, I dedicated an entire chapter to the empirical dataset of projects I have built up over the years. I demonstrated that most results were obtained through computer experiments on artificial projects (created without any connection to reality) but that the validation of the experiments was indeed carried out on real projects from various sectors (construction, maintenance, IT, etc.).

Furthermore, I argue in the book that I consider this the best method to gain a better understanding. Artificial project data can be generated under controlled design to answer the research question as effectively as possible, and validation on real projects is, of course, important but only comes afterwards.

If such an approach means that some results from the research are not practically usable, then so be it, and it indicates that the research question was not very interesting (because reality never lies). Fortunately, this did not happen very often.

How does your book add to/expand existing discussions on this topic?

I believe that the current book primarily expands the growing discussion around the use of data for projects by truly delving into depth. It is not a book to read on a cosy Sunday afternoon with a beer on the terrace. This book delves deep and tells the story of a quest for quality use of project data and statistical techniques, involving technical details and results from rigorous computer experiments.

Finally, what book(s) written by another author would you recommend as essential reading for your audience and why?

There have been quite a few books written on project management, and I definitely recommend the following two books (although they approach the subject differently):

• Project Management Analytics: A Data-Driven Approach to Making Rational and Effective Project Decisions, by Harjit Singh
• Leading Complex Projects: A Data-Driven Approach to Mastering the Human Side of Project Management, by Edward W. Merrow and Neeraj Nandurdikar

Additionally, my book contains one chapter on the so-called reference class forecasting method. If the reader becomes interested in more, I recommend the following book (which I believe is one of the best books ever written in this domain):

• How Big Things Get Done: The Surprising Factors That Determine the Fate of Every Project, from Home Renovations to Space Exploration and Everything In Between, by Bent Flyvbjerg and Dan Gardner

Of course, I would be lying if I did not think that my previous book is also interesting (which received positive attention and was the reason for writing the current book):

• The Data-Driven Project Manager: A Statistical Battle Against Project Obstacles, by Mario Vanhoucke

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