Data-driven project management

Smart data are increasingly central in companies, which base their planning and decisions on solid data. They also play an important role in numerous projects. What is the profile of a data-driven project manager? What skills does such a person bring to a team? We ask Mario Vanhoucke, expert and professor in project management and decision-making techniques.

'Project management' is a broad term. In what kind of projects can data play an important role?

In my opinion, you can work with data on any project. The degree of complexity and uncertainty determines the approach. For example, I worked on the project concerning the Westerscheldetunnel in Terneuzen; a project of 10 years with 10,000 activities and 2000 people. That's obviously different from a 2-month project with 10 people. There are also easily phased and quantifiable projects, such as a construction project, and projects that are more process management-oriented, such as a transition.

In data-driven project management, everything revolves around defining parameters, quantifying goals, and estimating risks. I believe that statistics should always - or as much as possible - determine where the goals and challenges lie. Otherwise, you're dependent on human interpretation. Someone might find 80% performance bad, while statistically, it's actually good. It all depends on what you're comparing it to.

A recommended book is 'Thinking, Fast and Slow' by Nobel Prize winner Daniel Kahneman. He says: don't trust yourself too much because we're not rational animals. I agree with that. Data is rational. Use it to objectify reality and make better decisions.

What if you have little data?

Even then, you can work in a data-driven way. I really like working with companies that have little data because then I can show that you can prioritize based on simulations. If 90% of the simulations reveal the same problem, then you've really found a point of attention.

The most important thing is knowing where to expect the greatest impact if things go wrong. And you can find that out with a 'best guess' analysis. Try simulating a small project with fictional data. You'll see how your gut feeling and such a simulation can lead to the same conclusion.

What major developments have you seen in the use of data in projects in recent years?

I mainly see a shift in terminology. I've been coaching people in practice for 25 years now. In the past, I found it difficult to get professionals on board with my 'statistics'. Today, everyone talks about big data, and the enthusiasm is unprecedented. However, I believe it's the same thing.

Project management today is much more data-driven than before. There's also more data available. And modern data analysis is no longer purely mathematical but lies at the intersection of mathematics and psychology. Avoiding 'human bias' has become an important academic research domain. I also involve the human factor more in my lessons and work today.

What makes a data analyst a project manager?

A data-driven project manager is someone who not only analyzes data but also understands and applies project management techniques. The art lies in applying data analysis to both traditional and new project management tools.

I apply data analysis differently in each phase of the project. When creating the plan, it's important to optimize the use of resources (people and budgets), so the analysis mainly consists of optimization techniques. As the project progresses, risks are mainly identified and monitored, so the data analysis mainly consists of simulations. And so, each phase of the project requires a different approach, both in project management and data analysis.

What skills are still important in your role?

I develop methodologies for risk analysis, for creating an optimal schedule, for converting time into costs, etc. I'm mainly a quantitative person. Your top priority is to understand the data story well. Because that's a difficult story that you translate to your team and client. Technical skills such as understanding methodology, data analysis, and statistics are crucial throughout the project. In my new book 'The Illusion of Control,' I show that these technical skills don't have to be that difficult, although you can, of course, go as far as you want with them.

Time pressure plays a role in every project phase, so you need to be resilient to stress and remain critical.

And other 'soft skills' also come into play: being able to lead people, assess the talents of your team, motivate, communicate clearly, be creative and flexible... All these skills are important to a greater or lesser extent in each project phase. So, a data-driven project manager is someone with very diverse skills who can navigate themselves at the intersection of mathematics and psychology.