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How to bring big data into project controls

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If you’re a project controller, your peers in management will be depending on you for valuable insights so they can deliver projects on time and to budget. Data analysis tools promise to make the task easier, but it’s not simply a case of installing the latest software and pressing go. Here are five key ways to make project data work for you.   

1. Think quality not quantity 

There’s no point having reams of data at your fingertips if it’s not the right stuff. Data must be accurate, up-to-date and complete. That requires work and scrutiny of your processes.  

“If you’re asking your project managers to provide you certain data, are they doing so?” asks Jonathan Williams, who’s leading the Environment Agency’s drive to become a ‘data-driven project delivery organisation’.  

“If not, why not? Are the tools not intuitive enough? Are you asking them to do too much? Or there may be so many competing priorities that they’re not focusing their time in the way they should.” 

2. Balance technology and people 

Despite the common idea that insights immediately improve how things work, we still need to understand how people fit into that equation.  

For starters, machines don't work perfectly all of the time. Projects need people with detailed technical know-how, so the machines can be challenged and made to work properly. 

Get it right and machine learning tools can remove much of the grunt work behind data, converting raw ingredients into actionable information. This will then free up people to do what they do best — manage stakeholders, make decisions and ensure the project is delivering the right outcomes.  

“Otherwise we risk becoming administrators to a project, rather than managers or leaders,” says Williams.  

3. Open it up 

In the machine learning-driven future of objective data, where project data is open to a far wider pool of people across the project, databases need to be created, owned and managed by everybody. This may not sit well with all project controls professionals, who may be protective of their patch.  

Some hand-holding may be required to help foster a more open data environment, where data is presented via easy-to-use tools with simple interfaces. 

4. Bring on the bad news 

For a proper understanding of a project and its problems, project professionals must feel comfortable telling the truth. Data can be a huge help here, as it provides an objective source. But leadership still has to make it clear that it wants the facts — even when they’re uncomfortable.  

“You need to be able to tell the truth about where your project is, and for that to be received positively by the people in power,” says Paul Kidston, lead author of Project Controls in the 21st Century 

“Because if you don't, you may be covering it up until it's too late to do something about it. Ideally, leadership takes project controls seriously and understands that it's integral to successful projects.” 

5. Look before you leap 

While it’s tempting to put all your eggs into the data basket, it may be wise to exercise caution. When tasked with introducing a project controls database system on HS2, Kidston realised the only way to trust whether it was actually delivering what was expected was to run it in parallel with a good old spreadsheet.  

“I felt the need to prove that the complicated machine was producing the right answer,” says Kidston. “That's how I got the confidence it could do the job.” 

6. Embrace what new talent can bring 

A generation of digital natives is now coming out of university with skills in coding and data visualisation skills. Yet when they come to work on real-world projects, they may find many decisions still being made on instinct and experience. Don’t push back against this changing world. A blend of instinct and objective data can make for a powerful decision-making foundation. 

Look out for the autumn 2023 issue of Project, where we take an in-depth look at project controls 

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