No two projects are ever the same, but sometimes engineers are lucky enough to work on similar projects, or project stages, concurrently. This was the case for Nicole Stoddart (pictured), Managing Director, Construction Services Australia/New Zealand at AECOM when she worked in London on an upgrade of St Pancras Station. Half of the project was completed without 3D modelling and the other half used data-driven technology.
“There were a lot of things that happened on the first stage that were design errors but because these were not addressed prior to the concrete being poured, contractor teams had to own and fix the problem by getting the jackhammers out and doing rework,” Stoddart says. “On the second half, when we modelled it we understood that the original design just did not work. This allowed us to refer the issue back to the consultant so they could amend the design before work began.”
The team on that project could see improvement from one part of the project to the next. But when projects are rarely so similar, how do you measure success?
Identify measureable patterns
“It's about the trends,” says Grant Holman, Melbourne Office Manager and Director at Wood & Grieve Engineers. “Issues that arise in parts of a job might seem like isolated incidents, but patterns usually begin to emerge, irrespective of the project.”
David Whatmough, General Manager Asset Management at Laing O’Rourke, agrees. He comes from a manufacturing background and says sometimes working in construction engineering, thanks to the unique nature of every project, feels as if he is a manufacturer who only ever produces bespoke products. But there are still datapoints on every job that can be compared.
“The issue is to break jobs down into small elements, so there are objects and items that are consistent and which you may just arrange in a different order, but the ingredients are still the same,” Whatmough says. “So when you use that certain formwork on a new build in a certain way, and you used it in a similar way on another project with a good quality outcome, you can take that learning and keep the data model up to date.”
Practical examples of measuring success
Such patterns might be seen in elements common to all jobs, says Georgina Mahony, Technical Director Transport Services at Aurecon Group.
“You can measure things like cost per drawing,” she explains. “In 3-D modelling, when you're generating cross-sections, for instance, you begin to see the efficiencies. If I look at our offshoring model and how we collaborate within a global office, you can actually see the efficiencies improve as we increasingly use share tools to collaborate with our peers. This constantly improves as we continue to share information centrally.”
“Along the same lines, in the work I’m doing with the Level Crossing Removal Authority in Victoria, while each level-crossing removal is quite unique, there are aspects that are very similar in each job. So there is a very strong piece going on in terms of what we measure and how we drive efficiencies. It is a bit tricky, but with data you can choose metrics that help you interpret trends, you just need to choose the right ones. Common denominators are important. If we choose the right metrics and use data to pinpoint similarities between projects, this is going to positively affect outcomes.”
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