Construction leaders tackle the industry’s big data problem

By many measures, the construction industry has a large and pricey problem with data management.

An Autodesk study released last fall concluded that data errors produced $1.8 trillion in losses for the construction industry worldwide in 2020. According to the study, 45 percent of construction project data contained minor or major errors while another 24 percent was missing. In December, Trillium Advisory Services released a study warning the industry also has a major problem with dark data. Of the masses of digital information generated for construction projects, only four percent is visible to and used by project stakeholders, according to Trillium.

Opportunities exist to improve construction data management and realize efficiencies and financial gains as a result. But seizing those opportunities requires effort, investment and strategic business decisions.

“One of the biggest challenges that we have faced is data sprawl,” said Ed McCauley, Vice President of Innovation for Wohlsen Construction.

Data about Wohlsen operations and project work was siloed in multiple, disparate computer systems, making it difficult to integrate data and “determine the source of truth” about construction operations, McCauley said.

Last year, Wohlsen decided to address the problem by severing its back-office data systems from its project information, and implementing Procore to handle frontline, project management data.

Before making the switch, “we did a time study where we processed an RFI through our old environment and through Procore. That comparison got the investment approved,” McCauley said. “It took about seven minutes in our old system and a minute and 15 seconds in Procore. When you think about the high quantity of RFIs on any project, that’s a big savings just from one simple, data entry process.”

Procore’s simply processes, streamlined data entry and ability to deliver targeted, timely information to project team members have generated construction efficiencies and increased job satisfaction among many Wohlsen workers, he said.

At the same time, Wohlsen’s decision to break another data management habit produced some unexpected benefits.

“Some of the systems we used in the past were highly customized. But that high level of customization made us more inflexible to change as business requirements, client requirements, contractual requirements changed,” McCauley said. “Also if you take a piece of software off the shelf and try to make it bend to your will and your processes, you might be shortchanging the value you can get out of that software.”

When Wohlsen invested in Procore, “we tried to go in with an open mind and look at whether changing some of our operations to match Procore would give us better processes,” he said.

That examination ultimately delivered benefits, including an improved safety inspection process.

No one software package, however, can solve all the data management challenges within or among construction companies. Improving data management requires a tailored data strategy with clear goals.

“If you try to solve all the data problems at the same time, you will end up spinning your wheels. It’s like playing whack-a-mole: The more stuff you tackle, the more stuff pops up,” said Justin Schmidt who leads the national construction technology group at DPR Construction. “Focus on your biggest business challenge right now and how data could help solve that challenge.”

In early 2020, DPR did just that. As Covid-19 began to delay projects and shut down job sites, DPR realized it needed a deeper, more detailed resource management system than the commercially available systems could provide.

“We went heads down for a couple of months and narrowly focused on how to get more insights into our resources and do a better job at forecasting and planning our resources,” Schmidt said.

The resulting system helped DPR more efficiently manage resources and advance projects during the tumultuous first year of the pandemic.

“It also opened the door to a whole new level of data,” he said. “That is producing great insights into operations across the company and improving our ability with tasks that we couldn’t really do at a scientific level previously – like projecting resources on new opportunities. For example, an owner comes to us with an RFP for a $700 million, ground-up hospital project that will take about two years. Historically, we kind of relied on thumb-in-the-air experience of superintendents and project executives who worked on similar projects, to determine what staffing would look like. But now, we have very, very detailed data around the resources on our projects, from the administration side to the craft workers in the field. We can use that data at scale to very quickly aggregate resource data across eight similar projects and exactly determine staffing needs and plan the project.”