改善施工数据实践并寻找新的方法来使用机器学习和其他高级算法，这是行业中的一个热门话题，但是有些公司已经看到了真正的好处。新利18备用网址这是2月24日至26日举行的Enr 2021年最佳年轻专业人士虚拟会议的专家小组的共识。新利18备用

“The situation is unwieldy but quite exciting. Folks can see the art of the possible,” says Jit Kee Chin, executive vice president and chief data and innovation officer at Suffolk. She added that while the construction industry seems to be overwhelmed with many different point solutions, there is an emerging view that better handling and analysis of data is needed across the board. “I think as an organization, you will streamline access to all the data,” she added.

Kiewit数据服务首席数据官Matt Pappas说：“算法非常渴望数据。”Pappas解释说，在像Kiewit这样的大型公司中使用数据为他提供了大量的项目信息，以违反团队的算法，但即使他也必须处理业内经常不完整的数据收集实践。

Still, even working with sporadic data, his team has developed algorithms for Kiewit's estimating group that have reduced the error rate from an average of 10% to only 1.25% in trial runs. “Right now we’re in the process of getting [that algorithm] into the system of Kiewit Construction,” he says. Algorithms can also be used to calculate the most efficient use of materials during preconstruction, and Pappas says that these data-driven approaches could save Kiewit 40% on estimating takeoff costs for megaprojects. “The industry has a lot of opportunities to evolve with data and analytics,” observes Pappas.

But the benefits of data science aren’t reserved for the big players alone, says Anna Jacobson, senior preconstruction manager with Morley Builders. “Working for a midsized builder is different. We don’t have the same volume of data available to us,” she says. Collecting better data, and building out the systems that will improve the business is often just as much about communication and coordination as it is analytics and data science. “If you’re dealing with an organization that has succeeded through traditional business practices … it’s hard to make a change,” explains Jacobson. “We’re coming at it in a very methodical way, taking it step-by-step.”

Tough Love

But sometimes it takes a little tough love to move things along, says Sam Holden, project executive at Skanska. He recalled one recent project where his team set up all of the project documents and data in the cloud for team members, but some were a bit stuck in their ways and kept doing work offline in Microsoft Excel. The risk this posed to version control and data integrity was beginning to get out of hand, so Holden and his team took drastic measures. “We banned Excel,” he says. While they didn’t uninstall the application from team members’ computers, they issued a rule that project work was to be done in the cloud and set out to build dashboards in PowerBI to collect and analyze relevant information for the team. By building useful tools that the team found superior to their old ways of working, they eventually came around. “Ultimately we were able to get everyone, from our side, from the customer’s side, into one sandbox,” he says.

尽管近年来的数据旅程已经走了很长一段路，但仍有很多工作要做。但是小组成员对事情的进展感到兴奋，并看到变化加速了。雅各布森说：“施工一直依赖文件。”“文档体现了数据，但它们不是数据和信息本身。我们将看到未来五到十年的变化。”雅各布森（Jacobson）预见了一个不太遥远的未来，承包商和其他项目团队成员将获得BIM而不是任何图纸，并且他们将期望他们在没有基于文件的环境的情况下提供项目。新利18备用网址她说：“该行业已经过去了200年，突然之间将大不相同。”

When a question came in from the audience about the threat of ceding too much decision-making control to algorithms or other derivatives of artificial intelligence, Jacobson was quick to point out that it's the busywork, not the high-level decision-making, where this technology will be used the most. “Data is going to be useful for computational tasks, and right now we have a lot of human labor doing that. It’s a mismatch: Humans are not as good at that,” she says. Speaking of her work in preconstruction, Jacobson says she would prefer for a computer to do 80% of the project plan, so that a human could come in then and make the complex decisions about how it all comes together.

Chin同意，数据驱动的建议旨在作为帮助，而不是替代。她说：“这是人类的肯定。”“理想情况下，它采用了一些不太兴奋的工作，并允许我们采用批判性判断。”