Maribeth Achterberg, CIO and CTO at The Boldt Company, speaks with Thiago Da Costa, CEO of Toric, in a video interview, about the company and her role, the organizational data culture, the impact of the AI and data wave on construction, and the cultural challenges of harnessing data in organizations.

Achterberg introduces Boldt Company as a 134-year-old construction management company based in Appleton, Wisconsin, with 17 offices across the U.S. Shedding light on her journey, she mentions spending decades in the IT and engineering world.

In addition to working in the transportation and utilities sector, Achterberg has worked as a consultant and owner of her consultation practice for a decade. Further, she has 10 years of experience in manufacturing for Johnson Controls in IT and engineering operations and Molson Coors beverage company as VP Solutions Delivery.

Speaking of her role at the Boldt Company, Achterberg states that the opportunity excited her. She adds that the role sits on the executive team in an industry that is considerably behind from the IT and data perspective.

Next, Achterberg asserts that data is finally getting its day in the sun due to the advent of AI. Stressing the importance of data, she notes that IT should be concerned about data on a daily basis.

Highlighting the data culture in the company, she states that being a construction management company, many people are interested in data as it is all about information. She maintains that everybody wants to solve the data issue but in their own silos.

Additionally, Achterberg states that organizations must have ways of thinking about data and working around data. Boldt has a small team of people dedicated to analytics and needs a cohesive strategy on how to leverage data as an organizational asset. Therefore, having a seat at the executive table enables her to have those conversations.

Emphasizing the AI and data wave in construction and how it relates to business, Achterberg takes the instance of having digital twins in the form of 3D models of buildings. She adds that one can look at the 3D models and understand how the different systems fit together.

Regarding parallels in manufacturing, Achterberg discusses having machine sensors that send back information like machine failure. Taking the instance of large construction projects, she says that over-usage of heavy equipment could cause failure and would cost millions waiting for the replacement.

In continuation, Achterberg states that through preventive maintenance analysis, a spare part could be arranged beforehand. By using technology in construction, organizations can improve the cycle time (time spent from beginning to completion of a project) and reduce the time to value for the owner and the occupant of that particular building.

Moving forward, Achterberg says that the demand for intelligent operations varies depending on the sector. She considers it to be a meeting between the owner and the construction company about the different types of technologies or the way data is used.

Anything done to build the building in time and on budget is good and cycle times are reduced by leveraging data, says Achterberg. The same ideas are extendable into construction management and construction in general, she says.

When asked about the challenges of harnessing data, she states that the challenges are people-centric, regardless of the domain. Achterberg stresses the importance of understanding the value of data and that in some cases it might be saleable.

Whereas, there is a disconnect in terms of how people think about data. Highlighting the digital twin, she maintains that it should not be thought of as digital exhaust. Achterberg notes that AI has been a huge accelerator in large language models, specifically generative AI.

How people think about data is a greater issue than industry-specific issues, she affirms. Achterberg adds that in the construction space, data is siloed and function-specific in many cases. To address this issue, it is critical to help people understand that while data generated in each silo is important, it needs to align with the other silos of marketing or HR.

Furthermore, Achterberg says that it is crucial for people to be data literate and understand its usage across the value chain from beginning to end. It is fundamental for them to be able to comprehend if the data generates revenue, and that it aligns from a data governance standpoint.

Concluding, Achterberg believes that it is a cultural misalignment that needs to be changed. She states that organizational people must treat the information created as an asset to be nurtured and not as exhaust.

CDO Magazine appreciates Maribeth Achterberg for sharing her insights with our global community.

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