(US & Canada) | Technology Will Assist Humans, Not Eliminate Them — The Boldt Company CIO and CTO

Maribeth Achterberg, CIO and CTO at The Boldt Company, speaks with Thiago Da Costa, CEO of Toric, in a video interview about key metrics to measure organizational success, challenges, getting data sources into a data lake, and key technologies that could evolve the construction industry.

The Boldt Company is a 134-year-old construction management company based in Appleton, Wisconsin, with 17 offices across the U.S.

While deciding on the key metrics to become successfully data-driven, Achterberg highlights the importance of understanding the technological impact before investing in new technology. Instead of going after new technology every time, she advises working on the human element.

According to Achterberg, technology is not going to eliminate humans; it is going to assist them. It is not about eliminating jobs but freeing humans to do higher-order work, she adds.

Therefore, with key metrics, organizations need to assess what could or could not be done unless that data technology is employed, and that builds the business case. It boils down to understanding what metrics are necessary for organizational development.

For instance, Achterberg mentions omnipotent financial metrics and recalls having financial KPIs and process metrics. She states that there are process-level metrics that, once identified, can roll up to a financial metric.

Adding on, Achterberg notes that any process that needed improvement and data application was tied to a financial metric. Further, the process metric heavily depends on the enterprise's needs.

Giving an example of a process metric, Achterberg refers to a year-end financial close and how black-out periods prohibit improvements in systems. In this scenario, if the cycle time is reduced, it can create opportunities and improve the bottom line.

Highlighting challenges, Achterberg points out the challenge of not knowing the data source, as some of it is automated and some are not. In the construction domain, a subcontractor or excavating company is not automated at all.

Consequently, it is critical to consider everybody’s data maturity level and what can be done to improve information flow into the data lake or warehouse. Achterberg advises picking a process that would create value, tracing it all the way to the information source, and automating it to the best possible level. She recommends having a proof-of-concept that would work for other businesses and different processes.

When asked about the approach to taking the data sources to the lake or warehouse, Achterberg states that it depends on the automation level of the company. She assumes that larger construction organizations may have an ERP or CRM system or an all-in-one integrated system.

While working with Johnson Controls, Achterberg admits to once thinking of getting all the ERPs in one instance, which turned out to be expensive and time-consuming. Now, she mentions thinking of it as a data issue and getting those systems to feed back into a data lake.

Delving further, Achterberg states that organizations should first think about where the system of record should be for a particular data domain or element, and then feed back into a data lake. She maintains that data latency is a massive delineator of solving the problem of whether or not to get everything in one ERP or get feedback into the data lake at regular intervals.

Emphasizing the key areas that could potentially evolve, Achterberg believes that there will be more technology-infused construction. Elaborating, she reflects on the safety quotient in construction and how technology is used to keep construction workers safe.

Speaking of technological advancements in construction, Achterberg mentions gear sensors, employing robots and robotics, and 3D printing, apart from exoskeletons. She asserts that like in manufacturing, robotics is feasible to employ and scale for the construction industry as well.

Furthermore, Achterberg discusses leveraging virtual reality in the pursuit part of the sales process as an opportunity. She confirms that generative AI is going to be a useful tool in construction, as, for instance, companies can get better at estimating by deducing patterns from a hundred years of project estimates.

Concluding, Achterberg states that while there is an opportunity, the data must be of good quality. That underscores the need for good data management and governance practices, ensuring that organizational people are data literate.

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

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