PCL Innovates to Standardize Industrial Project Data Management

PCL, one of Canada’s largest employee-owned construction companies, is making significant strides in standardizing industrial project data management. The initiative aims to address the challenges posed by inconsistent technical information across various construction projects, a concern highlighted during a recent community coffee event in Edmonton.

During the event, Rowan Andruko, a member of PCL’s industrial data science team, showcased examples of disparate product descriptions for identical piping components. “There is no industry standard for the description of these components,” he stated, illustrating how varying descriptions can delay project progress. This issue is particularly critical given that investment in building construction in Canada reached a staggering $24.5 billion in November 2025, with $6.9 billion allocated to non-residential industrial projects, according to Statistics Canada.

The discussion was led by Zach Storms of Built World Tech, featuring Brian Gue, PCL’s manager of data science, and several students from local universities, including MacEwan University and the University of Alberta. Their diverse backgrounds, ranging from mathematics to fine arts, contributed to a rich dialogue on how to leverage technology to transform industrial construction.

The construction sector faces the daunting task of managing vast amounts of technical data generated by large projects. Gue emphasized that the industry has struggled with productivity, reporting an average growth of just 0.4% annually since 1997, a trend that worsened in 2023. As construction jobs remain unfilled at higher rates than before the pandemic, Gue noted that the pressure to streamline processes has intensified.

Gue described the current information handling process as “information reconstruction from one party to the next,” highlighting the numerous handoffs that require reinterpretation. Addressing this inefficiency, PCL’s team is developing tools to standardize components, simplify reporting, and improve project management efficiency.

Innovative Solutions for Data Standardization

One of the tools being developed is titled “Boyle.ai — Universal Technical Translation.” This system aims to standardize thousands of technical descriptions into a consistent format before materials can be procured. Currently, this process is largely manual, with workers spending extensive hours translating each component. “Normally done by hand, with a couple of people sitting in front of Excel sheets for hours, days, or even weeks,” the PCL presentation detailed.

To expedite this process, the team is employing machine learning and artificial intelligence to classify and standardize data. Each automated translation is accompanied by a “confidence score,” which helps users gauge the reliability of the information. Andruko explained, “This confidence score is important for a user’s sense of trust for the tool.”

The data acquisition process presents its own challenges, as PCL primarily relies on internal data due to the lack of available datasets. Andruko revealed that it took the team a year to compile 80,000 records, which is relatively small for machine learning applications. To overcome this, they create artificial datasets that mimic real-world conditions, enhancing the algorithms’ accuracy.

Cross-Functional Collaboration and Immediate Impact

The PCL team’s approach involves collaboration across various disciplines, integrating insights from engineering, mathematics, and the arts. Michelle Fribance, a data scientist with a background in fine arts, emphasized the importance of making project reporting more intuitive. Her design strategy focuses on low-fidelity mock-ups that encourage constructive feedback on data visualization, rather than aesthetic details.

The team also responds to immediate project needs, as demonstrated by an intern-developed tool that geolocates devices within construction drawings, linking them to a digital twin of the facility. This innovation significantly reduces the time spent deciphering original design intent, streamlining project workflows.

Another initiative, named “Beeline: Precision Electrical Optimization,” aims to enhance the planning and visualization of electrical routing, which is critical in large industrial projects that often involve extensive electrical runs. By mapping these routes in advance, PCL seeks to minimize delays and manage risks effectively.

Gue believes these practical solutions can bridge industry-wide gaps, stating, “It’s usually a tip-of-the-iceberg situation.” Addressing small, localized problems often leads to insights that can benefit the broader industry.

As PCL continues to refine its digital tools and processes, Gue highlighted the importance of a structured approach, allocating about 80% of the team’s time to priority business needs while reserving 20% for experimentation. This balance enables the team to develop solutions that directly impact operational efficiency and project success.

In summary, PCL’s efforts to bring order to industrial project data represent a significant step forward in addressing long-standing challenges within the construction sector. By leveraging technology and fostering collaboration, PCL aims to enhance productivity and ultimately reshape the future of industrial construction in Canada.