PCL Innovates to Standardize Industrial Project Data Management

PCL, one of Canada’s largest employee-owned construction firms, is taking significant steps to standardize industrial project data management. During a recent community event in Edmonton, team members shared insights into the challenges and solutions associated with the vast amounts of data generated in large construction projects. The discussions emphasized the pressing need for consistency in data representation to streamline processes and improve overall productivity.

At the heart of the problem is the absence of an industry standard for describing components. Rowan Andruko, a computer science graduate working with PCL’s industrial data science team, highlighted this issue by comparing two descriptions of the same piping component. One originated from an engineering firm, while the other was adapted for use in PCL’s fabrication shop in Nisku, Alberta. “You can see they’re quite different, but they contain the same information,” Andruko noted, illustrating the complexities faced by professionals in the field.

The event, led by Zach Storms of Built World Tech, featured contributions from various team members, including Brian Gue, manager of data science at PCL. Gue’s team blends expertise from applied mathematics, engineering, and design, showcasing a diverse range of perspectives. Presenters included students from MacEwan University and the University of Alberta, whose high-quality work and delivery underscored the importance of fresh talent in the industry.

The discussions centered on a common challenge in industrial construction: the overwhelming volume of technical information generated by large projects that must be reconciled before any work can commence. According to Statistics Canada, investment in building construction reached $24.5 billion in November 2025, with $6.9 billion allocated specifically for non-residential projects, including industrial construction. As Gue pointed out, the industry’s current productivity levels, which have averaged just 0.4% annual growth since 1997, indicate a need for more efficient data management practices.

The data challenges are compounded by labour shortages. Statistics Canada reports that construction jobs remain unfilled at rates higher than pre-pandemic levels. Furthermore, BuildForce Canada forecasts that 270,000 experienced tradespeople will retire between 2025 and 2034. As Gue emphasized, the way information is managed within projects becomes crucial in this context.

He described a process termed “information reconstruction,” where data must be interpreted multiple times as it moves through various parties. Each handoff requires a new interpretation, leading to inefficiencies. To address this, PCL is developing tools aimed at standardizing components and simplifying reporting processes. For instance, the team presented “Boyle.ai — Universal Technical Translation,” a tool designed to convert thousands of technical descriptions into a consistent format for procurement and fabrication. Currently, this task is manual, often requiring teams to spend hours or even weeks translating components.

To enhance efficiency, PCL is leveraging machine learning and artificial intelligence to automate classification and standardization. Each automated translation is accompanied by a “confidence score,” which helps users gauge the reliability of the results. “This confidence score is important for a user’s sense of trust for the tool,” Andruko explained. The team continuously retrains their machine learning models, employing a competitive approach akin to sports playoffs, which ensures that only the best-performing models are used.

The arduous journey to gather adequate training data for these models has posed significant challenges. “It took us probably a year to get 80,000 records, and that is not very much data for machine learning models,” Andruko noted. To supplement this, the team synthesizes artificial datasets that mimic real-world patterns, allowing algorithms to practice and improve their accuracy.

Project reporting and forecasting are highlighted as critical elements for successful project management, encompassing cost, schedule, hours, and quantities. Michelle Fribance, a data scientist and engineer with a background in fine arts, aims to make reporting more accessible and insightful. She emphasizes the importance of focusing on data visualization rather than aesthetics during the development phase. “We want our clients to focus on things that matter and things we need input on,” she expressed.

Beyond design, some tools developed by PCL arise from immediate project needs. A notable example is a system created by a summer intern that geolocates devices within a drawing set, linking them to a digital twin of the facility. This innovation allows teams to see the exact location of equipment without sifting through numerous drawings, thus saving time and reducing misunderstandings.

Another tool, “Beeline: Precision Electrical Optimization,” addresses the complexities of electrical planning in large industrial projects. By mapping and visualizing cable routing before installation, the team aims to mitigate delays and manage risks effectively.

Gue shared insights into the operational philosophy of his team, likening it to a startup approach. “Work out in the open,” one of the key principles, promotes collaboration and transparency. Approximately 80% of the team’s time is dedicated to addressing prioritized business needs, while the remaining 20% is allocated for experimentation. This structure ensures that tools are relevant and valuable to users, measured by their ability to reduce manual effort and enhance decision-making.

While significant strides have been made, Gue acknowledged that the industry still has a long way to go in adopting digital-native decision-making processes. “It’s up to us to create compelling solutions for our industry,” he stated, emphasizing the need for algorithmic thinking to enhance project management.

In conclusion, PCL’s initiatives to bring order to industrial project data management reflect a commitment to improving efficiency and productivity in a sector faced with evolving challenges. By harnessing technology and fostering collaboration, the company aims to navigate the complexities of modern construction while addressing pressing labour shortages and operational inefficiencies.