By Caitlin Walsh Miller | January 08, 2025
“You’ve seen those signs that say, ‘In emergency, break glass,’ Well, it’s time to break the glass.” Those words were spoken by Carolyn Rogers, senior deputy governor of the Bank of Canada, during a speech in Halifax last spring, sounding the alarm on the country’s decades-long productivity crisis.
In 1970, Canada had the sixth most productive economy in the Organization of Economic Co-operation and Development (OECD). By 2060, the OECD predicts Canada will be dead last among its 38 member countries. This sluggish productivity manifests in a variety of ways: According to the Bank of Canada, the country’s economy generated just 71 percent of the value created by the U.S. per hour in 2022 — a decrease of 17 percent since 1984. And this is affecting us materially: Canadians’ standard of living, as measured by real GDP per person, was lower in 2023 than it was in 2014.
These challenges will only be exacerbated if Canada’s exporters are forced to contend with a proposed 25 percent tariff on all goods entering the United States. The U.S. is our most important trading partner by far; last year, it purchased nearly $600 billion of Canadian products, representing 77 percent of the country’s total merchandise exports.
Low investment, weak competition, overzealous regulation, the skills gap, cheap labour and, crucially, monumental technological advancements that no one knows quite how to navigate — all these factors have contributed to the gravity of Canada’s productivity crisis. So how do we best tackle this problem? Here, three experts share their opinions.
Caitlin MacGregor is the CEO and co-founder of Plum, a Waterloo-based talent assessment and recruitment platform that measures personality, intelligence and problem-solving ability to match candidates to the roles that best suit them.
“Let’s talk about what actually predicts productivity. We typically think it’s past performance: If a potential hire ran a successful marketing campaign for Company A, and I need to hire someone to do the same for Company B, I’d hire that applicant because they’ve done it before. It’s a shortcut in decision making, meant to de-risk the hiring process, which is expensive, labour-intensive and time consuming.
“But what actually drives performance is behavioural alignment between what intrinsically motivates somebody, independent of a job description or tasks, and the needs of a particular role: an aptitude for innovation, for instance, or the ability to adapt on a dime. According to our research, which is backed by a study of personnel psychology that looked at 85 years of data, behavioural alignment is four times more accurate than past experience and education when it comes to predicting future performance and retention.
“I applied the theory at my last job, when I was hiring for a ground-floor role at an edtech company. We had two applicants. One had five years of relevant work experience and a master’s degree in education. He was perfect on paper. The other wasn’t — she had two art degrees — but was through the roof on the execution, multi-tasking and problem-solving skills needed for the jack-or-jill-of-all-trades role we had to fill. So I hired both to see what would happen. After three months, the perfect-on-paper guy was doing 10 percent of his expected workload and he was let go. The woman with the art degrees was doing all of his work plus hers, and she replaced me as acting president while I went on maternity leave.
“Using a traditional screening process, she never would have made it past the first round of interviews. She didn’t even know how to use Excel. But you don’t need to be fluent in Excel anymore. Ask AI, and it will generate any formula under the sun. It will write our code, and it will write our copy. Hard skills like these are actually perishable skills, and we’ve overemphasized their importance. The solution to this rapidly changing workforce is to double down on durable skills — which means we need to be able to measure them.”
Pierre Cléroux is the vice-president of research and chief economist at the Business Development Bank of Canada, which supports small- and medium-sized businesses in Canada with loans, consulting services and capital.
“The last few years have been an economic roller coaster: a recession in 2020, followed by strong growth, then inflation and higher interest rates, and now the possibility of tariffs that the U.S. might impose on Canadian goods. But these factors are out of our control. What we can control is our productivity and efficiency. Businesses need a way to measure their productivity — but productivity can be difficult to assess in a vacuum.
“What we’ve found is that businesses that are part of a chain or larger group tend to be more productive, and more consistent in their productivity, compared to independent operators. They just have more information about how they’re doing compared to their peers. Take drugstores, as an example. Almost all are part of a chain. According to data from our workforce efficiency benchmarking tool, which rates businesses’ productivity on a scale between 0 and 100, their productivity is fairly consistent at around the 80th percentile. If you look at the manufacturing sector, productivity varies much more widely — between the 20th and 90th percentiles. But manufacturers are usually on their own, making it hard to benchmark themselves within their industry. Which makes it hard to know how they’re doing, and if they could be doing better. If you’re not as productive as you could be, you’re leaving money on the table. A government program that helps businesses assess productivity and diagnose issues is imperative to make sure that doesn’t happen.
“And a key way of improving productivity is through technology. When we compared the 10 percent most productive companies in Canada to the other 90 percent, the big difference was the way they invest in technology, which is two times more per employee. A client in London, Ont., for instance, has 40 employees as well as 40 robots on their manufacturing floor. Automation has allowed them not only to produce more, but to improve the quality of what they’re putting out. They produced one million parts last year, and just one had a default. That’s productivity. In the context of an aging population and a labour shortage that is likely to return in the next year or two, automation like that will be key to improving our productivity.”
Kristina McElheran is an assistant professor of strategic management at the University of Toronto Scarborough and the Rotman School of Management, specializing in technology, innovation and digital transformation in organizations.
“We are experiencing the growing pains of a fourth industrial revolution in many settings. We have a number of brilliant new technologies suddenly available for so many uses. Artificial intelligence is getting the most attention, but digitization, data analytics and cloud computing should not be overlooked. Yet, figuring out how to pull production apart, apply novel technologies and then get the system back up and running smoothly is a painful process. My research, based on U.S. data, points to this being a real issue over the past several years.
“Some firms and workers will adapt sooner and better, and others will fall behind. This can be good, overall, if society’s resources get allocated to their most-productive uses. In the short term, though, this can be very hard on the people and businesses that can’t make the shift. We have to be proactive about mitigating the costs and making sure they do not disproportionately fall on the most vulnerable. We need to protect people, not specific jobs or industry sectors, and help both firms and workers be as nimble as possible.
“To do that, we need data. We need to know more about the rate and direction of this technological shift and the frictions that are arising. Right now, we are flying blind into a fast-changing future. I am actively working with the U.S. Census Bureau to collect statistics on these trends there, but it is slow, painstaking work. A critical first step would be more resources for this in more countries including Canada, with more people involved, and faster sharing of findings. Academics have a role to play in terms of where we allocate our time and attention and how we move research through the pipeline. Governments can empower agencies and fund data-gathering. Managers can start getting more data-driven about what is going on in their firms and workers can share front-line insights about how to put recent advances to work most effectively.
“It can seem like a lot, all at once. However, tempting as it is to get overwhelmed or worried about the fast pace of technological change — especially AI — staying open will be vital. As Gordon Moore, the co-founder of Intel and father of “Moore’s Law” [a data-based prediction about trends in semiconductor technology] famously said, when it comes to technology, ‘change will never be this slow again.’ Nap when you can.”