Studying economics helped prompt the litigator to help launch a 'data-driven decisions' program
When Paul-Erik Veel was a junior associate at Lenczner Slaght LLP, he was preparing for his first jury trial. His client was a physician defending a medical negligence claim.
Veel told his client that attending the trial every day would be a good idea. “The jury really wants to see that you're involved and engaged,” he told the doctor.
Veel’s client said that even though it would disrupt his practice, he would follow Veel’s advice. “I assume there are studies that show that when defendants show up to jury trials, they're more likely to win,” the doctor said.
Veel’s response, he realized, highlighted a problem in the legal profession.
“We don't study these things,” Veel recalls telling his client. “The practice of law doesn't work that way. It's a bunch of old lawyers who have been doing something for 30 or 40 years, who say, ‘This is the way we should do things.’ And then the newer generation just learns that collective knowledge, really without interrogating it in any kind of systematic way.”
His client was not impressed.
“That was an unsatisfying answer for him, but also an unsatisfying answer for me,” says Veel.
The exchange set Veel on a path to incorporate quantitative and empirical analysis into how he and his firm deliver legal advice.
A passion for data
Back when Veel was studying economics for his undergraduate degree, he became fascinated by the tools economists used to aggregate data and predict what people, companies and markets are going to do.
His interest in competitive debating led him to law school, but he never left his passion for data behind. While he was studying law, he also completed a master’s in economics.
After law school, Veel clerked for Louise Charron at the Supreme Court of Canada. He then joined Lenczner Slaght as an associate. Despite warnings from friends that the firm was “intense,” and the lawyers worked too hard, Veel says, “Early in my career, I thought that actually sounds great. Sign me up. It seemed like a very exciting environment to be in for a litigator.”
Veel then developed a commercial litigation practice focusing on class actions, competition law, complex commercial disputes, and professional liability.
In 2020, he began to apply an empirical analysis he knew was missing from much legal reasoning to cases at the Competition Tribunal. Veel describes this as “the first small dataset that I had built on my own in an Excel document.”
Another project at the firm, a website tracking cases on the Superior Court of Justice’s commercial list, contained practice-related information on the list. Veel also began working on a Supreme Court of Canada leave project, which analyzed leave decisions at the top court.
The obstacles to good legal data
Veel says a major obstacle for all these projects was convincing what he terms “quantitatively averse” lawyers that there is value in tracking this information.
The “classic lawyer is not someone who has studied math, or physics or any other kind of heavily quantitative discipline in their undergraduate studies,” he says. “It's the philosophy student, the political science student, the English student. That’s the classic path to law school. And so, what that means is, a large portion of the bar doesn't necessarily have particular quantitative literacy.”
Veel says it took much less convincing when speaking to clients. “Across the board, as most businesses become more data-driven, and you see clients expecting data analytics internally from their own teams, they're looking for that from external legal counsel.”
The second big challenge, Veel says, was ensuring they were inputting good-quality data.
“We've got clients who expect good predictions if we're going to give them these numbers. And so, we're similarly obsessed with data quality, which means that it takes a long time to build up the dataset.”
Designing the system
So, Veel and his team of lawyers, articling students and undergraduate interns, spent a lot of time looking at cases, identifying information about those cases and plugging them into a dataset.
“One of the little secrets of a lot of data analytics programs is that the vast majority of the work is spent on building your data sets on the front end. You can get very robust predictive models in a matter of seconds from your data,” he says.
Computer coding took up much less time for the Lenczner Slaght team. Veel did not study computer science but did much of the coding himself.
Veel says he would find open-source platforms in the relevant coding languages, and he was comfortable using software to analyze data from his time studying economics.
“You end up out of necessity doing some coding in various statistical software packages.”
Despite its unproven approach, the firm encouraged Veel’s investment in the project.
“One of the things I love about Lenczner Slaght and [one of] the reasons that I have been here for the last 13 years is that there is a culture of innovation, a culture of experimentation. [There is] a lot of support for new ideas and new initiatives and a recognition that any good project is going to need some initial outlays and that it's okay if some percentage of those projects fail.”
In March 2021, the firm officially launched its “data-driven decisions” program, encompassing data from the Competition Tribunal, SCC leave and written decisions, Federal Court of Appeal patent disputes, the Ontario Court of Appeal and the commercial list.
“We are getting to the point where those types of models can be good enough to be useful complements to the reasoning that lawyers employ,” says Veel.
With the recent renewed interest in artificial intelligence and its uses in the legal profession, Veel’s work has taken on new urgency. Still, he is quick to differentiate it from tools such as ChatGPT.
“They're not language models. They’re more in the structured datasets that academics historically used. What we're doing is not fundamentally dissimilar from what empirically-minded social science researchers have been doing for decades.”
Veel stresses that this initiative is not just about speeding up his team’s work but about finding new insights that can challenge the profession’s conventional wisdom.
“It doesn't take the lawyer out of the equation, but it provides an additional data point to either confirm or interrogate what we know. It's effectively like another opinion you're getting from an unbiased external observer that can help us as the lawyer give better advice.”
Paul-Erik Veel was one of the Top 25 Most Influential Lawyers of 2022.
