As companies continue to amass zettabytes of data, the talent hunt for data scientists who can create clarity out of all the noise, has never been greater. But one of the greatest challenges a data scientist faces is communicating the uncovered insights wrangled from the relevant data to decision-makers.

To be successful, data science teams need to master the craft of design and storytelling, in addition to extracting and analyzing data. Answering the question, “What do these insights mean for the organization or business?” is easier said than done.

The annual Safe Roads Competition brings these skills together in a meaningful way. The competition allows participating student teams from Canada and Mexico to work with KSI (killed or seriously injured) incident report data from Toronto Police Services and aggregated Geotab fleet telematics showing traffic speeds, acceleration and hard braking, road conditions, and more to derive insights and help improve road safety. Final presentations explain the methodology used, the conclusions drawn and recommendations for TPS.

Student participants are drawn to the program for several reasons, says Sergeant Warren Stein of the Toronto Police Service.

“They’re driven. When I know there's a purpose to what I'm doing, it's not just theoretical, it makes a difference,” he explained.

The pandemic reduced vehicular traffic globally, but it also led to subtle shifts in people’s driving behavior. In Toronto, certain areas experienced increased speeding which heightened the severity of collisions in those regions. The growing analytics division within TPS are well-aware of these changes, but Safe Roads Competition participants add significant value to their data.

“We push that information up. Traffic enforcement is critical to preventing collisions,” Stein said. “The more eyes we get on it, the better chance we have to give front-line officers the best information possible.”

Turning raw data into business language

Robin Yap, a professor for the School of Management at George Brown College, stressed the value of a data analytics competition anchored to a real-world issue.

Robin Yap, professor for the School of Management at George Brown College.

“Competitions like this allow for an opportunity to tap into raw, individual ideas from students who are approaching problems with a fresh perspective,” said Yap.

Most George Brown students participating in the competition belong to the college’s Analytics for Business Decision-Making program, he said. It’s a business program that helps students become data analysts while speaking the language of technologists. Turning technical speak into business language that decision-makers can understand remains an elusive skill.

“This program allows for that merging,” Yap explained. “And that’s why the Safe Roads Competition is perfect because when students do their presentations, they will talk about the business decisions behind the numbers and not about ‘I have 14 million data entries, and here you go.’ The competition and the SAS product suite allow for a better understanding of how you handle data.”

Christopher Caballero, who is enrolled in an Analytics for Business Decision-Making course at George Brown College, said SAS Safe Roads pushed him and his team to think outside the box.

"I wanted to join because I thought it would be a great opportunity as a team to analyze real-world data using SAS in order to provide actionable insights," he said after his student team won first place at this year's competition.

One of Caballero's teammates, Kate Armstrong, said crafting those actionable insights was a big draw to SAS Safe Roads.

"Being able to work with real data, learn more about SAS and create recommendations that could have an actual impact in Toronto was a great experience," she noted.

During the development of their case studies, students are also encouraged to use open-source tools, such as Python and R. They can analyze and crunch the force’s crime, traffic and boundary data to document their findings and prepare recommendations. It amounts to more than two dozen datasets in total.

Cristian Gonzága Lopez, a fourth-semester student of engineering in data science and math at the Tec de Monterrey University in Mexico, said this year her team built an algorithm that predicts the probability of a traffic accident in every district of Toronto based on the hour, the day of the week and weather conditions. A separate algorithm also classified every public place in Toronto that was more prone to have an accident near them based on road conditions and historical records of accidents in that area.

"Data itself doesn't give us true knowledge, just helpful information," Lopez said.

Members of the 2020 SAS Safe Roads Competition participants from Humber College.

Having a dozen slides with no narrative or action to call on is easy, said Brooke Heitshu, a member of the winning 2020 Safe Roads Competition team from Humber College.

“Focus on what exactly you’re trying to figure out. It can be one or two things and really drill down and tell a story with the data.”

In her team’s case, they analyzed cycling data and discovered cyclists are the most vulnerable on the road due to having the fewest regulations and traffic controls in place. They highlighted how most accidents involving cyclists happen during ideal weather conditions, and in their final recommendations, suggested better cyclist traffic controls to reduce accidents where cyclists consistently fail to yield. Heitshu also leaned on some personal experience after a visit to the Netherlands, which boasts a passionate cycling community.

“It was a great project,” she said.

Mark Morreale, Global Academic Program Manager at SAS says the Safe Roads program is a creative and innovative event that allows students to display their analytics talent and research to potential employers.

“Students can display their understanding of research methodologies and management of large datasets rich in information,” he said.

Looking for new talent?

The SAS Safe Roads Competition is just one of the ways SAS helps foster the next generation of analytics talent across Canada and beyond.

  • Cortex, the analytics simulation game developed in collaboration between SAS and HEC Montréal. Cortex has become a worldwide phenomenon, with competitions as far afield as the U.S., Thailand, Malaysia, Finland and Australia. Learn more about Cortex.
  • Canadian Research Data Centre Network's National Policy Challenge, supported by SAS and Statistics Canada, encourages student researchers to develop policy ideas with microdata.

About Author

Alex Coop

Senior Communications Specialist

Alex Coop manages internal and external communications for the Canadian business, helps create stories with our incredible customers and subject matter experts, and prior to joining SAS, was an editor and community reporter.

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