Canada’s chief statistician announces ‘data challenge’ to gather staff ideas

The Canadian government is to run a ‘data challenge’ to identify and develop public servants’ ideas on how to make better use of data, the country’s chief statistician, Anil Arora, has announced.
Under the Public Service Data Challenge, public servants will be invited to send in their ideas for improvements in the government’s use of data, and to volunteer to join the teams developing the most promising concepts. Following a research phase, the teams will present their ideas to a judging panel of digital and data leaders – with the best securing the technical support and high-level backing required to move towards delivery.
Speaking to 6000 public servants attending the online Data Conference 2022 on Wednesday, Arora explained that the programme “will bring federal employees together to pitch their ideas on how government can make better use of data,” finding ways to “improve policymaking and power the green agenda, drive organisational efficiency, and help us better serve Canadians.”
Participating staff will “get the opportunity to collaborate in interdisciplinary, cross-departmental teams,” he added. “You will identify problems and propose data-driven solutions. You will bring your skills and experience to the table, where you’ll be encouraged to innovate and take intelligent risks.”
All ideas welcome
The Public Service Data Challenge will be run by partners including Statistics Canada, Natural Resources Canada and Global Government Forum (GGF), and backed by a set of senior ‘champions’ including Arora, government CIO Catherine Luelo, and Frank Des Rosiers, assistant deputy minister, strategic policy and innovation at Natural Resources Canada.

The goal is to tap into the experience and inventiveness of staff across the workforce, identifying ways to fix problems and realise opportunities in the government’s collection, management, sharing and deployment of data. Teams with the required skills, expertise and contacts will be built around the most promising ideas, receiving technical support along with assistance from judges and champions as they carry out research and develop their business cases.
“The potential for data solutions is immense,” Des Rosiers told GGF, noting that the programme is designed to “improve outcomes for citizens, while supporting cross-departmental collaboration.”
“I am constantly impressed by the talent and ideas of the public servants in our department, and I am looking forward to the initiatives that will be proposed,” he said. “The Data Challenge will bring together diverse talent from across the public service to showcase innovation and mobilize data to better serve Canadians. I am thrilled to be part of this, and I encourage all public servants to participate.”
Successful model
The model is “based on last year’s extremely successful United Kingdom Civil Service Data Challenge,” Arora told the data conference. The UK programme – run by GGF in association with the UK’s Cabinet Office, the Central Digital and Data Office, the Office of National Statistics, and NTT DATA UK – received nearly 200 ideas, ultimately backing a plan to use AI in peatlands restoration.
The other UK teams’ pitches included proposals to identify fraud and error by linking departmental datasets; create a dashboard plotting the distribution of citizens overseas; and track prisoners’ contacts with friends and family, improving the targeting of support services. Speaking at the UK’s December Final, UK civil service chief operating officer Alex Chisholm praised all eight finalists: “We want all of them to go forward; every one of the shortlisted ones,” he said. “We are absolutely determined that they should happen.”

Canada’s Public Service Data Challenge website will go live shortly, providing information for public servants with ideas for making better use of data, those interested in joining a team, and line managers. Meanwhile, read our feature on the UK’s Civil Service Data Challenge to learn how it transformed one public servant’s “vague possibility” into a live AI project.