Ontario’s Ministry of Education expects roughly 13,000 fewer students in publicly funded schools in 2026–27, and boards from Ottawa to Peel are adjusting budgets and staffing to match. Because provincial funding follows projected enrolment, a forecast miss is a budget miss. Colleges and universities face their own version of the problem: the federal cap on international study permits for 2026 is 408,000, about 7% below 2025 and 16% below 2024. Meanwhile, the province-wide assessments released in September 2026 put 52% of Grade 6 students at the provincial standard overall, with roughly half at standard in mathematics, a figure that has barely moved in years.

None of these pressures is new. What has changed is that the data to act on them already exists inside every board and institution, in the student information system, the learning platform, the finance system and the assessment files. The question for leaders is where to start.

1. Enrolment and capacity, by school and cohort

Board-level totals hide the decisions that matter. A board can shrink overall while two school families outgrow their buildings. Projections that work at the school and grade-cohort level draw on registrations, approved housing by dwelling type and historical yields, and they are refreshed monthly rather than once a year for the ministry submission. Tying the projection to the funding model turns a demographic chart into a financial one: trustees see what each boundary or program scenario means in dollars and in staff, before they vote.

2. Assessment analytics that follow the student

Pass rates are snapshots. A board whose Grade 6 result rose two points may have schools where the same students grew by fifteen points since Grade 3, and others where they lost ground. Cohort tracking, strand-level results and links to the programs in place make growth visible, and show where instructional support changes outcomes. The design rule is aggregation: results are reported by school, grade and strand, small counts are suppressed, and principals and superintendents each see what their role requires.

3. Student success in colleges and universities

Most students who leave in first year show signs in the first six weeks: missed assignments, no activity on the learning platform, a first grade below the pass mark. Early-alert programs at Ontario institutions bring those signals to advisors, and a Higher Education Quality Council of Ontario survey of Canadian colleges and universities found predictive retention models in use at about a third of them, with nearly 40% more considering them. The alert is the easy part. What changes outcomes is the follow-up: who was contacted, how quickly, and whether the students reached persist to the next term and year at a higher rate than those who were not. Measuring that by group is what turns a pilot into a program.

The condition: privacy and governance first

Education data is among the most sensitive an organization holds. A breach at a student-information vendor, disclosed in early 2025, touched about 5.2 million Canadians, and the privacy commissioners of Ontario and Alberta found that boards lacked breach plans and adequate vendor terms. New rules for digital technology affecting people under 18 took effect in Ontario on July 1, 2026. Every analytics program should start from the same decisions: who owns each data domain, how access follows roles, what is reported only in aggregate, and what the vendor contract requires. Done first, these decisions make the three use cases above possible; done late, they stop them.

Where to begin

Pick the one question leaders need answered this term, build the governed data model that answers it, and publish the result in the tools people already use. The enrolment, assessment and student-success examples on our Client impact page show what each of these looks like when it is done.

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