The Canadian Digital Service had analytics capability in place.
Building the cross-functional framework that made it usable across every discipline.
The Canadian Digital Service (CDS) is the federal government organization responsible for digital product and service delivery.
Its teams span research, design, product management, web operations, communications, and policy: disciplines that interact with digital performance from different vantage points, with different questions, and with different needs from the data.
The organization had analytics access. Google Analytics was in place and teams across product, content, and service design were using it. The tools were appropriate. The limit the measurement architecture had reached was organizational. Analytics knowledge had developed primarily within a specialist layer. Researchers, designers, communications professionals, and policy experts needed measurement capability in their daily work but had no consistent framework for applying it. CDS's mandate includes measuring the performance of public-facing digital services. The gap between the teams that had analytics fluency and the teams that needed it had direct consequences for how those decisions were made.
Measurement knowledge, without a shared language and practical frameworks, does not distribute across a multidisciplinary organization on its own.
Different teams interpreted performance data differently. A content team and a product team looking at the same report might draw different conclusions, not because the data was wrong but because the frame for interpreting it was not shared. Analytics stayed closer to the specialists who built fluency through daily use, and further from the researchers, designers, and communications professionals who needed it in their work but rarely had structured guidance on how to apply it.
The gap was organizational, not technical: analytics capability had not been designed to distribute across disciplines.
Building the cross-functional framework
Analytics capability became distributed across the organization rather than concentrated in a specialist layer.
— Victoria Chan, Website Lead, Canadian Digital Service
Five team types completed the training program across a series of live sessions: research, design, product management, communications, and web operations.
Multi-disciplinary teams came away with the practical fluency to ask sharper questions of the data and integrate measurement into their day-to-day work.
A shared measurement language formed across functions. Teams in different disciplines interpreted performance data with more consistency and discussed it with more confidence, working from a common framework rather than each building their own.
The organization now had a governed analytics foundation, replacing a setup that had accumulated incrementally without a governing architecture. The new measurement capability had a stable base to operate on.
If measurement capability is concentrated in a specialist team while the rest of the organization works around data rather than through it, the gap shows up in how decisions get made.
The Assessment maps the organizational and architectural state and identifies where to start.
The Measurement Architecture Assessment — a 30-minute call, a fixed-fee diagnostic, a clear picture of where your signal layer breaks and what to do about it.