Practice : Platform Usage Visualisation

Purpose and Strategic Importance

Platform Usage Visualisation enables platform teams and engineering stakeholders to understand how internal platforms, tools, and self-service capabilities are being adopted, used, and improved. By making platform adoption, friction points, and success visible, teams can proactively identify where support, education, or technical improvements are needed.

This practice reduces wasted effort on underutilised or misunderstood tools, accelerates platform adoption, and enhances the overall developer experience. Without clear visibility into platform usage, teams risk investing in unused solutions, increasing cognitive load, and missing opportunities to improve flow.

Description of the Practice

  • Usage metrics and dashboards track how teams interact with self-service platforms, CI/CD templates, infrastructure provisioning tools, or developer portals.
  • Data includes frequency of use, success rates, time to value, and areas of friction or abandonment.
  • Visualisation is shared with platform teams, engineering leadership, and consuming teams to support continuous improvement.
  • Improvements are prioritised based on usage insights, not assumptions.

How to Practise It (Playbook)

1. Getting Started

  • Identify key platform capabilities or self-service tools to track (e.g. pipeline templates, infrastructure provisioning, onboarding portals).
  • Instrument platforms with telemetry to capture usage patterns, success rates, and errors.
  • Create basic dashboards to visualise trends over time.

2. Scaling and Maturing

  • Segment usage data by team, product area, or capability to uncover adoption gaps.
  • Correlate usage patterns with delivery performance or developer satisfaction data.
  • Use visualisation to inform platform roadmaps, education, and support initiatives.
  • Encourage consuming teams to provide qualitative feedback alongside quantitative data.

3. Team Behaviours to Encourage

  • View platform usage as a product success indicator, not just an engineering output.
  • Treat low adoption or friction as signals for improvement, not failure.
  • Celebrate high-value use cases and successful adoption stories.
  • Use data to create feedback loops between platform teams and engineering consumers.

4. Watch Out For…

  • Tracking vanity metrics that don't reflect actual platform value.
  • Overlooking adoption barriers due to lack of qualitative feedback.
  • Assuming that availability equates to successful usage.
  • Neglecting to close the loop on identified improvement areas.

5. Signals of Success

  • Platform usage is increasing, with reduced friction and support requests.
  • Teams report higher satisfaction with self-service tools and developer platforms.
  • Usage data informs platform prioritisation and improvement work.
  • Platform adoption contributes to improved delivery flow and reduced cognitive load.