Standard : Real-time value metrics are surfaced through monitoring

Purpose and Strategic Importance

This standard ensures that real-time value metrics are captured and made visible through operational monitoring systems. It helps teams validate that their work delivers measurable outcomes, driving alignment between engineering, product, and business goals.

Aligned to our "Data-Driven Decision-Making" policy, this standard promotes continuous feedback, faster adaptation, and prioritisation based on real impact. Without it, teams risk focusing on technical outputs rather than delivering meaningful customer or business value.

Strategic Impact

Clearly defined impacts of meeting this standard include improved decision-making, reduced wasted effort, stronger alignment to business goals, and the ability to rapidly pivot based on real-world feedback.

Risks of Not Having This Standard

  • Delivery becomes output-focused rather than outcome-focused
  • Delayed discovery of misaligned features or initiatives
  • Reduced stakeholder confidence in engineering work
  • Missed opportunities to innovate based on customer needs

CMMI Maturity Model

Level 1 – Initial

  • People & Culture

    • Teams focus on delivering outputs without visibility into value impact.
    • Little or no discussion of customer or business outcomes.

  • Process & Governance

    • Success is measured by delivery volume rather than outcomes.
    • No requirement to define or monitor value metrics.

  • Technology & Tools

    • No systems in place to track real-time value indicators.

  • Measurement & Metrics

    • Value delivery is assumed but not measured.

Level 2 – Managed

  • People & Culture

    • Teams begin identifying intended outcomes during planning.
    • Some initiatives define value metrics manually.

  • Process & Governance

    • Basic tracking of selected value indicators begins.
    • Reports generated manually or inconsistently.

  • Technology & Tools

    • Teams use ad-hoc tools or spreadsheets for some initiatives.

  • Measurement & Metrics

    • Outcome tracking exists for key features but lacks consistency.

Level 3 – Defined

  • People & Culture

    • Defining and monitoring value metrics is standard practice.
    • Product and engineering roles collaborate on defining outcomes.

  • Process & Governance

    • Real-time value metrics are required as part of "Definition of Done."
    • Metrics are reviewed during retrospectives and release reviews.

  • Technology & Tools

    • Dashboards surface real-time value telemetry alongside technical health.

  • Measurement & Metrics

    • Every major feature or release links back to measurable outcomes.

Level 4 – Quantitatively Managed

  • People & Culture

    • Teams proactively use live value data to adapt priorities.
    • Data-driven experimentation is encouraged based on observed trends.

  • Process & Governance

    • Continuous improvement practices integrate value insights.

  • Technology & Tools

    • Metrics platforms automatically ingest and analyse value data.
    • Alerts and thresholds are defined for value degradation or anomalies.

  • Measurement & Metrics

    • Value metrics inform product investment decisions.

Level 5 – Optimising

  • People & Culture

    • Value-driven culture deeply embedded across engineering and product.
    • Teams continuously innovate based on value signals.

  • Process & Governance

    • Predictive value trend analysis supports proactive strategy shifts.

  • Technology & Tools

    • Advanced analytics and AI surface unexpected value opportunities.

  • Measurement & Metrics

    • Continuous refinement of value definitions based on customer behaviour and market trends.

Key Measures

  • % of initiatives with live, real-time value metrics
  • % of releases with linked outcome measurement
  • Frequency of roadmap adjustments based on value data
  • Rate of detection of underperforming initiatives
  • Alignment of engineering metrics to business OKRs