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Standard : Learning is prioritised over blame when delivery fails

Purpose and Strategic Importance

This standard reinforces the principle that when delivery fails, the response must prioritise insight over blame. By replacing judgement with curiosity, we encourage teams to explore system-level root causes, not personal faults. This enables continuous improvement, protects psychological safety, and promotes open dialogue across functions and roles.

It supports the policies to “Prioritise Learning Over Performance in Retrospectives” and “Create Resilience Through Empowered Teams” by creating a cultural norm where failure is used as fuel for growth. Without this, teams may conceal issues, miss learning opportunities, and erode trust.

Strategic Impact

  • Encourages candid discussion of failure without fear of punishment
  • Increases learning velocity and operational resilience
  • Enables early identification and resolution of systemic weaknesses
  • Strengthens collaboration across delivery, leadership, and support roles
  • Embeds learning culture into the rhythm of delivery work

Risks of Not Having This Standard

  • Blame culture discourages transparency and candour
  • Root causes remain hidden or misunderstood
  • Repeated issues reduce delivery confidence and morale
  • Improvement becomes reactive, inconsistent, or blocked
  • Psychological safety deteriorates, increasing attrition and disengagement

CMMI Maturity Model

Level 1 – Initial

Category Description
People & Culture - Failures are met with blame or avoidance.
- Individuals fear speaking up due to reputational risk.
Process & Governance - No consistent review of failures; ad hoc responses dominate.
Technology & Tools - No tooling to support learning or root cause analysis.
Measurement & Metrics - No visibility into repeated issues or learning outcomes.

Level 2 – Managed

Category Description
People & Culture - Teams discuss failures, but often limit transparency.
- Blame is reduced but not consistently eliminated.
Process & Governance - Basic retros and RCAs exist but follow-up is weak.
Technology & Tools - Lightweight templates used for postmortems or incident logs.
Measurement & Metrics - Improvements are occasionally tracked but often informal.

Level 3 – Defined

Category Description
People & Culture - Teams regularly reflect on failure without blame.
- Shared ownership of outcomes is encouraged.
Process & Governance - Structured retrospectives and RCAs are routinely used.
- Follow-through on actions is visible and reviewed.
Technology & Tools - Systems support categorisation and visibility of learnings.
Measurement & Metrics - % of failures with documented learnings and closed actions.

Level 4 – Quantitatively Managed

Category Description
People & Culture - Failure data is shared across teams for collective insight.
- Leaders model and reinforce a learning-first approach.
Process & Governance - Patterns in failure drive targeted improvement initiatives.
- Retrospective themes inform quarterly delivery planning.
Technology & Tools - Tools support trend analysis, tagging, and shared access to postmortems.
Measurement & Metrics - Reduction in repeat failures; cross-team reuse of improvements.

Level 5 – Optimising

Category Description
People & Culture - Failure is reframed as an opportunity and celebrated as progress.
- Continuous refinement of delivery practices is driven by reflection.
Process & Governance - Learning loops are embedded into daily and strategic planning rhythms.
- RCAs inform architecture, team design, and risk posture.
Technology & Tools - Learning systems integrate into delivery platforms and feedback tools.
Measurement & Metrics - Time-to-learn and time-to-improve are continuously reduced.

Key Measures

  • % of retrospectives that lead to implemented change
  • Number of recurring incidents without resolved root causes
  • Psychological safety scores from team surveys
  • Time from failure to documented learning
  • % of failures with complete and reviewed RCAs
Associated Policies
Associated Practices
  • Safe-to-Fail Experiments
  • Hypothesis-Driven Development
  • Iterative Learning Cycles
  • Modelling Psychological Safety

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