Learn from execution
Adherence findings, evidence, repeated deviations, and work-product patterns.
Continuous Improvement Service
Turn every improvement signal into a governed learning loop.
PEDCO expertise combined with the Applied SAFe® Platform to create a recurring improvement mechanism around the governed operating model — from signal to approved change to measurement.
- Capture the signal
- Understand the opportunity
- Recommend an improvement
- Analyse impact and approve
- Propagate the approved change
- Measure again
Overview
Improvement opportunities arise everywhere. Connecting them is the hard part.
Execution evidence, metrics, audits and assessments, retrospectives, practitioner experience, process-owner proposals, recurring workarounds, customer or regulatory changes, new engineering practices — the challenge is connecting those signals to the operating model, understanding the underlying cause, deciding what should change, and measuring whether the change actually helped.
Objective
Help the operating model learn from how the organization actually works.
Improvement signals
Five sources the loop can learn from.
Learn from performance
Process metrics, flow measures, quality indicators, and trends.
Learn from assurance
Internal assessments, review boards, audits, and compliance findings.
Learn from experience
Retrospectives, process-owner input, practitioner feedback, adaptive surveys, and targeted AI voice interviews.
Bring in better ways of working
New practices, tools, methods, standards, technologies, and engineering approaches.
How the service works
Six steps — and then round again.
Capture the improvement signal
Bring a finding, metric trend, practitioner observation, recurring deviation, external change, or new idea into the improvement process.
Understand the opportunity
Investigate the underlying cause and affected operating-model elements using execution evidence, metric analysis, surveys, voice interviews, process relationships, and compliance impact.
Recommend an improvement
Develop a targeted proposal rather than simply documenting the problem.
Analyse impact and approve
Understand which contexts, inherited variants, compliance relationships, roles, and interfaces may be affected. Accountable process owners decide whether the change should proceed.
Propagate the approved change
Update the relevant organizational baseline or tailoring logic and propagate the change to the contexts that inherit it.
Measure again
Use subsequent execution evidence, metrics, assessments, or practitioner feedback to determine whether the improvement achieved the intended result.
A proposal may affect
- Activities
- Roles
- Work products
- Practices
- Tailoring
- Guidance
- Controls
- Agent instructions
- Integrations
- Compliance mappings
Concrete example
Architecture review as a bottleneck for low-risk changes.
- Signal
Process metrics show increasing wait time, and practitioner interviews confirm that teams use the same review path regardless of change risk.
- Proposal — risk-based tailoring
- Low-risk changes use a lighter review path
- Higher-risk changes retain the full architecture review
- The criteria are made explicit in the operating model
- After approval
The change is propagated to the contexts that inherit it — and lead time is measured again.
Deliverables — depending on the engagement
- Improvement backlog
- Evidence-backed problem statements
- Root-cause findings
- Prioritized recommendations
- Impact analysis
- Proposed process changes
- Compliance impact
- Approved operating-model updates
- Propagation plan
- Before / after measurements
- Recurring improvement reporting
Applied SAFe® Platform capabilities used
- Findings and recommendations
- Process and requirement context
- Adherence evidence
- Metrics
- Adaptive surveys
- AI voice interviews
- AI-assisted root-cause analysis
- Impact analysis
- Governed change
- Tailoring and inheritance
- Improvement tracking