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Standard : Product and engineering decisions are backed by live data

Purpose and Strategic Importance

This standard ensures that product and engineering decisions are grounded in live, reliable data—enabling teams to prioritise effectively, validate assumptions, and adapt with confidence.

Aligned to our "Data-Driven Decision-Making" policy, this standard strengthens accountability, improves responsiveness, and reduces risk. Without it, teams operate on guesswork, slowing progress and increasing the chance of misaligned outcomes.

Strategic Impact

  • Stronger decision quality and speed
  • Reduced reliance on assumptions or outdated data
  • Faster alignment to user needs and system behaviour
  • Clear traceability between data and actions
  • Improved forecasting and strategic planning

Risks of Not Having This Standard

  • Decisions made on outdated or inaccurate data
  • Misaligned prioritisation and investment
  • Reduced credibility of engineering insight
  • Slower time to adapt or course-correct
  • Increased risk of missed opportunities or defects

CMMI Maturity Model

Level 1 – Initial

Category Description
People & Culture Decisions are made through intuition, anecdotes,
or HiPPO (highest paid person’s opinion).
Process & Governance No requirement for evidence-based decisions.
Assumptions are rarely validated.
Technology & Tools Live data sources are not accessible or are siloed.
Tools do not support real-time visibility.
Measurement & Metrics No standardised decision-support metrics.
Impact of decisions is not measured.

Level 2 – Managed

Category Description
People & Culture Teams begin consulting some data before decisions,
but usage is ad hoc and inconsistent.
Process & Governance Guidance exists to consider data during planning,
but follow-through is variable.
Technology & Tools Dashboards or reports provide some useful metrics,
but often delayed or incomplete.
Measurement & Metrics Key metrics are reviewed occasionally, not
routinely tied to product or technical decisions.

Level 3 – Defined

Category Description
People & Culture Teams use shared data sources and common metrics
to guide most decisions.
Process & Governance A standard process exists to review live data
before approving or changing plans.
Technology & Tools Data pipelines and telemetry tools feed into
planning, delivery, and retrospectives.
Measurement & Metrics Impact metrics are tracked and linked to decisions,
supporting accountability and learning.

Level 4 – Quantitatively Managed

Category Description
People & Culture Data fluency is a valued skill across product
and engineering teams.
Process & Governance Decisions are regularly evaluated based on
historical and predicted outcomes.
Technology & Tools Real-time data informs continuous prioritisation
and scenario modelling.
Measurement & Metrics Data quality and usage are tracked; metrics are
benchmarked and used to improve decision models.

Level 5 – Optimising

Category Description
People & Culture Teams proactively seek out new signals and refine
decision-making through data experiments.
Process & Governance Feedback loops ensure data-driven insights
continuously improve decision quality.
Technology & Tools Observability, usage analytics, and forecasting tools
are fully embedded into decision systems.
Measurement & Metrics Strategic and operational metrics are integrated,
allowing fast, high-confidence decisions.

Key Measures

  • % of decisions supported by live or real-time data
  • Accuracy and freshness of data used in planning or delivery
  • Time from signal detection to decision adjustment
  • Evidence of data-informed pivots or course corrections
  • Team confidence in data relevance and quality
Associated Policies
  • Data-Driven Decision-Making
  • Decentralised Decision-Making
Associated Practices
  • Live Dashboards
  • Synthetic Monitoring
  • Custom Metrics Instrumentation
  • Runbooks and Playbooks
  • Log Correlation for RCA
  • User Session Replay Tools
  • End-user Experience Monitoring
  • On-Call Rotation Health Checks
  • Container Security Scanning
  • Vulnerability Management Dashboards
  • Threat Modelling Workshops
  • Data Encryption-in-Transit & at-Rest
  • Threat Intelligence Feeds
  • Secure API Gateways
  • Shadow Testing in Production
  • Load & Performance Testing
  • Operational KPIs for Dev Teams
  • Service Mesh Implementation
  • Hypothesis-Driven Development
  • Mobile-First Design
  • Observability-Driven Design
  • Strategy & Outcome Mapping
  • Impact Mapping
  • Sprint Demos for Stakeholders
  • Code Reviews & Pull Requests
  • Data Mesh
  • Secure Code Training
  • Evolutionary Architecture
  • Serverless Architecture
  • Event Sourcing
  • Security as Code
  • Dependency Management Policies
  • Compliance-as-Code
  • Customer Feedback in Dev Loops
  • Feedback Loops from Ops to Dev
  • Application Performance Monitoring (APM)
  • Distributed Tracing
  • Real-time Event Streaming
  • Real-Time Logging

Technical debt is like junk food - easy now, painful later.

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