Document Type: Framework
Status: Canon
Authority: HeadOffice
Applies To: Data Brain, Product Brain, Experimentation Brain, Affiliate Brain, Finance Brain, Strategy Brain
Parent: Data Brain Canon
Version: v1.0
Last Reviewed: 2026-05-03
Purpose
The Core Metrics Framework defines how MWMS selects, structures, and maintains the key metrics used to monitor business performance.
This framework ensures:
- focus on what matters
- clarity across all Brains
- consistent measurement
- actionable monitoring
Without a defined core metrics system:
- data becomes noise
- teams lose focus
- decisions become inconsistent
Core Principle
You cannot manage what you do not measure.
But measuring too much destroys focus.
Role In MWMS System
Core Metrics connect:
- Data Brain → measurement
- Product Brain → usage
- Finance Brain → revenue
- Affiliate Brain → performance
- Experimentation Brain → testing
- HeadOffice → oversight
Core Metrics Objective
Core metrics must:
- Reflect business health
- Enable fast decision-making
- Signal problems early
- Guide optimisation efforts
Metric Set Structure
A core metric set must include multiple perspectives.
1. Acquisition Metrics
Measures:
- how users enter the system
Examples
- traffic volume
- cost per acquisition (CPA)
- channel performance
2. Activation Metrics
Measures:
- initial user engagement
Examples
- onboarding completion
- first action completion
- time to first value
3. Engagement Metrics
Measures:
- ongoing usage
Examples
- sessions
- feature usage
- monthly active users
4. Conversion Metrics
Measures:
- monetisation
Examples
- trial to paid
- purchase rate
- click-through rate
5. Retention Metrics
Measures:
- user persistence
Examples
- churn rate
- repeat usage
- cohort retention
6. Value Metrics
Measures:
- financial performance
Examples
- CAC
- CLTV
- revenue per user
Metric Balance Rule
A core metric set must include:
- leading indicators (predictive)
- lagging indicators (outcome-based)
Examples
Leading:
- trial activity
- engagement rate
Lagging:
- revenue
- churn
Rule
Leading metrics detect issues early.
Lagging metrics confirm outcomes.
Metric Set Size Rule
Recommended Range
3–7 core metrics per context
Rule
Too few metrics:
→ blind spots
Too many metrics:
→ loss of focus
Metric Selection Criteria
Every metric must:
1. Be Relevant
Directly linked to business objectives
2. Be Measurable
Derived from real data
3. Be Actionable
Leads to a decision
4. Be Understandable
Clear to stakeholders
5. Be Consistent
Defined the same way over time
Metric Definition Standard
Every metric must include:
- name
- definition
- calculation method
- data source
- update frequency
- owner
Rule
If a metric is not defined:
→ it cannot be trusted
Metric Hierarchy
Core Metrics
Daily/weekly monitoring
Supporting Metrics
Context for core metrics
Diagnostic Metrics
Used for deep analysis
Metric Drift Protection
The system must prevent:
- changing definitions
- switching data sources
- inconsistent calculations
- duplicate metrics
Metric Ownership Rule
Each metric must have:
- a responsible Brain
- a defined data source
Example
- churn → Product Brain + Data Brain
- CAC → Finance Brain
- conversion → Affiliate Brain
Monitoring Rule
Core metrics must be:
- regularly monitored
- compared against thresholds
- tracked over time
Rule
Metrics must trigger action
Threshold Definition
Each metric must define:
- acceptable range
- warning level
- critical level
Example
- churn < 5% → acceptable
- churn 5–8% → warning
- churn > 8% → action required
Reporting Integration
Core metrics must be:
- visualized
- accessible
- understandable
Rule
Metrics must tell a story
Testing Integration
Metrics must be used to:
- validate experiments
- measure impact
- compare outcomes
Common Failure Modes
1. Metric Overload
Too many metrics
2. Vanity Metrics
Look good but useless
3. Misaligned Metrics
Do not reflect business goals
4. Inconsistent Metrics
Different definitions
5. Ignored Metrics
Tracked but not used
Operational Rules
Rule 1: Start Small
Define a focused metric set
Rule 2: Expand Carefully
Add metrics only when needed
Rule 3: Review Regularly
Ensure relevance
Rule 4: Remove Noise
Eliminate low-value metrics
Cross Brain Integration
Data Brain
→ defines and maintains
Product Brain
→ provides usage context
Affiliate Brain
→ monitors performance
Finance Brain
→ monitors revenue
Experimentation Brain
→ validates changes
HeadOffice
→ oversees
Architectural Intent
This framework ensures MWMS:
- measures what matters
- maintains clarity
- supports decision-making
- avoids data overload
Final Rule
If a metric does not lead to action:
→ it should not be a core metric
Change Log
Version: v1.0
Date: 2026-05-03
Author: HeadOffice
Change:
Created Core Metrics Framework defining structured selection and management of key metrics across MWMS.
Change Impact Declaration
Pages Created:
Data Brain Core Metrics Framework
Pages Updated:
None
Pages Deprecated:
None
Registries Requiring Update:
MWMS Architecture Registry
Data Brain Page Registry
Canon Version Update Required:
No
Change Log Entry Required:
Yes