Document Type: Framework
Status: Active
Authority: HeadOffice
Applies To: All Brains
Parent: HeadOffice
Version: v1.0
Last Reviewed: 2026-04-18
Purpose
The HeadOffice Growth Lever Prioritisation Framework defines how MWMS selects the highest-impact optimisation focus areas.
Growth Levers identify the key constraints currently limiting system growth.
Because resources are finite, MWMS must focus on improving the constraints with the greatest expected system-level impact.
This framework ensures Growth Lever selection remains:
structured
evidence-based
aligned to North Star Metric
compatible with system constraints
Without structured prioritisation, experimentation becomes fragmented and inefficient.
Growth Lever prioritisation increases:
learning speed
capital efficiency
strategic clarity
experiment quality
Scope
This framework applies to:
Affiliate Brain optimisation direction
Experimentation Brain prioritisation logic
Conversion Brain optimisation focus
Research Brain signal interpretation
Product Brain capability prioritisation
Content Brain improvement focus
This framework governs:
selection of Growth Levers
comparison of potential leverage areas
evaluation of impact potential
alignment with North Star Metric
This framework does not govern:
individual experiment design
statistical validation methodology
channel selection decisions
These remain governed by relevant Brain frameworks.
Definition
A Growth Lever is a measurable constraint within the growth system that significantly influences progress toward the North Star Metric.
Growth Levers represent the highest-impact areas for optimisation.
Growth Levers guide experiment prioritisation.
Structure:
North Star Metric
↓
Growth Lever
↓
Theme
↓
Experiment
Growth Levers ensure optimisation effort remains focused on meaningful improvements.
Characteristics of a Strong Growth Lever
A strong Growth Lever:
is directly connected to North Star Metric improvement
has measurable impact potential
represents meaningful behavioural or structural constraint
can be influenced through experimentation
allows multiple experiment variations
does not depend heavily on external uncontrollable factors
does not create conflict with other active Growth Levers
supports long-term system improvement
Weak Growth Lever Characteristics
Weak Growth Levers often:
focus on vanity metrics
lack measurable connection to North Star Metric
represent symptoms rather than constraints
are overly broad
are overly narrow
conflict with other optimisation priorities
cannot be meaningfully influenced through experimentation
Examples of weak levers:
increase website traffic without quality qualification
increase clicks without conversion consideration
increase impressions without behavioural impact
Growth Lever Impact Evaluation Dimensions
Growth Levers should be evaluated across multiple dimensions.
Expected North Star Impact
Estimate potential influence on North Star Metric.
Higher expected influence increases prioritisation strength.
Example:
improving onboarding completion rate may strongly influence retention.
Improvement Potential
Evaluate distance between current performance and realistic achievable performance.
Large improvement gaps often indicate strong leverage potential.
Benchmarks may be:
internal historical benchmarks
industry benchmarks
expected behavioural benchmarks
Cost and Resource Requirement
Evaluate:
implementation effort
technical complexity
operational complexity
time requirement
capital requirement
Higher cost does not necessarily disqualify lever.
Cost must be considered relative to impact.
Confidence Level
Estimate likelihood that improvement is achievable.
Confidence may be informed by:
research insights
existing data
competitor patterns
previous experiment outcomes
Confidence informs prioritisation but does not guarantee outcome.
Time Horizon
Growth Levers may operate across different time horizons.
Short-term levers:
produce faster feedback cycles
Long-term levers:
produce compounding system impact
Balanced portfolio often includes both.
Lever Interaction Consideration
Growth Levers should be evaluated relative to each other.
Some levers may:
support each other
conflict with each other
mask performance signals of other levers
Example:
traffic expansion may reduce conversion rate.
In such cases:
metrics should be segmented appropriately.
Lever definitions should avoid signal distortion.
Lever Quantity Constraint
MWMS typically focuses on:
1–3 active Growth Levers simultaneously.
Too many concurrent levers:
reduce learning clarity
reduce experiment focus
reduce signal interpretability
Focus improves experiment velocity.
Lever Lifecycle
Growth Levers evolve as constraints change.
Once a constraint is sufficiently improved:
new constraint becomes dominant
Growth Lever focus shifts accordingly.
Lever lifecycle supports continuous improvement.
Relationship to Growth Strategy
Growth Strategy defines long-term direction.
Growth Levers define current optimisation focus.
Growth Levers translate strategy into experimentation direction.
Relationship to Experimentation Brain
Experimentation Brain tests hypotheses affecting Growth Levers.
Growth Lever clarity improves experiment prioritisation quality.
Governance Rule
Growth Lever selection must remain aligned with:
North Star Metric
Finance Brain survivability constraints
Experimentation Brain statistical discipline
HeadOffice strategic direction
Growth Lever definitions should remain stable during experimentation cycle.
Version Control
v1.0
Initial definition of Growth Lever prioritisation structure.