SPACE Framework

The SPACE framework provides a multidimensional approach to measuring developer productivity. Unlike single-metric approaches, SPACE recognizes that productivity is complex and requires multiple perspectives.

What is SPACE?

SPACE is a framework developed by researchers at GitHub, Microsoft, and the University of Victoria. It argues that developer productivity cannot be measured by any single metric and requires looking at five dimensions:

• Satisfaction and well-being
• Performance
• Activity
• Communication and collaboration
• Efficiency and flow

Mapping GuideMode to SPACE

Dimension	Key Metrics	Source Cube
Satisfaction	avgSatisfaction, npsScore	Survey Responses
Performance	changeFailureRate, validationRate	Deployment Flow, Discovery Flow
Activity	count (sessions), productionDeploymentCount	Sessions, Deployment Flow
Communication	avgCollaboration, avgPrToReviewDays	Survey Responses, Delivery Flow
Efficiency	medianTotalLeadTimeDays, avgInterruptionRate	Delivery Flow, Metrics

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Satisfaction & Well-being (S)

Satisfaction captures how fulfilled developers feel with their work, tools, and environment. Well-being includes factors like burnout and work-life balance.

Key Metrics

Metric	Description	Source
avgSatisfaction	Average job satisfaction (1-5 scale)	Survey Responses
npsScore	Net Promoter Score (promoter% - detractor%)	Survey Responses
avgWorkLifeBalance	Work-life balance rating (1-5 scale)	Survey Responses

How to Use

Track these metrics over time to identify trends. Sudden drops may indicate team health issues. Compare across teams to identify systemic problems vs individual team challenges.

Measures:
- avgSatisfaction
- npsScore
- avgWorkLifeBalance

Dimensions: Teams.name, time (monthly)

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Performance (P)

Performance focuses on outcomes and quality, not just quantity. It measures whether the work being done achieves its intended goals.

Key Metrics

Metric	Description	Source
changeFailureRate	% of production deployments that fail	Deployment Flow
validationRate	% of discoveries that become validated features	Discovery Flow

How to Use

These are outcome-oriented metrics. Change failure rate indicates deployment quality, while validation rate shows how well research leads to valuable features.

Measures:
- changeFailureRate
- validationRate

Filter: isProduction = true (for change failure rate)
Dimensions: Projects.name, Teams.name

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Activity (A)

Activity measures the actions developers take. The SPACE framework cautions against using activity metrics alone, as they can be gamed and don’t indicate productivity.

Key Metrics

Metric	Description	Source
count	Total AI coding sessions	Sessions
productionDeploymentCount	Production deployments	Deployment Flow
totalDurationHours	Total time in AI sessions	Sessions

How to Use

Use activity metrics as context, not targets. High session counts with low productivity may indicate tooling problems. Low activity during high-stress periods may be appropriate.

Measures:
- Sessions.count
- Sessions.totalDurationHours
- productionDeploymentCount

Dimensions: Users.name, provider, time (weekly)

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Communication & Collaboration (C)

Collaboration metrics capture how effectively team members work together. This includes code reviews, knowledge sharing, and cross-functional participation.

Key Metrics

Metric	Description	Source
avgCollaboration	Team collaboration rating (1-5 scale)	Survey Responses
avgPrToReviewDays	Time waiting for first review	Delivery Flow
avgPrToApprovalDays	Time from PR creation to approval	Delivery Flow

How to Use

Long review times indicate collaboration bottlenecks. Self-reported collaboration scores provide context that metrics alone can’t capture.

Measures:
- avgCollaboration
- avgPrToReviewDays
- avgPrToApprovalDays

Dimensions: Teams.name, Projects.name

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Efficiency & Flow (E)

Efficiency captures how smoothly work flows through the system. Flow state is the productive mental state when developers can focus without interruptions.

Key Metrics

Metric	Description	Source
medianTotalLeadTimeDays	End-to-end delivery time	Delivery Flow
avgInterruptionRate	Interruptions during AI sessions	Metrics
avgTaskCompletionTime	Time to complete tasks	Metrics

How to Use

Lead time measures system efficiency. Interruption rate indicates how often developers lose flow state. Track these together to understand both system-level and individual-level efficiency.

Measures:
- medianTotalLeadTimeDays
- avgInterruptionRate
- avgTaskCompletionTime

Dimensions: Teams.name, type (feature/bug/chore)

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Building a SPACE Dashboard

A comprehensive SPACE dashboard should include at least one metric from each dimension:

SPACE Dashboard Query:

Satisfaction:
- avgSatisfaction (Survey Responses)
- npsScore (Survey Responses)

Performance:
- changeFailureRate (Deployment Flow)

Activity:
- Sessions.count
- Sessions.totalDurationHours

Communication:
- avgPrToReviewDays (Delivery Flow)

Efficiency:
- medianTotalLeadTimeDays (Delivery Flow)

Time dimension: Monthly trend
Team dimension: For comparison

Discovery vs Delivery Teams

GuideMode’s Survey Responses cube includes SPACE-specific questions for different team types:

SPACE Dimension	Discovery Teams	Delivery Teams
Satisfaction	discoverySatisfaction	jobSatisfaction
Performance	stakeholderConfidence	codeQualityConfidence
Activity	customerTouchpointFrequency	deploymentFrequency
Collaboration	crossFunctionalParticipation	codeReviewQuality
Efficiency	avgTimeToFirstValidation	avgBuildCicdSatisfaction

See Surveys & Assessments for complete survey metrics.

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Key Principles

1. Use multiple dimensions - No single metric captures productivity
2. Combine quantitative and qualitative - Survey data provides context for metrics
3. Avoid gaming - Don’t use activity metrics as targets
4. Team context matters - Discovery teams need different metrics than delivery teams
5. Trend over absolute - Track changes over time, not arbitrary targets

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Related

• Survey Responses - Complete survey metrics reference
• Sessions & AI - AI session analytics
• Delivery Flow - Delivery metrics reference
• DORA Metrics - DevOps performance framework