Experiment Design Canvas
For Adaptive Leaders Testing Approaches
Experiment Overview
Basic Information
Experiment Name: [Clear, descriptive name]
Experiment ID: [Sequential tracking - EXP-2024-001]
Owner: [Person responsible for this experiment]
Team: [Team or department running experiment]
Start Date: [When experiment begins]
Duration: [How long experiment will run]
End Date: [When experiment concludes]
Strategic Context
Larger Goal/Initiative: [What bigger objective this experiment supports]
Strategic Question: [The key question this experiment will help answer]
Connection to Business Objectives: [How this relates to organizational goals]
Problem and Opportunity Definition
Current State Analysis
Problem Statement: [Clear description of the issue being addressed]
Current Metrics/Baseline: [Existing performance levels]
- Metric 1: [Current performance] - [Measurement method]
- Metric 2: [Current performance] - [Measurement method]
- Metric 3: [Current performance] - [Measurement method]
Pain Points: [Specific issues with current approach]
Stakeholder Impact: [Who is affected by current state and how]
Opportunity Hypothesis
Our Belief: [What we think might work better]
Because: [Why we think this approach will be better]
Which Will Result In: [Expected outcomes and improvements]
We'll Know We're Right If: [Specific, measurable indicators of success]
Experiment Design
Hypothesis Framework
IF [we make this change/intervention]
THEN [this outcome will occur]
BECAUSE [this is our underlying assumption about why it will work]
AND WE'LL MEASURE [specific metrics to test hypothesis]
Experiment Variables
Independent Variable (What We're Testing): [The specific change, intervention, or approach being tested]
Dependent Variables (What We're Measuring):
- Primary Outcome: [Main thing we expect to change]
- Secondary Outcomes: [Other changes we expect to see]
Control Variables (What We're Keeping Constant): [Factors that will remain unchanged during experiment]
Experiment Scope and Boundaries
What's Included:
- [Specific activities, processes, or groups included]
What's Excluded:
- [What will NOT be part of this experiment]
Experiment Environment:
- [Where experiment takes place - department, location, system]
Participant Selection:
- [Who will be involved and how they're selected]
Success Criteria and Measurement
Primary Success Metrics
Metric 1: [Primary measure of success]
- Current Baseline: [Starting point]
- Success Target: [What improvement indicates success]
- Measurement Method: [How this will be measured]
- Data Source: [Where data comes from]
Metric 2: [Secondary measure of success]
- Current Baseline: [Starting point]
- Success Target: [What improvement indicates success]
- Measurement Method: [How this will be measured]
- Data Source: [Where data comes from]
Leading Indicators
Early Signal 1: [What early indicator suggests experiment is working]
- When to Check: [How often/when to measure]
- What to Look For: [Specific signs of progress]
Early Signal 2: [What early indicator suggests experiment is working]
- When to Check: [How often/when to measure]
- What to Look For: [Specific signs of progress]
Data Collection Plan
Daily Measurements: [What will be tracked daily]
Weekly Measurements: [What will be assessed weekly]
End-of-Experiment Measurements: [Final assessment data]
Qualitative Feedback: [How subjective feedback will be collected]
Implementation Plan
Experiment Timeline
Week 1: [Setup and baseline activities]
- Day 1-2: [Specific activities]
- Day 3-5: [Specific activities]
Week 2: [Implementation activities]
- Key Activities: [What happens this week]
- Measurements: [What data is collected]
Week 3: [Continued implementation]
- Key Activities: [What happens this week]
- Measurements: [What data is collected]
Week 4: [Final implementation and assessment]
- Key Activities: [What happens this week]
- Final Measurements: [End-of-experiment data collection]
Resource Requirements
People: [Who needs to be involved and time commitment]
Budget: [Financial resources needed]
Technology/Tools: [Systems, software, or equipment needed]
Training: [Any preparation or education required]
Communication Plan
Stakeholder Updates: [Who needs updates and how often]
Progress Reporting: [How progress will be shared]
Issue Escalation: [Who to contact if problems arise]
Risk Assessment and Mitigation
Potential Risks
Risk 1: [Description of potential problem]
- Probability: [High/Medium/Low]
- Impact: [High/Medium/Low]
- Mitigation: [How risk will be prevented or managed]
- Contingency: [What to do if risk occurs]
Risk 2: [Description of potential problem]
- Probability: [High/Medium/Low]
- Impact: [High/Medium/Low]
- Mitigation: [How risk will be prevented or managed]
- Contingency: [What to do if risk occurs]
Experiment Safeguards
Stop Criteria: [Conditions that would cause experiment to be halted]
Rollback Plan: [How to return to original state if needed]
Stakeholder Protection: [How negative impacts on people will be prevented]
Learning and Decision Framework
Learning Objectives
Primary Learning Goal: [Main thing we want to learn from this experiment]
Secondary Learning Goals:
- [Additional insight we hope to gain]
- [Other questions this might help answer]
Decision Framework
If Results Are Positive: [What actions will be taken]
- Success Threshold: [Specific criteria for "positive"]
- Scale-up Plan: [How successful approach will be expanded]
If Results Are Negative: [What actions will be taken]
- Failure Threshold: [Specific criteria for "negative"]
- Learning Extraction: [How insights will be captured]
- Next Steps: [What alternative approaches to try]
If Results Are Mixed: [What actions will be taken]
- Analysis Plan: [How to interpret mixed results]
- Modification Options: [How approach might be adjusted]
Experiment Execution Tracking
Daily Log
Day 1: [Date]
- Activities Completed: [What was done]
- Observations: [What was noticed]
- Data Collected: [Measurements taken]
- Issues/Challenges: [Problems encountered]
Day 2: [Date]
- Activities Completed: [What was done]
- Observations: [What was noticed]
- Data Collected: [Measurements taken]
- Issues/Challenges: [Problems encountered]
Weekly Progress Summary
Week 1 Summary:
- Key Activities: [What was accomplished]
- Data Trends: [What the measurements show]
- Insights: [What we're learning]
- Adjustments Made: [Any changes to approach]
Results Analysis and Learning
Quantitative Results
Primary Metric Results:
- Baseline: [Starting measurement]
- Final Result: [Ending measurement]
- Change: [Difference and percentage change]
- Statistical Significance: [If applicable]
Secondary Metric Results:
- Baseline: [Starting measurement]
- Final Result: [Ending measurement]
- Change: [Difference and percentage change]
Qualitative Insights
Participant Feedback: [What people involved said about the experience]
Unexpected Observations: [Surprises or unintended consequences]
Process Insights: [What we learned about implementation]
Learning Summary
Hypothesis Validation: [Was our hypothesis correct?]
- Confirmed Assumptions: [What we got right]
- Incorrect Assumptions: [What we got wrong]
- New Assumptions: [New beliefs based on results]
Key Learnings:
- [Primary learning from this experiment]
- [Secondary learning from this experiment]
- [Process learning about experimentation]
Recommendations and Next Steps
Immediate Actions: [What should be done right away]
Scale-up Recommendations: [If/how to expand successful approaches]
Future Experiments: [Additional tests that should be run]
Process Improvements: [How to improve future experiments]
Experiment Database Entry
Classification
Experiment Type:
- [ ] Process improvement
- [ ] Product/service innovation
- [ ] Technology adoption
- [ ] Communication method
- [ ] Workflow optimization
- [ ] Team collaboration
- [ ] Customer experience
- [ ] Other: [Specify]
Success Level:
- [ ] Highly successful - recommend immediate scaling
- [ ] Successful - recommend broader implementation
- [ ] Partially successful - recommend modifications
- [ ] Unsuccessful - recommend alternative approaches
- [ ] Inconclusive - recommend follow-up experiments
Knowledge Sharing
Internal Sharing: [How learnings will be shared within organization]
Documentation Location: [Where full experiment details are stored]
Contact for Questions: [Who can provide more information about this experiment]
This canvas helps Adaptive Leaders design and execute systematic experiments to test new approaches while maximizing learning and minimizing risk.