kpi-dashboard-design
Design and build dashboards that track key performance indicators. Select relevant metrics, visualize data effectively, and communicate insights to stakeholders.
What this skill does
# KPI Dashboard Design
## Table of Contents
- [Overview](#overview)
- [When to Use](#when-to-use)
- [Quick Start](#quick-start)
- [Reference Guides](#reference-guides)
- [Best Practices](#best-practices)
## Overview
Effective KPI dashboards make performance visible, enable data-driven decisions, and help teams align around shared goals.
## When to Use
- Creating performance measurement systems
- Leadership reporting and visibility
- Operational monitoring
- Project progress tracking
- Team performance management
- Customer health monitoring
- Financial reporting
## Quick Start
Minimal working example:
```python
# Select relevant, measurable KPIs
class KPISelection:
KPI_CRITERIA = {
'Relevant': 'Directly aligned with business strategy',
'Measurable': 'Can be quantified and tracked',
'Actionable': 'Team can influence the metric',
'Timely': 'Measured frequently (daily/weekly)',
'Bounded': 'Has clear target/threshold',
'Simple': 'Easy to understand'
}
def identify_business_goals(self):
"""Map goals to KPIs"""
return {
'Revenue Growth': [
'Monthly Recurring Revenue (MRR)',
'Annual Recurring Revenue (ARR)',
'Customer Lifetime Value (CLV)',
'Average Revenue Per User (ARPU)'
],
'Customer Acquisition': [
'Customer Acquisition Cost (CAC)',
'Conversion Rate',
'Traffic to Lead Rate',
// ... (see reference guides for full implementation)
```
## Reference Guides
Detailed implementations in the `references/` directory:
| Guide | Contents |
|---|---|
| [KPI Selection Framework](references/kpi-selection-framework.md) | KPI Selection Framework |
| [Dashboard Design](references/dashboard-design.md) | Dashboard Design |
| [Dashboard Implementation](references/dashboard-implementation.md) | Dashboard Implementation |
| [KPI Monitoring & Governance](references/kpi-monitoring-governance.md) | KPI Monitoring & Governance |
## Best Practices
### ✅ DO
- Start with business goals, not data
- Limit dashboards to 5-7 core metrics
- Include both leading and lagging indicators
- Assign clear metric ownership
- Update dashboards regularly
- Make drill-down available
- Use visual hierarchy effectively
- Test with actual users
- Include context and benchmarks
- Document metric definitions
### ❌ DON'T
- Create dashboards without clear purpose
- Include too many metrics (analysis paralysis)
- Forget about data quality
- Build without stakeholder input
- Use confusing visualizations
- Leave dashboards stale
- Ignore mobile viewing experience
- Skip training on dashboard usage
- Create metrics no one can influence
- Change metrics frequently
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