--- name: okr-kpi-patterns description: OKR framework, KPI trees, leading/lagging indicators, and success metrics patterns. Use when defining goals, measuring outcomes, or building measurement frameworks. context: fork agent: metrics-architect version: 1.0.0 tags: [product, metrics, okr, kpi, goals, measurement, 2026] author: OrchestKit user-invocable: false --- # OKR & KPI Patterns Frameworks for defining goals, measuring success, and building metrics-driven organizations. ## OKR Framework Objectives and Key Results align teams around ambitious goals with measurable outcomes. ### OKR Structure ``` Objective: Qualitative, inspiring goal ├── Key Result 1: Quantitative measure of progress ├── Key Result 2: Quantitative measure of progress └── Key Result 3: Quantitative measure of progress ``` ### Writing Good Objectives | Characteristic | Good | Bad | |---------------|------|-----| | Qualitative | "Delight enterprise customers" | "Increase NPS to 50" | | Inspiring | "Become the go-to platform" | "Ship 10 features" | | Time-bound | Implied quarterly | Vague timeline | | Ambitious | Stretch goal (70% achievable) | Sandbagged (100% easy) | ### Writing Good Key Results | Characteristic | Good | Bad | |---------------|------|-----| | Quantitative | "Reduce churn from 8% to 4%" | "Improve retention" | | Measurable | "Ship to 10,000 beta users" | "Launch beta" | | Outcome-focused | "Increase conversion by 20%" | "Add 5 features" | | Leading indicators | "Weekly active users reach 50K" | "Revenue hits $1M" (lagging) | ### OKR Example ```markdown ## Q1 2026 OKRs ### Objective 1: Become the #1 choice for enterprise teams **Key Results:** - KR1: Increase enterprise NPS from 32 to 50 - KR2: Reduce time-to-value from 14 days to 3 days - KR3: Achieve 95% feature adoption in first 30 days - KR4: Win 5 competitive displacements from [Competitor] ### Objective 2: Build a world-class engineering culture **Key Results:** - KR1: Reduce deploy-to-production time from 4 hours to 15 minutes - KR2: Achieve 90% code coverage on critical paths - KR3: Zero P0 incidents lasting longer than 30 minutes - KR4: Engineering satisfaction score reaches 4.5/5 ``` ## Leading vs. Lagging Indicators Understanding the difference is crucial for effective measurement. ### Definitions | Type | Definition | Characteristics | |------|------------|-----------------| | **Leading** | Predictive, can be directly influenced | Real-time feedback, actionable | | **Lagging** | Results of past actions | Confirms outcomes, hard to change | ### Examples by Domain ``` Sales Pipeline: Leading: # of qualified meetings this week Lagging: Quarterly revenue Customer Success: Leading: Product usage frequency Lagging: Customer churn rate Engineering: Leading: Code review turnaround time Lagging: Production incidents Marketing: Leading: Website traffic, MQLs Lagging: Customer acquisition cost (CAC) ``` ### The Leading-Lagging Chain ``` Leading Lagging ─────────────────────────────────────────────────────────► Blog posts Website MQLs SQLs Deals Revenue published → traffic → generated → created → closed → booked │ │ │ │ │ │ ▼ ▼ ▼ ▼ ▼ ▼ Actionable Actionable Somewhat Less Hard Result (SEO, ads) (content) control control ``` ### Using Both Effectively ```markdown ## Balanced Metrics Dashboard ### Leading Indicators (Weekly Review) | Metric | Current | Target | Status | |--------|---------|--------|--------| | Active users (DAU) | 12,500 | 15,000 | 🟡 | | Feature adoption rate | 68% | 75% | 🟡 | | Support ticket volume | 142 | <100 | 🔴 | | NPS responses collected | 89 | 100 | 🟢 | ### Lagging Indicators (Monthly Review) | Metric | Current | Target | Status | |--------|---------|--------|--------| | Monthly revenue | $485K | $500K | 🟡 | | Customer churn | 5.2% | <5% | 🟡 | | NPS score | 42 | 50 | 🟢 | | CAC payback months | 14 | 12 | 🔴 | ``` ## KPI Trees Hierarchical breakdown of metrics showing cause-effect relationships. ### Revenue KPI Tree ``` Revenue │ ┌─────────────────┼─────────────────┐ │ │ │ New Revenue Expansion Retained │ Revenue Revenue │ │ │ ┌─────┴─────┐ ┌─────┴─────┐ ┌─────┴─────┐ │ │ │ │ │ │ Leads × Conv Users × Upsell Existing × (1-Churn) Rate Rate ARPU Rate Revenue Rate ``` ### Product Health KPI Tree ``` Product Health Score │ ┌──────────────────┼──────────────────┐ │ │ │ Engagement Retention Satisfaction │ │ │ ┌────┴────┐ ┌────┴────┐ ┌────┴────┐ │ │ │ │ │ │ DAU/ Time Day 1 Day 30 NPS Support MAU in App Retention Retention Tickets ``` ## North Star Metric One metric that captures core value delivery. ### Examples by Business Type | Business Type | North Star Metric | Why | |---------------|-------------------|-----| | SaaS | Weekly Active Users | Indicates ongoing value | | Marketplace | Gross Merchandise Value | Captures both sides | | Media | Time spent reading | Engagement = value | | E-commerce | Purchase frequency | Repeat = satisfied | | Fintech | Assets under management | Trust + usage | ### North Star + Input Metrics ```markdown ## Our North Star Framework **North Star:** Weekly Active Teams (WAT) **Input Metrics:** 1. New team signups (acquisition) 2. Teams completing onboarding (activation) 3. Features used per team per week (engagement) 4. Teams inviting new members (virality) 5. Teams on paid plans (monetization) **Lagging Validation:** - Revenue growth - Net retention rate - Customer lifetime value ``` ## Metric Definition Template ```markdown ## Metric: [Name] ### Definition [Precise definition of what this metric measures] ### Formula ``` Metric = Numerator / Denominator ``` ### Data Source - System: [Where data comes from] - Table/Event: [Specific location] - Owner: [Team responsible] ### Segments - By customer tier (Free, Pro, Enterprise) - By geography (NA, EMEA, APAC) - By cohort (signup month) ### Frequency - Calculation: Daily - Review: Weekly ### Targets | Period | Target | Stretch | |--------|--------|---------| | Q1 | 10,000 | 12,000 | | Q2 | 15,000 | 18,000 | ### Related Metrics - Leading: [Metric that predicts this] - Lagging: [Metric this predicts] ``` ## Common Pitfalls | Pitfall | Mitigation | |---------|------------| | Vanity metrics | Focus on metrics that drive decisions | | Too many KPIs | Limit to 5-7 per team | | Gaming metrics | Pair metrics that balance each other | | Lagging only | Include leading indicators for early signals | | No baselines | Establish current state before setting targets | | Static goals | Review and adjust quarterly | ## 2026 Best Practices - **OKRs for goals, KPIs for health**: Use together, not interchangeably - **Leading indicator focus**: Key Results should be leading indicators - **Cascade with autonomy**: Align outcomes, let teams choose their path - **Regular calibration**: Weekly check-ins on leading, monthly on lagging - **AI-assisted insights**: Use AI to detect anomalies and suggest actions ## Related Skills - `product-strategy-frameworks` - Strategic context for metrics - `business-case-analysis` - Financial metrics and ROI - `prioritization-frameworks` - Using metrics to prioritize ## References - [OKR Workshop Guide](references/okr-workshop-guide.md) - [KPI Tree Builder](references/kpi-tree-builder.md) **Version:** 1.0.0 (January 2026)