Pivot Analyzer Skill Skill

Pivot Analyzer Skill

Overview

The Pivot Analyzer skill provides evidence-based frameworks for analyzing pivot decisions. It enables startups to systematically evaluate whether to pivot or persevere by compiling validation evidence, scoring pivot signals, generating alternatives, and planning pivot execution with documented rationale.

Capabilities

Core Functions

Evidence Compilation: Compile and organize validation evidence from customer discovery
Pivot Signal Scoring: Score and weight signals indicating need for pivot
Alternative Generation: Generate and categorize pivot alternatives
Option Evaluation: Evaluate pivot options against defined criteria
Cost Calculation: Calculate pivot costs (time, resources, opportunity)
Execution Planning: Plan pivot execution with milestones and metrics
Rationale Documentation: Document pivot rationale for stakeholders and investors
Progress Tracking: Track post-pivot progress against goals

Advanced Features

Pivot type classification (customer, problem, solution, channel, etc.)
Team alignment assessment
Investor communication planning
Resource reallocation modeling
Risk assessment by pivot type
Success probability estimation
Competitor response prediction
Market timing analysis

Usage

Input Requirements

Current business model/hypothesis
Validation evidence collected
Key metrics and trends
Customer feedback summary
Market signals and changes
Resource constraints
Team capabilities

Output Deliverables

Pivot signal scorecard
Evidence synthesis report
Pivot alternatives matrix
Evaluation criteria framework
Cost-benefit analysis
Recommended pivot type
Execution roadmap
Stakeholder communication plan

Process Integration

This skill integrates with the following processes:

pivot-decision-framework.js - Primary integration for all phases
product-market-fit-assessment.js - PMF signal analysis
business-model-canvas.js - Business model iteration
mvp-definition-development.js - MVP pivot requirements

Example Invocation

Skill: pivot-analyzer
Context: B2C mobile app struggling with retention
Input:
  - Current Model: Freemium B2C fitness app
  - Evidence:
    - DAU declining 10% MoM for 3 months
    - 40% of churned users cite "too generic"
    - Enterprise inquiries from 5 companies
    - High NPS among power users (small segment)
  - Runway: 8 months
Output:
  - Pivot Signal Score: 7.5/10 (Recommend Pivot)
  - Key Signals: Retention trend, market feedback, opportunity signals
  - Pivot Alternatives:
    1. Customer Segment Pivot: B2C to B2B (enterprise wellness)
    2. Zoom-in Pivot: Focus on power user segment
    3. Platform Pivot: Become API/SDK for other apps
  - Recommended: B2B pivot based on pull signals
  - Execution Plan: 12-week pivot roadmap
  - Investor Communication: Draft narrative

Dependencies

Lean Startup methodology frameworks
Decision analysis tools
Evidence tracking systems
Financial modeling capabilities
Communication templates

Best Practices

Base pivot decisions on evidence, not intuition or frustration
Distinguish between "not working yet" and "fundamentally flawed"
Ensure sufficient runway to execute pivot (6+ months recommended)
Consider multiple pivot types, not just the obvious one
Evaluate what assets and learnings carry forward
Get team alignment before committing to pivot
Communicate pivot rationale clearly to investors
Set clear success metrics for the pivot
Time-box pivot validation (avoid endless pivoting)
Preserve optionality when possible
Consider hybrid approaches (pivot + partial perseverance)
Document learnings from pre-pivot phase for future reference

Agent Skills: Pivot Analyzer Skill

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