HYP: Hypothesis Management

Document Type

Code: HYP
Name: Hypothesis Management
Domain: Learning & Decisions

Abstract

This specification defines the Hypothesis Management document type within the BSpec 1.0 Universal Business Specification Standard. It establishes normative requirements, structured templates, and implementation guidance for organizations documenting hypothesis management within the learning-decisions domain. This specification enables systematic, machine-readable documentation that supports strategic planning, operational execution, and organizational alignment.

Purpose and Scope

The Hypothesis Management document captures testable assumptions and beliefs about business, customers, markets, and solutions that guide organizational decision-making and learning. It establishes hypothesis frameworks that enable evidence-based validation, systematic experimentation, and continuous learning through iterative hypothesis development and testing.

Document Metadata Schema

---
id: HYP-{hypothesis-area}
title: "Hypothesis Management — {Hypothesis Area or Theme}"
type: HYP
status: Draft|Review|Approved|Active|Testing|Validated|Invalidated|Superseded
version: 1.0.0
owner: Product-Manager|Researcher|Team-Lead|Innovation-Manager
stakeholders: [product-teams, research-teams, decision-makers, stakeholders]
domain: learning-decisions
priority: Critical|High|Medium|Low
scope: hypothesis-management
horizon: strategic|tactical|operational
visibility: internal|team|organization

depends_on: [THY-*, STR-*, CUS-*, MKT-*]
enables: [EXP-*, LRN-*, DEC-*, PRD-*]

hypothesis_category: [customer, market, product, business-model, technical, strategic]
hypothesis_scope: [core assumption, feature assumption, market assumption, user assumption]
confidence_level: [high, medium, low confidence in hypothesis]
testability: [easily testable, moderately testable, difficult to test]
impact_potential: [high, medium, low potential impact if validated]
validation_status: [untested, testing, validated, invalidated, inconclusive]

success_criteria:
  - "Hypotheses clearly articulated and testable with defined success criteria"
  - "Systematic validation process produces reliable evidence and insights"
  - "Hypothesis learnings drive informed decision-making and strategy"
  - "Hypothesis culture promotes experimentation and evidence-based thinking"

assumptions:
  - "Hypotheses based on clear logic and reasoning"
  - "Validation methods appropriate for hypothesis type and context"
  - "Resources available for hypothesis testing and validation"

constraints: [Time, resource, and testing constraints]
standards: [Hypothesis formulation and testing standards]
review_cycle: experiment-cycle
---

Content Structure Template

# Hypothesis Management — {Hypothesis Area or Theme}

## Executive Summary
**Purpose:** {Brief description of hypothesis management scope and objectives}
**Hypothesis Category:** {Customer, market, product, business-model, technical, strategic}
**Hypothesis Scope:** {Core assumption, feature assumption, market assumption, user assumption}
**Confidence Level:** {High, medium, low confidence in hypothesis}

## Hypothesis Framework

### Hypothesis Philosophy
- **Evidence-Based Thinking:** {Decisions and beliefs grounded in testable evidence}
- **Systematic Validation:** {Structured approach to testing and validating assumptions}
- **Learning-Oriented Experimentation:** {Experiments designed to maximize learning}
- **Iterative Refinement:** {Continuous refinement of hypotheses based on evidence}

### Hypothesis Foundation
    ```yaml
    hypothesis_strategy:
      hypothesis_development:
        assumption_identification: [systematically identifying key assumptions]
        hypothesis_formulation: [creating clear, testable hypothesis statements]
        prioritization_framework: [prioritizing hypotheses for testing]
        validation_planning: [planning appropriate validation approaches]
    
      testing_methodology:
        experiment_design: [designing experiments to test hypotheses]
        measurement_frameworks: [defining metrics and success criteria]
        data_collection: [systematic approaches to gathering evidence]
        analysis_methods: [methods for analyzing and interpreting results]
    
      learning_integration:
        insight_synthesis: [synthesizing learnings from hypothesis testing]
        decision_application: [applying learnings to decision-making]
        hypothesis_evolution: [evolving hypotheses based on new evidence]
        knowledge_building: [building organizational knowledge from hypothesis work]
    ```

### Hypothesis Architecture
- **Hypothesis Hierarchy:** {Strategic, tactical, and operational hypothesis levels}
- **Hypothesis Categories:** {Different types of hypotheses and their characteristics}
- **Testing Strategies:** {Various approaches to hypothesis validation}
- **Learning Flows:** {How hypothesis insights inform broader learning}

## Hypothesis Development and Formulation

### Hypothesis Identification Process
    ```yaml
    identification_framework:
      assumption_discovery:
        strategic_assumptions: [assumptions underlying strategic decisions]
        operational_assumptions: [assumptions about how work gets done]
        customer_assumptions: [assumptions about customer needs and behaviors]
        market_assumptions: [assumptions about market dynamics and opportunities]
    
      hypothesis_sources:
        strategic_planning: [hypotheses emerging from strategic planning]
        problem_analysis: [hypotheses from problem identification and analysis]
        opportunity_exploration: [hypotheses from opportunity assessment]
        stakeholder_input: [hypotheses from stakeholder feedback and input]
    
      prioritization_criteria:
        impact_potential: {potential impact if hypothesis is validated}
        learning_value: {value of learning regardless of validation outcome}
        testability: {feasibility and cost of testing hypothesis}
        strategic_importance: {importance to strategic objectives and decisions}
    ```

### Hypothesis Formulation Standards
- **Clear Statement:** {Precise, unambiguous hypothesis statements}
- **Testable Format:** {Hypotheses structured for empirical testing}
- **Success Criteria:** {Clear criteria for validation or invalidation}
- **Measurable Outcomes:** {Specific, measurable outcomes for testing}

### Hypothesis Documentation Structure
    ```yaml
    hypothesis_documentation:
      hypothesis_statement:
        if_condition: {specific condition or intervention}
        then_outcome: {expected outcome or result}
        because_rationale: {underlying logic or reasoning}
        success_metrics: [specific metrics that indicate success]
    
      hypothesis_context:
        background: {situation and context that led to hypothesis}
        stakeholders: [who is affected by this hypothesis]
        assumptions: [underlying assumptions supporting hypothesis]
        constraints: [limitations affecting hypothesis testing]
    
      validation_plan:
        testing_approach: {how hypothesis will be tested}
        success_criteria: {what constitutes validation or invalidation}
        timeline: {when testing will occur and for how long}
        resources_required: [resources needed for testing]
    ```

## Hypothesis Testing and Validation

### Experiment Design Framework
    ```yaml
    testing_methodology:
      experiment_types:
        controlled_experiments: [formal A/B tests and controlled trials]
        observational_studies: [analyzing existing data and behaviors]
        prototype_testing: [testing with prototypes and mock-ups]
        market_research: [surveys, interviews, and market analysis]
    
      validation_approaches:
        quantitative_validation: [statistical testing and data analysis]
        qualitative_validation: [interviews, observations, and feedback]
        behavioral_validation: [observing actual user behavior]
        market_validation: [testing in real market conditions]
    
      measurement_design:
        leading_indicators: [early signals of hypothesis validation]
        lagging_indicators: [ultimate outcomes measuring hypothesis success]
        control_variables: [variables that need to be controlled during testing]
        success_thresholds: [specific thresholds for validation]
    ```

### Testing Implementation
- **Experiment Setup:** {Establishing proper testing conditions and controls}
- **Data Collection:** {Systematic collection of relevant evidence}
- **Quality Assurance:** {Ensuring reliability and validity of testing}
- **Bias Mitigation:** {Addressing potential biases in testing and analysis}

### Results Analysis and Interpretation
    ```yaml
    analysis_framework:
      statistical_analysis:
        significance_testing: [determining statistical significance of results]
        confidence_intervals: [establishing confidence in result accuracy]
        effect_size_analysis: [understanding magnitude of effects observed]
        power_analysis: [ensuring adequate sample sizes for reliable results]
    
      qualitative_analysis:
        pattern_identification: [identifying patterns in qualitative data]
        theme_analysis: [analyzing themes from interviews and feedback]
        contextual_interpretation: [understanding results in proper context]
        triangulation: [validating findings across multiple data sources]
    
      interpretation_guidelines:
        validated_hypotheses: [criteria for considering hypothesis validated]
        invalidated_hypotheses: [criteria for considering hypothesis invalidated]
        inconclusive_results: [handling ambiguous or unclear results]
        unexpected_findings: [addressing results that contradict expectations]
    ```

## Hypothesis Lifecycle Management

### Hypothesis Status Tracking
    ```yaml
    lifecycle_management:
      status_definitions:
        proposed: {hypothesis identified but not yet approved for testing}
        approved: {hypothesis approved for testing with resources allocated}
        testing: {hypothesis currently being tested through experiments}
        validated: {hypothesis supported by sufficient evidence}
        invalidated: {hypothesis contradicted by evidence}
        inconclusive: {testing completed but results unclear}
    
      progression_criteria:
        approval_criteria: [requirements for moving from proposed to approved]
        testing_initiation: [conditions for beginning hypothesis testing]
        validation_thresholds: [evidence required for validation]
        invalidation_thresholds: [evidence required for invalidation]
    
      documentation_requirements:
        status_updates: [regular updates on hypothesis testing progress]
        evidence_documentation: [comprehensive documentation of evidence]
        decision_rationale: [rationale for status changes and decisions]
        learning_capture: [learnings captured regardless of validation outcome]
    ```

### Hypothesis Evolution and Refinement
- **Hypothesis Updates:** {Modifying hypotheses based on initial evidence}
- **Sub-hypothesis Development:** {Breaking down complex hypotheses}
- **Hypothesis Combinations:** {Combining related hypotheses for testing}
- **Successor Hypothesis Creation:** {Creating new hypotheses from learnings}

### Portfolio Management
    ```yaml
    portfolio_approach:
      hypothesis_portfolio:
        portfolio_balance: [balancing different types and risk levels of hypotheses]
        resource_allocation: [allocating testing resources across hypothesis portfolio]
        timing_coordination: [coordinating testing timing across hypotheses]
        dependency_management: [managing dependencies between hypotheses]
    
      risk_management:
        testing_risks: [risks associated with hypothesis testing]
        outcome_risks: [risks if hypotheses are validated or invalidated]
        resource_risks: [risks related to resource allocation and availability]
        timeline_risks: [risks related to testing timelines and schedules]
    
      performance_tracking:
        portfolio_metrics: [metrics for evaluating overall hypothesis portfolio]
        success_rates: [tracking validation and learning success rates]
        learning_velocity: [measuring speed of learning and insight generation]
        decision_impact: [measuring impact of hypothesis learnings on decisions]
    ```

## Learning Integration and Application

### Learning Synthesis
    ```yaml
    learning_framework:
      insight_development:
        validated_learnings: [insights from validated hypotheses]
        invalidated_learnings: [insights from invalidated hypotheses]
        process_learnings: [insights about hypothesis development and testing]
        meta_learnings: [insights about learning and validation processes]
    
      knowledge_integration:
        strategic_implications: [what learnings mean for strategy]
        operational_implications: [what learnings mean for operations]
        product_implications: [what learnings mean for product development]
        market_implications: [what learnings mean for market approach]
    
      decision_application:
        immediate_decisions: [decisions that can be made based on current learnings]
        future_decision_preparation: [preparation for future decisions]
        strategy_adjustments: [strategic adjustments based on learnings]
        resource_reallocation: [resource changes based on validated learnings]
    ```

### Organizational Learning Integration
- **Best Practice Development:** {Developing best practices from hypothesis work}
- **Capability Building:** {Building organizational capability for hypothesis management}
- **Culture Development:** {Fostering hypothesis-driven culture}
- **Process Integration:** {Integrating hypothesis work into organizational processes}

### Continuous Improvement
    ```yaml
    improvement_framework:
      process_improvement:
        hypothesis_quality: [improving quality of hypothesis formulation]
        testing_efficiency: [making testing more efficient and effective]
        analysis_sophistication: [enhancing analysis and interpretation capabilities]
        learning_application: [improving application of learnings to decisions]
    
      capability_development:
        skill_building: [developing hypothesis management skills]
        tool_enhancement: [improving tools and technologies for hypothesis work]
        methodology_evolution: [evolving hypothesis methodologies and approaches]
        cultural_strengthening: [strengthening hypothesis-driven culture]
    
      innovation_support:
        experimentation_acceleration: [accelerating experimentation and learning]
        risk_taking_encouragement: [encouraging intelligent risk-taking]
        failure_learning: [learning effectively from failed hypotheses]
        breakthrough_recognition: [recognizing and scaling breakthrough insights]
    ```

## Hypothesis Culture and Governance

### Hypothesis-Driven Culture
    ```yaml
    culture_building:
      mindset_development:
        curiosity_promotion: [encouraging curiosity and questioning]
        evidence_appreciation: [valuing evidence over opinion]
        learning_orientation: [focusing on learning over being right]
        experimentation_comfort: [comfort with uncertainty and testing]
    
      behavioral_norms:
        hypothesis_articulation: [clearly stating assumptions as hypotheses]
        evidence_seeking: [actively seeking evidence for beliefs]
        bias_recognition: [recognizing and addressing cognitive biases]
        learning_sharing: [sharing learnings from hypothesis testing]
    
      support_systems:
        training_programs: [training in hypothesis development and testing]
        tool_provision: [providing tools for hypothesis management]
        time_allocation: [allocating time for hypothesis work]
        recognition_systems: [recognizing good hypothesis work]
    ```

### Governance and Standards
- **Quality Standards:** {Standards for hypothesis formulation and testing}
- **Review Processes:** {Regular review of hypothesis portfolio and progress}
- **Resource Governance:** {Governance for allocating testing resources}
- **Ethical Guidelines:** {Ethical guidelines for hypothesis testing}

### Advanced Hypothesis Practices
    ```yaml
    advanced_practices:
      systematic_frameworks:
        lean_startup: [applying lean startup methodology to hypothesis testing]
        design_thinking: [using design thinking for hypothesis development]
        scientific_method: [applying scientific method rigor to business hypotheses]
        agile_experimentation: [integrating hypothesis testing with agile development]
    
      sophisticated_testing:
        multivariate_testing: [testing multiple hypotheses simultaneously]
        longitudinal_studies: [long-term testing and tracking]
        cohort_analysis: [analyzing different groups over time]
        causal_inference: [establishing causal relationships from hypothesis testing]
    
      organizational_integration:
        strategy_integration: [integrating hypothesis work with strategic planning]
        product_integration: [integrating with product development processes]
        innovation_integration: [integrating with innovation and R&D processes]
        decision_integration: [integrating with organizational decision-making]
    ```

## Validation
*Evidence that hypotheses drive learning, inform decisions, and enable evidence-based organizational development*

## Quality Standards

### Bronze Level (Minimum Viable)
- [ ] Basic hypothesis formulation with simple testing and validation approaches
- [ ] Simple tracking and basic learning capture from hypothesis work
- [ ] Basic hypothesis governance and quality standards
- [ ] All required metadata fields completed

### Silver Level (Investment Ready)
- [ ] Comprehensive hypothesis framework with systematic development and testing
- [ ] Structured lifecycle management with portfolio approach and learning integration
- [ ] Active hypothesis governance with quality standards and continuous improvement
- [ ] Regular hypothesis effectiveness review and process optimization

### Gold Level (Operational Excellence)
- [ ] Advanced hypothesis capabilities with sophisticated testing and analysis
- [ ] Comprehensive hypothesis ecosystem with integrated culture and governance
- [ ] Hypothesis excellence driving organizational learning and decision-making
- [ ] Strategic hypothesis management enabling innovation and competitive advantage

## Common Pitfalls

1. **Untestable hypotheses**: Creating hypotheses that cannot be empirically tested
2. **Confirmation bias**: Testing hypotheses to confirm rather than to learn
3. **Poor measurement**: Using inappropriate or insufficient metrics for validation
4. **Learning isolation**: Not integrating hypothesis learnings into decision-making

## Success Patterns

1. **Clear formulation**: Well-structured, testable hypotheses with clear success criteria
2. **Rigorous testing**: Systematic, unbiased testing with appropriate methodologies
3. **Learning focus**: Emphasis on learning regardless of validation outcome
4. **Decision integration**: Strong connection between hypothesis learnings and decisions

## Relationship Guidelines

### Typical Dependencies
- **THY (Theory)**: Business theory provides foundation for hypothesis development
- **STR (Strategy)**: Strategic framework guides hypothesis prioritization
- **CUS (Customer)**: Customer insights inform customer-related hypotheses
- **MKT (Market)**: Market analysis informs market-related hypotheses

### Typical Enablements
- **EXP (Experiments)**: Hypotheses drive experimental design and execution
- **LRN (Learnings)**: Hypothesis testing generates organizational learning
- **DEC (Decisions)**: Hypothesis validation informs decision-making
- **PRD (Products)**: Product hypotheses guide product development

## Document Relationships

This document type commonly relates to:

- **Depends on**: THY (Theory), STR (Strategy), CUS (Customer), MKT (Market)
- **Enables**: EXP (Experiments), LRN (Learnings), DEC (Decisions), PRD (Products)
- **Informs**: Innovation strategy, product development, strategic planning
- **Guides**: Experimentation design, learning priorities, resource allocation

## Validation Checklist

- [ ] Executive summary with clear purpose, category, scope, and confidence level
- [ ] Hypothesis framework with philosophy, foundation, and architecture
- [ ] Development and formulation with identification process, standards, and documentation
- [ ] Testing and validation with experiment design, implementation, and analysis
- [ ] Lifecycle management with status tracking, evolution, and portfolio management
- [ ] Learning integration with synthesis, organizational integration, and continuous improvement
- [ ] Culture and governance with development, standards, and advanced practices
- [ ] Validation evidence of learning driving, decision informing, and organizational development

---

## Related Documents

- [Back to Document Types](/docs/document-types)
- [Domain: Learning & Decisions](/docs/domains/learning-decisions)
- [Full Specification](/spec/v1-0-0)