The Stratified Analysis Framework
Our analytical approach builds understanding through layered investigation, moving from market foundations through competitive dynamics to detailed financial assessment. Each analytical stratum informs the next, creating comprehensive insight that supports confident decision-making.
Return to HomeFoundational Principles
Evidence-Based Analysis
Our methodology prioritizes verifiable data over narrative convenience. When industry projections seem optimistic, we examine historical precedents. When management presents growth plans, we assess execution capacity against comparable situations. This discipline helps distinguish realistic expectations from aspirational thinking.
Evidence-based doesn't mean skeptical by default—it means proportioning confidence to supporting data quality. Strong evidence warrants stronger conclusions. Weak evidence merits acknowledged uncertainty. This calibration supports decision-makers who need to understand not just what we think, but how certain we are.
Practical Implementation
Academic rigor matters, but so does delivering work that actually helps people make decisions. Our frameworks structure analysis in ways that align with how investment committees evaluate opportunities and how boards assess management performance. Theory informs our approach, but practical utility shapes our deliverables.
This means anticipating the questions decision-makers will ask and structuring analysis to address them directly. It means using familiar financial frameworks rather than proprietary models that require extensive explanation. Implementation-focused methodology produces work that integrates smoothly into existing processes.
Why This Approach Developed
The stratified framework emerged from observing common analytical shortcomings across investment contexts. Many diligence processes jump directly to financial projections without establishing market reality. Quantitative models sometimes optimize for statistical elegance over practical implementability. Board presentations occasionally bury key insights beneath excessive detail.
Our layered approach addresses these patterns by enforcing analytical sequence. Market assessment establishes context before competitive analysis. Industry structure informs company positioning. Operating fundamentals ground financial projections. Each analytical layer provides foundation for the next, preventing unsupported conclusions from propagating through the analysis.
This methodology also acknowledges resource constraints. Not every engagement warrants exhaustive investigation of every topic. The stratified structure allows appropriate depth allocation—comprehensive where it matters most, sufficient where supporting detail serves the decision rather than the analysis itself.
Framework Components
Market Foundation
Establishes market reality through size estimation, growth trajectory assessment, and structural characteristic identification. This layer grounds subsequent analysis in verifiable market conditions rather than aspirational projections.
Addressable market quantification using multiple methodologies
Historical growth pattern analysis and trend identification
Market structure assessment and competitive intensity evaluation
Competitive Dynamics
Maps competitive landscape through player identification, positioning analysis, and differentiation assessment. Understanding competitive dynamics prevents overestimation of market share capture potential and identifies genuine competitive advantages.
Competitor identification across direct and adjacent segments
Positioning analysis relative to established and emerging players
Sustainable differentiation evaluation based on defensibility factors
Operating Assessment
Evaluates operational fundamentals that drive financial performance. This layer connects business model claims to execution reality, examining unit economics, operational leverage, and scaling characteristics.
Unit economics validation across different business segments
Operating leverage analysis and scaling economics assessment
Execution capability evaluation relative to growth plans
Financial Integration
Synthesizes prior analytical layers into financial assessment framework. Projections connect to market opportunity, competitive position, and operational fundamentals established in earlier analysis. This integration prevents financial models from becoming detached from business reality.
Revenue projection grounded in market capture assumptions
Margin trajectory based on operating leverage characteristics
Sensitivity analysis highlighting key assumption dependencies
Analytical Adaptation
While the stratified framework provides consistent structure, application varies by engagement type and time constraints. Not every project requires equal depth across all layers. Private equity diligence emphasizes different aspects than quantitative model development or board reporting.
PE Diligence
Heavy emphasis on market foundation and competitive dynamics layers, with detailed operating assessment for portfolio fit evaluation
Quantitative Models
Focus on financial integration with systematic rules for market and competitive assessment, optimizing for consistent application
Board Support
Operating assessment and financial integration emphasis, contextualizing performance within competitive dynamics
Research Foundation and Standards
Academic Research Integration
Our analytical frameworks draw on established finance research in market efficiency, competitive strategy, and valuation methodology. This doesn't mean we cite academic papers in client deliverables—it means underlying principles reflect tested theory rather than arbitrary choices.
Market structure analysis informed by industrial organization economics
Competitive advantage frameworks grounded in strategic management research
Valuation approaches aligned with established corporate finance principles
Quality Assurance Processes
Systematic review processes ensure analytical consistency and catch errors before they reach clients. Multiple team members review work at different stages, checking for internal logical consistency, assumption reasonableness, and calculation accuracy.
Dual review requirement on all financial calculations and projections
Logic consistency checks across analytical layers before integration
Final senior review before deliverable release to clients
Data Source Standards
Primary Sources Prioritized
We preferentially use company filings, regulatory databases, and industry association reports over secondary aggregations. Primary sources reduce interpretation layers between original data and our analysis. When using aggregated data, we verify sampling methodology and understand any adjustments made by the aggregator.
Limitation Documentation
All deliverables include clear documentation of data limitations, gaps in available information, and resulting analytical constraints. If market sizing relies on dated figures or assumptions bridge information gaps, we state this explicitly. Acknowledging uncertainty builds appropriate decision confidence calibration.
Common Analytical Limitations
Disconnected Financial Projections
Conventional Approach
Many analyses begin with financial models, working backward to justify assumptions. This produces internally consistent projections that may lack connection to market reality. Growth rates get set based on what returns look attractive rather than what market capture implies.
Our Framework Difference
The stratified approach establishes market foundation first, then builds projections up from that base. Financial assumptions connect explicitly to prior analytical layers. This forces reconciliation between attractive returns and realistic market capture, making assumption quality transparent.
Superficial Competitive Analysis
Conventional Approach
Competitive sections often list major players without examining why market share distributions exist or how stable they've been. Differentiation claims go unexamined. This produces competitive landscapes that describe but don't explain, missing dynamics that affect investment outcomes.
Our Framework Difference
We assess competitive position through sustainability lenses—examining what creates observed market shares and how defensible they appear. Differentiation claims get tested against customer behavior and competitor capabilities. This focus on competitive dynamics rather than static positioning better predicts market share evolution.
One-Size Framework Application
Conventional Approach
Standardized analytical templates get applied uniformly regardless of context. PE diligence uses identical depth across all topics. Board presentations follow rigid formats. This consistency aids efficiency but can misallocate analytical effort, spending equal time on material and immaterial factors.
Our Framework Difference
While maintaining stratified structure, we adjust layer emphasis based on engagement type and key uncertainties. Material factors receive proportionate attention. This adaptive approach concentrates analytical effort where it most affects decisions, rather than distributing it uniformly across topics.
Distinctive Methodology Elements
Assumption Transparency
Every analytical conclusion traces back to explicit assumptions documented in methodology appendices. Clients can examine not just what we concluded, but why we concluded it and what would need to change for different conclusions. This transparency supports internal review and enables informed challenge of our work.
Integrated Quality Checks
The stratified structure creates natural validation points. Market findings should align with competitive dynamics. Operating metrics should support financial projections. When layers don't reconcile, we investigate rather than force consistency. These internal checks catch analytical errors before they reach deliverables.
Continuous Refinement
Post-engagement reviews examine which analytical elements proved most valuable and where effort could have allocated differently. These insights inform methodology evolution. Frameworks remain consistent in structure but continually improve in application through systematic learning from each engagement.
Technology Integration
Data Processing Enhancement
We use technology to accelerate data gathering and processing, not replace analytical judgment. Automated data collection focuses human effort on interpretation rather than compilation. Financial modeling tools enforce calculation accuracy and documentation standards. These efficiencies expand analytical capacity without compromising quality.
Methodology Documentation
Structured templates ensure consistent application of the stratified framework across different team members and engagement types. Documentation systems capture analytical decisions and supporting rationale, creating audit trails that support quality review. Technology serves methodology rather than directing it.
How We Track Analytical Quality
Client Feedback Integration
Post-engagement discussions explore which analytical elements proved most useful for decision-making and where deliverables could have better addressed needs. This feedback directly shapes how we structure future work, ensuring methodology evolution aligns with practical utility.
Internal Quality Metrics
We track internal indicators of analytical rigor and process effectiveness. These metrics help identify where methodology application succeeds and where improvements would strengthen future work. Quality measures focus on process discipline rather than arbitrary targets.
Success Definition
We define engagement success through decision support quality rather than validation of predetermined conclusions. Effective analysis sometimes challenges initial hypotheses or identifies material uncertainties. Success means providing clear, well-supported insight that improves decision confidence—even when that insight complicates rather than simplifies choices.
Methodology Application Across Contexts
The stratified analysis framework adapts to diverse investment contexts while maintaining structural consistency. Private equity diligence engagements emphasize market foundation and competitive dynamics layers, providing investment committees with grounded assessment of opportunity size and competitive positioning. These engagements typically span six to ten weeks, allowing comprehensive analysis across all framework layers with appropriate depth for deal decision support.
Quantitative model development applies the framework systematically across investment universes. Market foundation analysis establishes selection criteria boundaries. Competitive dynamics assessment informs positioning metrics. Operating evaluation creates financial health screens. This systematic application produces rules-based frameworks that institutional asset managers can implement consistently, with clear documentation supporting governance and investor reporting requirements.
Board presentation support focuses analytical effort on operating assessment and financial integration layers, contextualizing portfolio company performance within competitive dynamics established in earlier analysis. These engagements serve time-sensitive board cycles, requiring efficient analytical focus on material factors affecting oversight decisions. Our methodology's layered structure allows rapid depth deployment where boards require enhanced insight.
Methodology effectiveness depends on appropriate application rather than rigid adherence. Each engagement begins with scope discussions that identify which analytical layers require depth and which serve primarily as context. This flexibility allows methodology to serve decision needs rather than forcing decisions to accommodate analytical preferences. The stratified structure provides consistent quality framework while permitting adaptive emphasis across different investment contexts and timeline constraints.
Discuss Analytical Approach for Your Needs
If you're evaluating analytical support options, we'd welcome discussing how our methodology might address your specific requirements. Initial conversations focus on understanding your analytical needs and decision context rather than presenting standardized solutions.
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