PEMA

Methodology by Aethova

Private Equity + Mergers & Acquisitions

Will the portfolio company actually execute the Value Creation Plan?

Coming Soon

Execution risk intelligence for post-merger integration and PE portfolio assessment. PEMA replaces rear-view-mirror cultural due diligence with predictive behavioral intelligence—quantifying transformation readiness before the deal closes.

Cultural Due Diligence Is Broken

PE firms pay $100K+ for Big 4 cultural assessments that deliver backward-looking analysis. By the time the report lands, integration is already stalling.

$5M+

Synergy Delay Cost

A 6-month integration stall on a $10M Value Creation Plan costs $5M+ in delayed synergies.

70%

Transformation Failure Rate

Most post-merger transformations fail because leaders can't see human resistance until it's too late.

Rear View

Descriptive, Not Predictive

Standard cultural assessments tell you what happened. PEMA tells you what will happen next.

Predictive Intelligence for PE & M&A

PEMA extends BRIDGE's behavioral intelligence specifically for the PE operating partner's highest-stakes question.

🎯

VCP Execution Probability

Predict whether the portfolio company will actually deliver on the Value Creation Plan—before Day 1.

⚠️

Integration Risk Scoring

Quantify post-merger integration risks across leadership, culture, and operations before they surface.

🔍

Say/Do Gap Detection

Triangulate management claims against behavioral signals to surface hidden resistance in target companies.

📊

Day 1 Messaging Simulation

Test integration messaging before launch—predict employee reaction and optimize communication strategy.

Predictive vs. Descriptive

Existing Alternative PEMA Advantage
Big 4 Cultural Due Diligence Predictive vs descriptive—we forecast behavior, they report sentiment
Qualtrics / Culture Amp / Glint Behavioral intention vs satisfaction—BIS predicts action, NPS doesn't
Management Interviews Say/Do Gap detection—triangulates claims against behavioral signals
ChatGPT on Transcripts Multi-agent consensus—higher accuracy via agentic debate, not single-model guessing