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ma-playbook

Plan an acquisition or prepare a company for sale using structured checklists and decision frameworks. Examine strategic fit, due diligence—the investigation before a deal—valuation approaches, negotiation terms, and plans for combining operations after acquisition.

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M&A strategy for acquiring companies or being acquired. Due diligence, valuation, integration, and deal structure. Use when evaluating acquisitions, preparing for acquisition, M&A due diligence, integration planning, or deal negotiation.

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适用场景

  • Screening acquisition targets against strategic goals
  • Organizing due diligence questions by business area
  • Preparing documents before selling a company
  • Reviewing negotiation terms and post-acquisition integration plans

包含的文件(3)

  • SKILL.md6.0 KB
  • references/due-diligence-checklist.md4.8 KB
  • references/integration-playbook.md5.6 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

M&A Playbook

Frameworks for both sides of M&A: acquiring companies and being acquired.

Keywords

M&A, mergers and acquisitions, due diligence, acquisition, acqui-hire, integration, deal structure, valuation, LOI, term sheet, earnout

Quick Start

Acquiring: Start with strategic rationale → target screening → due diligence → valuation → negotiation → integration.

Being Acquired: Start with readiness assessment → data room prep → advisor selection → negotiation → transition.

When You're Acquiring

Strategic Rationale (answer before anything else)

  • Buy vs Build: Can you build this faster/cheaper? If yes, don't acquire.
  • Acqui-hire vs Product vs Market: What are you really buying? Talent? Technology? Customers?
  • Integration complexity: How hard is it to merge this into your company?

Due Diligence Checklist

DomainKey QuestionsRed Flags
FinancialRevenue quality, customer concentration, burn rate>30% revenue from 1 customer
TechnicalCode quality, tech debt, architecture fitMonolith with no tests
LegalIP ownership, pending litigation, contractsKey IP owned by individuals
PeopleKey person risk, culture fit, retention riskFounders have no lockup/earnout
MarketMarket position, competitive threatsDeclining market share
CustomersChurn rate, NPS, contract termsHigh churn, short contracts

Valuation Approaches

The ranges below are illustrative, not current market data — always verify against current market comps before using them in a model or negotiation.

  • Revenue multiple: Industry-dependent (illustrative range: 2-15x ARR for SaaS, varying with growth rate, NRR, and rate environment)
  • Comparable transactions: What similar companies sold for — the most defensible anchor
  • DCF: For profitable companies only (most startups: use multiples)
  • Acqui-hire: Illustrative range: $1-3M per engineer in hot talent markets

Sources to verify against (check the latest edition): the SaaS Capital Index (private SaaS revenue multiples, updated monthly), Software Equity Group (SEG) Annual/Quarterly SaaS M&A Reports (transaction multiples), and Aventis Advisors' SaaS valuation multiples reports. Cross-check at least two before anchoring a price.

Integration Frameworks

See references/integration-playbook.md for the 100-day integration plan.

When You're Being Acquired

Readiness Signals

  • Inbound interest from strategic buyers
  • Market consolidation happening around you
  • Fundraising becomes harder than operating
  • Founder ready for a transition

Preparation (6-12 months before)

  1. Clean up financials (audited if possible)
  2. Document all IP and contracts
  3. Reduce customer concentration
  4. Lock up key employees
  5. Build the data room
  6. Engage an M&A advisor

Negotiation Points

TermWhat to WatchYour Leverage
ValuationEarnout traps (unreachable targets)Multiple competing offers
EarnoutMilestone definitions, measurement periodCash-heavy vs earnout-heavy split
LockupDuration, conditionsYour replaceability
Rep & warrantiesScope of liabilityEscrow vs indemnification cap
Employee retentionWho gets offers, at what termsKey person dependencies

Red Flags (Both Sides)

  • No clear strategic rationale beyond "it's a good deal"
  • Culture clash visible during due diligence and ignored
  • Key people not locked in before close
  • Integration plan doesn't exist or is "we'll figure it out"
  • Valuation based on projections, not actuals

Verification Loop (before any LOI or signature)

This skill frames the deal; two sibling skills verify it. Hand off — don't duplicate:

  1. Legal terms → general-counsel-advisor: run the LOI/term sheet through ../general-counsel-advisor/scripts/term_sheet_analyzer.py (12-dimension 0-100 score) and the definitive docs through ../general-counsel-advisor/scripts/contract_risk_scanner.py (12 founder-killer patterns: earnout traps, uncapped indemnity, vague IP, etc.). Any 🔴 finding goes to outside counsel before signing.
  2. Data diligence → chief-data-officer-advisor: run ../chief-data-officer-advisor/scripts/ai_training_data_audit.py (training-data rights, GDPR Art. 6 basis) and ../chief-data-officer-advisor/scripts/data_asset_valuator.py (data-asset value, M&A multiplier with carve-out penalties) on the target's data estate. Undocumented consent provenance is a price-reduction or walk-away item.
  3. Valuation math → cfo-advisor tools for the quantitative model; this playbook stays qualitative.

Loop the findings back into the negotiation-points table above before the next counter.

Integration with C-Suite Roles

RoleContribution to M&A
CEOStrategic rationale, negotiation lead
CFOValuation, deal structure, financing
GCLOI/term sheet review, contract risk scan, regulatory triggers
CDOData diligence: training-data rights, data-asset valuation
CTOTechnical due diligence, integration architecture
CHROPeople due diligence, retention planning
COOIntegration execution, process merge
CPOProduct roadmap impact, customer overlap

Resources

  • references/integration-playbook.md — 100-day post-acquisition integration plan
  • references/due-diligence-checklist.md — comprehensive DD checklist by domain
  • ../general-counsel-advisor/SKILL.md — term sheet analyzer + contract risk scanner
  • ../chief-data-officer-advisor/SKILL.md — data diligence + data-asset valuation

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