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conducting-growth-due-diligence

Structures growth-focused DD with revenue quality, customer concentration, technology scalability, and organizational readiness. Use when conducting growth DD, validating revenue sustainability, or assessing scale capability.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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Conducting Growth Due Diligence

When To Use

  • Evaluating a growth-stage company for minority or majority equity investment
  • Validating whether reported revenue growth is sustainable and repeatable
  • Assessing whether a company's infrastructure (technology, people, processes) can support 2–5x scale
  • Conducting commercial DD alongside financial DD for expansion-capital or late-stage deals
  • Re-underwriting a portfolio company ahead of a follow-on round

Inputs To Gather

  • Financial data: Monthly P&L (36+ months), cohort revenue schedules, bookings vs. billings vs. revenue reconciliation, deferred revenue roll-forward
  • Customer data: Full customer list with ARR/revenue by account, contract start/end dates, expansion and churn history by cohort
  • Sales & pipeline data: CRM export (stage, close date, ACV, source), quota attainment by rep, win/loss analysis
  • Product & technology: Architecture overview, infrastructure cost trends, tech debt assessment, product roadmap, uptime/SLA history
  • Organization: Org chart, key-person dependencies, open headcount plan, employee tenure distribution, Glassdoor/pulse survey data
  • Market context: TAM/SAM sizing from third-party sources, competitive landscape, pricing benchmarking

Workflow

1. Revenue Quality Analysis

  • Decompose revenue into new, expansion, and renewal components by quarter
  • Calculate net revenue retention (NRR), gross retention, and logo retention by cohort vintage
  • Identify one-time, non-recurring, or channel-stuffed revenue; strip out and restate organic growth rate
  • Assess ASP trends — are deals getting larger (land-and-expand working) or compressing (discounting to hit targets)?
  • Test revenue recognition timing against cash collections; flag divergences > 10% [VERIFY against applicable accounting standards]

2. Customer Concentration & Dependency

  • Compute top-1, top-5, top-10, and top-20 customer concentration as % of total revenue
  • Flag any single customer > 10% of ARR or any top-5 cohort > 30%
  • Evaluate contract structures for at-risk customers: auto-renew vs. opt-in, termination-for-convenience clauses, pricing renegotiation windows
  • Cross-reference largest customers against public financial health indicators and industry headwinds
  • Map customer acquisition channels — over-reliance on a single channel (e.g., one partnership) is a concentration risk

3. Go-to-Market Scalability

  • Calculate CAC payback period, LTV/CAC ratio, and magic number by quarter and by channel
  • Assess sales capacity model: quota-carrying reps × average attainment vs. bookings plan
  • Evaluate ramp time for new reps and historical quota attainment curves (cohort of hire date)
  • Review marketing funnel conversion rates stage-by-stage; identify bottleneck stages
  • Test pricing power: history of price increases, competitive pricing position, willingness-to-pay data if available

4. Technology & Product Scalability

  • Review infrastructure architecture for horizontal scaling capability and single points of failure
  • Analyze cloud/hosting cost as % of revenue over time — should be flat or declining at scale
  • Assess tech debt burden: what % of engineering time goes to maintenance vs. new features?
  • Evaluate product-market fit signals: NPS/CSAT scores, feature adoption rates, support ticket trends
  • Review security posture: SOC 2 status, penetration test history, incident response plan [VERIFY compliance requirements by industry]

5. Organizational Readiness

  • Map key-person risk: identify roles where a single departure would materially impair operations
  • Assess management team completeness against the next stage of scale (e.g., does a $30M ARR company have a real CFO, VP Sales, VP Engineering?)
  • Review employee retention data — regrettable attrition > 15% annually in critical functions is a red flag
  • Evaluate board composition and governance maturity relative to stage
  • Identify cultural or process gaps: is the company still running on founder heroics or has it built repeatable systems?

6. Synthesis & Risk Mapping

  • Score each workstream (revenue quality, concentration, GTM, technology, org) on a 1–5 risk scale
  • Identify the 3–5 "must-believe" theses required for the investment to work
  • Map key risks to mitigants (contractual protections, post-close initiatives, management commitments)
  • Quantify downside scenarios: what happens to growth if NRR drops 10pts, if the top customer churns, if rep productivity declines?

Output

Deliver a structured growth DD memo containing:

  • Executive summary: Investment thesis, key strengths, top 3–5 risks, and overall DD verdict (proceed / proceed with conditions / pass)
  • Revenue quality section: Restated organic growth rates, cohort retention analysis, revenue composition breakdown
  • Customer analysis: Concentration tables, renewal risk calendar, dependency flags
  • GTM assessment: Unit economics summary, sales capacity model, channel analysis
  • Technology review: Scalability assessment, cost trajectory, tech debt impact
  • Org readiness: Key-person risk matrix, hiring gap analysis, management scorecard
  • Risk register: Tabulated risks with severity, likelihood, mitigant, and residual risk rating
  • Diligence items outstanding: Open questions, data requests pending, items requiring [VERIFY]

Quality Checks

  • Every quantitative claim traces back to a named data source (e.g., "per CRM export dated MM/DD" or "per management-provided cohort schedule")
  • Cohort math is internally consistent — individual cohort retentions must reconcile to blended NRR
  • Customer concentration percentages sum correctly and match the revenue totals used elsewhere
  • All [VERIFY] markers are preserved for jurisdiction-dependent, regulation-dependent, or unconfirmed data points
  • Revenue restatements clearly separate management-reported figures from analyst-adjusted figures
  • Downside scenarios use explicit, stated assumptions rather than arbitrary haircuts
  • The memo distinguishes between confirmed findings and management representations not yet independently validated

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