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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.

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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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