A commercial due diligence answers one question, asked from the buyer's or lender's chair: will this business perform commercially the way the deal model assumes it will, and why or why not? That's narrower than it sounds. CDD doesn't audit the target's books. Financial due diligence does that job: quality of earnings, working-capital normalization, off-balance-sheet exposure. It doesn't review contracts, IP, litigation, or employment law, which is legal due diligence, and it doesn't model tax structuring or exposure, which is tax due diligence. CDD's territory is the commercial engine: the market the target competes in, the customers who fund it, the competitors who constrain it, and the operational levers the plan depends on. You read all of it commercially, and leave the forensic work to others.
In practice the four workstreams run in parallel on the same tight clock and hand findings to each other constantly. A customer-concentration finding from CDD becomes a contract-review priority for legal. A same-store deceleration from CDD becomes a quality-of-earnings flag for financial DD. Each still keeps its own lane. A good CDD analyst never drifts into re-auditing the balance sheet just because it feels more concrete than calling customers.
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Who commissions a commercial due diligence?
So who commissions a CDD, and why is the clock always short? It might be a private-equity sponsor evaluating a platform investment or an add-on, inside an exclusivity window measured in weeks. It might be a corporate acquirer sizing up a target before a board goes to market with an offer. Or it might be a lender underwriting a leveraged loan, who needs comfort that the cash flows will service the debt. In every case you're working against a hard deadline set by someone else's process. Your access to the target is generous on paper: a data room, management presentations, sometimes management interviews. In practice it's stingy, because management has every incentive to show you their best quarter, their happiest customers, their most defensible narrative. Everything that follows exists because of that one structural fact. The seller controls what you see first, so your job is to go and find what the seller didn't think to show you.
The CDD thesis: from "we like this deal" to something that can be killed
Every CDD starts life as an investment thesis, the sponsor's or acquirer's story for why this deal, why now. A thesis is still only a hypothesis about the world, and a hypothesis is useful only if it can be wrong. It's the hypothesis-driven problem solving you already know, applied at the scale of an entire deal. State the thesis as two or three specific, falsifiable claims. Then attach to each one an explicit kill criterion: the finding that, if you saw it, would flip your recommendation from go to no-go. You write it down in advance, before you know the answer. A thesis with no kill criterion is a hope, and a team that only ever confirms hopes is doing theatre.
Why do kill criteria matter in a CDD?
Kill criteria do real work beyond intellectual hygiene. First, they force you to be specific. Nothing can kill "the market is attractive", but one number can cleanly kill "same-store growth, stripped of acquisition effects, is durably above 3%". Second, they focus the four weeks. Once you know what would kill each hypothesis, you know which exhibit, which customer segment, which expert call would move the needle. Everything else is a nice-to-have. Third, and most important for the synthesis at the very end, kill criteria create a veto rule: no weighted scorecard, however favorable, is allowed to overrule a hypothesis that was actually killed. A team that lets a good composite score talk it out of a killed hypothesis has slipped back into confirming hopes.
Key questions: the CDD issue tree across five lenses
A CDD workplan is a MECE issue tree built around five standard lenses. Each one answers a distinct question and produces a distinct work product:
| Lens | Central question | Typical work product |
|---|---|---|
| Market | Is the market big enough, growing, and structured attractively? | Top-down + bottom-up market model, reconciled |
| Competitive position | Does the target have a real, durable advantage, or just current share? | Competitor benchmarking table + moat read |
| Customer | Do real customers behave the way the deal model assumes they do? | VoC program: interviews, surveys, churn/loyalty reads |
| Financial quality | Is the reported growth and margin real, recurring, and not concentrated in a few accounts? | Same-store bridge, cohort/retention read, concentration check |
| Execution / organizational risk | Can this team actually deliver the plan, and what happens if a key person leaves? | Management assessment, key-person and regulatory risk flags |
Every hypothesis from stage 2 gets mapped onto the lens, or lenses, that will test it. That map is the page a partner reads before the four weeks start. It's what turns "go find out if we're right" into a staffed workplan with named owners and named deliverables.
How do you keep the CDD issue tree MECE?
Two habits keep the tree MECE and stop it turning into a checklist copied from the last deal. First, no lens is optional by default. A target can look unimpeachable on market and competitive position and still fail on execution risk, say because the one person who holds every key customer relationship is retiring next year. So all five get scoped, even if some get only a day of work. Second, the tree is bespoke to the thesis. You don't apply a template blind. The meta-skill of spotting when a framework misleads you applies here at the level of a whole engagement. If the thesis is a roll-up at heart (buy small, integrate, resell at a higher multiple), the execution lens needs to weigh far more heavily than it would for a straightforward organic-growth story. The entire investment case rests on integration actually working.