Don't start with the biggest portfolio company or the easiest — start with the most convincing. Rank companies on four factors: how referral- or partner-driven the revenue is, how much recoverable upside the size and dormancy suggest, how ready the data is, and how much hold period remains to act on the result. The best first pick scores high on all four: a relationship-driven business with material recoverable revenue, clean accessible data, and runway. Starting there makes the first win large and fast — which is what earns the mandate to roll out across the portfolio.
- The first engagement is a proof, not a maximum — pick for undeniability.
- Four factors: relationship-driven revenue, recoverable upside, data readiness, hold-period fit.
- Balance upside and speed — large enough to matter, simple enough to land fast.
- Defer transactional models and near-exit companies — they move down the queue, not off it.
The first engagement's job
When a firm decides to deploy revenue recovery across the portfolio, the instinct is to start with the company that has the most obvious problem or the most available executive. Both are wrong reasons. The first engagement is not really about that company — it is about proving the method to the rest of the firm. Its job is to produce a result so clear that the second, third, and tenth engagements become easy to authorise. That reframes the selection question entirely: you are not choosing where recovery is needed most, you are choosing where a win will be most convincing, soonest.
The four factors
1. Relationship-driven revenue. Recovery works on referral and partner dormancy, so the company's revenue must actually run through relationships — referrers, distributors, partners, repeat accounts. A business whose demand is genuinely relationship-mediated has dormancy to recover; a pure transactional model does not.
2. Recoverable upside. Size times dormancy. A larger company, or one you suspect has let many relationships lapse, carries more recoverable revenue. This is what makes the eventual number matter to the investment committee rather than reading as a rounding error.
3. Data readiness. The diagnostic runs on historical referral and pipeline data. A company that can produce a clean read-only extract quickly will deliver a result in days; one whose data is fragmented across systems will be slower regardless of its upside. Readiness is the speed dial.
4. Hold-period fit. There must be enough runway to act on the findings. A company early-to-mid hold can recover revenue and compound it; one weeks from a process can't act in time. Hold stage decides whether a great diagnosis can become a realised result.
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The rubric is most useful applied lightly and quickly across the whole book rather than agonised over for one company. Score each portfolio company on the four factors — even a simple high/medium/low on each is enough — and the shortlist usually reveals itself: the companies that are clearly relationship-driven, clearly material, data-ready, and mid-hold rise to the top. The free recovery tool gives you a fast upside estimate per company to make the "recoverable upside" factor concrete rather than a guess. The output is a ranked queue, not a single pick, which matters because the queue is the rollout plan: you work down it in waves, and each completed engagement makes the next easier to start.
What to avoid first
Two kinds of company belong lower in the queue, not because recovery can't help them but because they make poor first proofs. The first is the genuinely transactional business with little relationship-driven revenue — there is simply less dormancy to recover, so the result understates the method. The second is the company so close to exit that there's no time to act on the findings before a process; the diagnosis would be real but unrealised, which is unconvincing in exactly the wrong way. Neither is excluded permanently. They are simply not where you prove the point. Start where the proof is cleanest, then let the ranked queue carry you through the rest of the portfolio. On qualifying $30M+ engagements the recovery work carries our 3× fee recovery guarantee: we recover at least three times our fee, or we keep working at no additional fee until we do.
FAQ.
How do you decide which portfolio company to start revenue recovery with?
Rank companies on four factors: how referral- or partner-driven the revenue is, how much recoverable upside the size and dormancy suggest, how ready the data is, and where the company sits in its hold. The best first engagement scores high on all four — a relationship-driven business with material recoverable revenue, clean data, and runway. That makes the first win large and fast.
Should you start with the biggest portfolio company or the easiest?
Neither extreme. The biggest often has the most recoverable revenue but also the most complexity, slowing the first result; the easiest may produce a fast but unconvincing number. The right first pick balances upside and speed — large enough to matter, simple enough to land quickly. The first engagement's job is to be undeniable, not maximal.
What disqualifies a portfolio company from early revenue recovery?
Mainly two things: revenue that isn't relationship-driven (a transactional or e-commerce model has little dormancy to recover), and a company so close to exit there's no time to act before a process. Neither is a permanent exclusion, but both move a company down the queue behind referral-driven businesses with runway.
How to start.
Here is the fastest path to a real answer. No leap. A stair.
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Five inputs. Sixty seconds. A recoverable-revenue range to rank candidate companies by. No email required.
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How the ranked queue becomes a portfolio-wide rollout.
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Julia or Tyler personally. We triage your portfolio and pick the first engagement. No pitch.