CRM ROI Calculator for Professional Services: Price the Proposals That Go Quiet

The leak is the proposal nobody chased

Firms lose very few pitches outright. What happens instead is that a good proposal goes out, the client says they are discussing it internally, and three weeks pass. Nobody wants to appear to be chasing fees, so nobody calls, and eventually the opportunity is quietly reclassified as lost. Ask any partner group to list the last ten proposals that died and most of them died of silence rather than of price.

The second leak is fee-earner time spent on pipeline admin

In a firm where people bill by the hour, every hour spent assembling a pipeline spreadsheet, hunting for the last version of a scope document or preparing numbers for a partner meeting has a defined cost. It rarely appears in a software business case because it is spread thinly across senior people who would never describe it as administration.

Five inputs carry the model. Proposals issued per month, counted firm-wide rather than per partner. Win rate over at least four quarters, because professional services volumes are too low for a single quarter to mean anything. Average engagement value, net of pass-through costs. Number of fee earners who would hold a licence. And weekly hours per fee earner spent on pipeline administration, which you should estimate by asking three people rather than by assuming.

Two sharpeners: median days between proposal issued and last recorded contact, and the share of revenue arriving through referrals.

These are example figures, substitute your own. None of them is a measured result or a claim about outcomes. They exist to show where each of your numbers belongs.

Note the deliberate omission: won value is not profit. An extra engagement consumes delivery capacity, and if your teams are already full the correct comparison is against the work you would otherwise have taken, not against zero. State that in the same paper as the arithmetic or the finance director will state it for you.

Take a baseline before go-live: proposals issued last quarter, wins, average value, and the number of live proposals with no recorded contact in fourteen days. That last figure is the one that should move first, and it is also the easiest to verify because it is a simple count rather than a rate.

At 90 days, win rate will still be noisy. A firm issuing a dozen proposals a month has not accumulated enough decisions for a four-point change to be distinguishable from chance, so resist declaring victory. Judge the quarter on leading indicators instead: stale proposals, median response time to inbound enquiries, and the share of opportunities with a next action recorded. Revisit win rate at twelve months, when the sample is large enough to say something.

It treats win rate as if it responds to follow-up alone, when in professional services it responds mostly to reputation, referral quality and whether the partner presenting is the partner delivering. It assumes proposal volume stays constant, when better pipeline hygiene often reduces volume by disqualifying weak opportunities earlier, which is a good outcome that makes the model look worse.

It values recovered fee-earner hours at rates that assume those hours become billable, which they frequently do not. And it ignores adoption, the real risk here: senior people who have run their own relationships for twenty years often decline to log them, and a pipeline covering two- thirds of the firm produces a forecast worse than none.

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