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You Missed the Number but Every Commit Deal Closed. Here Is Where the Revenue Went

Pete Furseth 6 min read
forecast diagnosticscommit forecastpipeline analysisrevenue analyticsrevenue forecasting
You Missed the Number but Every Commit Deal Closed. Here Is Where the Revenue Went
Home/ Blog/ You Missed the Number but Every Commit Deal Closed. Here Is Where the Revenue Went

This is the most disorienting kind of miss. The commit list converted. The deals the team promised all landed. The number still came up short, and the forecast call has no explanation because every deal it discussed did exactly what it was supposed to do.

The forecast was not wrong about the deals. It was wrong about what a quarter is made of.

Why did we miss when every commit deal closed?

Commit describes one source of quarterly revenue, and a quarter has three.

Most teams forecast the pipeline they can see and miss the revenue motion they cannot see yet. Commit is a statement about deals that already exist in the CRM. It says nothing about revenue that will be created and closed inside the same quarter, and nothing about revenue pulled forward from a future period.

When a company runs a commit-only forecast, the in-quarter motion still happens. It just happens unforecasted. In a good quarter it delivers more than usual and the team beats the number without knowing why. In a bad quarter it delivers less and the team misses without knowing where.

The disorientation comes from the model, not the deals.

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Where does the missing revenue usually come from?

Decompose the quarter into three sources and the gap becomes a specific line rather than a mystery.
Revenue sourceWhat it isHow to measure itWhat breaks it
Carry-overDeals already in pipeline on day one with close dates in the quarterDay-one pipeline by stage, times realized stage conversionSlippage, stale deals, close dates set by convention
In-quarter created and closedDeals created, qualified, and closed inside the same quarterClosed won where created date and close date share a fiscal quarterPipeline creation shortfall in weeks 1 through 6
Pull-forwardDeals from future periods closed earlyClosed won where the prior period close date was laterFewer future deals available, or discount capacity exhausted
Run those three lines for the last four quarters. Most teams find that the in-quarter line carries a meaningful and stable share of bookings, and that they have never once forecasted it. A quarter where the carry-over line performs perfectly and the in-quarter line runs below its own average produces exactly the miss described here.

How much can day-one pipeline really tell me?

Less than the coverage ratio implies. Across ORM customers, about 20% of the in-quarter dated pipeline sitting there on day one closes in the quarter.

That means roughly 80% of the value carrying an in-quarter close date on the first day of the quarter is not realized in that quarter. It slips, it shrinks, or it dies.

This reframes the coverage conversation. A 3.5x coverage ratio built on day-one pipeline is not describing the quarter. It is describing a pool from which a minority converts, and the size of that minority depends on stage distribution, age, and segment rather than on the total.

Two teams with identical pipeline coverage can produce very different quarters. One is holding late-stage deals with buyer-confirmed dates. The other is holding aged opportunities with close dates that have already moved twice. The ratio cannot tell them apart, which is the argument in the 3x pipeline coverage rule is wrong.

Is pull-forward saving the quarter or borrowing from the next one?

Both, and the borrowing is almost always understated.

Pull-forward is a legitimate tool. It is also expensive in two ways that rarely appear in the same report.

The direct cost is discount. Buyers who accelerate a decision expect something for it, so the revenue you book is smaller than the revenue the deal would have produced on its natural timeline.

The indirect cost is the starting position of the next period. Every pulled-forward deal is removed from next quarter's carry-over line. If you saved this quarter with pull-forward and left next quarter's creation plan unchanged, you have already reduced the pipeline next quarter starts with.

Track pull-forward as its own number every quarter. A rising pull-forward share is the clearest sign a business is consuming future revenue to protect current reporting.

How do I catch this on day one instead of day ninety?

Model each source separately before the quarter starts, and hold each one to a named owner.

Build the quarter as an operating plan rather than a single number:

- Carry-over: which day-one deals close, at what realized amount, based on stage and age rather than rep sentiment. - In-quarter: how much revenue must be created and closed inside the period, translated into a weekly creation target. - Pull-forward: how much you are willing to accept and at what discount ceiling, decided in advance rather than in week 12.

The value of this work is the timing. Getting the forecast right in the last week of the quarter does not help anyone, because by then the quarter has already happened. The point is knowing the likely shape of the quarter on day one, early enough to change it. A model that holds from day 1 to day 90 and updates as conditions move is what makes that possible, and it is why ORM targets 95% accuracy on new and expansion revenue without manual adjustment.

What changes in the forecast call?

The call stops being a deal review and starts being a source review.

A commit-only call spends an hour interrogating 15 opportunities. That is useful for coaching and close to useless for forecasting, because the deals under discussion are the ones the team already understands best.

A source-based call asks four questions instead. Where does carry-over stand against its expected conversion? How much has been created and closed in-quarter against the required run rate? What has been pulled forward and at what cost? Which of the three lines is off, and by how much?

That structure makes a miss diagnosable. When commit converts and the quarter still misses, you can point at the line that failed, and you can point at it in week 4 rather than week 13. Track the result over time with a consistent forecast accuracy measure so the pattern shows up across quarters rather than as a one-off surprise.

Frequently Asked Questions

How can a quarter miss when every commit deal closed?

Commit only covers one of the three sources of quarterly revenue. The others are deals created and closed inside the quarter, and deals pulled forward from future periods. If your model treats commit as the whole forecast, the miss lands in the sources you never quantified.

What share of in-quarter pipeline actually closes in the quarter?

Across ORM customers, about 20% of the pipeline carrying close dates inside the quarter on the first day of that quarter closes in it. The remaining 80% of that value is not realized in the period, which is why day-one pipeline is a weak proxy for the quarterly number.

How do I measure revenue created and closed inside the same quarter?

Filter closed won deals where the opportunity created date and the close date fall in the same fiscal quarter, then track that as a percentage of total bookings across at least four quarters. That percentage is a forecastable input once you have a stable history for it.

Is pulling deals forward from next quarter a real cost?

Yes, and it is usually understated. Pull-forward normally requires a discount, so you book less revenue than the deal was worth, and you remove it from the next period's starting pipeline. The cost shows up as a harder quarter immediately after a saved one.

What should replace a commit-only forecast?

A decomposition that names each revenue source separately: carry-over pipeline expected to close, in-quarter created and closed revenue, and pull-forward. Each gets its own number and its own owner, so a miss can be traced to a specific source rather than to sentiment.

PF
Pete Furseth
ORM Technologies
Pete has built custom revenue forecast models for B2B SaaS companies for over a decade.

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