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A pipeline is worth its probability, not its headline

Sales pipelines are presented at full value. Weighting deals by stage, checking historical conversion and removing stale deals shows how much revenue is realistically coming.

10 min read · Level 3

The point

I trust a company's forecasting record more than its forecast. A founder whose past quarters landed close to plan has earned some confidence in the next one; a founder who has missed by half three times running is telling you something about the pipeline that no slide will contradict.

What is it?

A founder may say: 'We have 3,000,000 in pipeline.' That figure adds up every deal at full value.

Weight by stage.

Stage Value Conversion Weighted Discovery 1,500,000 10% 150,000 Proposal 1,000,000 30% 300,000 Negotiation 500,000 60% 300,000 Total 3,000,000 750,000

Use the company's actual conversion history, not generic percentages. If historically only 40% of negotiation-stage deals closed, not 60%, the weighted pipeline falls to 650,000.

Negotiation at 40%: 500,000 x 40% = 200,000 Total: 150,000 + 300,000 + 200,000 = 650,000

Remove stale deals. Deals sitting in a stage far longer than the typical sales cycle are unlikely to close.

Check timing. A deal expected 'this quarter' that has moved quarter to quarter several times is a forecast, not a pipeline.

Why does an investor care?

Because revenue forecasts, hiring plans and fundraising timelines often rest on the pipeline. Treating headline pipeline as expected revenue overstates growth and understates risk.

Historical conversion is also a direct test of how reliable the company's forecasting has been.

Educational, not personalised financial advice. Nothing in the Investor Academy is a recommendation to buy, sell or hold anything — what is right for you depends on your own circumstances and the rules where you live.

Example

Previous forecasts versus results.

Quarter Forecast new revenue Actual Hit Q1 400,000 180,000 45% Q2 450,000 210,000 about 47% Q3 500,000 240,000 48%

The company has consistently closed less than half of what it forecast. A current forecast of 600,000 is more realistically around 280,000 to 290,000 on this record (600,000 x 47% = 282,000).

The common mistake

Accepting total pipeline as a measure of future revenue, or using generic stage probabilities instead of the company's own conversion history.

How it works

Step 1: Ask for the pipeline by stage and age

Get value, stage and time in stage for each deal.

Step 2: Apply historical conversion

Use the company's actual stage-to-close rates.

Step 3: Remove stale deals

Exclude deals far beyond the normal sales cycle.

Step 4: Compare past forecasts with results

Use the forecasting record to adjust current forecasts.

When to use this

When a company's plan or valuation depends on revenue expected from its sales pipeline.

When not to use it

Do not rely on weighted pipeline for very early companies with too few closed deals to establish conversion rates.

How investors actually did it

A recurring pattern: forecast accuracy in sales operations

Sales operations practitioners and research firms have widely reported that many business-to-business sales teams miss their forecasts by significant margins, which is why weighted pipelines and historical conversion rates are standard tools for revenue planning.

A pipeline forecast is only as reliable as the conversion history behind it.

Do this now

  • Ask a company for its pipeline by stage
  • Compare its last three forecasts with actual results

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Related lessons

  • The most important line in an update is often the one that is missing — Founders naturally lead with good news. Reading an update well means comparing it with last period, noticing which figures disappeared and separating real warning signs from normal early-stage noise. (11 min)
  • Red flags: the signals that mean slow down — A red flag is not a reason to stop. It is a reason to stop moving at the speed you were moving, and to go and find out which of two explanations is the true one. (11 min)
  • What you were told, what you inferred, and what you checked — Almost everything that later turns out to be wrong was never actually verified - it was assumed, because it arrived alongside things that were true. (10 min)

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