Deriving Realistic Revenue Forecasts From Your Pipeline

At the start of every quarter, the same question tends to come up: how much revenue will we actually close? Many teams answer it with gut feeling or an optimistic total of all open deals. Both reliably lead to disappointment. A realistic forecast doesn't come from hope, but from what the pipeline tells you about how your deals behave. This article shows how to derive a number you can genuinely trust in a management review from the data you're already collecting anyway.

Why the sum of open deals is not a forecast

If you add up all your open deals and present that total as expected revenue, you're effectively assuming every single deal will be won. That never happens. The opposite extreme is just as wrong: counting only the deals that have already been verbally confirmed. That ignores most of your pipeline and systematically underestimates you.

A useful forecast sits in between. It weights each deal by the probability that it will actually close. That's exactly why you need clean stages and honest numbers from the past.

The building blocks of a reliable forecast calculation

Three figures determine the quality of your forecast. Once you know them, you can work out the rest:

• Win rate per stage: How many deals at "proposal sent" are won in the end? You determine this rate from your historical data, not from a hunch.
• Average cycle time: How long does a deal take from a given stage to closing? It tells you which deals can realistically still land in the current quarter.
• Deal value: The expected order value, ideally without rounded-up wishful numbers.

The weighted forecast is then simple: you multiply each deal value by the win rate of its stage and add up the results. A proposal worth CHF 20,000 at a stage with a 40 percent historical win rate therefore contributes CHF 8,000 to the forecast, not the full CHF 20,000.

A quick worked example

Suppose you have four deals in the pipeline: CHF 20,000 at 40 percent, CHF 15,000 at 60 percent, CHF 30,000 at 20 percent and CHF 10,000 at 80 percent. The weighted total comes to CHF 8,000 plus CHF 9,000 plus CHF 6,000 plus CHF 8,000, so CHF 31,000. That is your realistic expectation, even though the nominal pipeline shows CHF 75,000. This difference isn't an error, but exactly the honest information you want to steer by.

A forecast is not the sum of your wishes, but the average of your last twenty deals.

The most common sources of error

Even a clean formula produces nonsense if the input data is wrong. These pitfalls are especially common in Swiss SMEs:

1. Stale deals: Deals that have been sitting at the same stage for months inflate the pipeline. Set a clear rule for when a deal is marked as lost.
2. Subjective probabilities: If every salesperson assigns their own percentage, the values aren't comparable. Derive the rates from real closes, not from estimates.
3. Mixed time frames: A big deal that won't close until next year doesn't belong in the quarterly forecast. Filter consistently by expected close date.

Anyone who has these three points under control is already much closer to reality than with any spreadsheet workaround.

From manual calculation to a live overview

In theory the calculation is simple. In practice it often fails because no one has time to re-evaluate rates and maintain deals every week. This is exactly where a CRM helps that already runs the pipeline in a structured way and doesn't make you guess the probabilities, but calculates them from your actual track record.

At Advanzo, "deal scoring" handles this assessment in the background and turns your pipeline into a continuously updated forecast instead of a snapshot in a spreadsheet. The data stays in Switzerland, and the experience follows the principle "remove complexity, not add it": you should reach the right number faster, not have to learn yet another tool. That turns the weekly forecast question into a calm routine rather than a calculation exercise under pressure.