Deal probability is often optimism disguised as data

If I had to permanently remove one field from a CRM, Deal Probability would be high on my list.

Not because forecasting is unimportant. Quite the opposite. I have spent enough time trying to build reliable forecasts to care a lot about knowing which deals are actually likely to close.

The problem is that manually entered probability often tells us something different. It tells us how confident the salesperson feels.

I have seen opportunities sitting at 80, 90 or even close to 100 percent because the rep genuinely believed the customer was going to sign before the end of the month. Then the deal slipped. Procurement had not been involved. The budget was not actually approved. The person driving the evaluation did not have authority to sign. Sometimes the customer simply stopped responding.

None of this means the salesperson was being dishonest. They were making a judgment based on the information they had, their experience and probably some natural optimism about a deal they had spent weeks working on.

The problem appears when we take that judgment, put a percentage sign behind it and start treating it like data.

Two experienced salespeople can look at almost identical opportunities and assign very different probabilities. One might call a deal 70 percent because the buyer likes the product and has verbally agreed to move forward. Another might call the same situation 40 percent because procurement has not started and the economic buyer has not been involved.

Both can have perfectly reasonable logic behind their estimate. But if every rep uses a different internal definition of 70 percent, the number stops meaning very much when we aggregate it across the pipeline.

We average those opinions, multiply them by deal values and suddenly we have something that looks mathematically precise.

That does not necessarily make it a forecast.

The percentage hides the interesting information

What bothers me most about Deal Probability is not simply that the number can be wrong. Every forecast is uncertain by definition.

The bigger problem is that the percentage compresses a lot of useful information into one number.

Suppose two €100,000 opportunities are both marked as 70 percent likely to close.

In the first deal, the team has spoken with the economic buyer, agreed on the business case, completed security review and has a procurement meeting booked for next week. The main remaining uncertainty is contract negotiation.

In the second, the champion is enthusiastic and says they want to move forward, but nobody has spoken to finance, budget approval is unclear and the last meeting was two weeks ago.

The CRM can tell us both are 70 percent.

Operationally, they are completely different deals.

I would rather see the evidence behind the confidence. Who have we actually engaged? Is there a clear problem the customer is trying to solve? Is there a compelling reason to act now? Has the economic buyer been involved? What remains unresolved? Is there a concrete next step? Has buyer engagement increased or decreased over the last few weeks?

Those things still do not give us certainty, but they help explain why a deal might close or why it might not.

That is much more useful than knowing that someone chose 70 instead of 60.

Forecasting needs judgment, but judgment should have something underneath it

I do not think the answer is to remove human judgment from forecasting.

A good salesperson often knows things that are difficult to represent in structured CRM fields. They hear hesitation in a conversation. They know whether a champion is genuinely influential or simply enthusiastic. They understand the politics of the account. Experienced managers can often look at a deal and spot something that a scoring model misses.

The problem is not judgment. The problem is judgment without enough visible evidence behind it.

This is one reason qualification frameworks can be useful when implemented well. MEDDPICC, for example, tries to break confidence into things we can actually examine: metrics, economic buyer, decision criteria, decision process, pain, champion and competition.

The framework itself does not magically make a forecast accurate. It can easily become another collection of CRM fields that reps fill because someone made them mandatory. But at least it asks a more useful question than “How confident are you from zero to one hundred?”

It asks what we actually know about the deal.

The same principle applies even if you do not use a formal methodology. A forecast becomes more useful when confidence can be traced back to observable evidence.

If a salesperson says a deal is likely to close this month, I am much more interested in why.

What happened recently that supports that view? What still needs to happen? Who is involved? What could prevent the deal from progressing? Is there evidence from the customer, or are we mostly interpreting our own sales activity?

The percentage is the conclusion. The evidence is what lets us evaluate whether that conclusion makes sense.

Momentum is often more useful than static confidence

There is another piece of information I would like to understand better than Deal Probability: direction.

Is the deal becoming healthier or weaker?

A static probability does a poor job of showing this. A deal can sit at 80 percent for weeks even while the underlying situation deteriorates. The next meeting gets pushed back. An important stakeholder stops joining calls. A procurement process that was supposed to start never starts. The expected close date moves once, then again.

The probability field remains 80 because nobody has changed it.

This is why momentum interests me more.

A deal may still have plenty of uncertainty, but if customer engagement is increasing, more stakeholders are getting involved and agreed next steps are happening on time, there is evidence that it is progressing.

The opposite is equally valuable. If communication slows down, meetings disappear and important actions remain unresolved, something has changed even if the opportunity stage and probability have not.

This is one of the limitations of traditional CRM data. We store snapshots of the seller’s view of the deal, while the actual deal is constantly changing.

Increasingly, we have more information available to understand that change. Meeting history, email activity, call transcripts and CRM updates all contain signals about whether an opportunity is moving forward or losing momentum.

The interesting question is how to turn those signals into something useful without creating another arbitrary score that everyone eventually learns to ignore.

I would rather forecast from evidence than optimism

I am not suggesting that every company should literally delete the Deal Probability field tomorrow. In many CRMs it is connected to stages, weighted pipeline calculations and existing reporting. Removing it may create more problems than it solves.

But I would question how much confidence we place in it.

If a probability is automatically tied to a stage, it is primarily telling us something about historical conversion from that stage. That can be useful at an aggregated level, but it says relatively little about one specific opportunity.

If the salesperson enters it manually, it may contain valuable intuition, but we should recognise that it is subjective.

Either way, the number should probably be the beginning of a conversation rather than the answer.

For individual deals, I would rather understand the evidence: stakeholder engagement, unresolved blockers, next steps, qualification gaps and how momentum has changed over time.

For the overall business, I would rather build forecasting around patterns that can be tested against what actually happened.

That does not remove uncertainty from sales. Nothing will.

But it does make the uncertainty more visible.

And that seems more useful than taking a collection of opinions, adding percentage signs and calling the result precision.