What this covers
- What is usually happening
- The four things to check
- How to tell which one it is
- Why this is hard to see in most stacks
What is usually happening
Forecasts that miss in the same direction every quarter are not random. They are systematically biased, which is fixable.
Diagnosis is worth more than technique here. Applying the right fix to the wrong cause is how teams spend a quarter improving something that was not the constraint.
The four things to check
Close dates are recording intention, not evidence
This is the most common cause and the easiest to test.
Stage weights come from a benchmark rather than your own history
Worth checking before you conclude the previous one is the answer.
The forecast measures bookings while finance measures collections
Less common, but expensive when it is the cause.
Nobody tracks how wrong last quarter was, so nothing corrects
Frequently the real constraint once the obvious ones are ruled out.
How to tell which one it is
Each cause leaves a different fingerprint in the data. Look at stage conversion first — if losses concentrate in one stage, you have a process problem at that stage. If they are spread evenly, the problem is upstream in qualification or targeting.
Then look at time in stage, comparing won deals against lost. Where the two diverge is where intervention pays back.
Why this is hard to see in most stacks
Every diagnosis above needs engagement data and revenue data in the same place. When outreach lives in one tool, deals in another and invoices in a third, the questions become quarterly export exercises that nobody performs.
That is the practical argument for one database — not elegance, but that the diagnostic questions become answerable on a Tuesday afternoon.