The Pipeline Slip Report Playbook
Works with
Implementation kit
- The seven slip rules, the research behind each, and your thresholds
- The HubSpot and Salesforce fields each rule reads
- The weekly report template, with a question for every flag
- The quarterly calibration check, by category and by rule
- Six sample deals run from input to report
Commit deals that slip in the last two weeks? Check every deal against seven evidence rules each week, and find the slips while there is still time to act.
The full method is below. Lines set from the deals you won, the evidence your CRM already keeps, a weekly report with one question per flagged deal, and a quarterly check of the forecast's record.
The number looks safe until the last two weeks.
The failure this playbook fixes
How it works
01Set your lines from the deals you won
Pull won deals from the last four quarters and work out the average days each one spent in each stage. A deal past 1.5 times that average gets flagged.
Write down the titles that sign at your buyers, so every manager flags the same deals.
02Find the evidence your CRM already keeps
Stage dates, last and next activity, close date history, contact roles and logged meetings. HubSpot and Salesforce both keep most of it, and the kit names the field for each rule.
Check that you can see each deal's past close dates. Without that history you cannot count pushes.
Watch for a field that exists and is mostly empty. A rule that reads a blank field flags nothing and looks clean.
03Run seven rules on every Commit and Best Case deal
Each week, check every deal closing this quarter. Flag a deal when it is
- stuck in stage, past 1.5 times your won deals' average
- gone quiet, more than 7 days with nothing booked next
- already pushed, its close date moved out once this quarter
- missing the signer, nobody who can sign has been in the deal
- on one contact, a single person engaged on the buyer's side
- without a critical event, no date or outside force behind the close date
- without a path to signature, the steps after a yes unknown
The first five rest on published research. In one study of 4.2 million opportunities, deals whose qualification stage ran 50% longer than average were 120% more likely to slip, and slipped deals won 67% less often. It is vendor research and shows which deals slip more often, not why. Your own quarters replace it. The kit carries every source.
04Ask one question per flagged deal, a day before the call
Send the report to the deal owners the day before the forecast call, flagged deals first. Ask one question per deal about what happened on the buyer's side, from the flag the owner can answer soonest.
A flag is a question, never a verdict. The owner's answer, with evidence, decides.
05Move the deals the evidence does not hold up
One flag, the deal stays and the owner answers. Two or more flags, it moves from Commit to Best Case unless evidence clears a flag.
A deal already pushed with no signer in it is Best Case until the signer joins a conversation.
06Freeze a snapshot in week one
Export every deal closing this quarter with its category and flags, then leave it untouched. A snapshot edited later will agree with the outcome whether or not the forecast was any good.
07Score the quarter against the snapshot
Compare what each category promised with what closed, and what flagged deals did against unflagged ones. A rule earns its place when the deals it flags close less often.
After two quarters, your own record replaces the research. That record is what makes a forecast the board can trust.
A forecast earns trust from its record, checked every quarter.
The implementation kit above packages the slip rules, the CRM fields for each, the weekly report, the calibration check and six sample deals run from input to report.
