A deal slippage report answers one question with evidence: how much of the value dated for this period left it, and where did it go. It compares a starting snapshot against the closing outcome, then breaks the gap into deals that closed, deals that pushed, and deals that were lost.
Snapshots are the requirement
A live CRM query shows current state, so it cannot tell you what the quarter looked like on day one. Capture a pipeline snapshot at the start of every period and weekly through it, storing deal ID, amount, stage, close date, owner, and forecast category. Pair that with close-date field history so each push is timestamped.
Define meaningful activity before building anything. ORM counts a change in stage, close date, or amount. If the report treats logged emails as progress, dead deals will look active.
The cuts that change decisions
Four views carry most of the value.
- Value moved by destination period. Deals pushed one quarter behave differently from deals pushed two or more. - Push count per deal. ORM's data identifies close-date changes as the strongest slippage signal, and deals that slip across a quarter boundary are less likely to close even while sitting in commit. - Slippage by segment and deal size. Concentration matters more than the rate, since one large pushed deal can outweigh twenty small ones. - Slipped value that eventually closed, at what amount, and how much later.
That last cut is the one most teams skip, and it is the one that tells you whether slipped deals are delayed revenue or losses that have not been recorded.
Reading the report without breaking it
Baseline expectations before assigning blame. ORM's data shows roughly 20% of the pipeline dated inside a quarter on day one closes in that quarter, so a large amount of movement is normal rather than exceptional. Compare each rep against that reality instead of against a target someone invented.
The report should feed two actions. First, downgrade or requalify the deals it flags. Second, correct the forecast and the pipeline coverage view for the remaining periods, since slipped value arriving in the next quarter is not the same as new pipeline. Teams that run this consistently improve forecast accuracy because they stop counting the same failed deal twice. For the process it plugs into, see how to forecast revenue.
Frequently Asked Questions
What data does a slippage report need?
Pipeline snapshots taken on a fixed cadence plus close-date field history. Live CRM queries cannot reconstruct what a period looked like on day one, so the snapshot is the requirement.
How often should the report run?
Weekly during the quarter and once at period close. The weekly view catches pushes while there is still time to build replacement pipeline.
What is the most useful cut of the data?
Push count per deal. A deal on its second or third push behaves very differently from a deal pushing for the first time, and averages hide that.
Should the report be used in rep reviews?
Use it to change forecasting behavior, not to punish honesty. If moving a date is treated as a personal failure, reps stop moving dates and the report loses its signal.
Put these metrics to work
ORM builds custom revenue forecast models that turn concepts like deal slippage report into prescriptive action for your team.
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