Every opportunity type has a close curve
Deals do not decay at a uniform rate. Opportunities cluster into groups with similar behavior, and each group has its own expected time to close. ORM builds those groups with a machine learning model and predicts a curve for each one. The curves span 1 to 80 weeks, most of the expected closing lands before week 12, and very few groups carry real expectation past 52 weeks.
The practical consequence is that "old" is relative. A deal at week 20 in a group whose curve peaks at week 6 is far past its expected close. A deal at week 20 in a long cycle enterprise group is on schedule. Comparing every deal against one company average produces the wrong answer in both directions.
Age plus activity beats age alone
Age by itself is a weak signal when a deal is genuinely progressing. What separates a slow deal from a dead one is movement. ORM counts a change in stage, close date, or amount as meaningful activity, and applies a 12 month rule for most customers.
Across ORM's customer base, 10% or more of pipeline has gone untouched for 12 months. That value still shows up in coverage ratios and in board reports as though it converts like the rest of the pipeline.
What to do with the curve
Build the bucket table once, then use it three ways.
Set an expiration rule per opportunity group rather than one global rule, based on where each group's curve flattens.
Reweight the forecast so aged pipeline carries the win rate its own age bucket earned historically rather than the stage default. That change improves forecast accuracy without touching a rep's judgment.
Watch the age mix as a leading indicator. A pipeline whose average age is climbing while total value holds flat is losing quality, and the aging deals are the ones most likely to show up later as deal slippage.
See win rate for the base metric and the other segmentations worth running alongside age.
Frequently Asked Questions
Does win rate really drop as a deal gets older?
For most opportunity types it does, and the decline is steep rather than gradual. ORM models each opportunity into a group with a machine learning model and predicts a close curve for that group. Those curves run from 1 to 80 weeks, with most of the expected closing concentrated before week 12 and very few groups carrying meaningful expectation past 52 weeks. Once a deal is past its group's curve, the historical odds of it closing are low.
How do you decide when an aged deal should be closed out?
Set the rule on evidence of movement, not on age alone. ORM applies a 12 month rule for most customers and counts a change in stage, close date, or amount as meaningful activity. A deal older than the window with none of those changes is not a live opportunity, it is a record. Closing it out costs nothing and stops it from inflating coverage.
How much of a typical pipeline is aged out?
ORM sees 10% or more of pipeline sitting stale with no activity in the last 12 months across its customer base. That share matters because it is counted in coverage ratios and in weighted pipeline totals as if it converts at the same rate as fresh pipeline, which it does not.
What deal age buckets should you use?
Use buckets that match your own close curve rather than round numbers. If most of your closing happens inside 12 weeks, buckets of 0 to 4, 5 to 8, 9 to 12, 13 to 26, and 27 or more weeks will show the decline clearly. Buckets set in months on a business with an eight week cycle hide the drop inside the first bar.
Put these metrics to work
ORM builds custom revenue forecast models that turn concepts like win rate by deal age into prescriptive action for your team.
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