Two clocks, two meanings
Won cycle time describes a buying process running to completion. It is the number to use for capacity planning, in-quarter eligibility, and velocity math.
Loss cycle time describes something else entirely: the interval between a deal going quiet and the CRM admitting it. That interval is pure cost. The rep kept the deal in forecast conversations, the record kept inflating coverage, and no revenue came out the other end.
Why losses run long
Buyers rarely send a rejection. ORM's read on deal risk is that the earliest signal is the absence of a signal, meaning no activity, no data changing, and no notes. A deal in that state stays open by default because nobody has to do anything to keep it there.
The result shows up in pipeline aging. ORM sees more than 10% of pipeline sitting stale with no activity in twelve months across customer bases, which is why ORM applies a twelve-month rule for most customers. Those records carry a closed-lost date eventually, and every one of them lands in loss cycle time as if the deal was live the whole way through.
What the gap tells you
| Pattern | Read |
|---|---|
| Losses close much slower than wins | Disqualification is not happening |
| Losses close faster than wins | Qualification is catching bad fits early |
| Loss time rising, win time flat | Reps are holding dead deals through forecast cycles |
| Both rising together | Buyers are slower, and the market changed |
Measure it honestly
Stop treating the closed-lost timestamp as the death date. Record the last meaningful change on the opportunity and measure two spans: creation to last activity, and last activity to formal close. The second span is dead time, and on abandoned deals it can run longer than the selling span that preceded it.
Publishing that split changes behavior faster than a lecture on pipeline hygiene, because it makes the cost of holding a dead deal visible per rep. It also cleans up the inputs that everything else depends on. ORM finds that only about 20% of the pipeline carrying in-quarter close dates on day one of a quarter actually closes in that quarter, so coverage built on unpurged records is overstated before the quarter begins.
Pair loss cycle time with win rate to see whether slow losses are dragging conversion, and with deal slippage to catch the close-date pushes that keep dying deals alive one quarter at a time.
Frequently Asked Questions
Do lost deals take longer to close than won deals?
In most pipelines yes, because a loss rarely arrives as a decision. The buyer goes quiet and the record sits open until a rep or an aging rule finally closes it, so the timestamp reflects administrative cleanup rather than the moment the deal died.
Why does loss cycle time matter?
It measures how long selling capacity stays committed to deals that never convert. A team whose losses take twice as long as its wins is spending most of its hours on outcomes that produce nothing.
How do you measure the real death date of a deal?
Use last meaningful activity rather than the closed-lost stamp. ORM counts a change in stage, close date, or amount as meaningful activity, and the gap between that date and the formal close date is dead time.
What is the fastest way to shorten loss cycle time?
Enforce disqualification. A stage-exit rule that closes deals with no meaningful activity inside a defined window removes the dead weight, which tightens coverage math and makes cycle-length reporting accurate at the same time.
Put these metrics to work
ORM builds custom revenue forecast models that turn concepts like time to close won vs lost deals into prescriptive action for your team.
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