What it means
A sales team expects a customer to sign by the end of September, but the buyer postpones legal review until October, so the opportunity moves out of September's forecast. That is slippage even if the customer eventually signs.
To measure it, set a baseline by preserving the deal's expected close date and forecast category at a named snapshot, such as the start of a month, and keep history, since a CRM that overwrites close dates needs a snapshot or change log to measure movement accurately. Choose the unit and the period: you can count slipped opportunities or sum their forecast value, and one large deal may dominate a value-based rate.
A move from September 28 to October 3 matters to a September forecast even though the delay is short. Separate outcomes too, because a deal that is lost, a deal still open past period-end and a deal intentionally rescheduled can have different causes, which should be segmented since pricing disputes, legal review, an absent sponsor and internal sales delays call for different action.
Review buyer evidence by confirming whether decision-makers have agreed scope, price, procurement and timing, because a seller's desired date is not the buyer's process. Contract review, security checks and funding decisions can push a close after product selection, and a revised close date is more credible when linked to an actual meeting, signature step or funding decision.
Watch date hygiene as well, since some CRM systems insert default close dates when an opportunity is created, and a date chosen by software is not a confirmed customer commitment. Avoid endless pushes, because a deal moved forward every month may need a new probability, a different category or removal from the near-term forecast.
Consider seasonality, as customers may pause decisions around holidays or budget cycles, but use evidence specific to the customer rather than a universal assumption. Assess concentration too, since several slips among top deals can change the company's hiring or cash outlook far more than many small delays.
Distinguish sales from revenue, because a contract signed late can also shift service delivery or accounting recognition, which should be checked separately. A later signature often means later invoicing and payment, but contract terms determine the actual cash path, and finance and operations need the revised timing if they planned capacity on expected sales.
Check new deals entering as well: a period may receive opportunities that offset slips, but net pipeline movement should not erase the slipped-deal analysis. Use quality metrics such as forecast accuracy, stage aging and win rate to explain whether a slip signals temporary timing or deeper risk, and review pace weekly to catch a missed buyer milestone early.
Coach rather than blame, since punishing every slip can encourage sellers to hide changes until the period ends, and avoid false certainty because a slipped opportunity can still win and should not automatically be marked lost or guaranteed for the next period. Salesforce pipeline inspection explicitly tracks opportunities moved out of a period, and HubSpot documentation notes that close-date fields can be set or updated automatically, so verify whether a changed date reflects a real buyer event; for an owner, the metric is useful only when the baseline and causes are visible.
In practice
Real-world examples.
Example
A proposed contract moves from September to October after the buyer changes its approval schedule. The seller records the original and revised dates, along with the reason. The deal stays open, but it leaves the September forecast.
Example
A late-stage deal's CRM date moves repeatedly, prompting a manager to remove it from commit. The manager asks for the next buyer milestone, and none can be named. The deal moves to a lower forecast category until evidence returns.
Example
Several slips leave the quarter's total target unchanged only because new deals entered the pipeline. The manager reports slipped value separately from new pipeline. The net figure alone would have hidden the timing problem.
Formula
Calculation
Illustrative slippage rate by value = baseline forecast value of deals moved beyond the period / baseline value forecast to close in that period x 100. If 1.2 million of 4 million moves out, the rate is 30%. Preserve the baseline and define how lost and newly created deals are treated.Case study
Seen in the real world.
Fictional case: Oak Systems forecast 4 million for a quarter. Deals worth 1.2 million moved beyond quarter-end when buyers postponed approvals. Its sales lead recorded each cause, revised the cash outlook and trained reps to distinguish customer-confirmed dates from target dates. The 30% illustrative slip rate did not imply the deals were permanently lost.
Watch out
Common mistakes.
- Overwriting close dates without preserving the earlier forecast snapshot.
- Treating an automatically inserted CRM date as evidence of a buyer commitment.
- Counting a slipped deal as lost or guaranteed next quarter without checking its status.
Questions
People also ask.
Is a slipped deal lost?
No. It missed an expected closing period; it may still close later or be lost.
Why track deal slippage?
It shows timing risk in sales, cash and capacity forecasts.
What should be recorded?
The original and revised dates, amount, status, cause and next buyer milestone.
From the founder's library
Take it further with the book.
Build your financial confidence beyond this definition. Shihan's full-length guide, Accounting Fundamentals, takes the same plain-English approach and turns it into a complete, practical playbook for non-finance managers, business owners and students - with chapter-end quiz answers and presentation slides included.
25% off with code MMHQ25, applied at checkout. Priced in USD - checkout may show the equivalent in your local currency.
View the book and save 25%