KPI · Sales

Deal slippage rate: formula and example.

Deal slippage rate is the percentage of deals that do not close in the planned period but move to a later one. You compare each deal's original expected close date with the date it actually closed or is now expected to close. High slippage makes your forecast unreliable, even if the deals are eventually won.

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Deal slippage rate formula

Number of deals pushed to a later period ÷ number of deals with an original close date in the period × 100%

Worked example

Acme Groothandel had 50 deals worth €900,000 planned to close in the third quarter. Of these, 18 deals worth €342,000 slipped to the fourth quarter or later. Slippage is 18 ÷ 50 × 100% = 36% by count and €342,000 ÷ €900,000 × 100% = 38% by value.

Fictitious figures for Acme Groothandel, a sample wholesaler.

How to read this KPI

The higher the slippage, the less you can rely on the planned close dates in your pipeline. Compare slippage by rep and by stage: consistently high slippage for one rep often points to overly optimistic planning. Track the percentage each quarter and use it to adjust your forecast.

Pitfalls with deal slippage rate

Not storing the original close date, so you can no longer trace the changes.
Counting lost deals as slippage, while they have an outcome of their own.
Counting deals only, while a few large slipped deals determine the quarter's result.

SQL & DAX

Calculating deal slippage rate in SQL and DAX

Two examples on a fictitious data warehouse for Acme Groothandel: a PostgreSQL query and a measure for a Power BI model. Adjust table and column names to your own model.

SQL · PostgreSQL

WITH d AS (
  SELECT date_trunc('quarter', original_close_date) AS quarter, amount,
         COALESCE(closed_at::date, expected_close_date)
           >= date_trunc('quarter', original_close_date) + interval '3 months' AS slipped
  FROM deals
  WHERE status <> 'lost'
    AND original_close_date < date_trunc('quarter', current_date))
SELECT quarter,
       COUNT(*) AS planned_deals,
       COUNT(*) FILTER (WHERE slipped) AS slipped_deals,
       ROUND(100.0 * COUNT(*) FILTER (WHERE slipped) / NULLIF(COUNT(*), 0), 1) AS slippage_pct,
       ROUND(100.0 * SUM(amount) FILTER (WHERE slipped) / NULLIF(SUM(amount), 0), 1) AS slippage_value_pct
FROM d
GROUP BY quarter
ORDER BY quarter;

DAX · Power BI

Slipped Deals =
COUNTROWS(
    FILTER(
        Deals,
        Deals[Status] <> "lost"
            && YEAR(COALESCE(Deals[ClosedAt], Deals[ExpectedCloseDate])) * 4
                + QUARTER(COALESCE(Deals[ClosedAt], Deals[ExpectedCloseDate]))
            > YEAR(Deals[OriginalCloseDate]) * 4 + QUARTER(Deals[OriginalCloseDate])
    )
)

Deal Slippage % =
DIVIDE([Slipped Deals], CALCULATE(COUNTROWS(Deals), Deals[Status] <> "lost"))

In ENABLE

Tracking this KPI in ENABLE

Plain-language questions

Ask for deal slippage rate per month, customer or product in the SQL Explorer with AI. The AI writes the SQL, you see the query and run it yourself; the AI only receives metadata.

In your Power BI dashboard

Define the KPI as a measure in your Power BI model and show it in the portal, with "Last refreshed" next to it. Access profiles and optional row-level security decide who sees which figures.

Custom dashboards (pilot)

Add the KPI as a tile to a custom dashboard, compared with last year. The Dashboard Builder is a pilot and can be switched on per client.

Monthly targets

With the built-in Targets app you set a target for the KPI per month, so you see actuals and target side by side.

FAQ

Frequently asked questions

What is deal slippage?

Deal slippage is when deals move to a later period than originally planned. As a percentage, it shows what share of planned deals did not close on time. It is a measure of how reliable your sales forecast is.

How do you calculate pipeline slippage?

Take all deals with an original close date in a period and count how many closed later or are still open with a later date. Divide that number by the total and multiply by 100%. To do this, store the first expected close date in your CRM alongside the current one.

How can you reduce deal slippage?

You reduce deal slippage by basing close dates on concrete agreements with the customer, such as a decision date, rather than on gut feeling. Review deals whose date has already moved in every pipeline meeting. If a deal keeps slipping, move it back to an earlier stage.

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