Build a Sales Pipeline-to-Revenue Forecast

Build a probability-weighted revenue forecast from pipeline data — stages, probabilities, and expected close dates — using a Pipeline custom dimension in Adaptive Planning.
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Pipeline-to-revenue forecasting bridges the gap between the CRM and the financial model. Instead of treating bookings as a single top-down number, this approach builds the forecast bottom-up from deal stages and probabilities. This tutorial walks through assembling a probability-weighted revenue forecast in Workday OfficeConnect, assuming your pipeline data is already loaded into Adaptive Planning through a custom dimension.

What you’ll build: A report that lists pipeline by stage, applies a stage-weighted probability, and projects expected revenue by month for the next two quarters.

What you’ll need:

  • OfficeConnect installed and signed in (Build Your First Report)
  • A Pipeline Stage custom dimension in Adaptive Planning (Prospect, Qualified, Proposal, Negotiation, Closed Won)
  • A Pipeline Amount account loaded with deal values dimensionalized by stage and expected close month
  • Familiarity with custom dimensions (Custom Dimensions and Attributes)

Step 1 — Set up the stage rows

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Add the time headers On a blank sheet, click B1 and drag the first forecast month (for example, Current Month +1). Repeat across C1:G1 for the next five months. This gives you a six-month forward view.
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Add stage rows from the custom dimension In column A, list the pipeline stages: Prospect, Qualified, Proposal, Negotiation, Closed Won. In B2 drag the Pipeline Amount account and filter it on the Pipeline Stage = Prospect dimension value using the Reporting pane. Repeat for B3:B6, filtering on each stage.
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Copy across the months Select B2:B6 and copy into C2:G6. Each cell now resolves to the pipeline amount for that stage and that month.

Step 2 — Apply stage probabilities

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Add a probability column In column H, type the stage probability next to each row: 10% for Prospect, 25% for Qualified, 50% for Proposal, 75% for Negotiation, 100% for Closed Won. These are static values you can tune to match your historical win rates.
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Compute weighted pipeline per stage per month In a second block below the raw pipeline table (rows 10-14), repeat the stage labels in column A, then in B10 write =B2*$H2 and copy across and down. This block shows the probability-weighted contribution from each stage by month.

Step 3 — Build the forecast row

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Total the weighted contributions In row 16, label A16 Expected Revenue. In B16 write =SUM(B10:B14) and copy across to G16. This is the bottom-up pipeline-weighted forecast for each month.
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Compare to plan Below the forecast row, add a row labeled Plan and drag the Budget version of your Revenue account into each month. Add a third row labeled Gap with =B16-B17 to show where pipeline coverage is short.
For admins & power users Many teams define a coverage ratio — total unweighted pipeline divided by the revenue target. A coverage ratio of 3x is healthy in most B2B SaaS contexts; below 2x is a leading indicator of a miss.

Step 4 — Refresh and review

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Refresh and validate Click Refresh. The raw pipeline rows populate from the custom dimension. Weighted rows and totals recalculate automatically. Spot-check the Closed Won row — it should match closed-won bookings already in your CRM for those months.
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Add stage drilldown For any cell that looks off, use Cell Explorer Drill-Down to see exactly which deals contribute to the value.

Result

You now have a probability-weighted revenue forecast driven directly by your pipeline data. Each refresh pulls the latest deal stages and amounts from Adaptive Planning, applies your tuned conversion rates, and shows month-by-month expected revenue against plan. Sales leadership sees pipeline coverage; FP&A sees a forecast they can defend with deal-level math.

Next steps

Last modified May 19, 2026: Rename 'Get Started' section to 'Wiki' site-wide (6ebea16d)