Pipeline Value
Sum of the dollar value of all active deals currently in the sales pipeline — unweighted (raw deal-value sum, not probability-weighted). Boards read this as the top-of-funnel sufficiency check: if pipeline coverage (pipeline value / forecast) drops below the historic conversion-rate-implied threshold, the forecast is at risk. Common pitfall: confusing pipeline value with weighted forecast — the unweighted number always exceeds the weighted, often by 3–5× depending on the stage mix. Always report both and the implied conversion ratio. — Sales KPI, I'mBoard-authored (editorial tier).
I'mBoard-authored (editorial tier)
No public third-party standard anchors this KPI yet, so I'mBoard authors and maintains the definition — transparently labeled as editorial tier. See the ontology methodology for the published vs editorial tier system and the back-attribution workstream.
Rogue ID: sales.pipeline_value
Type: Currency
Domain: Sales
Definition
Sum of the dollar value of all active deals currently in the sales pipeline — unweighted (raw deal-value sum, not probability-weighted). Boards read this as the top-of-funnel sufficiency check: if pipeline coverage (pipeline value / forecast) drops below the historic conversion-rate-implied threshold, the forecast is at risk. Common pitfall: confusing pipeline value with weighted forecast — the unweighted number always exceeds the weighted, often by 3–5× depending on the stage mix. Always report both and the implied conversion ratio.
Formula
Pipeline Value = Σ (deal_value) across all open opportunities in stages between qualification and signature (excludes closed-won and closed-lost). No probability weighting — for that, see sales.weighted_forecast.Why it matters
The capacity number for the forecast — without sufficient pipeline value, the forecast is structurally unachievable regardless of close-rate execution. Coverage ratio (pipeline / quota) is the first read on whether the team can hit the period.
How to interpret
Typical SaaS pipeline-coverage benchmark is 3× quota for the current quarter and 4–5× for the next quarter (industry folk-wisdom — varies meaningfully by historical win rate; the right multiple is 1 / historical-win-rate, not a fixed number). Coverage below the historic-conversion-implied threshold is the canonical "you will miss" signal.
Calculation policy
How an AI agent should compute this KPI from messy company data. Free-text rules consumed at reasoning time — not a deterministic DSL. The most common ways to get this wrong are listed under Common miscomputations.
Inclusion rules
- Σ deal_value across all open opportunities in stages between qualification and signature — a point-in-time snapshot of the live pipeline.
- Unweighted: raw deal-value sum, NO probability weighting (for the probability-weighted number see
sales.weighted_forecast). - Apply a consistent stage-floor (typically SQL or higher) and the same value convention (TCV vs ACV) used across the other pipeline metrics.
Exclusion rules
- Closed-won and closed-lost opportunities — those have left the pipeline (see
sales.closed_won_value/sales.closed_lost_value). - Probability-weighting of any kind — that is
sales.weighted_forecast. - Non-bona-fide opportunities below the stage floor (orphaned trials, demo requests that never became a real evaluation).
Required inputs
- Open opportunities with stage and deal_value at the snapshot date.
- The stage-floor and value (TCV / ACV) conventions.
- The current / next-period quota for the coverage read.
Data-source priority
- CRM pipeline report (Salesforce / HubSpot) at the snapshot date.
- Rev-ops pipeline export as a fallback — verify stage hygiene first.
Edge cases
- Stale "open" deals that should be closed-lost inflate pipeline value; enforce a max-age auto-flag so coverage is not overstated.
- A few oversized mega-deals can dominate the sum — inspect alongside
sales.average_deal_size/ median for concentration risk. - Mid-stage re-scoping: use the current deal_value, consistently across the series.
Validation checks
- Pipeline value ≥ weighted forecast always (unweighted exceeds weighted, often 3–5× by stage mix) — if not, the weighting is wrong.
- Coverage ratio (pipeline value / quota) should be read against 1 / historical-win-rate, not a fixed 3× folk number; coverage below the historic-conversion-implied threshold is the canonical "you will miss" signal.
- Identity: pipeline_value =
sales.pipeline_deal_count×sales.average_deal_size.
Common miscomputations
- Reporting the weighted forecast as pipeline value (or vice versa) — the unweighted-vs-weighted distinction is the entire point of the two lines.
- Counting closed deals or sub-floor junk opportunities — overstates coverage.
- Switching the TCV / ACV convention between pipeline_value,
sales.closed_won_value, andsales.weighted_forecastso the dashboard math stops reconciling.
Related KPIs
sales.weighted_forecastsales.pipeline_deal_countsales.average_deal_sizesales.win_ratesales.quarterly_forecastsales.pipeline_stage_metrics
Source
I'mBoard editorial — authored and maintained by I'mBoard, first published 2026-04-01. No third-party standard is cited for this KPI; when one emerges, the definition is back-attributed and promoted to the published tier (a minor version bump). Read the ontology methodology for the published vs editorial tier system, attribution rules, and dispute process.
Stage relevance
| Company stage | Priority |
|---|---|
| Series A | Core |
| Series B | Core |
| Series C+ | Core |
| Public | Core |
Suggested for stages: Series A, Series B, Series C+, Public.
Default owning functions
- Sales
Machine-readable
- This KPI as JSON:
/api/ontology/sales/pipeline_value.json - All Sales KPIs:
/api/ontology/sales.json - Full catalog:
/api/ontology/index.json
Pipeline Stage Metrics
Container handle for the per-stage pipeline metrics grid — for each pipeline stage (qualification, discovery, evaluation, proposal, negotiation, closing) tracks dealCount, totalValue, closingProbability, winRateFromStage, and avgTimeToClose. The most diagnostic surface in the pipeline view: where deals are bunching, which stage is the bottleneck, where conversion math is breaking. Rendered via the StageMetricsGrid widget seeded from PipelineStageValues. Common pitfall: trusting unchanged stage probabilities even as the deal mix shifts — re-calibrate the per-stage close rates quarterly against actuals or the weighted forecast drifts unreliably. — Sales KPI, I'mBoard-authored (editorial tier).
Quarterly Forecast
The team's expected closed-won dollars for the current quarter — usually a sales-leader judgment call informed by weighted forecast but adjusted for deal-by-deal commit confidence. Distinct from weighted_forecast (which is mechanical, stage × probability). Boards read both: a quarterly_forecast materially below weighted_forecast means the team has explicit negative judgment on specific big deals; above it means they're calling deals stronger than the stage probabilities suggest. Common pitfall: anchoring the call to plan rather than reality — boards quickly learn to discount "we will hit plan" forecasts and reward calibrated commit-vs-actual track records. — Sales KPI, I'mBoard-authored (editorial tier).