Pipeline Flow
Definition
Container handle for the additive / subtractive pipeline-flow bridge — reconciles opening pipeline to closing pipeline through the period's adds, wins, and losses (opening + new_opps − closed_won − closed_lost = closing) with dual count + value columns. Renders via the FlowSubform widget. The audit trail of the pipeline motion — without this, period-over-period pipeline changes are unexplained. Common pitfall: a "scrub" line (deals reclassified from open to lost mid-period) is needed to keep the math reconciling when CRM hygiene happens; without it the flow appears not to balance and trust in the underlying numbers erodes.
Why it matters
Makes the period's pipeline changes auditable line-by-line — boards can immediately see whether closing pipeline shrank because deals closed (good) or because deals were lost / scrubbed (bad). Without the flow, only the net change is visible and the underlying motion is opaque.
How it's calculated
Container — start/end slots with dual (count + value) columns. Identity that must hold: opening_pipeline_value + new_opps_added_value − closed_won_value − closed_lost_value − scrubs = closing pipeline_value. Same identity holds on the count side using deal counts. Any gap surfaces a data-quality issue worth root-causing before next period. How to interpret it
A healthy flow shows new_opps_added ≈ (closed_won + closed_lost) at steady state (top-of-funnel replacing what closes). When new_opps_added consistently lags closes, the closing pipeline shrinks period-over-period — future quarters will run into coverage stress. Disproportionate scrubs (large negative reclassifications) signal a CRM hygiene problem that's been suppressed.
Source
imboard Editorial
Stage relevance
Typically owned by
Related KPIs
Total pipeline value at the start of the period — the baseline against which the period's pipeline flow (+ new opportunities − won − lost = closing) reconciles. Equal to the prior period's closing pipeline by construction. Surfaces in sales.pipeline_flow as the `start` slot. Common pitfall: restating opening pipeline to retroactively "clean up" stale deals masks the hygiene problem rather than addressing it; cleanup should happen via explicit "old-deal scrub" lines in the flow, not by editing the opening baseline.
Total dollar value of new opportunities entering the pipeline during the period — the top-of-funnel inflow line in the pipeline flow. The single best read on the marketing-and-SDR engine's output. Common pitfall: counting inflated, un-qualified opportunities (e.g. every demo request) overstates the engine's output; restrict to opportunities that pass a defined qualification stage (typically SQL or higher) before counting. Boards expect this number to track forward quota — a quarter's top-of-funnel should be ~1× the same quarter's quota for a normal sales-cycle business.
Total dollar value of all opportunities closed-won during the period — the period's realized bookings from the pipeline motion. Reconciles to (sales.new_business + sales.expansion) when split by deal type. Common pitfall: reporting TCV (total contract value) here when the rest of the dashboard uses ACV — pick one and apply it consistently across closed_won_value, weighted_forecast, and pipeline_value, or the dashboard math stops reconciling.
Total dollar value of opportunities closed-lost during the period — the opportunity-cost view on the pipeline motion. Useful for sizing the "what we missed" gap and prioritizing post-mortem efforts on the highest-value losses. Common pitfall: post-mortems on small lost deals waste time relative to insight; tier the post-mortem cadence by value (e.g. every loss above the 80th-percentile deal size gets a written debrief). Boards expect the largest 2–3 losses to be explained explicitly in commentary.
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.
Total number of active opportunities in the pipeline (open stages only — excludes closed-won and closed-lost). The volume side of pipeline coverage; paired with pipeline_value gives the average deal size and the deal-count vs deal-size ratio that characterizes the motion shape. Common pitfall: counting non-bona-fide opportunities (orphaned trials, demo requests that never converted to a real evaluation) inflates the number — apply a stage-floor cutoff (e.g. SQL or higher) so the count reflects committed evaluation activity.
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