Pipeline & Forecasting
Measuring pipeline, predicting what will close, and locating where deals actually stall — and the hygiene dependency that makes every one of these numbers unfalsifiable when ignored.
The dependency nobody states first
Every pipeline metric is computed from the record. Pipeline hygiene — whether close dates are current, stages accurate, ownership correct — is therefore a precondition rather than a separate concern. When hygiene is poor, health metrics are not merely inaccurate but unfalsifiable, because a genuine decline cannot be distinguished from a maintenance lapse.
Four hygiene measures require no interpretation and no targets: the proportion of open opportunities with a close date in the past, those with no activity within a typical cycle, those whose stage has not changed in more than one typical stage duration, and those missing an owner or amount. Establish these before reading anything downstream.
Is there enough pipeline?
Pipeline coverage divides open pipeline expected to close in a period by the target for that period. The commonly cited 3x is not a law: the correct multiple is the inverse of your own conversion rate from the relevant stage. If a fifth of qualified pipeline closes, 3x coverage guarantees a miss.
Weighted pipeline applies stage probabilities to produce an expected value. Those probabilities are only meaningful when derived from your own historical stage-to-stage conversion — inherited defaults produce a number with the appearance of rigour and none of the substance. Weighted pipeline is also not a forecast: it describes what a large number of similar deals would produce on average, not what this quarter will close.
Is it moving?
Pipeline velocity composes four variables — opportunity count, average deal size, win rate and cycle length — into revenue per unit of time. The composite matters less than which input moved: velocity improving because cycle length shortened is a healthy process change, while velocity improving because deal size rose as win rate fell may be a segment shift worth understanding rather than celebrating.
Time in stage localises where deals stall, which total cycle length cannot. A stage where opportunities accumulate usually has unclear exit criteria or an unowned next action. A stage everything passes through instantly is being skipped, which means it models nothing real.
Cohort, do not snapshot
Will the forecast hold?
Forecast accuracy should be measured on the process rather than the outcome. A forecast that lands because a large unexpected deal offset several unexpected losses is compensated, not accurate. Track the variance of individual deal calls, and fix direction before magnitude — a forecast reliably ten percent high is more useful than one that is randomly correct.
16 terms
Activity Metrics
Counts of seller actions — calls, emails, meetings booked — used as leading indicators of pipeline.
Close Date
The date an opportunity is expected to be signed. The single most consequential field in a pipeline record.
Deal Pipeline
The ordered set of stages a deal moves through from creation to closed. A model of the buying process, which is why stages defined by seller activity rather than buyer evidence stop predicting anything.
Forecast Accuracy
How closely forecasts match actual results, measured consistently over time. The metric that separates disciplined forecasting from lucky forecasting.
Opportunity
A record representing a specific potential purchase, with a value, a close date and a stage.
Pipeline Coverage
The ratio of open pipeline value to the target for a period. Answers whether there is enough in play to hit the number at historical conversion rates.
Pipeline Generation
The creation of new qualified opportunities, as an activity measured and owned separately from closing.
Pipeline Hygiene
Whether pipeline records are accurate and current — as distinct from pipeline health, which is whether the pipeline is any good.
Pipeline Velocity
A composite of the four variables determining how fast pipeline converts to revenue: number of opportunities, average deal size, win rate, and sales cycle length.
Sales Cycle Length
The elapsed time from an opportunity's creation to its close. The time dimension underneath capacity planning and forecasting.
Sales Forecast Category
A judgement label applied to an opportunity — commit, best case, pipeline — expressing confidence independently of stage.
SQL-to-Close Rate
The proportion of sales-qualified leads that eventually become closed-won revenue.
Stage-to-Stage Conversion
The proportion of opportunities moving from each stage to the next. The most localised view of where pipeline dies.
Time in Stage
How long opportunities remain in each pipeline stage. The diagnostic that localises where deals actually stall.
Weighted Pipeline
Pipeline value multiplied by a probability assigned to each stage, producing an expected value rather than a gross total.
Win Rate
The proportion of opportunities that close won, measured against a defined denominator — which is where most of the disagreement lives.
COMMON QUESTIONS
- How much pipeline coverage do I need?
- Derive it rather than borrowing it. The required multiple is roughly the inverse of your own conversion rate from the stage you are measuring: if a third of qualified pipeline closes, you need about 3x. Using a published rule of thumb against a different conversion rate produces a plan that cannot work.
- What is the difference between pipeline hygiene and pipeline health?
- Hygiene is a property of the record — whether the data is maintained. Health is a property of the business — whether pipeline is sufficient and converting. Health metrics are computed from the record, so poor hygiene makes them unreadable rather than merely imprecise.
- Why is my win rate different depending on who reports it?
- Almost always the denominator. Win rate against all created opportunities, against qualified opportunities, and against those reaching a late stage are three different metrics. None is wrong; reporting one without stating which is.
- How do I stop deals slipping to the next quarter?
- Close dates are usually set from the seller's optimism rather than from the buyer's decision process. Map the buyer's steps — including procurement, security review and legal — and derive the date from those. A deal without an identified critical event has no natural close date.
Course: RevOps 101: Revenue Operations Foundations
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