Pipeline hygiene

Five weekly checks on the open pipeline: close dates in the past, no activity in a window, stuck in stage past the team's own median by a multiple, late-stage value unchanged since creation, and duplicates on one account. Each with the count, the weighted value and the rep.

DefinitionFive weekly checks on the open pipeline: close dates in the past, no activity in a window, stuck in stage past the team's own median by a multiple, late-stage value unchanged since creation, and duplicates on one account. Each with the count, the weighted value and the rep.

Before the call

The five lists are what the forecast call would otherwise spend twenty minutes discovering.

Never automatic

Automatic closure teaches reps to move dates the day before the check. The list is the pressure; the rep is the decision.

How it is computed

Five weekly checks on open deals: close date in the past, no activity inside a window, in stage beyond twice the norm, no next step, and no contact role.

Example

Of 80 open deals, 12 have a past close date, 19 have had no activity in thirty days and 9 have no contact. Twenty-six distinct deals fail at least one check.

Where it goes wrong

Done before the quarter-end review and at no other time.

Articles that use this term

Data quality and reconciliation

A CRM data quality scorecard: five fields, five checks, one number per rep

How to score CRM data quality from the export rather than from complaints: five fields that every coverage and pipeline measure depends on, owner, close date, stage, activity date and account identifier, the check for each, the completeness and validity rate per rep, why the score is reported beside the measures that depend on it, and the rule that a measure computed on data under a stated score is shown greyed.

16 Sept 20263 min read Data quality and reconciliation

Pipeline hygiene: five checks to run on the CRM every week before the forecast call

Five checks on the open pipeline that take a minute from a weekly export and remove most of the argument from the forecast call: close dates in the past, deals without a next step or activity in a stated window, deals in the same stage past the team's own median stage duration, values unchanged since creation on late-stage deals, and duplicate opportunities on one account. Each with the count, the value affected and the rep.

16 Sept 20263 min read Forecast and pipeline

Slip count per deal: how many times a close date moved, and what it predicts

How a sales leader measures slip count from weekly pipeline snapshots: the number of times each open deal's close date has been pushed, the close rate by slip count from the team's own history, the weighted forecast that discounts multi-slip deals by that rate, the reps whose pipeline carries the most slips, and why a deal that slipped three times is a different object from a deal that slipped once.

16 Sept 20263 min read