Score a target yourself.

1. 1No forecast history or no snapshots. Accuracy unmeasured or below 60%. The number is set top-down.
2. 2A forecast exists but accuracy is 60-75% and consistently optimistic. Commit has no written criteria.
3. 3Written commit criteria. Accuracy 75-85%, bias under 10%. Reviewed weekly but mostly by opinion.
4. 4Forecast built from stage conversion and deal evidence. Accuracy 85-92%. Slippage tracked per rep.
5. 5Bottom-up and top-down reconciled. Accuracy above 92% for four quarters. The forecast is trusted by the board.

Red flags: The number moves most in the final fortnight; Historical snapshots cannot be produced; Forecast lives in a spreadsheet outside the CRM

1. 1Coverage below 1.5x after cleaning. No stage history. Over a third of open pipeline is past its close date.
2. 2Coverage 1.5-2.5x against a 3x need. Pipeline is reviewed rarely. Ageing is unmeasured.
3. 3Coverage 2.5-3.0x after cleaning. Stage ageing is visible. Stale deals are cleared monthly.
4. 4Coverage above 3.0x after cleaning, and stage conversion is known and used to plan. Weekly pipeline reviews with clean-ups.
5. 5Pipeline generated to a plan by source. Conversion by stage and age drives hiring and spend. Stale pipeline is rare.

Red flags: Large deals sit unchanged for quarters; Pipeline created in the last two weeks of the quarter to fill a gap; Management cannot say how much pipeline is real

1. 1No written process. Qualification varies by rep. Discounts approved ad hoc.
2. 2A process exists on paper but the CRM does not enforce it. Fields mostly blank.
3. 3Stages and qualification written and mostly used. Discount bands exist. Deal reviews are irregular.
4. 4Exit criteria enforced in the CRM. Deal reviews weekly. Discounts traded for terms.
5. 5One process, measured and improved from win/loss data. Variation between reps is explained by skill, not by method.

Red flags: Reps describe different stages; Qualification fields blank on over 30% of opportunities; Discounts cluster in the last week of the quarter

1. 1Fewer than 30% of reps at quota. Top 3 reps carry over 70% of bookings. No ramp plan.
2. 230-50% at quota. Ramp longer than 9 months. Heavy reliance on one or two people.
3. 350-60% at quota. Ramp 6-9 months. Hiring profile exists but is applied unevenly.
4. 460-75% at quota. Ramp under 6 months. Coaching rhythm in place. Top 3 reps under 45% of bookings.
5. 5Over 75% at quota. Ramp under 4 months. A repeatable hiring and onboarding system.

Red flags: Two or more of the last five hires left inside a year; Quota reset yearly to match last year's result; Compensation rewards bookings that churn

1. 1Key CRM fields blank on over 30% of records. Many overlapping tools. No owner.
2. 2A CRM exists but data is unreliable. Tools bought by individual teams. Manual reporting.
3. 3One CRM, written definitions, a weekly report. Some overlap and manual reconciliation.
4. 4Clean data, integrated tools, a named RevOps owner. Reporting automated.
5. 5A lean stack, each tool with an owner and a measured effect. Data quality monitored and enforced.

Red flags: More than four overlapping sales tools; Forecast built outside the CRM; Loss reasons recorded as free text

1. 1No outbound motion. One source supplies over 70% of pipeline. Pipeline depends on a founder's network.
2. 2Ad hoc outbound with no targeting. Meetings booked but rarely become opportunities.
3. 3A defined outbound motion with target accounts and sequences. CAC payback 18-30 months.
4. 4Account-based targeting, measured conversion at every step, payback 12-18 months.
5. 5A predictable outbound engine tested with holdouts. Payback under 12 months and stable at higher spend.

Red flags: Lots of activity and few opportunities; No agreed target-account list; Meetings counted without checking they were with buyers

1. 1No documented process and no AI in use, or AI claims without evidence.
2. 2Pilots exist, none in production. Process mostly in people's heads. Data not ready.
3. 3One or two workflows in production with a measured effect. Process written for the core steps.
4. 4AI embedded in several workflows with evaluation and approval gates. Process documented and followed.
5. 5AI measurably lifts productivity or product value. Governance in place. Process is the basis for automation.

Red flags: Management cites tools, not results; No policy on what data AI tools may touch; Process lives in one person's head

1. 1No written ICP. Roles overlap and nobody owns a number. Territories are ad hoc.
2. 2An ICP on a slide but not in the CRM. Handoffs between teams drop deals.
3. 3ICP and territories documented. 50-70% of new revenue from the ICP. Owners named for the main numbers.
4. 4ICP drives territories and messaging. 70-85% of new revenue from the ICP. A regular operating cadence.
5. 5The model is reviewed yearly against data. Over 85% of new revenue from the ICP. Clear ownership of every number.

Red flags: Marketing and sales describe different customers; Nobody owns the handoff from sales to customer success; Territories unchanged for three years

1. 1Several functions at 1. The engine depends on individuals.
2. 2Most functions at 2. Gaps in at least one function that touches revenue directly.
3. 3Functions at 3 on average. Some strong, some thin.
4. 4Functions at 4 on average with no function below 3.
5. 5All functions at 4 or 5, supporting each other.

Red flags: A function with no owner; Customer and sales disagree about who owns renewals; Enablement ends after the first month

1. 1The number is a target with no capacity model. Quotas are set without reference to history.
2. 2A model exists but ignores ramp and attrition. Plan misses are explained after the fact.
3. 3Plan built from capacity and historic conversion. Reviewed quarterly.
4. 4Capacity, pipeline and conversion reconciled in one model. Scenarios prepared.
5. 5A planning process that predicts the year within a few percent and updates monthly.

Red flags: Targets raised without added capacity; Quota coverage over 130% or under 90% of plan; No scenario if the first quarter misses