Revenue Systems & Operations
Fix the machine underneath the number: funnel definitions, pipeline hygiene, forecast accuracy, compensation alignment and the CRM architecture that makes any of it trustworthy.
You are probably here because of one of these.
None of these is the problem. Each is a symptom, and the diagnostic exists to find out which underlying constraint is producing it, because the obvious answer and the correct one are frequently different.
- The forecast misses in the same direction every quarter and the explanation changes each time.
- Pipeline coverage is reported but forecast accuracy has never been measured.
- Two teams define “qualified” differently and both report against it.
- Deals sit in a stage for months because no exit criteria exist to move or kill them.
- The compensation plan rewards behaviour the strategy is trying to stop.
- Reporting takes three days of manual assembly and is contested when it arrives.
What you actually receive
Artefacts, not impressions. Everything below is yours to keep, rerun and hand to a board.
Funnel definition set
Every stage defined with entry and exit criteria that a third party could apply identically. The end of definitional drift.
Forecast accuracy baseline
Historic forecast versus actual by segment and rep. Bias measured, not asserted, usually the first genuinely uncomfortable slide.
Pipeline hygiene standard
Ageing rules, stall triggers, mandatory fields and the automated enforcement that makes compliance the path of least resistance.
CRM architecture review
Object model, required fields, reporting layer. What to fix, what to rip out, what to stop asking reps to type.
Compensation alignment read
Where the plan and the strategy disagree, and what changing it would cost.
Operating cadence
The weekly, monthly and quarterly rhythm, who meets, what is reviewed, what decision each meeting exists to make.
The shape of the engagement
The 4D Method →Diagnose
CRM extract and audit, forecast-versus-actual reconstruction, stage conversion analysis, RevOps and rep interviews.
Decide
Definitional set agreed, hygiene rules chosen, architecture decisions made with IT in the room.
Design
Configuration specification, reporting layer, cadence design, enablement materials.
Drive
Rollout, training session, first cycle run with support, accuracy tracking started.
Fixed fee, agreed before work starts. Scope boundaries, assumptions, change control, IP ownership and the AI-use clause are written into every SOW. The fee is quoted after the complimentary audit, because the audit is what establishes which of these problems you actually have.
When this works, and when it does not
This engagement fits when
- A CRM exists with at least a few quarters of history
- Someone owns RevOps, even part-time
- Sales leadership will enforce a definition once agreed
- You want the uncomfortable version of the forecast accuracy number
Look elsewhere if
- The expectation is that a tool purchase fixes this
- Reps cannot be asked to change any behaviour
- There is no history to reconstruct and none will be created
- The real issue is that the product does not sell
The right-hand column is not modesty. A poorly matched engagement costs you a fee and costs this practice the only asset it has, which is a record of work that landed.
Revenue Systems & Operations
Is this RevOps consulting or systems implementation?
The former. The engagement produces the definitions, the architecture decisions, the specification and the cadence. Implementation inside the CRM is executed by your admin or an implementation partner against that specification. Keeping those separate is deliberate, the expensive failures happen when the configuration decision is made by whoever is holding the keyboard.
What is a realistic forecast accuracy target?
Less important than measuring it at all. The single most diagnostic observation in most revenue organisations is that forecast accuracy has never been tracked, which means the forecasting process has never been improvable. Establishing the baseline and the bias direction is the first deliverable; the target follows from where you actually start.
Where does AI fit in revenue operations?
Mostly in the unglamorous places, which is where it pays: call synthesis into CRM fields so reps stop typing, automated hygiene flagging, anomaly detection on deals whose behaviour does not match their stage, and enrichment. Each is scoped against a baseline. Predictive forecasting on top of untrustworthy stage data is not a fix. It is the same wrong number, faster.
Related
Thirty minutes on your version of this problem.
A working session, not a sales call. If the honest answer is that you do not need an advisor, that is what you will hear.