The Trap of Revenue Forecasting Tools
Putting a £60,000 forecasting tool like Clari or BoostUp on top of a broken CRM will not give you predictable revenue. It just gives you expensive guesswork.
Software Cannot Fix Bad Governance
The pattern is always the same.
Executives miss a quarter. The board asks questions. Someone says the word "predictability." And within a week, there's a vendor demo on the calendar for a forecasting tool.
Clari. BoostUp. Aviso. They all promise the same thing: AI-powered revenue intelligence that turns your pipeline into a predictable engine.
It sounds compelling.
But algorithms cannot predict revenue if your sales reps are lying to the CRM.
And they are. Not maliciously. Structurally.
If opportunity stages mean nothing — if "Discovery" and "Qualification" are just boxes reps click to make their manager stop asking — the model has no signal to work with.
If every close date is "end of month" because that's what reps default to, the AI is training on fiction.
If pipeline coverage ratios look healthy but half the pipeline is recycled deals that were never going to close, your 3x coverage is meaningless.
No amount of machine learning fixes this.
Forecasting is a behaviour and governance problem. Not a technology gap.
You don't need a better algorithm. You need stage definitions that mean something, enforcement mechanisms that hold, and incentives that reward accuracy over optimism.
Buy a £60k tool without fixing any of that, and you'll get exactly what you had before.
Guesswork. With a dashboard.
Building a Predictable Engine
I've built forecasting systems from raw pipeline data through to board-level predictive models.
Not configured a vendor's tool. Built the system. Owned the output. Presented the numbers to the board and been accountable when they were wrong.
That's the difference between advice from someone who's reviewed forecasting and advice from someone who's carried the forecast.
My approach starts with the root cause. Not the symptoms.
First, I fix the incentives. If reps are rewarded for inflating pipeline, no tool will give you clean data. The governance layer comes before the technology layer.
Then I fix the qualification criteria. Stage definitions get rewritten with explicit, observable exit criteria. Not feelings. Not "the rep thinks it's going well." Concrete evidence that a deal is real and progressing.
Then I fix the pipeline architecture. Clear ownership. Consistent data hygiene. Automated enforcement where possible, human accountability where it matters.
Once the data is clean, the forecasting model almost builds itself.
I architect custom forecasting systems that replace tools costing six figures a year. They're built on your actual data, calibrated to your sales cycle, and owned by your team.
No per-seat licensing. No vendor dependency. No waiting on someone else's product roadmap to fix what's broken.
Off-the-Shelf Forecasting
Clari, BoostUp, Aviso
Overlay tools that ingest CRM data and apply AI models. Require clean input data to function — but don't fix it. Per-seat licensing. Vendor-dependent. Only as good as the pipeline hygiene underneath.
Typical annual cost: £60k+
Operator-Built Forecasting
Architected by RevOps On-Demand
Fixes the governance and data quality first. Then builds custom forecasting models calibrated to your sales cycle. Owned by your team. No per-seat fees. Trustworthy because the inputs are trustworthy.
Typical annual saving: £60k+ in eliminated SaaS spend
£60k+/Year in Saved Intelligence Tools. And a Forecast You Can Trust.
The licence saving is real. But it's not the point.
The point is board-level confidence in your numbers.
- Trustworthy pipeline data — Stage definitions that mean something. Close dates that reflect reality. Coverage ratios built on deals that are actually progressing.
- Accurate commit calls — When your CRO commits a number, the organisation trusts it. Not because of AI — because the underlying data and governance are sound.
- Eliminated vendor dependency — No more per-seat licensing that scales with headcount. No more overlay tools that add cost without fixing the root cause.
Nicholas Gollop has built forecasting systems from pipeline data through to predictive models, and lived with the consequences when the numbers were wrong. That first-hand accountability informs whether a custom system makes sense for your business, or whether fixing your governance layer is the smarter first step.
Stop Guessing. Start Governing.
Let's discuss your pipeline hygiene and build a forecasting model you can actually trust.
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