GOHVIO · BUSINESS RISK SCORE · SEPTEMBER 2026
How Gohvio decides which findings matter, the formula behind it, and how to run the same maths on your own data. No platform required.
Three things. Read them in this order.
Why record counts are the wrong headline.
Twenty three broken records means nothing on its own. Twenty three broken records holding $2.4M of pipeline attribution is a decision. Gohvio never leads with a count.
The formula.
Business Impact × Financial Exposure × Confidence × Blast Radius. Four dimensions, one to five each, multiplied. One to 625. The full maths, written out. No black box.
Run it yourself.
The four dimension tables are on this page. Score your own findings by hand against them. You do not need the platform to see which of your problems is actually expensive.
Business Risk Score v1.0 · From the team at Gohvio · 31 August 2026
THE FORMULA
Gohvio prioritises business impact, not record count.
Business Risk Score = Business Impact × Financial Exposure × Confidence × Blast Radius. Four dimensions, each scored 1 to 5. Range 1 to 625. Scored per finding, never per dataset.
The object does not determine severity, the business impact does. A contact can be a 4 if a broken association corrupts a forecast rollup. An opportunity can be a 1 if the missing field is next step.
Exposure is the sum across every affected record, drawn from whatever money field is present. Fifty opportunities worth $800K collectively is $800K of exposure, not fifty errors. Where a dataset carries no amount field at all, Gohvio says so in plain words and never invents a figure.
This is the dimension that stops Gohvio becoming the data police. A deal sitting in negotiation for 75 days is unusual, not wrong. It may be strategic. Staleness and anomaly signals are capped at 2. A Gohvio default rule you have not confirmed is capped at 4, because our opinion about your business is never certain.
Record count is the floor, not the answer. Blast radius is records times teams times periods times systems. A finding spanning three owners and two fiscal periods spreads further than its row count suggests.
SEVERITY FLOORS
Some findings are serious regardless of what the multiplication says. A floor only ever raises a severity, never lowers it. When a floor fires, Gohvio says which one and keeps the raw score visible.
WHAT A FINDING LOOKS LIKE
The risk score and the dollar exposure are always shown separately. The money never hides inside the score. The order is fixed: severity, dollars, plain English, then the score, because the score is the least interesting line to the person reading it.
CRITICAL $2.4M forecast exposure 31 opportunities have close dates inconsistent with your forecast rules. Risk Score: 320
LOW Financial exposure unquantified, no amount field in this dataset 412 contacts are missing a phone number. Risk Score: 10
A dataset's headline severity is its single worst finding after floors, never an average. Averaging buries a severe finding under hygiene noise. Headline dollars are the sum across findings, de-duplicated by record, so one opportunity caught by three rules is counted once.
WHY IT MATTERS
Agents running on bad data are worse than people running on bad data. The score tells you which of your problems is expensive enough to fix before you automate on top of it.
Marketing, sales and finance argue about record counts. They do not argue about $2.4M. A dollar figure with a traceable set of records behind it ends the meeting.
The intelligence is in your guardrails, not in a model trained on everyone else's CRM. You bring your attribution model and your sales process. We score against your business logic, and we cap our confidence when the rule is ours rather than yours.
Connect your CRM, run your guardrails, get your findings ranked by what they put at risk. HubSpot and Salesforce are both supported.