A Salesforce pipeline audit examines the structural reliability of opportunity data inside Salesforce — whether close dates are current, whether stage progression reflects actual deal advancement, and whether the reported pipeline value is supported by recent activity. This is distinct from Salesforce's native forecasting, which summarizes current data without evaluating its structural integrity.
48–72 hour delivery. Independent. Versioned. Deterministic.
Built for structured CRM environments with $3M–$50M in annual revenue.
Used by leadership teams who want decision-grade forecasting.
Salesforce is mature and standardized. But its IsClosed and IsWon field dependencies, stage probability configurations, and forecast lock mechanics create structural patterns that forecast views cannot diagnose.
Salesforce's forecasting tools show you probability-weighted pipeline. Structural audit shows you whether the probabilities can be trusted for decision-making.
The audit requires opportunity and account data from Salesforce. Both are accessed through Salesforce Reports with no special permissions required.
Salesforce forecasting shows probability-weighted pipeline. An opportunity in Negotiation stage with 50% probability counts as $500K on a $1M deal. Salesforce reports this accurately. But it doesn't audit whether the stage assignment or the probability factor still reflects deal reality.
An opportunity can sit in Negotiation for 120 days with no recent activity, and Salesforce will include it in the forecast with its standard probability without qualification. The system is working as designed. The problem is structural: the stage definitions, the close-date discipline, and the activity recency have drifted out of alignment.
This drift accumulates silently. It doesn't trigger an alert. It doesn't fail a validation. It simply makes the forecast less reliable, quarter after quarter.
By the time it shows up as forecast variance, the structural problems have compounded through hiring decisions, marketing allocation, and resource planning — all based on numbers that felt reliable but weren't structurally audited.
The Revenue Risk Framework™ applies a deterministic, versioned rule set to your Salesforce export and quantifies structural exposure. It measures five domains of opportunity integrity, calculates a Composite Exposure Index (0–100), assigns a classification tier, and surfaces dollar-quantified findings with control gap recommendations.
Contract values present and consistent. Close-date discipline maintained. Account and contact records complete enough to support the pipeline they claim to represent.
Stage durations that reflect real progression, not neglect. Opportunity aging patterns that distinguish momentum from stagnation. Revenue velocity consistent enough to forecast against.
Response-time consistency across the organization. Engagement decay between touches. Follow-up gaps that indicate process breakdown.
Source attribution that holds under scrutiny. Routing logic that still matches your current go-to-market. Qualification standards that haven't quietly loosened.
Forecast variance traceable to structural causes. Revenue concentration quantified. Decision-grade data integrity across the pipeline.
Every finding is deterministic, versioned, and reproducible. The same Salesforce export produces the same result every time. Repeat diagnostics allow structural movement to be measured over time under continuity controls.
The Free Revenue Risk Score™ applies a subset of deterministic rules to your Salesforce export. It takes minutes, requires no login access, and surfaces early structural signals — the kind that don't appear in Salesforce's native forecasts.
If exposure intensity warrants deeper analysis, a full diagnostic quantifies dollar impact, maps control gaps, and delivers a version-stamped structural assessment.
Early structural signals are inexpensive to measure. Late exposure is expensive to unwind.
The question is whether your forecasting is reading it correctly. Export your opportunities, run the free assessment, and see what your Salesforce pipeline is actually saying beneath the probability calculations.
Measure Your Salesforce Pipeline