When Dashboards Lie: Fixing Forecasts at the Source

Executives rely on dashboards to make decisions. But when CRM data is inaccurate, forecasts become fiction.

How Bad Data Skews Forecasts

  • Inflated pipeline: Dead deals and departed champions stay in CRM.
  • Inconsistent fields: Stages and categories logged inconsistently.
  • Attribution gaps: Campaigns missing source data.
  • Stuck stages: Deals rot without alerts.

One survey found 39% of sales professionals say bad data undermines their forecasts.

The “Forecast Data Contract”

To build trust, you need a clear data contract:

Opportunities: Stage, Close Date, Amount, Forecast Category, Primary Contact (required).
Contacts: Role on opportunity, Last Verified, Last Activity.
Rules: Block past close dates, stage mismatches, or opps without active contacts.
SLA: Stage-aging thresholds trigger alerts.
Ownership: Sales = timeliness, RevOps = validity, Finance = audits.

Trust Dashboard Metrics

  • % opps with active primary contact
  • Stage-stuck count/age
  • Past-due close dates
  • Forecast variance by segment
  • Data completeness score

By Role: What To Do

  • CROs: Tie forecast acceptance to data quality score.
  • Sales Managers: Review contact activity in 1:1s.
  • RevOps: Own enrichment cadence.
  • Finance: Reconcile bookings vs. pipeline hygiene.

The Payoff

  • More accurate forecasts
  • Fewer quarter-end surprises
  • Higher executive confidence

Salesforce-native enrichment ensures forecasts reflect real humans, not ghosts.

Call to Action

This quarter, add Primary Contact (Active <30 days) to your forecast commit criteria. You’ll instantly improve accuracy.

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