Compile a leadership-ready summary of validation accuracy, return-rate reduction, and processing time saved across the Registry using Instabase Analytics.
Leadership needs a clear operational case for automated document verification: how much validation accuracy has improved, how far document return rates have fallen, and how much manual review time has been saved. As a Registry manager, you translate day-to-day verification activity into headline numbers that show where Instabase has delivered impact and where to invest next.
This guide walks you through compiling a leadership-ready summary from Instabase Analytics, rolling up validation pass rates, return-rate reductions, and processing-time savings across a full reporting period.
Configure workflow automation so validated cases move directly to license issuance or amendment processing without manual handoff.
Create and implement new validation rules in Instabase to automatically catch recurring document defects.
Use Instabase Analytics to identify the top reasons documents fail validation and which document types cause the most returns.
Open Instabase Analytics and set the reporting period (for example, the last quarter), with the previous period selected for comparison.
Pull the headline metrics: total cases processed, average documents per case, validation pass rate, and average time from submission to validated.
Compare the current document return/defect rate against the baseline to quantify the reduction in documents reaching Registry with errors.
Estimate the manual review time saved by multiplying the auto-validated case volume by the average manual review time those cases would otherwise have required.
Break the results down by document type — MOA, passport, lease, annual return — to show where the largest gains occurred.
Summarise the headline numbers into a short leadership update, alongside recommendations for the next quarter.
INSTABASE ANALYTICS — LEADERSHIP EFFICIENCY SUMMARY For last quarter versus the previous quarter, show total cases processed, the validation pass rate, the average time from submission to validated, and the change in document return rate. Estimate the manual review hours saved and break the results down by document type. --- Hypothetical output: Total cases processed: [value] (up [value]% from previous quarter) Validation pass rate: [value]% (up from [value]%) Average time from submission to validated: [value] hours (down from [value] hours) Document return rate: [value]% (down from [value]%) Manual review hours saved: [value] auto-validated cases × [value] hours per manual review = [value] hours Breakdown by document type: - MOA: [value]% pass rate - Passport: [value]% pass rate - Lease: [value]% pass rate - Annual return: [value]% pass rate Recommendations: 1. [Expand validation rules for document type with remaining defects] 2. [Consider automated routing for passed cases to reduce downstream bottlenecks]
For last quarter versus the previous quarter, show total cases processed, the validation pass rate, the average time from submission to validated, and the change in document return rate. Estimate the manual review hours saved and break the results down by document type.
Cross-check company details across Annual Return and Customer Confirmation Letter documents for renewal cases.
Cross-check a share transfer or amendment addendum against the original MOA to see exactly what has changed.