Verona Police
Process Optimization
A comprehensive process mining project that analyzed traffic violation workflows for the Verona Police Department, resulting in a 27% improvement in fine collection success rates.
Project Overview
The Verona Police Department was experiencing significant inefficiencies in their traffic violation processing system. With thousands of fines issued monthly, they needed to identify bottlenecks and process leaks that were preventing successful collection.
Using advanced process mining techniques, we analyzed their existing workflows and provided actionable insights that dramatically improved their success rates.
Key Metrics
Technical Approach
Data Collection
The Verona Police provided us with their existing process data, including timestamps, case statuses, and workflow transitions.
Disco Process Mining
Used Disco software to mine process patterns, identify bottlenecks, and visualize the actual vs. intended workflow paths.
BPMN Modeling
Created detailed BPMN models to map current state processes and design optimized future state workflows.
Key Findings & Solutions
Problem: Manual Verification Bottleneck
Manual verification steps were creating a 3-week delay in processing, causing many cases to timeout before collection.
Solution:
Automated 70% of verification checks using existing database lookups, reducing processing time to 3 days.
Problem: Notification Delivery Failures
Address mismatches and delivery failures were causing 40% of notifications to never reach violators.
Solution:
Implemented multi-channel notification system with address validation and electronic delivery options.
Problem: Follow-up Process Gaps
Missing systematic follow-up procedures for unpaid fines, leading to revenue loss.
Solution:
Created automated escalation workflow with defined intervals and clear accountability measures.
Project Impact
This project demonstrated the power of data-driven process optimization in government operations, providing lasting improvements to citizen services and municipal revenue collection.