DevOps

QA Monitoring and Batching

Problem

The client needed to integrate criminal history from state agencies into a data warehouse to accurately predict employment and benefit eligibility. The larger challenge was creating an efficient and thorough process to monitor this data for real-time changes.  The process needed to be fast and prevent any performance degradation. The current manual process was time-intensive and costly.

The client had attempted to automate this prior using out of the box software which was too limited.  The complexity of the data sources available from the state agencies was a moving target. The uniqueness of each state meant the solution must be adaptable.  On top of those challenges, the security required to manage personally identifiable information was top priority.

Challenges

  • Ensuring that criminal history data matched with correct records
  • Interfacing seamlessly with data services hub, existing web and mobile application systems
  • Using enhanced algorithms that applied “fuzzy matching logic” to detect change
  • Tracking staff actions against policies and best practices
  • Complying with a wide array of state and federal regulations
  • Adhering to stringent privacy and security requirements
  • Providing audit functionality

Solution

Our team analyzed the data sources to find inclusions and exclusions. Data matching was facilitated by combining publicly available data with social security number. The data was presented to staff through a combined report. A quality assurance (QA) portfolio within the data services hub utilized a daily extract.

As an extension of this project, our team developed and implemented Portfolio Monitoring and Batching Services.  This monitored against a web service or flat-file data sources for specific changes in status. Portfolios could be updated using dynamic query criteria.  We then compared data using a systematic batch processes.

The monitoring services provided data as a snapshot.  We applied change-detection logic against scheduled watch cycles that triggered alerts within a web service.  The nature of these changes pushed from the state agencies, created up to the minute accuracy. The monitoring service was now able to provide beneficial information to the decision process and was automated.

The solution also included automated processes designed to measure the quality assurance of staff decisions against policy adherence. QA portfolio monitoring alerted staff to situations that might require case action.  Additionally, our team tracked any benefits that were terminated or reduced because of the monitoring services. That data was provided periodically to the client to meet Federal reporting requirements.

Benefits

  • Integration with interagency system for routing of tasks and information to staff
  • Automatic notifications of changes in status that might impact eligibility
  • Significant cost savings to state
  • Improved program integrity
  • Increased staff productivity and accuracy
  • Easy integration of new data sources and/or factors

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