PRODUCT USE CASE: Enable new and existing Workforce Solution and Identity and Fraud Products by migrating 179M criminal justice records into the enterprise data lake Organization: Credit and Data Sector Role: Vanessa Ross: MDA Program Manager
Year Implemented: 2022
Scope
The strategic initiative aims to leverage the vast amount of criminal justice data to enhance the accuracy, efficiency, and security of identity verification processes and fraud detection mechanisms. Integrating these records into the enterprise data lake will establish a more robust foundation for data analysis. Once data is available in a data lake, streamlining operations and delivering more sophisticated solutions can evolve to address users' and stakeholders' needs.
Solution
The Google Cloud Platform (GCP) solution employs Cloud Storage and SFTP for secure data replication, alongside Cloud Dataflow and Cloud Dataprep for advanced ETL processes. Cloud Pub/Sub ensures efficient data ingestion, while BigQuery facilitates data analysis, linking, and the creation of compliant data views. This streamlined, GCP-based approach offers a secure, scalable framework for comprehensive data management and analytics, ensuring regulatory compliance and informed decision-making.
Delivery
PM Management
Program Charter
Stakeholder Engagement Plan:
Risk Management Plan
Budget and Resource Plan, Monitoring and Reporting
Compliance and Security Framework
Program Roadmap
Change Management Plan
Technical Approach
Data Migration Plan
Data Analysis
Data Model and Schema Definitions
Security and Access Controls
Data Quality Framework
Integration APIs
Testing and Validation Report
Agile (SDLC) Approach
Sprint Plans
Sprint Reviews/Demos
Retrospectives
Burndown Charts
User Stories
Definition of Done (DoD)
Tools
AHA Road mapping Tool
JIRA
Outcomes
Scalability and Performance Improvements: System can handle a 2-3x increase in transaction volume without significant performance degradation, indicating robust scalability and reliability.
Employee Productivity: 15-25% increase in employee productivity metrics related to using these products, including time saved on manual tasks and faster processing rates.
Operational Efficiency Gains: 20-40% improvement in operational processes, such as reduced processing times and increased automation, to indicate efficiency gains.
PRODUCT USE CASE: Migrate Health Application from Legacy On-premise and Data to AWS Platform
Role: Vanessa Ross: Program Manager
Client: Change Health Care
Year Implemented: 2020
Scope
CHC's directive required the migration of 25 terabytes of legacy healthcare data to a new system, bolstering security measures for protecting personal information and modernizing applications. Adherence to data protection laws and maintaining security and client trust throughout data migration was mandatory. We designed the process to be scalable, ensuring the seamless and secure addition of new clients' data to our system.
Solution
Using AWS, the solution employs S3 for secure storage, Database Migration Service for data transfer, and Lambda for processing, ensuring compliance with data protection laws. Amazon RDS and DynamoDB modernize applications, bolstered by security through AWS KMS and Shield. This scalable approach maintains client trust and security throughout the migration, facilitating the seamless addition of new clients' data.
Delivery Approach
Project Charter
Stakeholder Analysis and Communication Plan
Re-hosting and Re-factoring Migration Plan/Defined Outcomes
Well-Architected Framework Reviews
Risk Management Plan
Resource Management Plan
MS Project Schedule
Quality Management Plan
Security and Compliance Documentation
Change Management Documentation
Post-Migration Review
Project Closure Document
Communication & Release for 30K Aggregators and Medical Facilities
Outcomes
Enhanced Data Security and Compliance: Following the migration, CHC reported a 40% reduction in security incidents related to personal information breaches. Compliance with data protection laws was achieved at a 100% rate, demonstrating a commitment to legal standards and boosting client trust.
Modernized Healthcare Applications: The system's modernization led to a 30% improvement in application performance and a 50% increase in user satisfaction, as measured by faster processing times and positive feedback from healthcare providers.
Scalable Data Management Infrastructure: The scalable migration process enabled the seamless addition of data from new clients, with CHC experiencing a 60% growth in client data integration capacity within the first year. System scalability assessments showed a 90% readiness to accommodate future data volume increases without impacting performance.
PRODUCT USE CASE: Revolutionize Dealer Contract Onboarding Journey to Efficiency, Risk Mitigation, and Cost Savings through Automation and ML Role: Vanessa Ross: Director, Intelligent Automation
Company: Cox Automotive
Year Implemented: 2019
Opportunity
Cox Automotive aimed to transform its contract onboarding process for new and used car dealers. The preceding method was labor-intensive, prone to errors, and time-consuming. It necessitated manual data entry from paper-based application forms, identity proofs, and financial statements into their Salesforce CRM system. Furthermore, Cox Automotive sought a more efficient approach to risk assessment and early fraud detection within the onboarding process.
Solution
The Intelligent Automation solution for Cox Automotive's contract onboarding process included:
- Leveraging Blue Prism for Robotic Process Automation (RPA).
- Salesforce as the CRM backbone.
- Integrating machine learning (ML) for risk assessment and fraud detection offers a robust solution.
Delivery Approach
Data Driven Analysis
Intelligent Automation Business Case
Strategic Roadmap Design
Agile Experimentation and Prototyping
Human-Centric Design Thinking
Continuous Learning and Adaptation
Collaborative Ecosystem Building
Metrics-Driven Performance Management
Outcomes
Reduced Processing Time: Outcome: Streamlining the contract onboarding process resulted in a 40% reduction in average processing time, enhancing efficiency and customer satisfaction.
Minimized Error Rates: Outcome: By automating data entry and implementing standardized validation checks, Cox Automotive successfully reduced error rates in the onboarding process by 60%, leading to improved data accuracy and compliance.
PRODUCT USE CASE: Streamline HR Time Off and Timesheet operations, enhance accuracy and compliance, and empower employees with a seamless and efficient experience.
Role: Vanessa Ross: Director, Intelligent Automation
Client: Cox Automotive
Year Implemented: 2019
Opportunity
Implement an HR Bot equipped with advanced natural language processing (NLP) and machine learning capabilities to automate and streamline the process of Paid Time Off (PTO) requests and timesheet submissions, enhancing efficiency, accuracy, and employee satisfaction.
Solution
The solution integrates Optical Character Recognition (OCR) technology with Blue Prism's Robotic Process Automation (RPA) platform and the Kronos Workforce Management system to automate document processing and streamline workforce management workflows. OCR technology accurately processes documents like timesheets and invoices, extracting relevant data fields. Blue Prism robots then automate tasks such as updating employee timesheets in Kronos and processing leave requests. Integration with Kronos enables real-time updates to employee schedules and payroll data.
Delivery Approach
Automation Strategy
BPM Process Maps
Agile Sprint Backlog
Human-Centric Design Prototypes
Iterative Development Sprints
Project Charter and Plan
Status Reports and Meetings
Training and Change Management Materials
Performance Metrics and Monitoring:
Outcomes
Efficiency Improvement: 50% reduction in average processing time, saving one business day per request.
Accuracy Enhancement: 60% decrease in error rate, reducing errors by 3% per submission.
Employee Satisfaction: Employees using the new system reported a 20% satisfaction rating.