Insurance | Case Study

Transforming Enterprise Data Management

One client's journey to a modern data platform to support advanced data analytics across the enterprise.

The Client

A Fortune 500,
Multi-Line Insurer

The Business Objective

Our client is a multi-billion-dollar insurer operating in 26 states across the U.S. Their siloed data environment and processes posed a number of reporting and analytical challenges resulting in long turnaround times, data inconsistencies and significant IT involvement. Additionally, fragmented data hindered the client’s ability to develop more advanced analytics and business intelligence capabilities.

To modernize and mature its data and analytics capabilities, the client approached X by 2 to:

  • Implement a data lake to handle increases in data volume from traditional and non-traditional data sources
  • Improve and integrate data governance processes and workflows
  • Improve data quality, reconciliation and balance
  • Support advanced analytics
  • Support big data needs, such as storing unstructured documents and images
  • Replace legacy data warehouse, mainframe system and extracts
  • Support the modernization of enterprise-wide reporting and analytics of both policy and claims data

The Work

X by 2 created a big data architecture and modern data platform to improve enterprise reporting, support advanced analytics, and drive business intelligence.

Current State Assessment

  • Analyzed and assessed the existing data environment, integrations, data flows, pain points, areas of friction, and reporting processes across various data management divisions

Future State Architecture & Data Governance

  • Defined and developed a future state solution, conceptual technical architecture, and information architecture
  • Identified inhibitors to achieving the desired future state
  • Rationalized existing tools and technologies
  • Conducted solution evaluation and selected various data lake automation, ETL, reporting, and BI tools
  • Established supporting MDM practices and processes to improve data quality

Data Strategy & Roadmap

  • Developed a business-aligned strategy and roadmap – including team/resource, timeline, and cost estimates – for transforming enterprise data management and analytics

Mobilization

  • Socialized program to build cross-departmental buy-in
  • Established program leadership and governance
  • Developed a staffing plan and on-boarded a hybrid team with client and X by 2 members
  • Finalized the implementation roadmap

The Business Impact

  • Improved Data Insight

    Began refocusing team toward harvesting actionable insights and away from data “plumbing.”

  • Unified Data Platform

    Broke down data silos allowing all business divisions to gather reporting and analytics from a governed data source.

  • Streamlined Data Quality

    Resolved data quality issues across business, IT, and end consumers.

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