Data Governance Success Story by Tech Mahindra: Transforming Allianz Indonesia's Data Management

Overview

The client is a global leader in the insurance and asset management industry. It operates in 70+ countries, has 155,000 employees, and serves millions of customers worldwide. However, it faced significant challenges with fragmented data governance, which caused inconsistencies and inefficiencies. Tech Mahindra implemented a robust data governance framework, defining roles, streamlining processes, and ensuring seamless data flow.More

The client is a global leader in the insurance and asset management industry. It operates in 70+ countries, has 155,000 employees, and serves millions of customers worldwide. However, it faced significant challenges with fragmented data governance, which caused inconsistencies and inefficiencies. Tech Mahindra implemented a robust data governance framework, defining roles, streamlining processes, and ensuring seamless data flow. The solution enhanced data quality, compliance, and decision-making, driving digital excellence and operational agility.

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Client Background and Challenges

The client is a global leader in insurance and asset management. With a workforce of 155,000 employees, it operates in 70+ countries and delivers comprehensive insurance and asset management services to millions of customers worldwide. As part of its digital transformation efforts, the company faced significant challenges in data governance, role definition, and tool migration. Addressing these challenges required a structured framework, a business glossary, a data catalog, and a seamless transition to Informatica CDGC.

Our Approach and Solution

Cloud Migration Strategy

Migrated the client’s on-premise Informatica AXON/EDC solution to the cloud-based Informatica CDGC. The solution included planning, identifying compatible business and data assets, and converting incompatible assets to align with CDGC standards.

Organization and Stewardship

Partnered with the client’s data office, led by the Chief Data Officer, to define governance roles. Conducted discussions and workshops with business leaders, establishing 18 data owners and 39 data stewards. Developed training modules covering data governance principles, roles, responsibilities, and tool usage.

Standardized Data Practices

Collaborated with data owners and stewards to create and document a structured business glossary. Addressed 14 key business use cases, leading to the documentation of 500+ business glossary entries and 900+ data quality rules, and introduced sensitivity labeling to classify data as public, internal, confidential, or strictly confidential.

Metadata Management and Tooling

Documented business glossaries in Informatica Axon, ensuring clear ownership with defined data owners, stewards, and officers. Scanned over 150,000 technical objects across six data sources, including databases, tables, and stored procedures, and established end-to-end business and technical lineage in AXON and EDC, providing complete data traceability.

Process Optimization

Implemented best practices for bulk asset uploads and streamlined data governance workflows. Enhanced data quality, compliance, and operational efficiency to support the client’s transformation into a data-driven enterprise.

Business and Community Impact

  • Top Industry Recognition: Ranked among the top five operating entities for data and analytics across 27 entities.
  • Sustainable Data Governance: Established frameworks for a long-term, scalable governance program.
  • Enhanced Decision-Making: Streamlined KPI tracking and improved data-driven insights across domains.
  • Unified Business Language: Created a common terminology, fostering collaboration across teams.
  • Accelerated Issue Resolution: Enabled data lineage for faster identification of system-wide impact.
  • Improved Technical Competency: Enhanced proficiency in Informatica’s data governance tools.
  • Standardized Metadata Management: Shifted from siloed practices to a consistent documentation approach.
  • Increased Governance Maturity: Improved scores across 21 KPIs, rising from 64 to 89.
  • Superior Data Quality: Achieved a minimum 95% data quality score across 350+ data elements.