A Fortune 500 global insurance company wanted to migrate the majority of its business applications and infrastructure workloads to the public cloud. With data spread across multiple platforms and geographies, manual collation and reconciliation was leading to inconsistent information, preventing real-time insight into revenue and profitability. When one of its largest business units decided to reduce operating costs, the client opted to migrate 70% of all its information management data. This required moving associated applications, infrastructure, development, and support programs to the public cloud within the next three years.

After a competitive process, Trianz was chosen to join the program governance team consisting of business and IT leadership from the client’s side, and a technology support team from AWS. Trianz deployed a unique model for execution where agile teams worked in parallel with business leads and IT managers, while simultaneously leveraging Trianz’ proprietary TCO Calculator and an accelerated migration planning methodology. The resulting robust, end-to-end strategy included prioritization of over 80 use cases based on business value generation by cloud migration. Ultimately, Trianz built a cloud reference architecture, a financial framework, and a roadmap aligned with business goals.

The Business Challenge

Inconsistent manual processes and data spread across disparate systems had created a lack of real-time visibility into the client’s revenue and profitability, and raised operating costs.

Technology Components

  • Informatica Powercenter
  • Netezza (PDA)
  • Qlik
  • Aginity
  • Cognos Framework
  • Cognos Active Reports

The Approach

  • Identified business use cases, assessed complexity and value from migration to cloud
  • Defined a conceptual cloud reference architecture on AWS to meet business and IT goals
  • Evaluated and prioritized use cases depending on complexity and business value
  • Started with data analysis and profiling across geographies and LOBs
  • Conducted workshops to facilitate decisions and agreement on common definitions
  • Centralized all source data in a staging area and built data tree
  • Developed proof of concept for two countries and later extended to 10 other countries
  • Rolled out enterprise data warehouse to include auto lines of business across all countries

Transformational Effects

  • Roadmap established based on business use cases and incremental development of AWS services
  • ROI model developed for the global enterprise data warehouse initiative
  • Risks mitigated from addressing data quality issues upfront
  • Common business definitions established across regions and countries
  • Enabled business users to analyze and unearth insights on revenue and profitability across LoBs
  • Developed an ROI model for global enterprise data warehouse initiative

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