Statistics show that in 2031, the U.S. population over the age of 65 will be around 75 million — almost double what it was in 2008. This national retirement services organization recognized that a generation of this size transitioning out of the workforce would cause two significant economic shifts. First, it would instigate a considerable transfer of wealth as balances switched from asset accumulation to asset withdrawal. Second, asset wealth will move to the next generation as wills are executed, and the upcoming generations have different needs, a greater digital focus, and increasing expectations for customer service and engagement.
The annuity organization knew that to better serve transitioning and emerging clients, they needed a more integrated approach to accessing and leveraging comprehensive data about their clients, products, and beneficiaries. However, they had several challenges blocking their goals.First, their data assets were scattered across a disintegrated data warehouse, siloed business systems, and disparate reporting assets. They needed a partner to look at their entire data landscape, assess its current state, and create a strategic and actionable plan to meet their new business needs.
- A lack of integrated architecture for data across the diverse systems landscape
- Redundant sources of reporting and analytics data
- Mistrust of their data resulting from a lack of data integrity and inaccuracies across different platforms
- Challenges with data analytics due to difficulty accessing applicable integrated data
After collaborating with the company leaders, we understood their goal — to better serve different client populations and prepare for changes in asset management — and how their current challenges were blocking their path forward. With that clarity, our team began a three-phased approach to meeting the objective.
We began by assessing their data and analytics environment. This gave us a foundation for determining gaps and opportunities as well as identify and prioritize business needs and drivers.
Program strategy alignment
Our team created a data charter that included a full inventory of their strategic business and use cases, an outline of their objectives and program goals, and a list of the identified challenges and barriers to meeting them. We used this to build a cohesive strategy to realign their data management and analytics capabilities with their business objectives, including:
- Prioritization of strategic business initiatives
- Key milestone targets for program increments
- Capability gaps to address
Maturity assessment and program roadmap
With the assessment and strategy in place, we then worked with our client to understand where they wanted to be on the data maturity scale. From there we could create an integrated, multi-year roadmap to address master data challenges, starting with the highest priority tasks.
With a clear strategy in place, our data experts designed and built a modern data platform for the financial service company. The new platform would support data science, management reporting, and executive dashboards with integrated data that was accurate and reliable.