Client: One of the largest integrated health care delivery and financing systems in America.
Challenge: De-centralized data and analytics functions led to disparate analyses, unclear insights, and duplicative spend
Solution: Create a federated enterprise analytics model with clear roles, responsibilities, and governance
Results: More consistent and cross-functional analytics, accelerated activation, ~$5.7M in value
Our client performed data management and analytics in several isolated functions across their enterprise. As the client became more interconnected, this approach constrained leaders’ ability to use data and analytics to draw consistent insights and support cross-functional decision making.
- Teams were focused on solving localized and discrete analytics questions requiring them to often develop distinct data structures, build “one-off” tools and analytic models, and develop analyses that were not fungible to other areas. Increasingly cross-functional projects created a need to streamline duplicative resources, utilize consistent data management and analytics approaches, and produce consistent analytic conclusions. At the same time, individual business units were still engaging in function-specific projects and needed to guide prioritization to best support their individual needs.
- Residing in the business units, analysts functioned with a clear sense of department-specific expectations and data ownership. As departments began to collaborate, it became clear that new standards of responsibility would help analysts better support enterprise-wide engagements.
- When analytic functions were tied to individual business units, project sponsors knew exactly where to go for data and analysis. Now, as enterprise-wide initiatives increased cross-functional collaboration, business leaders needed an equally direct way to engage multiple analytic areas at once.
The client was becoming a robust ecosystem of shared resources and collaboration. For Data and Analytics to fully support enterprise growth, it was time to unify, streamline, and optimize.
Lumevity worked with the client’s analytics leaders to develop a new operating model that:
- Restructured previously discrete functions into a blend of enterprise-led teams (that set standards and performed high-level analyses) and business-led teams (that set priorities and performed function-specific analyses)
- Established a shared library of standardized analytic tools
- Simplified the customer journey with a single contact entry point and several self-service resources.
The reorganized model optimized data and analytics functions from every angle.
In terms of pure analytic output, Lumevity helped leaders evaluate their current software ecosystem, eliminate duplicative tools, and create a standardized library of shared analytic programs.
Now, with an entire toolset centrally housed in a universally accessible domain, analytic teams throughout the enterprise produce consistent and widely applicable insights.
For the data analysts, the federated model created an organized framework that clarified responsibilities, roles, and expectations. Further, the rich library of standardized assets freed them from creating duplicative tools or chasing data. Analysts can maximize their effectiveness at generating insights and optimizing analytical conclusions.
Lumevity also helped data analysts apply a product orientation mindset to their workflow. Before this project, data analysts provided one-off analyses to business leaders – now, with this new mindset, analysts approach their work as a continual analytic product that maintains a long-term customer relationship and adapts to the fluctuating needs of business units. To help enable this newly iterative process, Lumevity consultants introduced agile principles to analysts’ workflow. This allowed teams to accelerate outcomes while continually improving their customer-focused analytic output.
Finally, for the business units engaging analytical resources, the new operating model streamlined the customer journey with a single contact entry point and several self-service resources. With a well-publicized and transparent matrix of domain responsibility, business leaders know exactly where to go for each of their specific analytical needs. Even better – Lumevity enlisted leading analytics employees to help design and sustain the new data and analysis framework, which activated the business units in the change on day one.
This collaboration between Lumevity and the client highlights our commitment to transformation that supports specific business units’ needs and broader organizational strategy – at the same time.
By design, the federated framework and shared resource library facilitated cross-functional collaboration and enterprise-wide analytical pursuits. But at the same time, the blended model allowed individual business units to retain essential autonomy and decision rights.
One-off solutions only create one-off results. But integrated solutions – like this collaboration between Lumevity and analytics leaders – balance local need with organizational growth, driving both individual innovations and collective, enterprise-wide transformation.
More consistent and cross-functional
The shared resource library and federated domain framework has enabled more effective collaboration between business units.
The inclusive design process and streamlined customer journey has vastly improved the engagement model for analytics customers and stakeholders.
~$5.7M in value
Streamlining the operations model and eliminating duplicative tools unlocked ~$5.7M to re-invest in new analytic opportunities.