Data Governance is more than centralized data access, metadata management, and governance.  It is taking these high-level concepts and embedding it in everyday processes.  Embedding these concepts into our day-to-day checklists enables us to achieve the goal of developing a coordinated, efficient information infrastructure with accountability.

As Prominence works with their customers on analytics projects, we take the principals of quality, access, literacy, content, master data, security and metric management –  and infuse them into the application creation process.

We engaged with a health plan as they developed their analytics framework to move towards data-driven decision making.  They were being bombarded with one-off requests for data about utilization, case management, and readmissions data and were spending a lot of time answering the question they were being asked. They recently purchased Tableau and wanted to quickly jump-start their analytics team into application development based on best practices.

Task

Prominence was engaged to guide an organization as they built up their team. They were interested in following best practices and having an experienced team there to guide them along their path.

Action

You can see that in:

Ownership

• Clearly defined sponsors, SMEs and project team roles before the project started
• Roles and responsibilities shared before people agreed to take the position
• Each data element and metric assigned ownership and definitions had to be approved by both operational and technical SMEs
• Communication lines established across teams and across operations and IT

Goal-Setting

• Application goals discussed and agreed upon by the team as the first step in the process
• ROI discussed from the beginning and metrics and scenarios were flagged for monitoring
• Checkpoints set to review the ROI flagged metrics at 30, 60 and 90 days post live to identify a message of value to share with the rest of the organization

Architecture

• Transformations stored as close to the source of truth as possible to aid in reuse instead of duplication
• Calculations for metrics pushed out of the UI and into the transformation layer to aid in reuse across workbooks

Visualization and Design

• A UI template created and used for future projects to aid in quick consumption and navigation
• Visualizations designed to support the goals of the application, following the MAD design principal of providing aggregate data to Monitor, pointed information to Analyze and Detailed information on which to act

Data Quality

• Validating data quality and integrity was core to the validation phase of the install
• Expectations set concerning time commitments, scenarios across time and dimensions established, expected vs. actual results diligently tracked

Result

As a result of the engagement, the health plan’s analytic team is now running with the application development process and tools on their next application independent of the Prominence team.

At the application launch meeting the project sponsor, the Director of Medical Economics, said ‘I love the dashboard, the look and feel, the access to information, the ability to interact with it. I love what you have done and am excited to see what else you do!  We don’t have anything else like this to help put together such a strategic plan before diving into details and making it relevant.’