Blog Post

The Next Chapter of Enterprise Analytics for Payers Part 1: How Mature is your Enterprise Data Warehouse?

Share this post:

In the introduction to this 3-part blog series, we discussed how a new approach to enterprise analytics can help payers accelerate business value and transformation by leveraging proven, off-the-shelf methodologies. In part 1 of our series we explore enterprise data warehouse (EDW) maturity, and how payers can evaluate this asset against the following measurable characteristics of a mature EDW:

 There is only one
A data warehouse is an EDW if it holds all your information and makes it available for various stakeholders across your company. If there are other data warehouses in use for reporting that have overlapping subject matter or additional information not in or derived from the EDW, then analytics and reports may be generated that differ or compete with one another.
Maturity goal: A single EDW that holds all the business information necessary to support team members.

Latency and freshness
The timeliness of analytic data should meet the needs of your business operations. If your users need a daily report of patients who are being admitted or discharged from the hospital, a weekly refresh of your EDW will not meet the business expectation. Not all situations require real-time data latency, but nearly all situations require consistent and dependable data refreshes.
Maturity goal: An EDW with data refreshed on a frequency that aligns with your business operations.

Data mart strategy
Various project teams will need different views of the same data to answer specific business questions. Though it’s critical for the underlying data and definitions to be consistent, the questions that are asked by different stakeholder groups will vary. If your end users are building their own copies of your data to fit their needs, then your EDW maturity level may be low.
Maturity goal: An EDW that allows stakeholder groups to customize views, rather than making copies of your data.

Usability and training
Users should be able to navigate the domains of your EDW easily after training and online guidance. If more than 80 percent of new query and report needs are completed by users without a call for assistance or a support ticket, your EDW is considered mature.
Maturity goal: An easy-to-use EDW that enables users with basic training.

Governance and growth
Another aspect of EDW maturity is its ability to handle change and adapt accordingly. If project teams feel like it is too much work to create new domains or implement changes, your EDW strategy and solution may be at risk.
Maturity goal: An EDW that can scale as your business needs evolve.

Click here to read Part 2 of the blog series, which explores three types of data quality checks payers can implement to advance their data management practices and analytics initiatives.

More Value-Based Care Stories

Are you able to assess the impact of an employee health program when data is stored in multiple, diverse systems? Whirlpool did.

Written by Watson Health | Blog Post, Value-Based Care

Comprehensive analytics enabled Whirlpool to look at the outcomes of an employee health program from a number of angles and organize results to support decisions about the future of the program. ...read more


Four ways to help your employees find their best-fit benefit plan and potentially reduce out-of-pocket expenses

Written by Watson Health | Blog Post, Value-Based Care

As open enrollment periods are coming to an end, it may be a good time to evaluate how you can help your employees make better, more personalized decisions about their healthcare coverage to get the best-fit plans for their situations next year. ...read more


Leveraging Data and Analytics to Achieve MACRA Peer Performance Benchmarks

Written by Watson Health | Blog Post, Value-Based Care

IBM Watson Health’s Senior Program Director, Clinical Quality Research, Donna Daniel, PhD, explores the role that data and analytics will play in achieving MACRA peer performance benchmarks. ...read more