How to run a successful analytics rollout

Healthcare executives across the industry are citing value-based care and health equity as two of their top priorities in 2024. To execute successfully on these goals, health plans and care providers must be prepared with interconnected data and powerful analytics capabilities. If you’re considering implementing a new or improved analytics platform in the new year, this blog post is for you. Explore three key objectives and accompanying strategies to make sure your analytics rollout is as straightforward and seamless as possible.

Objective #1: Make a good first impression

  • Strategy: Be proactive in sharing information about the new or improved analytics capabilities that are being introduced—including what value is anticipated for each team or role, the timeline you’re working with, and what the organization hopes to gain from this investment.
  • Strategy: Work closely with potential users to get an understanding of their roles, the tasks they are performing, and the questions they are asking. Consider developing role-based best practices for data utilization.
  • Strategy: Build a resource hub that includes tips for getting started, how-to guides for reporting, site maps to different types of data, and anything else that would be relevant or meaningful to your user base.

Objective #2: Keep engagement high

  • Strategy: Establish experienced or super users who can act as advisors to newer users. The options here are vast; you could hold regular collaboration hours, scheduled teaching sessions, an asynchronous Q&A channel, or another mode of interaction that works for your organization.
  • Strategy: Provide opportunities for advancement and additional training. Some users will be satisfied using basic analytics to accomplish their daily tasks. Others, however, may be interested in developing their skillset further and digging deeper into the data. Ensure these interests are noticed and attended to! This keeps engagement high AND ensures a greater ROI from your analytics platform.
  • Strategy: Proactively solicit feedback from users and managers on both the platform and the rollout progress. Are they satisfied with the resources available? What features might they need to perform their roles more effectively?

Objective #3: Achieve sustainability

  • Strategy: After the initial implementation is complete, stay on top of the numbers! Assess user behaviors and utilization statistics to understand what features are most used, who is getting the most from the platform, and what important capabilities might be underutilized.
  • Strategy: Keep a strong relationship with your platform vendor (perhaps MedeAnalytics?) to stay informed on important software updates, take advantage of technology enhancements, troubleshoot user challenges, learn best practices, and explore opportunities to gain greater ROI.
  • Strategy: Conduct a regular review of your tech stack to ensure you’re running on the best combination of tools and resources. Along with general performance metrics, assess technology for alignment with organizational goals. Is your analytics platform getting you closer to reaching key metrics? Are your technologies working together or operating in siloes? Are you considering how to incorporate emerging technologies like AI-assisted analytics capabilities into your analytics solution?

Have other objectives for your analytics rollout that we didn’t cover here? Our team of industry and topic experts would love to understand what you’re shooting for and how we can help you get there with focused collaboration and best-in-class tools. Start the conversation.

Mike Doeff

Mike Doeff is senior director of Product Management for the MedeWorks platform at MedeAnalytics. He's led this team for over 10 years and prior to this role, Mike built data driven applications at enterprise SaaS companies. In his role on the MedeWorks team, Mike has played an instrumental role in advancing MedeAnalytics from retrospective reporting to the current focus on actionable insights. Mike is dedicated to developing systems that not only possess robust capabilities but also maintain simplicity and ease of use. He believes that the key to impactful analytics lies in user interfaces that are both intuitive and powerful.

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