What’s the point of working with tons of data if nobody can understand it?
To avoid this scenario, Paige Leonnig, manager of client data analytics for Healthcare Management Administrators, regards tech expertise and communication skills as equally important traits for her team.
“It’s crucial for our team to be able to have the skill to communicate complicated data analysis in a concise, easy-to-understand way,” Leonnig said.
But the lines of communication don’t end there. In fact, clearly conveying information has been a guiding principle in how Leonnig scaled her team, ensuring seasoned and new employees alike remain aligned and working in unison. That means comprehensive documentation of processes, open lines of dialogue between team members and utilizing tools like PowerBI to keep data insights readable.
To see how this emphasis on clarity has helped HMA’s data team stay aligned — even through periods of growth and remote work — Built In Seattle connected with Leonnig. She filled us in on how her best practices have brought success and collaboration to her team, and how other data leaders can follow suit.
Healthcare Management Administrators uses a data-driven approach to provide employers affordable, comprehensive healthcare plans.
When it comes to scaling your data team, what are the most important decisions to make around personnel?
When building an analytics team, it’s vital to scope out candidates that are eager to learn, develop new skills and work directly with clients.
What makes my team unique is the fact that we are data analysts and also client-facing. It’s crucial for our team to be able to have the skill to communicate complicated data analysis in a concise, easy-to-understand way. I’ve also found that if a candidate has a passion for healthcare, they will be driven to go the extra mile to develop insights that positively impact our members’ healthcare experiences!
What steps have you taken to make sure your tools, systems, processes and workflows are scaleable?
Throughout my career, I have had the opportunity to take part in the evolution of our analytical reporting abilities. The majority of this work has been in automating tasks when possible, which has allowed the team to focus on more detailed analysis and case studies.
There has also been a huge effort to visualize our data in a clean, eloquent way by using PowerBI instead of a spreadsheet. This has had a profound impact on us being able to use our data to tell a story through interesting graphs and data points. Lastly, we have focused on documenting workflows and processes to make sure that, moving forward, the protocol for a given task is clear. This includes developing a formal process for documenting KPIs to ensure we are able to correctly assess workload, accuracy, turnaround time and volume of reporting requests.
What’s the most important lesson you’ve learned as you’ve scaled your data team?
The most important lesson I have learned is to foster a team culture where nobody is hesitant to ask questions. To better encourage this, I set time aside to meet with my team on a daily basis for a quick huddle. This time is beneficial for the team to communicate tasks and find potential collaborations.
As a leader, I get asked questions daily about projects, reporting requirements and more. I have found it helpful to ask these questions back to the team to see if anyone has input or suggestions on how they would approach it. This has opened opportunities for collaboration and involvement, and we often come up with innovative ideas and tools during the process.
