During my 22 years working for the Wisconsin Department of Workforce Development I held roles from unemployment adjudicator and business analyst on a reengineering project to quality control and unemployment insurance law trainer. The final few years of my time there were transformative ones, because that’s when I started working with Tableau and became a data analyst. 

I learned the importance of a lot of things during my first career, and they all apply to data leadership, whether you work in government or private enterprise. 

  1. Cross-departmental learning is crucial. I used to work in an organization made up of very small working units focused on specific tasks. This can lead to hyper-focusing on one tool or one repeating set of deliverables. To excel, you must encourage conversation and partnerships from one department to another. This is true even if you have a lot of contractors onsite working beside your full-time employees. Sharing information with others is essential. It’s also the foundation of good data culture. 
  2. Consistent training creates a well-running organization. If managers receive information but have no understanding of how it was created or structured, they are unlikely to know if it’s accurate, can’t read metrics effectively, and can’t explain it to their staffs. Anyone who deals with data needs at least basic training to read and interpret it, and more advanced training to create visualizations using it. When I worked with managers on creating metric dashboards so they could understand staffing requirements, I made sure they knew how to drill down as far as they needed to get absolute specifics and verify that the data worked correctly. If you have the power to do so, pay for training or advocate for it, then encourage people to take advantage of it. It’s good for the people and the organization. 
  3. Collaborative practices and sharing information build a strong culture. Collaboration is part of the zeitgeist of some cultures, and not part of others. I first learned how to push for more opportunities to collaborate within my state bureaucracy, and it made the road easier later. You may be struggling with a single, important data set that is updated ten times by ten different contractors or departments without consistent data definitions. That’s a clear sign of a weak culture. Creating visualizations that senior leadership (in my case, the cabinet’s office up through the Governor’s office) could trust meant that I often had to insist on teamwork. 
  4. Engagement in data communities gives you a window on other worlds. I helped start a Tableau User Group within my state government division because I wanted to see how other groups were using it. User groups and communities are essential because you learn collaboration, even if there may be little evidence of it in your day-to-day job. 
  5. Securing executive sponsorship ensures projects happen. If you believe that you need executive sponsors in private enterprise, it’s doubly true in government. If a data culture or a particular initiative is considered superfluous at the top, it will not gain support or be funded. If it’s seen an essential to the department’s mission, it is likely to happen. 


Because I tried in my own roles to follow these best practices, I found that when I landed the top position as senior data analyst and business automation specialist in 2019, I wanted to give back. I became more vested, helping a lot of people out and leading several initiatives. If you build your data leadership on continuous learning, training, collaboration, sharing and senior-level engagement, I guarantee that you’ll start giving back as well. It makes work feel like a more sustainable and far more enjoyable experience.