Early in my career in analytics, I had a team that had built many fantastic tools. They would set up models, reports, and reviews with the business. Every tool or process did a great job showcasing the capabilities we had with our data. But we were missing something. Teams didn’t fully grasp the concepts behind reading and understanding data. We would complete one analysis, only to repeat the information to executives with an incorrect interpretation. We would have misunderstandings on reports when leaders tried to create their curated versions, and they would break simple logical rules. The problem was that we were giving people tools, but we weren’t making them data literate. We determined that without more people who understood data, we were never going to achieve any success at self-service BI/analytics.
We set out thinking about how we could develop programs and engagement models to help people grow and build data literacy. We had a moderate data literate executive team, very focused on defensive data needs (auditing, risk, financials, etc.), but the middle management and staff were struggling. Fortunately, communication is easy, and you have to have everyone on the same page, talk and listen to the right amount, document everything in a way that everyone can understand, etc. Super easy (note the sarcasm). We set out to develop a training program, and we selected individuals from all around the organization that had the “gift.” Maybe it wasn’t a gift, but they had some training and had a good foundation for us to begin to build. These individuals were to become our influencers. We infected them with our thinking, gave them access to the data programs’ architects and directors, taught them the basics of SQL, and made them a part of the team. We started creating a culture with this group that could help other groups. At the time, I had two incredible leaders, Jamie Hines (Eavey) and Nathan Maxfield, committed to building and growing this practice. There’s still more work to do as if you don’t maintain a literacy program, the data literacy decays. Self-service started moving forward after that, incremental but a good step.
While thinking about this article, it got me thinking about the challenges of digital transformation and the need for data-driven culture to steer decisions in efforts. One of the key drivers to enabling that data-driven culture is data literacy. Gartner defines data literacy as “the ability to read, write and communicate data in context, including an understanding of data sources and constructs, analytical methods and techniques applied, and the ability to describe the use case, application and resulting value.” I define it as a way to communicate effectively with data.
A few things to note about a data literacy program:
Programs like data literacy have to be part of your data governance strategy that’s putting the guardrails in place. Guardrails create the ability to move quickly and experiment and learn within the bounds of the program. If you have a data governance program that lacks data literacy strategies, it’s likely missing a guardrail to make the program successful.
Data literacy starts at the top. If you are developing a data governance program, part of its core job is to inform the executive team so they can support data literacy efforts around the organization. It’s critical to have data thinking be part of the top of the house before trying to rally it in other business areas.
You will not attain any amount of reasonable self-service without a data literacy approach.
Hopefully, this is helpful. I had a data interpretation experience yesterday that had me thinking about this all day!