A Data Competence Journey

Do you find yourself working more and more with data and exploring ways to maximize its value? I do and for me it was quite the journey.

I was looking to introduce new features and tools for the business to use. We needed to increase scalability, improve data quality and communicate these technologies. Yet, it was not just about knowing how to read charts and count widgets. Understanding what the data was telling us became key to articulating this. Including even using it to argue with others.

Arguing with data is exactly what we should be able to do. Focusing on data helps remove the emotions associated with feeling attacked. We become less defensive and make fewer decisions based on gut feelings. I like to describe arguing with data as a process of level setting. We are working together to come to come to the same conclusion.

For example, my wife and I had gone to the dentist for regular cleaning. We were charged different amounts for the same procedure. Instead of getting emotional and becoming irate, I asked if we could look at it together. Now we were on the same team trying to find out the truth about the data and come to a consensus. We agreed to reclassify the process under a different code, and everything was fine.

When we left, the staff stopped me and thanked me for the process we had gone through. You see, it is common for people to get upset with their bill and yell at them. They have a gut reaction it is wrong or too much without choosing to look at the data to figure it out.

There are many processes involving strategies and migrations from the old to the new. There are budgets and resource considerations.  This was a whole new kind of data to understand. Getting the data right would be a challenge without understanding the complete process. Data is at the center of the technology, the people and the processes, so it all must come together.

I had started hearing about information as a second language. I began connecting with people who were creating data driven cultures. It made sense to me now more than ever that I need to start with good data.

So, I looked at preparing data and transforming it to good logic. How do we handle blanks or mismatches and then governance? Who has access, permissions, and what does it mean when I read an access report vs. an entitlements report? Then of course having data in the right place, integrations, feeds, and frequency of when we need it, and so on. Finally, we need the insights from our data and that is where the visualizations come in. Charts, graphs, trend analysis and understanding these becomes particularly important. Data Literacy was not about being able to read a bar or pie chart but understanding if 12% good or bad. Do we want it to go up or down, why is it 12% and do we think it should be something else or is something missing? At the foundation of all these steps was data literacy.

You can improve your business and technical knowledge by reading and understanding, writing and communicating and, of course, arguing and gaining confidence in your understanding of data. To become an expert, you need to base your steps on your data competence, not on the data itself. So, at this point it seemed obvious to me I was becoming that expert!

Having good data means that you can measure your business process. You can take action, show performance, and achieve results. Using data to achieve desired outcomes means having good, clean data. But if I did not know what the desired outcomes were, how did I know what data I needed?  I started to think I was wrong and was not the expert I thought I was

Instead of going up from a data strategy to vision, I needed to start with the vision of we wanted to achieve.  From there I could proceed from the vision down to the data strategy. I started asking the “5 whys” figuring out what would tell us we achieved the desired outcomes or not. Then I would know what kind of metrics would be needed and where would I get the data from in a good, ready state. Ultimately, I had come to realize, data and analytics enable everything we do.

Think about this . . .  data guides every action we take.

It can be as simple as reading the gas gauge on your car. You know if it is near E you need to go get gas. Some of us understand our car data well enough to know we can go 1.6 miles further while it flashes red, get gas, get gas!

We adapt our processes and look at our outcomes. Every decision we make is based on data and we work to understand that data. We look at the data, make informed decisions to create the desired outcome. Data with its outcomes and analytics contributes to the bottom line. We use data to make leadership decisions. We impact our culture and people. We make investment decision. All based on data we think we understand.

So, I have learned that first, no one is illiterate when it comes to data. We all know something about data in our lives or at work. Some we are more familiar with than other. Second, it is not about becoming an expert or a professor of data literacy. Instead it is about using our understanding of data to be curious.

So, let us not think of ourselves as experts, and start thinking of ourselves as explorers. Be curious!