“I am not a data person”
Throughout my career, I have heard "I am not a data person" hundreds of times. I want to break that down and reorient that perspective to show you exactly how you ARE a data person.
So let's explore the various reasons I think people think they are not a "data person":
Data is math and I don't like math. Okay, so first of all, math is not that bad. But I get it if math was not your favorite subject in school. Data and math share one really fundamental thing - numbers. You are constantly processing how numbers impact your life - how much do I owe so and so, how many bagels do I need to take to the office today, if every kid in my child's class eats a 1 x 1 slice of cake and there are 30 children in the classroom, how big should the cake be….etc. Silly examples, but they demonstrate that your brain is working with numbers all the time. Data is even more relevant to you because it is the application of math in a real world environment.
And let's not forget about all of the cultural norms and stereotypes about who is and who is not good at math. These are rubbish and contribute to keeping people out of math and science fields. Maybe you got caught up in this and have hung onto a "not good at math" belief for a long time. Time to let that go, y'all.
2. Data can be manipulated, so I rely on my gut instead. Mmkay. Well, the first part of this sentence is true. Data can be used to try mislead people. So can words, or videos. However, "good" data is often accompanied by transparency about how it was assembled and what are its limitations. For example, if you visit the US Census website, you can read yourself silly with their methods and data dictionaries. Working with data is skill-intensive and time-intensive and for most organizations there isn't an incentive to intentionally mess with the data. So calm down and realize that most people are not trying to mislead you.
It is important to acknowledge that data has been used extensively to create false claims for the oppression of various peoples throughout history. A healthy skepticism is needed to insure equity and transparency in data. So lean in MORE to being a data person, not less: understand where the data comes from, how it is collected, who is in charge of analyzing it…etc. Not all data sources have good intentions because not all people do. But you can help by understanding enough about data to identify its strengths and its faults.
PS… that "gut instinct"? Might have a few biases of its own.
3. I have employees that do data for me: Well, good for you. Do you know what they're working on? Does it align with the organization's needs? Are their insights useful to you? Everyone has a role to play in data. Executive leadership should request data prior to making big decisions. Middle management translates leadership's questions about operations into data questions. Analysts are responsible for finding the data and creating meaningful data narratives. All others in an organization are likely involved as data collectors, implementors and/or observers. Everyone should be attuned to data, not just people with the title "analyst".
If you're not doing the data work but you're also not contributing to it (by asking for analysis, trying to understand it and asking clarifying questions, playing devil's advocate, integrating it with other information, etc.), then it's not as good as it could be. Data is more valuable to the organization when more of the organization is involved with the data.
So to sum it up (see, math!), if you say you are not a data person, I say that's a choice and you can and should be. You may be intimidated or feel out of your element. Maybe someone told you long ago that math wasn't for you. But there is a 100% chance that you can use data for better information on both a personal and professional basis. Where to start? Look at your company's KPIs or annual report or an article or chart on Twitter or even the percent chance it will rain today. Lean in to understand where the data is coming from and what it's saying. Get curious and start asking questions. Turns out, you are a data person after all.