It's no longer optional. All leaders need to be data literate.
CFW Spotlight on Mitchel Roling CEO & Founder of My Dataist
We met Mitchel Roling through our extended recruiting engagement with eMarketer (now Insider Intelligence) and saw the significant contributions Mitchel made to that fast-scaling organization through his data fluency. Mitchel gained skills and experience that he was ultimately able to build into his own consultancy, My Dataist. Today he’s advising a host of clients around their data needs— and, of course, he’s our trusted go-to for anything data-related. With the power of data and analytics top of mind, we thought it timely to have Mitchel weigh in on the topic.
I'll never forget the first time I traveled to a foreign country. It was a high school trip to Europe, and we had just landed in Germany. I suddenly found myself surrounded by an airport full of people speaking a language I couldn't understand. It was disorientating for this high schooler from a rural Minnesota farm. However, I quickly learned how far you can get with some basics. While I wouldn't be mistaken for a local, I learned I could communicate my essential needs with a few critical words: please, thank you, bathroom, water, bratwurst.
This experience is similar to working with data for the first time. It can feel like you've been dropped into a foreign country where everyone else seems to possess some secret knowledge you don't have. But as with learning a language, becoming data literate takes time and is most effective when you learn one thing at a time and practice daily.
Over a decade ago, I transitioned into a data analyst role when our CEO acknowledged the pressing need for our organization to become more data-driven. Back then, most of our organization's leaders had minimal access to data, and it was my responsibility to change that.
My initial challenge was to present our organization's KPIs to the executive team using a simple, easy-to-understand format. I created a spreadsheet that I would update and email monthly. Although the spreadsheet appeared to be a huge success initially, it wasn't long before I received feedback like, "This is great, but now what do I do with it?" This was when I realized that merely providing access to data was only part of the challenge; leaders also needed help interpreting it.
To address this issue, I complimented my monthly metrics spreadsheets with a companion write-up summarizing key metric shifts relevant to the team. While my write-ups were not perfect (I was new in the role, after all), my analysis improved with time, and the team gradually became more comfortable handling data independently.
Soon, team members started to respond with their own counter-analyses. Far from being antagonistic, these exchanges typically led to productive discussions where we would both delve deeper into the data. Ultimately, we usually emerged with a better understanding of the business and better analysis.
As we evolved from spreadsheets to real-time dashboards, I shifted from manually creating monthly spreadsheets to automating reporting and conducting in-depth investigations of more complex questions. By this point, the teams had become familiar with key metrics, and many team members could identify high-level trends independently. In essence, they were developing data literacy and needed less hand-holding.
Fast forward to today, it's rare to find a senior leader without access to at least one dashboard, and they are seldom handed a pre-packaged analysis of their team's KPIs each month. Instead, they are expected to be able to do this work themselves, at least at a high level. My experience building out a data role within an organization for the first time made me realize that access to data isn't enough. Knowing how to use and act on data is arguably more important.
To become data literate, it's vital to incorporate data into your daily professional life and continuously expand your skill set. Here are five practical strategies to help you begin:
Start with spreadsheets: Spreadsheets are user-friendly mini-databases that don't require advanced technical expertise. Use them to track productivity, monitor marketing campaigns, or any other aspect of your work that can be assigned a number. Start small by using simple SUM functions, and only experiment with more advanced techniques as you gain confidence.
Utilize internal tools: The software you use for your job likely collects data, so you might as well use it! See if your internal applications have reporting or dashboard capabilities. If so, try building out some basic KPI reports. As always, start small and high-level. Don't make too many granular reports right off the bat.
Partner with colleagues: I mentioned that exchanges with the exec team helped everyone understand our data better and led to improved analysis. Seek input from your peers to poke holes in your conclusions. It will only make your work better.
Maintain objectivity: A common pitfall for those new to data analysis is cherry-picking metrics that support their initiatives. Strive to remain objective by considering all relevant factors. Don't end your analysis just because you found something that proves your point. Search for data proving the opposite and then work to understand why. Play your own devil's advocate or find someone who can help. It's harder to see past your own biases than it seems.
Continuously learn: Add new skills one at a time. Seek out new tips or techniques (YouTube and blogs have a wealth of free knowledge). Bring these new learnings back to your role and reinforce them daily.
Remember, pursuing data literacy is a continuous process. With dedication and persistence, you'll be better equipped to navigate the complexities of today's data-rich environment. This will not only enhance your performance as an individual but will also contribute significantly to the overall success of your organization. Moving forward, this skill is no longer optional.
Mitchel Roling is CEO & Founder of My Dataist, a consultancy focused on using data to enable senior leadership to make better and more informed decisions