In the digital age, data is king. Businesses generate vast volumes of data daily—including customer transactions, social media interactions, and website visits. And as our world has become digitized, the importance of data has become evident at the highest levels of corporations. To remain competitive in today's economy, businesses must analyze and use their data effectively. That's where data literacy comes in.
"Everybody needs data literacy because data is everywhere. It's the new currency. It's the language of the business. We need to be able to speak that."
But what is data literacy, exactly? And why should companies care about it? In this post, we'll answer these questions. We'll start by explaining what data literacy is, then dive into why it's so essential for modern enterprises, whether you're a startup or a global organization. We'll then discuss a few obstacles to data literacy and propose some first steps to overcoming those. By the end of this post, you'll understand just how critical data literacy skills are for your organization's ability to generate winning results.
What is Data Literacy?
Data literacy is a broad term used to describe skills needed for handling and analyzing data. Most definitions of data literacy include the ability to:
- Identify valuable sources of data
- Collect data
- Process and explore data
- Recognize the value of data
- Analyze and interpret data
- Communicate using data
- Convey the value of data to others
- Use data to inform decisions and strategies
Each of these data literacy skills represents a body of sub-skills. As with any language, the language of data has its own structure, vocabulary, and requirements for learning, practicing, and becoming fluent.
How Important is Data Literacy?
"In a world of more data, the companies with more data-literate people are the ones that are going to win."
Before 2002, Major League Baseball team the Oakland Athletics (A’s) struggled to attract top-tier talent with their limited budget for player salaries. In contrast, the New York Yankees — one of the top teams at the time — had over three times the A’s budget. This financial gap translated directly into the two teams’ performance. The Yankees could afford to sign superstar players who took them to the World Series multiple times. The A’s were left with the remaining underperforming talent who made it nearly impossible to progress past the playoffs.
Then in 2002, the Oakland Athletics had a record-setting season. And they achieved it with, you guessed it, data. That year the A’s manager, Billy Beane, adopted a recruitment approach that evaluated players based on two data points: their slugging percentage and their on-base percentage. Beane and his team analyzed the data of hundreds of baseball players to find those who fit the criteria. By looking at data traditionally overlooked by scouts, the A’s identified a pool of talented but undervalued players to field a team that could win while staying within the club’s budget.
As a result of this data-driven method, the 2000s was one of the most successful decades for the A’s that included a record 20-game winning streak. The moral of this story is that winning came down to the fact that the A’s had a data-literate manager who could gather player data, analyze it and use it to make decisions that drove wins.
If you want to defeat your competitors, you need data-literate leaders and a data-literate team. Numerous studies have proven that the top-performing companies, so-called “data leaders”, whose workforce and leadership understand and use data to their advantage, far outperform “data laggards.” One study found that data leaders achieve 81% more profit than data laggards. That’s winning using data.
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