Why Data Literacy is the Prerequisite for Data-Driven Cultures
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As a subscriber you can listen to articles at work, in the car, or while you work out. Subscribe NowData-driven decision-making is good for business. It’s been proven that the organizations that rely on data to inform decision-making grow faster and are more profitable than those that don’t. But what many business leaders don’t realize is before an organization can become data-driven, it must first become data-literate.
Data is something most knowledge workers have encountered in their careers regardless of role. This, combined with the amount of information we’ve had to make sense of in the Covid-19 era, underscores the importance of being able to thoughtfully filter and assess data to draw conclusions. But data literacy is in short supply, as Gartner predicts that 50 percent of organizations lack sufficient data literacy skills to achieve business value.
Before an organization can be data-driven, it must first become data-literate. Data literacy can be defined as “the ability to evaluate, work with, communicate and apply data.” Here are four distinct hallmarks of a data-literate culture.
Curiosity. In data-literate cultures, questions are not just encouraged, they’re expected. Curiosity, or perhaps more specifically, the desire to understand something from every angle, is an essential component of data literacy. There are a few key questions people should always ask when evaluating any kind of information:
- What is the problem?
- What is the opportunity?
- What is the source?
- Is the source objective?
- Why is it captured?
- Who are the consumers?
- Who needs this data?
- What is the timing and context?
Skepticism (but not cynicism). Being data-literate means understanding where information comes from, why it is collected and how it’s used to drive the business. People employed at organizations with data-literate cultures know not to make decisions based on assumptions alone. They are experts at “poking” and “prodding” in an effort to see if their own interpretations hold up under scrutiny. Data availability does not equal accuracy, so data-literate cultures are quick to investigate and consistent in decision making.
Storytelling. Data literacy not only involves being able to evaluate and work with data, but also communicating and applying data. And, while it may seem counter-intuitive, communicating data effectively requires strong storytelling skills. Good storytelling requires empathy to communicate in a way that is compelling and promotes understanding. Additionally, unlike communicating a singular piece of factual information, data storytelling requires the storyteller provide context to “set the scene.”
Excellent change management. Application is a critical aspect of data literacy, which often means using data to inform and track organizational changes. Data literate cultures can only thrive when change is embraced with open arms, and then expertly managed to create as little friction as possible throughout the process.
Achieving organizational data literacy won’t happen overnight, but don’t be discouraged. Any change worth making takes time and intentionality. Building a data-driven organization starts with taking a single step toward creating a data-literate culture.