Be Data Literate: The Data Literacy Skills Everyone Needs to Succeed

t, data literacy has become as important as traditional literacy. It equips individuals to make informed decisions by enhancing their ability to read, work with, analyze, and communicate data. Jordan Morrow, often referred to as the "Godfather of Data Literacy," emphasized that everyone possesses some level of data literacy. However, the goal is to cultivate confidence and comfort in utilizing data more effectively. "We want to empower people with more confidence and comfort using data more," Morrow notes. This empowerment is particularly vital as data becomes increasingly central to both professional and personal decision-making.

Moving Beyond Descriptive Analytics

Many organizations remain fixated on the first level of analytics, known as descriptive analytics, which involves merely observing and reporting what is happening. Morrow uses a medical analogy to illustrate this point: "Imagine that you're sick, and the doctor tells you you're sick but doesn't offer a diagnosis or treatment." This represents descriptive analytics. The real value lies in progressing to diagnostic (why it's happening), predictive (what might happen), and prescriptive analytics (what should be done). However, Morrow argues that diagnostic analytics, which is vital for understanding the underlying causes of data trends, is often the most neglected stage. This neglect hinders the ability to make informed predictions and decisions.

Leadership and Cultural Buy-In

The success of data literacy programs heavily depends on leadership and cultural support. Morrow points out that "the number one roadblock to data and analytics success is culture." Executive leadership must genuinely support the initiative, making it a priority and allocating time for employees to engage with data literacy training. Middle management plays a vital role in implementing and managing these programs, ensuring that team members have the opportunity to develop their skills. Morrow warns against viewing tools as a substitute for a comprehensive data literacy strategy, emphasizing that "a tool is not a data literacy program."

Integrating Data Literacy in Education

Morrow advocates for the integration of data literacy into educational curriculums, suggesting that it should begin at an early age. By encouraging a natural curiosity and teaching children to ask questions and seek data-driven answers, we can build a more data-literate society. This approach can help maintain the innate curiosity children possess, which is often stifled by corporate environments in adulthood. He suggests that data literacy education should not necessarily be a standalone course but should be woven into existing curriculums to teach critical thinking and problem-solving skills.