Data Literacy

What is data literacy?

Data literacy describes the ability to handle data competently. It encompasses various individual competencies in order to record, adapt, change, interpret and present data. Data competence is the basis and important skill of digitization.

Data literacy skills include the following abilities: 

Knowing what data is appropriate to use for a particular purpose.

Interpreting data visualizations, such as graphs and charts.

Thinking critically about information yielded by data analysis.

Understanding data analytics tools and methods and when and where to use them.

Recognizing when data is being misrepresented or used misleadingly.

Communicating information about data to people lacking data literacy, an ability sometimes referred to as data storytelling.

Why is data literacy important?

80% of organizations initiate deliberate competency development in the field of data literacy to overcome extreme deficiencies. 50% of organizations lack sufficient AI and data literacy skills to achieve business value.

The increasing volume and variety of data that businesses are flooded with on a daily basis require employees to employ higher-order skills such as critical thinking, problem-solving, computational, and analytical thinking using data. And as organizations become more data-driven, poor data literacy will become an inhibitor to growth. In fact, in their survey “The Human Impact of Data Literacy”, Accenture found that: 

75% of employees are uncomfortable when working with data.

1/3 of employees have taken a sick day from work due to headaches working with data.

A lack of data literacy costs employers 5 days of productivity translating to billions of dollars in lost productivity per employee each year.

Data uplifts the success of organizations in creating both physical and digital business opportunities—improving accuracy, increasing efficiency, and augmenting the ability of the workforce to deliver greater value. It is therefore important and essential to be able to interpret, analyze and communicate findings on data to be able to uncover the secrets to a successful business and competitive advantage. 

Many people are also seeking to visualize and communicate about data (including in infographics), and data literacy is critical to do this well. When you understand well what the data is saying, you are better prepared to highlight key takeaways for your audience.

Are data literacy skills hard to build?

If it’s so important, then why is it lacking in the workplace?

A major reason is that leaders may not have these skills themselves. The fact that data-literate employees are typically isolated on IT or BI teams also doesn’t help colleagues share and spread this know-how.

Sure, some people haven’t yet recovered from that awful math class in high school. They may think that they are simply bad at math.

Others may be ok or even good at math, but don’t want any mistakes they make to lead to potentially hugely detrimental consequences, including a loss of reputation.

All these challenges are understandable, and they can be overcome. Many data-savvy folks struggle to keep it basic for beginners, so my goal is to help you slowly grasp some basics to gain some skills and more confidence.

Tips on how to become data literate

***UNDERSTAND***

In order to start working with data, you need to be able to understand the data. Data is usually presented in various forms within an organization, such as a bar chart, pie chart, table, or pivot. A user should be able to understand what is presented in the graph. What does the data tell us? Which insights can be derived from it? What is the impact on business processes? It also requires critical thinking about the presented data

***ENGAGE***

To engage with the data, people need to use data and know what is available within the dataset. This includes knowing how the data is composed; understanding the type of data; where it originates from and who is using it. Answering these questions will help understand the data and its context. The first step is to look at the data definitions or define them when not available. Using data definitions, you can establish the type of data fields and the expected values.

***ANALYZE***

Inevitably, the skillset to analyze a dataset is an important step in becoming more data-literate. Understanding data and being able to engage with data helps in starting discussions and shifting from creating information to creating insights and ultimately concrete business actions. These insights can only be generated by analyzing the data. Being able to use statistical and analytical methodologies to create valuable insights will become a skill that is necessary for more and more (business) roles within an organization.

***REASON***

One of the most important (My preferred one hahaha) and complex, aspects of data literacy is the ability to reason with data. Understanding and analyzing data is important, but if you cannot talk the language of data or reason with data in a proper way, misalignment or misunderstanding will take place. Communicating with data can be done verbally but also by showing visualizations. The power of a good visualization is often underestimated, especially because a chart can perfectly support your story or emphasize the point you’re trying to make. Telling the right story and guiding your audience through the steps you have followed within an analysis will clarify your results and create a starting point to discuss the impact of the results. When doing this, always consider the level of data literacy of your audience, to ensure you send a clear message that can be understood by everyone.

"If you want to talk more about this topic, I invite you to message me privately or just drop your thoughts or questions in the comment section. Thank you for reading."