These days, decisions cannot be based on intuition and experience alone. Instead, data shows the way and makes the difference between success and stagnation. So what do all employees need? That’s easy, data literacy! We'll show you what's behind the term data literacy, why everyone really needs it and how you can improve this skill (in your company)!
Compact Overview: What Is Data Literacy?
Data literacy (or data competence) is the ability to collect data of a required quality, to process and critically analyze it and to present the information it contains in the right context.
Generally speaking, data literacy ensures the confident handling and correct understanding of data sets.
The challenge is not only to collect and present numbers, but also to understand them and derive meaningful information that can be used to take measurable actions.
Data literacy therefore encompasses various areas of expertise, including:
- Collection or compilation of reliable (raw) data
- Critical evaluation of data quality and sources
- Preparation of raw data into valid data sets
- Correctly interpreting, reading and understanding data
- Use of tools for data analysis and visualization
- Awareness of the ethical handling of data
- Consideration of data protection aspects
- Preparation and presentation of results
- Deriving and implementing sensible measures
- Recognizing trends on the basis of ongoing developments
Data Literacy in the Company: Who Needs to Know How to Handle Data?
Customer trends in sales, website and usage numbers in marketing, company KPIs at the C-level – working with data is no longer just an IT issue. Today, every department works with it.
Even if there are different areas of expertise, specialist areas, roles and positions within companies, all jobs have one thing in common: the increasing importance of number-driven processes.
So when asking who (whether today or in the future) should know how to process and apply data, the answer is:
All employees in a company should be data literate.
If you want to highlight one group, data literacy is particularly important at leadership level. As one of several leadership skills, it supports results-oriented action and entrepreneurial thinking.
Depending on the department, data-based work still varies to a greater or lesser extent in most companies. However, this is likely to change over the next few years: Sooner rather than later, most job profiles will require and assume competent handling of data.
Why Data Literacy Is So Important – Both for Today and Tomorrow
In a world increasingly driven by data, data literacy is crucial for making informed decisions and actively participating in shaping our digital future.
Among other aspects, data literacy enables us to:
- Optimize business processes more efficiently
- Better understand customer needs and
- Make well-founded strategic decisions
According to the Masterplan Study 2024 "Upskilling for the Future", almost two thirds (62.1%) of the HR and L&D experts surveyed consider digital skills to be a necessary skill for the future. An essential part of this is data literacy.
The relevance of data literacy across all company levels is also reflected in the results of other surveys:
- 85% of managers believe that data literacy will be just as important in the future as the ability to operate a computer is today.
- 70% of managers expect their employees to have basic data literacy.
- 94% of people who already use data in their position believe that data helps to improve their work – 82% even feel that their data literacy gives them more credibility in the workplace.
6 Data Literacy Basics: What Everyone Should Know
Data literacy is important and affects us all. But what does it look like in detail? What skills are required and what needs to be taken into account?
Here are six basic data literacy aspects:
1. Methods of Data Collection: Precision and Care
The way in which data is collected has a considerable influence on its quality and informative value. Methodical and careful data collection is therefore greatly important.
This includes selecting the right data collection method (e.g. survey or observation), assessing the quality of the data, formulating clear and unbiased questions and accounting for the ethical aspects of data collection.
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2. Analysis: Between Accuracy and Misinterpretation
An objective and critical approach to data analysis helps to avoid the pitfalls of data collection and arrive at well-founded conclusions.
It is important to filter out the relevant data from the mass of information, interpret it correctly and create conflusive findings.
Here, both the analytical tools and the ability to understand contexts and test hypotheses play a significant role.
3. The Subtleties of Data Interpretation: Correlation vs. Causality
A central concept of data literacy is the distinction between correlation and causality.
Correlation means that two variables are related, but this does not mean that one necessarily causes the other. Causality means that one variable causes the development of another variable.
People repeatedly fall into this trap when interpreting data. Understanding this difference is crucial in order to avoid false conclusions and interpret data correctly.
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4. Data Ethics: Responsibility and Transparency
In an age where data is omnipresent, ethical considerations in dealing with data are essential.
Data protection, data security and responsibility in dealing with sensitive information are topics that cannot be ignored in the context of data literacy.
5. Visualization: The Art of Letting Data Speak
Well-designed visualizations transform complex data sets into comprehensible and appealing graphics. They are a crucial tool for making insights accessible and facilitating communication.
But not every visualization is helpful. Misleading axis scaling, unsuitable chart types or an overload of information can make interpretation difficult. For example, 3D representations of pie charts may be visually appealing, but they distort the actual distribution of the individual components.
6. Technology: Tools and Trends
The rapid development of technology has revolutionized the way we handle data.
From advanced analytics tools to artificial intelligence and machine learning, technology provides us with powerful tools to capture, analyze and visualize data. Knowing and using these tools are important aspects of data literacy.
3 Tips: How to Train Data Literacy (In the Company)
The world of data is dynamic and constantly changing. The development of data literacy is therefore a continuous process that requires curiosity, critical thinking and a willingness to continously and actively learn.
Here are three basic tips for developing your own data literacy in everyday life:
- First of all, remain skeptical:
If you think you see a causal relationship, consider why that might be. If you can't state a plausible theory behind the causal relationship, be skeptical of your conclusion! - Ask critical (follow-up) questions:
Getting into the habit of critically questioning data can help you develop a more informed view and draw better conclusions. Always remember: A visible correlation does not equal direct causality! - Also ask obvious questions:
Curiosity with a healthy dose of common sense can get you pretty far. Instead of blindly accepting assertions, ask questions: How do you know that? Who did you ask? How did you phrase the question?
Nevertheless, these three measures alone will not turn anyone into a data literacy professional. Lifelong learning is essential and data literacy is multi-layered.
Skills in dealing with data are and will be increasingly in demand, especially in the working environment. In order to keep up with the latest developments and the competition, companies in particular should therefore continuously expand their employees' data literacy skills and include them in their corporate learning program.
Data Literacy Training in the Company: The Best With Masterplan
Data literacy is a component of the skills that all employees will need in the future and that companies should proactively develop in their employees – we call these Power Skills.
These include skills in the areas of leadership and collaboration, emotional intelligence and communication.
You can find out which power skills are also important for the future and how companies can develop them efficiently in this blog article!
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Stefan Schulze
