Data literacy | Numeracy | How data-literate are you?
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Data literacy: the center of attention

Data literacy is a specialized form of (digital) literacy which is becoming increasingly important due to the rise of big data, machine learning, and artificial intelligence (AI).

Data literacy is an essential skill to develop for team leaders, employees, and managers who want to stay relevant. It enables you to ask critical questions about data and make better decisions, faster. However, experts estimate that only a third of all people can confidently and effectively work with data.

Literacy is more than just reading and writing

According to Wikipedia, literacy covers many aspects besides reading and writing. Literacy is the ability to work with, understand, and use information with a goal in mind. The term “literacy”, derived from Latin Littera (letter), involves knowledge of the spoken and written word, as well as the ability to transmit information through various media.

Three competencies for literacy

Essentially, literacy covers the following abilities:

  1. Using language to communicate and process information.
  2. The ability to work with numbers and visual information.
  3. Being able to use ICT.

Numeracy

Numeracy, according to wikipedia, is defined as the “ability to reason and to apply simple numerical concepts.” According to the Organization for Economic Co-operation and Development (OECD), one in four adults in developed countries achieves only the lowest level of numeracy possible. They might have difficulty interpreting numbers and graphs. Fear of mathematics is a serious issue. In a 2012 study, the OECD reported that about 30% of fifteen year-olds suffers from such a fear.

PIAAC: 5,000 respondents

In order to assess the level of knowledge and competency, the PIAAC (Program for the International Assessment of Adult Competencies) is performing large-scale international research. By testing 5,000 respondents, they aim to assess the level and use of skills of people between the ages of 16 to 65. PIAAC builds upon a tradition of measuring core skills. In 1994, the International Adult Literacy Survey was performed, and in 2007 the ALL, the Adult Literacy and Life Skills Survey, followed it up.

Data literacy infographic

Three core competencies for data literacy

The PIAAC was performed in 24 countries, and shows how competent people are at using language and numbers to solve problems in digital environments. These skills are called core competencies, because they’re essential to understanding, analyzing, and using information that we come across at work and in everyday life. This covers information in texts, images, or graphs, both online and on paper. The emphasis is on functional skills: understanding and using information in everyday life.

1. Literacy

Literacy is defined as the ability to use written information to function in society, achieve your own goals, and develop your knowledge and skills. Literacy encompasses a range of skills. From understanding written words and sentences to interpreting and evaluating complex texts. Information about the competency of adults with a low level of literacy is obtained by running a test with linguistic components, where researchers assess vocabulary, understanding, and the ability to read seamlessly.

Literacy covers reading and understanding written texts, but also the ability to use the information effectively. In the PIAAC, this concept also covers working with digital texts.

2. Numeracy

The researchers define numeracy as the ability to use, interpret, and share mathematical information and ideas in order to cope with mathematical demands in a wide range of situations. The numeracy skills in the PIAAC are aimed at controlling a situation or solving a problem in realistic contexts by reacting to mathematical information displayed in various ways.

Although numeracy and literacy are independent concepts, numeracy is more than just applying mathematical skills to information in texts.

3. Problem-solving capacity in a digital environment

Problem-solving capacity in a digital environment is defined as the ability to use digital technology and means of communication to gain and evaluate information, to communicate it to others, and to perform practical tasks. Problem-solving capacity encompasses the skills required to solve problems for personal, work-related, and social goals, by formulating fitting goals and plans, looking for information, and using it with the aid of computers and networks.

Problem-solving capacity in a digital environment is the intersection of computer skills (the ability to use ICT applications) and the cognitive skills required to solve problems. It doesn’t just test computer skills, but the ability of people to use digital resources (tools) in order to effectively find, process, evaluate, and analyze information.

Illiteracy and low literacy

According to the authors of the PIAAC report, past research into adult literacy has often had a strong correlation to illiteracy and low literacy, but that can be misleading. It’s about core competencies that are important to functioning optimally in a knowledge society. This is why the OECD discusses key information processing skills; the skills needed to absorb and process new information.

Finally, the PIAAC researchers draw an important conclusion related to demographic ageing. The actual use of the three mentioned core competencies (literacy, numeracy, and problem-solving) contributes to the level of core skills at an older age. In other words: use it or lose it!

Data Literacy Project

According to the people behind the international Data Literacy Project, training and education are the antidote to data illiteracy. The goal of this project is to enliven discussion and develop the necessary tools to strive for a data-literate society. The participants of the Data Literacy Project provide individuals and companies with training materials, interactive assessment tools, and access to a network of experts.

Data literacy assessment

Based on our years of experience with data-driven working and Big Data, we developed a data literacy assessment. You can test how data literate you and your colleagues are. The assessment can also easily be scaled up to be organization-wide. By using an automated questionnaire, you can quickly get an overview of your data literacy. Contact us for more information about the data literacy assessment.

Data literacy awareness

This network doesn’t just support the development of personal skills, but also works on encouraging a data-driven culture within companies. Schools and educational institutions around the world should include data literacy in their curriculum, according to the researchers. Passionned Academy has several training courses designed to improve data literacy. Consider our 3-day Business Analytics training, the Big Data training (which focuses on data mining), or our 10-day Master of Data Science training.

Data Literacy Index

According to the founders of the Data Literacy Project, it’s becoming increasingly important to be able to trust in our own data skills, due to the rise of automation, robotics, and artificial intelligence. The Data Literacy Index tracks how countries and organizations fare when it comes to data literacy. That’s the sum of human skills, the amount of data-driven decisions, and the degree to which data has spread within organizations and government agencies.

Various research shows that the skills described above have a strong correlation with the successful participation of individuals in society in general and the job market in particular. Individuals who possess a higher level of core skills are less likely to be unemployed, have a higher income, enjoy better health, and are more politically and socially active (Leuven, Oosterbeek & Van Ophem, 2004; Rudd, Kirsch & Yamamoto, 2004; Heckman, Stixrud & Urzua, 2006; Schuller & Desjardin, 2007; Statistics Canada & OECD, 2008).

Another definition of data literacy

According to a different knowledge platform, data literacy is the skill of reading existing data sources and the ability to work with them using sound arguments. Data literacy can help with making choices by predicting possible outcomes based on large volumes of data. Systematically analyzing data and using it for analyses are valuable skills for organizations in every industry. Research has proven that data literacy leads to faster decision-making and demonstrably higher revenue (Empowering analytics, Aberdeen Group, 2016).

The importance of data literacy

These days, we have access to much more data than before. Data-driven decision-making and datacratic working is on the rise. Datacratic working also means scoring employees and teams on several aspects and scaling based on their degree of data literacy. Are they able to read data? Can they apply data analytics in their daily tasks? How many data-illiterate people are you working with in your team? These kinds of insights can help you use data more effectively and increase data literacy. The following four aspects play a crucial role in this:

  1. Access to data.
  2. Attitude towards data.
  3. Skills.
  4. Critical thinking.

Checklist: 30 indicators of data literacy

  1. Can the person access the necessary data? Do they know the right contacts?
  2. Are they familiar with the data analytics team and tooling?
  3. Do they have a tooling account, and are they logged in?
  4. Do they know where to go for ad-hoc questions and analyses?
  5. Do they regularly come to the data analytics team with questions, improvements, and analyses?
  6. Do they have a positive attitude with regards to data-driven decision-making? Do they consider this important?
  7. Do they have a positive attitude towards data in general?
  8. Are they prepared to invest time in learning (new) skill sets?
  9. Do they invest in improving skills related to using data (Excel, Tableau, Access training, etc)?
  10. Can they work with relevant software?
  11. Can they read graphs and make data visualizations?
  12. Are they able to draw the correct conclusions?
  13. Are they capable of reading graphs in data analytics tools?
  14. Can they interpret axes on graphs?
  15. Do they avoid making obvious mistakes when interpreting data?
  16. Can they make their own tables in Excel, PowerPivot, or Power BI?
  17. Can they make their own dashboards and reports using self-service analytics?
  18. Can they draw fitting conclusions?
  19. Are they handy with Excel VLOOKUP?
  20. Are they familiar with statistics?
  21. Can they formulate a correct hypothesis and test it using data?
  22. Can they accurately assess the reliability of data?
  23. Are they aware of their own confirmation bias?
  24. Can they make a well-founded decision based on incomplete data?
  25. Do they have a feel for data?
  26. Do they have reasonable expectations regarding the data?
  27. Can they draw the correct conclusions from a graph, but do they need help in finding the right graphs/dashboards/data to match an issue?
  28. Can they formulate a simple hypothesis and test is using an existing dashboard?
  29. Are they aware of the limitations and opportunities of data?
  30. Can they turn a decision-related question into a hypothesis and test it using relevant data?

Do you want to know more?

Do you want to know more about data literacy and data-driven working? Contact us for an appointment with one of our specialists.

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Daan van Beek, Managing Director

DAAN VAN BEEK MSc

Managing Director

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