What is data literacy and why is it important

For more and more businesses the ability to leverage data – to increase operational efficiency and to improve decision-making – is gaining executive attention and attracting investment.

This makes data literacy, the ability to derive meaningful information from data, an increasingly important capability, both for organisations and individual knowledge workers.

“By 2023, data literacy will become essential in driving business value”

GARTNER

According to a?Qlik?study of over 11,000 people worldwide, only?1 out of every 5?participants felt that they were data literate.

The desire to learn and work with data is there, but the skills are lacking.

What is data literacy?

“Data literacy?encompasses the critical thinking skills required to interpret data and communicate the significance to others”

FORBES

Gartner?describes data literacy as “the ability to read, write and communicate data in context, including an understanding of data sources and constructs, analytical methods and techniques applied — and the ability to describe the use case, application, and resulting value.”

Our simple definition: Data literacy is the ability to derive meaningful information from data.

Data literacy examples

Here are some examples of basic data literacy skills:

1. Understanding Charts and Graphs: Data literacy involves being able to read and interpret charts and graphs, such as line graphs, bar charts, and scatterplots.
2. Identifying Trends and Patterns: Data literacy involves being able to identify trends and patterns in data, such as seasonal fluctuations in sales or demographic trends in a population.
3. Data Visualization: Data literacy involves being able to create and interpret data visualizations, such as heatmaps, infographics, and interactive dashboards.
4. Data Analysis: Data literacy involves being able to analyze data using statistical methods, such as regression analysis, hypothesis testing, and correlation analysis.
5. Data Story-Telling: Story-telling is the art of using data to convey a message or tell a story in a way that is easy to understand and engaging for the audience.

In our post,?the Impact of story-telling and presentation, we gave some examples of these basic data literacy competencies.

Data literacy creates opportunities

According to?business-of-data.com, increasing data literacy in enterprises can create several opportunities, such as:

• Higher profitability: Research conducted by Qlik in 2018 shows that enterprises with high data literacy levels are typically worth USD $320-534 million more than those without. This means that having staff with the right data skills can have a direct impact on the company’s financial performance.
• Increased productivity: The better the staff within an organization get at using data, the more productive they generally become. According to Qlik’s survey of more than 7,300 business decision-makers, 85% of data-literate people say they’re performing very well at work compared to just 54% of the rest of the workforce.
• Improved decision-making: Data-literate people make better decisions, and as more things get automated, the tasks humans do often require judgment, which is improved by data literacy. When executives insist on interrogating their own decisions with potentially adverse data, it sends a message that data is important.
• Competitive advantage: Enterprises with high data literacy levels have a competitive advantage over those without, as they can use data to make better decisions, improve data accuracy, and avoid misleading BI.
• Better customer experience: Frontline workers who leverage their data literacy skills to boost the customer experience should be rewarded for their efforts through public recognition, bonuses, gifts, paid time off, and other incentives. Data-savvy customers can be a company’s most loyal customers if data is used to help them make informed decisions.

Why is data literacy important to your business?

Data literacy is crucial for businesses, as it enables employees to make better decisions, prioritize work, see new opportunities, and drive efficiency. Building a thriving data culture is essential in empowering employees, and businesses depend on data-literate employees to drive them forward.

Leading organizations such as Amazon, Facebook, and Netflix are extremely good at utilizing data, following trends, and analysing information. They realize that data is one of the best assets to harness and that the key to success in the fourth industrial revolution requires harnessing data’s power within an organization.

According to?Precisely, “enterprises that have higher corporate data literacy scores can have $320-$534 million in higher enterprise value.”, while?Gartner?identifies that “poor data literacy is ranked as the second-biggest internal roadblock to the success of the CDO’s office.”

“Uncertain business environments, the changing nature of work and acceleration of digital business technology are causing skills gaps that need to be filled by developing new skills within the workforce,” says?Alan D. Duncan.?Distinguished Vice President for Data and Analytics Strategy and Chief Data & Analytics Officers (CDAO) Gartner

Why should data literacy be important to individual knowledge workers?

Traditionally regarded as the purview of IT, data literacy is now increasingly becoming a critical job skill.?The increasing reliance on data means that almost every worker is either a producer or a consumer of data. Everybody that works with data, and makes decisions based on data, needs to have the basic abilities to communicate, read, and work with data.

“Everybody needs data literacy, because data is everywhere. Data is the new currency, it’s the language of the business. We need to be able to speak that.”

PIYANKA JAIN, DATA SCIENCE EXPERT AND AUTHOR OF “BEHIND EVERY GOOD DECISION: HOW ANYONE CAN USE BUSINESS ANALYTICS TO TURN DATA INTO PROFITABLE INSIGHT

Not all jobs require hard-core data science skills, fortunately, but the ability to deliver trusted and understand data context is critical.

A basic understanding of underlying, fundamental data management competencies – such as data governance, data quality and data lineage – that allow them to assess the integrity of the data they are working with is the next level.

Each producer of data, for example, should be conscious of the impact of poor-quality data on downstream consumers.?The concept of “garbage in, garbage out” is more relevant than ever as companies invest in advanced analytics and AI.

For data consumers, the ability to trust data goes beyond data quality and may need to include a basic understanding of lineage, the context of data, and the ability to interpret basic figures.

Improving data literacy skills is advantageous, even if one is not working with data every day. Data is a part of everyday life, and it is necessary to have a basic grounding in data literacy. Individuals who work in tech or data-based roles need to be able to know their way around machine learning tools and have an appreciation of accuracy, facts, and how they can inform everything from business decisions to personal health. Technology enables data professionals to work with huge sets of data to find out more facts faster.

This does not mean that everybody needs to be a?data management expert?– literacy is about building a common understanding.

Important data literacy skills

A data-literate individual has the ability to understand, interpret, and apply data to fulfil the knowledge-gathering, decision-making, and communication responsibilities of their specific job roles. Every individual takes part in creating a data-literate organization with the ability to communicate, collaborate, and innovate using data.

Data literacy combines both technical and non-technical skills.

Starting with the soft skills:

Critical thinking is a crucial skill for analysing and comprehending data. It involves questioning assumptions, applying logic to problem-solving, and obtaining information from diverse sources. To enhance critical thinking abilities, individuals must possess research skills to evaluate sources, identify implicit or explicit biases, and narrow their search to gain a thorough understanding of the data.

Effective communication is also essential in data literacy, as individuals must convey their data findings to others. To improve communication skills, individuals should practice active listening, work on public speaking, and seek feedback from trusted peers.

Technical skills:

According to eLearningCurve’s?Data Literacy Body of Knowledge, data-literate individuals develop their understanding of the following technical capabilities:

• Data and databases: By improving their database skills, individuals can gain a deeper understanding of the data they are working with, which can help them make better decisions based on that information
• Data knowledge and governance: By understanding data governance, individuals can make informed decisions about data collection, use, and sharing, and comply with legal and ethical guidelines
• Data resource management: By understanding data resource management, individuals can identify data gaps, prevent data duplication, and ensure that data is properly categorised and labelled for easy retrieval. This enables individuals to make more informed decisions based on accurate and up-to-date data
• Data provisioning: By understanding data provisioning, individuals can identify data sources, request data, and ensure that data is properly prepared for analysis.
• Data analysis: By understanding data analysis, individuals can select appropriate tools and techniques to analyse and visualise data, interpret results, and communicate findings effectively.

Building Organization-Wide Data Literacy

According to Gartner, Chief Data Officers must take three steps to build?enterprise-wide data literacy:

Assess current levels of data literacy

Garter suggests answering the following questions as a start:

• How many people in your business do you think can interpret straightforward statistical operations such as correlations or judge averages?
• How many managers are able to construct a business case based on concrete, accurate, and relevant numbers?
• How many managers can explain the output of their systems or processes?
• How many data scientists can explain the output of their machine-learning algorithms?
• How many of your customers can truly appreciate and internalize the essence of the data you share with them?

Individuals can complete a?data literacy self-assessment?to get a good idea of their overall competence and gaps in their knowledge.

Establish a data literacy training program

Improving data literacy skills can be done in several ways, such as taking online?data literacy courses, attending workshops, and reading books. It is essential to start with the basics and gradually move to advanced levels of data literacy. One can also seek out mentorship or networking opportunities to learn from experts and peers.

eLearningCurve’s Data Literacy Certification is an entry-level course to build basic skills, while data specialists can benefit from our advanced?BI training?and CIMP accreditation.

Measure the effectiveness of your data literacy initiatives

To derive a clear and measurable value from the intended training, Gartner suggests that CDOs can:

• Identify the success criteria of data literacy programs by reviewing the objectives and expected outcomes of the training.
• Require employees to learn aside from on-the-job activities after the training.
• Solicit regular feedback from employees so that the training becomes more relevant and addresses existing skill gaps and knowledge requirements.
• Put the content and delivery mechanisms in place and enable employees to apply what they’ve learned.

Barriers to Data Literacy

Data literacy implies that skills must be developed within your workforce. While skills development is the focus of this article, in fact, there are several factors that hinder the adoption of data literacy. Here are some of the barriers to data literacy:

Barrier 1: Culture

The culture of an organization can be a significant barrier to data literacy. Leaders must?lead by example?and encourage the use of data in meetings, decision-making, and pitches for new products or services. Without leaders’ encouragement, employees may see no incentive to adopt a data-first approach. Resistance to change and a lack of awareness of how data can be used to the company’s strategic advantage can also hold back the adoption of new skills.

Barrier 2: Progress

Some organizations may not have prioritized data literacy above other initiatives and are moving more slowly than other organizations. Some companies are still collecting data rather than training employees on how to evaluate and use the data to their business advantage. It is crucial to improve data literacy gradually and in sequential stages.

Barrier 3: Data Integrity

Organizations may be collecting data, but if the?data is not accurate, complete, or contextualised, it will not be able to inform decisions. Not all data is equally valuable to an organization; therefore, it is essential to collect the right data. It often makes sense for organizations to go beyond the data that is immediately available from primary operations or that’s the easiest to collect because insight can be found in unexpected places.

Barrier 4: Misunderstanding of Data Literacy Programs

Some employees may misunderstand what is expected of them in data literacy programs. Organizations need to communicate and help employees understand that they need to learn to read, interpret and critically evaluate data. Data literacy does not require every member of an organization to have the knowledge of a data scientist.

Barrier 5: Lack of Skills and Knowledge

The?lack of skills and knowledge?is a significant barrier to data literacy. To overcome this barrier, leaders need to define what data literacy means and establish a common language for learning. A recent Accenture survey found that only 21% of employees were confident in their data literacy skills. Organizations should invest in training programs that cater to the specific needs of employees and their roles.

Barrier 6: Budget Constraints

Learning and Development (L&D) teams face budgetary pressures, which can make it challenging to eliminate common barriers to data literacy. eLearning allows organisations to minimise disruption to their business, provide consistent, expert training to employees across multiple locations, and maximise ROI by ensuring that every dollar spent is actually used towards education.

While there is work to do, data training is worth it.

“In a world of more data, the companies with more data-literate people are the ones that are going to win,” said MIT Sloan senior lecturer, Miro Kazakoff, who teaches courses on communicating and persuading with data.

“Data literacy has always been a requirement in successful organizations. It’s just that data illiteracy is more obvious now —?or data illiteracy just causes more damage now than it used to,” Kazakoff said.

Culture eats strategy for breakfast

A data-driven strategy can only succeed if the culture of the organisation allows it. Education provides a common language and understanding to shift the culture of the organisation to become data-centric.

Ultimately, data literacy must help to bridge the gap between business and IT data custodians by reducing the communication gap that often inhibits value.

The data train continues to gather steam. Data literacy is the ticket to hop aboard.