Developing and applying data literacy in business

Introduction to data literacy in business

“Data is the fuel that runs the fourth industrial revolution,” futurist Bernard Marr says in an article for Forbes, “and learning how to work with data is more important than ever for employees at many organisations.”

Steam and early mechanisation ushered in the first Industrial Revolution, while electricity and petroleum powered the second. Nuclear energy and computing pushed the world into the third. Today, business processes in every industry are increasingly shaped by — and reliant on— data. That’s why many, including McKinsey, say we are now in the Fourth Industrial Revolution.

In this data-driven world, business leaders and decision-makers use data analytics to set strategies, improve efficiency, and measure business outcomes. Big data is the key to better decisions and process optimisation. All these data-driven organisations call for a more data-literate workforce.

Unless you’re lucky enough to work at an organisation with a mature data literacy training programme, it may be up to you to develop your data literacy skills. This article is your comprehensive guide to understanding, developing, and applying data literacy skills in any line of business. Whether you’re currently a student, a mid-career professional, or a manager, you can continually improve your data-related skills. Read to the end for resources for starting a data literacy programme if your business doesn’t already have one.

Understanding data literacy in business

It’s important to realise that data literacy is a broad business skill set and doesn’t require expertise in data science. In their work at MIT, Professor Catherine D’Ignazio and research scientist Rahul Bhargava define data literacy as “the ability to read, work with, analyse, and argue with data.”

And business data doesn’t exist in a vacuum. Gartner’s definition of data literacy emphasises the importance of business context to real-world data.

“Gartner defines data literacy as the ability to read, write, and communicate data in context — with an understanding of the data sources and constructs, analytical methods, and techniques applied — and the ability to describe the use-case application and resulting business value or outcome.”
Definition of Data Literacy, Gartner Glossary: Information Technology

According to Dataversity, "organisations with the top tier of data literacy had a greater enterprise value of three to five percent. This translated to hundreds of millions of dollars of value and better return on equity."

Poor data literacy, on the other hand, is costly. A report from Accenture and Qlik on behalf of The Data Literacy Project reported that “stress around information, data, and technology issues” lead to, on average, 43 hours of lost productivity per employee per year. The lost business value quickly adds up to billions of dollars.

Colleagues across an organisation need to speak the same language of data and follow shared rules as part of a unified, data-driven culture. For example, each organisation develops its own rules and policies surrounding data access and compliance, also known as data governance. Understanding general data governance concepts is a foundational data literacy skill. Learning to work within a real-world data governance framework is a business-critical next step.

Developing data literacy in business

General data literacy and data-driven decision-making skills are valuable in any field or industry. Everyone should know how to ask the right questions, evaluate data sources, and make a persuasive argument with data.

Business professionals can also benefit from building industry-specific or job-specific data competencies. Think of an energy trader who builds specialised data literacy skills involving petroleum market data sources. That domain expertise may not transfer to other industries, but it could be highly desirable within the energy sector.

Your data literacy goals may be dictated by current job’s demands. As a learner, your first step is to identify your strengths and weaknesses when it comes to data literacy. Once you know your baseline, you can address your skills gaps, measure your progress, and set further goals based on your interests and career aspirations.

There are many ways to develop data literacy throughout your lifetime:

  • Study data literacy in education settings. While focused data literacy programmes are still new, there are many avenues for students to build data literacy skills at school, from data science, data analysis, and statistics courses to graphic design classes about data visualisation.
  • Take advantage of workplace data literacy trainings. Programmes offered by your employer have the benefit of being tailored to your company’s technologies and data culture, so don’t miss out when training is offered.
  • Build your data skills with online resources. From free videos on YouTube to online courses to product training resources, there have never been more resources to teach yourself data literacy skills.
  • Get hands-on experience with data. Keeping your data skills fresh can mean using data at work, but also consider building data jobs for fun.
  • Push your own limits. Challenging tasks encourage you to apply your data literacy skills, and learn new skills and tools.
  • Get active in professional communities. Talking to your peers is a natural way to practise and grow your data communication skills and keep up with best practises.

Data literacy training programmes in business

In a recent survey by Forrester for Tableau (download the PDF report), workers across all departments reported basic data skills as the most important skills for success in their roles — but only 40% of employees said their employer had provided training on the data skills that were expected of them. This gap in data literacy training robs employees and employers alike of the benefits of data literacy.

More and more organisations are implementing broad data literacy training programmes for upskilling employees. As of 2022, 65% of companies surveyed by Talend reported having a data literacy programme. Employee training is part of a healthy retention strategy, especially when it’s framed as a career-long employee development programme. Data literate employees report higher job satisfaction and retention.

Data literacy training often falls under a Chief Data Officer or central IT organisation, but anyone can get the ball rolling. If you want to champion data literacy in your business, here’s how to identify stakeholders and get the conversation started.

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Online resources for data literacy in business

Job-specific training may fall outside of the scope of a general data literacy training programme. Fortunately, there are a lot of online resources for teaching yourself.
Explore these resources for assessing and expanding your data literacy skills:

Hands-on experience for data literacy in business

An organisation can’t build a data culture if its employees don’t have access to trusted data. To build a data-driven business, you’ll need to provide employees with modern data management tools, shared data, and a common language of data.

Watch this video to see how Talend’s employees use Talend tools to improve data access and data literacy.

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Applying data literacy in business

One way to build a stable career is to develop data skills for a particular industry. Every industry has its own relationship with data, and becoming an expert can make you indispensable. For example, fluency in health data would support many career paths in the healthcare industry.

Data literacy skills for certain fields, like marketing, sales, or human resources, are broadly applicable across many industries. Build these skills if you want flexibility to take your career to different kinds of organisations.

Data literacy in marketing

Marketing teams include many functions with their own specific skill sets. A data-literate graphic designer has a different skill set than a data-literate product marketing manager.

Examples of some of the many ways to leverage data literacy skills on a marketing team:

  • Customise marketing analytics dashboards — go beyond vanity metrics like pageviews to track, improve, and report on activities that matter to your business.
  • Understand search, ad, and social algorithms — keep up with changing SEO best practises by learning more about search engine optimisation.
  • Master the language of data visualisation — communicate complex ideas effectively with the right charts, graphs, and graphics for every occasion.
  • Get market segmentation right — you don’t need to guess about target audiences when you have trusted data about your customers and the broader market.
  • Conduct deep competitive analysis — understanding the competitive landscape is all about having the right data about your competitors and sharing it internally.
  • Create informed user personas and customer profiles — understand why and how customers use your products.
  • Prove marketing return on investment (MROI) — gather and analyse performance data to evaluate campaign outcomes and show your team’s value.

Data literacy in finance

Data literacy in finance absolutely requires numeracy, or an understanding of numbers. But graphical literacy and language skills are also important for finance roles. After all, the higher-ups need to understand your reports. Corporate policies and paperwork need to deliver information in terms that employees beyond the Finance team can easily understand. Communication about financial data is the most valuable skill in a finance department’s toolkit.

Examples of how to use data literacy skills in a finance role:

  • Build data dashboards — customise dashboards that integrate data flows for at-a-glance status updates on financial activities across your company.
  • Produce readable and engaging reports — financial reporting is useless if your audience doesn’t understand it — or doesn’t see the point of it.
  • Evaluate business cases for spending — data literacy helps you cut through the pitch to examine business value and assess ROI of requests.
  • Solve business problems collaboratively — establish a common language for financial data at your company to communicate better across lines of business.
  • Communicate with effective visuals — communicate complex ideas effectively with the right charts, graphs, and graphics for every occasion.
  • Take advantage of AI forecasting tools — understand which tools are best suited to your needs and get your company on a path to being more proactive.

Data literacy in operations

The day-to-day administrative tasks of running a business have become highly data-driven.

  • Identify and mitigate causes of attrition — use people analytics to find patterns in job dissatisfaction, and test and improve programmes to solve problems.
  • Track and report on DEIB and ESG initiatives — stand by your company’s social and environmental promises by measuring and sharing successes.
  • Equip managers to manage with data — teach team leaders to evaluate team performance consistently and determine fair bonuses.
  • Analyse performance data and act on it — evaluate programme outcomes with data, then iterate and optimise processes.
  • Make the most of your resources — gain visibility across the organisation by knowing where to find all the data you need.

Conclusion and further resources

Basic data competency means knowing how to communicate information with words, numbers, and data visualisations. In the context of business, data literacy also means understanding relevant data sources and systems — and knowing how to create business value with data.

Data literacy has real-world applications in every line of business. Since a data-literate workforce is a proven asset, business leaders should aim to raise the level of data literacy on their teams. That doesn’t just mean hiring for data skills. Data-driven companies should continually train employees to support their work with data and provide modern data management tools that foster business-wide data culture.

Whatever your level of data literacy is, you’re never done learning. Continue to practise and expand your data skills. If you aren’t getting the job-related data training you need, you can find learning opportunities on your own. Every businessperson should know how to read a dashboard, sketch a graph, and ask data-driven questions. Professionals in any line of business can also pursue specific data literacies and communication skills within their field or industry.

Today’s businesses need modern data management that encourages data literacy and supports a data-driven workforce. To learn more about complete, flexible, trusted data management for your company, reach out to Talend today.

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