eLearning Skills 2030: Data Literacy

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Start With Why. Engage. Learn. Iterate. Repeat.

As machines become increasingly accurate and intelligent, we humans will need to sharpen our skills. One of your primary responsibilities as a Learning and Development leader is to sharpen your skill and ensure that you empower the workforce to develop the four sets of skills critical to thriving in 2030. I have compiled a series of articles titled “eLearning Skills 2030” to explore the essential skills to help you future-proof your career and lead your team. This article explores the skill of data literacy, why it is critical, and what actionable steps you can take today to improve it.

What Is Data Literacy?

According to Gartner, “data literacy is 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.” [1] Qlik, a data visualization company, expands that data literacy is a skill that empowers all levels of workers to ask the right questions of data and machines, build knowledge, make decisions, and communicate meaning to others. [2] MIT Professor Catherine D’Ignazio defines data literacy as the ability to read data, work with it, analyze it, and leverage it to convey a message to a larger audience. [3] Data literacy requires analyzing and visualizing data, and then telling their story to others.

Why Is Data Literacy Critical?

It has been said that data is the new currency and the new oil fueling the way we do business. All need to be able to speak it. Organizations collect and use data about their processes, resources, employees, and, above all, their customers, needs, and preferences to develop and deliver better products and services. Research by Harvard Business Review revealed that organizations that use data to make decisions and make the data transparent and accessible to their frontline employees have a better track record in employee and customer satisfaction and better overall performance. Qlik also reports that organizations with a strong corporate data literacy have to outvalue other organizations by 5%. [2] In other words, data literacy is good for business. This means that you must be able to read, use, depict, and explain data to make data-driven decisions that drive business performance.

How Can You Sharpen The Data Literacy Skills In Your Organization?

1. Differentiate Data Literacy From Technical Literacy

A first and essential step is to clarify that, while related, data literacy and technical literacy are quite different. Data literacy pertains to why data is critical and how to use it; in other words, the business impact of data. In contrast, technical literacy teaches people the mechanics of the systems that use or depict data. Organizations often focus training on the latter, which is insufficient. Data literacy teaches people how to think about data and use it.

2. Start With “Why” To Craft A Data Literacy Strategy

Engage leadership as champions of the strategy and discuss why the organization needs a data literacy strategy and how you will implement it. Engage teams to provide input to craft the strategy, messages, and approach to assessing the data literacy skills gap within the organization, conduct a data literacy pilot, and measure and communicate outcomes. Engaging employees early and often will help socialize the strategy and gain engagement during the outreach process.

3. Gauge The Employee Data Literacy Skill Gap

You will need to review the data on what employees need and want to learn regarding data literacy and what your organization currently offers. You can access basic literacy skills in the organization by determining how data is used inside the organization and your customers. Start with a few “how” questions, including how many managers can build sound business cases based on credible and relevant data, how many can explain the output of their systems’ processes, and how many data scientists can explain how the Artificial Intelligence (AI) algorithms work. Ask your customers whether the data you share with them is meaningful. Then, you will need to review the data. What did the data tell you?

4. Build A Data Literacy Learning Pilot

Think big. Start small. Running a pilot to test your data literacy strategy is a low-cost, low-risk approach. Based on your data gap analysis results, engage employees to curate a six-week learning program consisting of online microlearning options, a mentoring element where more experienced data analysts mentor pilot participants and offer opportunities to practice using, analyzing, and storytelling with data. Capture the learning journey with short videos of the participants interacting with their mentors, tracking their understanding, and embracing data to make business decisions. The goal of the pilot is to demonstrate behavioral change as a result of learning about and using data to deliver better performance outcomes. 

5. Measure The Pilot Results, Iterate, And Improve

After the pilot ends, conduct a review and discuss with the organization what worked well and what did not. Celebrate the new learners and the wins, and learn from the things that did not work so well. Communicate the pilot results and the review with articles, presentations, and town-hall-style meetings to spread the word. Ensure you capture continuous feedback to continue iterating on the literacy strategy and learning program.

6. Cultivate A Culture Of Curiosity And Lifelong Learning

As discussed in the relevant article, building a learning culture is critical for organizational strategy and performance. In the book Forward-Focused Learning, I wrote chapter four on defining a learning ecosystem, why leaders must focus on fostering a learning ecosystem in their organizations, and how to do it. A learning ecosystem is a symbiotic environment where employees interact with each other and with the knowledge content, data, and technologies surrounding them to facilitate, develop, deliver, and share learning experiences based on the governance guardrails set by the broader organization. Lifelong learning and curiosity go hand in hand. As discussed in the relevant article by Harvard Business School Professor Francesca Gino, curiosity is a critical skill for individuals and a foundational value for organizations because it can drive performance outcomes. [4] Fostering curiosity helps leaders be more agile in problem-solving and adaptive to change. Curious learners are better at exploring new ideas, thinking differently, and finding new solutions.

Conclusion

Data is the new language of business, and every organization needs to be able to speak it fluently to achieve performance outcomes. As a Learning and Development leader, you are responsible for ensuring that you and your teams have the necessary data literacy skills to thrive today, in 2030, and beyond.

References:

[1] A Data and Analytics Leader’s Guide to Data Literacy

[2] What is data literacy, and why does it matter for your organization?

[3] How to build data literacy in your company

[4] The Business Case for Curiosity

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