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A man analyzing data on his laptop
More data equals more knowledge - or does it?
Across all industries, companies are collecting more data than ever before. It's proven that intelligent data enables companies to make better decisions, gain visibility, streamline processes, increase productivity and drive higher profits. It is for this reason that data literacy has become a core competency for all employees.
But even if organizations have recognized the benefits and the necessity of a holistic data understanding, upskilling an entire workforce doesn’t come easy. Therefore, it's not surprising that most organizations are still struggling to equip their workforces to effectively use all this data.
To stay competitive, companies need to find a way to teach data skills to their employees. In this post, we want to share our experiences with educating data skills at scale and building a data literate workforce.
Being data literate enables us to make fact-based decisions using the massive amounts of information at our hands. Making everyone within an organization data literate doesn’t mean turning them into data scientists or data analysts. Actually, there is a variety of skills, tasks, and responsibilities revolving around data. Let us bring some light to the dark:
Being data literate is actually not about coding and complicated tools or programs, but about mastering three necessary skills:
Data literacy has recently been called the most critical skill of the 21st century, comparing it to the role alphabetical literacy played for society centuries ago. It is the most essential skill to work reliably and critically with analytics and its insights. It should be mastered by everyone making decisions, reporting, or policy recommendations within an organization.
A lack of data literacy costs employers an equivalent of 5 productive days per employee. Translating to billions of dollars in lost productivity per employee each year.
Data literacy is not a single skill that can be taught in a week-long seminar but instead consists of a mixture of technological skills, critical and analytical thinking, and problem-solving capabilities. All of which need a lot of time, training, and experience to develop.
Nevertheless, the most effective way to build data skills is to upskill your workforce.
The first step has to be a skill assessment. It reveals the skill-levels of all employees cohesively. It provides management, Learning and Development managers, and learners with an overview of existing competencies. The learning efforts’ real impact is displayed along the learning program by continuous assessment and visualization, as well as by comparison with a second assessment at the end of the program.
Breaking down the barriers and inhibitions towards working with data is a central part of any data literacy upskilling program. To get out of a culture and mentality of “it’s always been this way,” it is not sufficient to refresh everybody’s memory about Microsoft Excel. Preferably, conveying a holistic picture of methods, tools, and use cases for data handling the understanding of data and its impacts increases. The program has to give employees the liberty to learn the basics of various applications and tools. Encouraging them to try out their new skills, e.g., in a low code environment, while executing their daily tasks helps break down barriers. Additionally, it eliminates outdated ways of thinking and teaches safe handling of data and information.
Teaching and learning data skills cannot follow a one-size-fits-all solution.
Especially when looking to upskill large numbers of employees or an entire workforce in data skills. When looking to create lasting effects and benefits for daily business and operations by trained new skills, it is essential to offer personalized learning methods which concern, among others, the time, medium, and specific content of learning. In the past, it was virtually impossible at the level of an entire company to ensure this depth of individualization using traditional upskilling programs. Now, new technologies and innovative platforms make it possible to personalize the learning experience for every single employee. This is why Learning Experience Platforms (LXP) portray the future of corporate learning.
The process of learning and acquiring new skills can be frustrating and demotivating at times. Often gamification methods are used to keep employees engaged in the learning process. Those can be receiving points for learning, competing on a leaderboard, or collecting badges, ultimately resulting in higher motivation and engagement.
Studies show that implementing gamification methods increases employee productivity by 90%.
Famous gamification examples, probably most of us have encountered, are the language learning platform Duolingo or running app Nike+ Run. Gamification provides the right tactics to make learning and performing on the job more fun and engaging and, therefore, ultimately efficient and effective.
One of the most significant flaws in traditional training seminars is the lack of transfer of the acquired knowledge into the participants’ everyday tasks and responsibilities in their work environment.
To ensure the best possible knowledge transfer for learners, practice-oriented projects can be implemented in small teams throughout the program. They allow for a direct application of skills in a less artificial context while also allowing participants to experiment with tools and insights in a safe environment together as a team. Our tip is to start projects not at the end but rather halfway through the learning content. That way learners are exposed to feedback-mechanisms that enhance the learning impact.
While online learning has some notable advantages compared to in-person seminars, it lacks human interaction. Allowing learners to talk to knowledgeable mentors and professional data experts has an enormous impact on learning effectiveness. It reduces frustration with materials significantly. Additionally, technical discussions consolidate the understanding of a topic and stimulate to view it from differentiated perspectives.
Providing learners with internal mentors to guide the learning journey may teach organization-specific processes and handling of frequently used tools. Though, it comes at the price of quality and diversifies education. External mentors have a set of different experiences and oftentimes a broader vision and view beyond the company horizon. Additionally, External mentors provide neutral confidence, that every question asked or topic discussed will be handled confidentially. Employees are put at ease that there truly are no stupid questions and that they won’t have to fear any consequences from asking away.
Data has become a highly valuable resource to businesses and will gain even more importance and impact in the future.
Yet, data skills are kept in a knowledge silo of data experts like data analysts, data engineers, and data scientists. Actually, data allows every single member of an organization to create an impact. While considering to upskill an entire organization’s workforce may seem like a massive challenge, it is a practical and necessary step in an increasingly data-dominated world.
In this e-book, we dive deeper into the topic, demystify the root cause of lacking data skills and propose a persona-driven strategy for developing data literacy skills at scale.
Want to master data literacy? Find out how in our e-book!
edyoucated is funded by leading research institutions such as the Federal Ministry of Education and Research (BMBF), the Federal Institute for Vocational Education and Training (BIBB), Federal Ministry for Economic Affairs and Climate Action (BMWK).