Data literacy is more than just training – it’s organizational development

Because it involves more than just imparting technical knowledge, data literacy upskilling is more about organizational growth than it is about training. It means establishing a culture that encourages data-driven decision-making and gives people the tools they need to do it successfully.

Imagine you want to train a team of penguins to dance ballet. Sure, you can teach them the moves, but can they understand the nuances of the art form? Can they feel the emotions behind the choreography? Can they apply the techniques to different pieces of music? Probably not, right?

Data literacy upskilling is a lot like teaching penguins to dance ballet (stay with me here). It's not just about providing training and teaching technical skills. It's also about creating an environment where people can:

• understand the value of data
• interpret it correctly
• apply it effectively to their work

Organizational development comes into play here because you need to create a culture that values data and encourages people to use it in their decision-making. It's about building the right infrastructure and systems to support data analysis and communication. It's also about having leaders who can champion the use of data and make it a priority.

Without these organizational elements, data literacy training might be like teaching penguins to dance without a stage or music. It might be possible to learn technical skills, but without the right environment, it won't lead to meaningful outcomes.

Hybrid models yield the best results

From what we’ve seen from our clients, a hybrid model of online self-paced education and live sessions is the way to go if you want to foster a community of decision-makers.

If participants only do online self-paced education, they might learn the technical skills but not have the opportunity to practice and apply them in a real-world context. And if they only do live sessions, they might miss out on the flexibility and convenience of self-paced learning.

By combining online self-paced education with live sessions, participants can practice and apply those skills in a live setting with other decision-makers. This creates a community aspect by connecting training participants so they can share ideas, ask questions, and get feedback while building relationships and supporting each other on their data literacy journey.

Starting your data literacy academy

Another valuable strategy comes from building what many companies are calling an academy. This is really a matrix that reinforces and connects people who are doing data and analytics across different functions in the company. These academies are valuable for organizational development because they:

• create a culture of curiosity
• provide opportunities to share findings and present them to each other
• develop real data storytelling capabilities

From my perspective, the biggest mistake to avoid in data literacy training is to try to do this one-off or completely self-paced, i.e. leaving it up to every individual. This often leads to organizations failing to reach their desired benchmark of a good data-literate culture.?

From what we see on the ground, the most successful companies are those that are leading from the top by making a strategic, sustained investment in upskilling, and then sustaining that community on an ongoing basis.?

About the author

As the Global Head of Data Literacy at Qlik, I lead an integrated, business-driven approach to enabling companies to become more data-driven. I’ve spent decades developing advanced data and analytics solutions for Fortune 100 companies, and I’m a longtime advocate for business-driven data strategies and best practices. If you’d like to learn more about how leading companies are transforming through data literacy, please visit https://www.qlik.com/us/bi/data-literacy.?