4 simple ways to improve data literacy at your organization

Generating data is easy. Making sure it’s accurate, reliable, and useful is harder. And with clean data forming the backbone of AI and machine learning models, understanding data and improving data literacy across teams has become even more essential.

Data literacy is the ability to understand, interpret, and talk about data to ultimately make better decisions and drive strategic business outcomes. It’s a skill everyone needs, not just data scientists and analysts.

After all, data is only as useful as your team’s ability to use it. When employees possess data literacy and data analysis skills, they can avoid making the same mistakes in the future or recreate the magic of a successful strategy.

So how do you build data skills across your organization?

Start by understanding your team’s current data literacy skills. Skill assessments, surveys, and other methods can help you benchmark and identify skills gaps.

You might also consider these questions to assess data literacy throughout your organization:

• Can everyone access the data they need for their roles?
• How many employees are comfortable using data analytics tools?
• Can everyone interpret graphs and data visualizations correctly?
• Do team members use data to make decisions and inform new processes or ideas?
• Can data scientists explain their models and how they relate to business use cases?
• Can sales and customer service professionals explain the reporting and analytics your product offers?

When you’ve identified data literacy levels across your organization, create an upskilling program to fill the skills gaps. Try sorting employees into different groups based on their skill levels and the degree of data literacy they need. Then tailor training programs to each group. 

For example, the first group might consist of people who aren’t confident in their data skills. They don’t know how to read or interpret data to make decisions. The second group might include people who understand data and use it to drive decision making, but don’t know how to clearly communicate their findings or share their insights. 

A third group might be able to analyze data, use it to make decisions, share their findings, and promote a data-driven culture throughout the organization. These are usually your data analysts and data leaders.

The level of data literacy someone needs will depend on their role and responsibilities. Tailored learning paths for data analytics literacy and data visualization literacy can help teams develop the data skills they need. 

Language plays a key role in any culture, and organizational culture is no exception. To improve data literacy across your organization, limit jargon and create a shared vocabulary for everyone to pull from. You might even create a list of definitions for common terms. This reduces miscommunication and gives everyone the same baseline.

Data terminology is also the basis of AI/ML. Teams who can talk about data are better equipped to talk about artificial intelligence and understand how they can use it to optimize business processes.

Create clarity around who’s in charge of data at every level of your organization. To figure out who should have ownership, start conversations with people and figure out who has the relevant expertise. Then document each data owner so team members can easily find who to go to for answers.

Whether you host a talk at lunch or send out valuable information in a Slack message, teaching data literacy at your organization as a regular practice will have big benefits. Ideally, you should also build it into your onboarding process. Tell new team members what they need to know to be data literate at your company and how they can gain the necessary skills.

Sustain your upskilling efforts with a data-first culture, one where people are encouraged to ask questions and experiment safely. These questions can be valuable conversation starters that help your teams discover more about the story your data is telling: 

• What are we missing?
• How does this help us get closer to our goals?
• Is everyone looking at the same thing?

Your data teams will be crucial in helping other teams build their data story and create a data-first culture. Thanks to their existing knowledge, data scientists can answer other teams’ questions and walk them through data processes.

Data literacy simplifies cross-functional collaboration and empowers team members to make better decisions. There are endless ways to encourage team members to get better at navigating the complex world of data, but the most important thing is ensuring your company emphasizes data literacy as a valuable skill across all levels. 

This might mean allocating specific time periods for everyone to learn or rewarding those who level up their data skills. Whatever your company’s data journey looks like, it’ll be one worth going on.

Build data literacy foundations in your org.