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4 simple ways to improve data literacy across your organization

Generating data is easy. Making sure it’s actionable, reliable and useful is harder. No one has “cracked” data yet. It’s a continuous journey for even the most successful companies, which means improving data literacy across all your team members is essential.

Data is only as useful as your ability to understand it correctly, and a team that understands data makes better data-driven decisions.

Even the designer who hates math benefits from understanding data better, as it allows them to demonstrate the impact of their work. Good data allows you to draw conclusions around why a new strategy worked or didn’t—so you can avoid making the same mistakes in future or recreate the magic of what you just successfully pulled off.

So if data literacy is so important, how do you make it the default standard across your org? 

1. Make sure there is a clear owner

There should be clarity around who’s in charge of data at every level of your organization. To figure out who should have ownership, start having conversations with people and figuring out who has what expertise. Then start documenting it, so team members with questions can easily find out who to seek answers from.

2. Choose tools your team understands

Mode analytics let you customize all your visualizations and make data clearer, so your team members have an easier time understanding the story data is telling. This is a great example of making data work for you, rather than wrestling with tools that display data in a less-than-intuitive way. Naming things in a way that makes sense can also make all the difference. 

3. Teach

Whether you host a talk at lunch or send out valuable information in a Slack message, teaching data literacy at your company as a regular practice will have big benefits. Ideally, you should make it a part of your onboarding process, by telling new team members what they need to know to be data-capable at your company, and how they can gain the necessary skills.

4. Encourage questions about data interpretation

Getting a wider variety of perspectives can strengthen your data and the validity of what you take away from it. Data is human and therefore flawed, so the more humans you have involved in interpreting it, the better. Questions like, “What are we missing?”, “How does this help us get closer to our goals?” and “Is everyone looking at the same thing?” can be valuable conversation starters that help you discover more about the story your data is telling. 

Data literacy empowers team members to be more successful in their roles, and makes cross-functional collaboration easier and more impactful. 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.