How Can You Improve Data Literacy?
Most organisations around the world are grappling with data literacy shortfalls in their organisation. This is something I see every day in my work with companies all across the globe. While many companies collect more data than ever before, they aren’t using it to its full advantage because all employees aren’t trained to use data to make strategic decisions. I have helped many of the world’s best-known brands improve their data literacy, and with this post, I want to share five key elements that will help any organisation improve its data literacy.
The true objective of data literacy is to give everyone access to the data so that every business unit can use it to make better decisions that will lead to success for the organisation. It’s not just about being able to read numbers, graphs and charts, but extrapolate useful meaning from data and the various visual representations that are used to make it easier to consume.
So, if helping everyone in your organisation become more fluent in data is the objective, how is that done?
While this might take a different shape for every organisation, here are some key elements that lead to data literacy success.
1. Identify data advocates Identify individuals in your organisation who will be strong data leaders and who can help craft a data literacy programme. This group should be a cross-functional team who can help champion the benefits of data literacy to those who are not entirely convinced. They can also help determine what business units are missing opportunities because they aren’t using data effectively and prioritise those groups for the data literacy programme.
2. Be the change The shift to making your organisation’s culture data-focused needs to start from the top. When you and other company leaders model data-informed meetings, decision-making and expect your teams to do the same, it shifts the culture. An essential part of helping the rest of the team understand the power of data is to share data success storeys with employees so they can see how data influenced real-world outcomes.
