How do you foster a data literate culture and mindset in your organization?

A great way to start is a simple thought experiment with your colleagues: "What important questions, that if we could answer them accurately, would have the largest impact on our success?" It might take a few tries to get everyone in the right mindset for thinking about this. It'll require a bit of imagination. Some examples questions might be: "What will prevent our next new sales hire from working out?" "What do our customers find most appealing about our products vs. the competition?" "How many new store locations should we open this year?" Good questions concentrate your data efforts, and provide people with meaningful, satisfying goals.

It's difficult to imagine an organization that doesn't work with data in one way or another and probably many organizations have already Data Management processes in place, which should enable the data literacy's effort. The first step is to understand the broader context, what other organizations do, what has been done within the organization, identify the direct related needs, what's the literacy level, what level is needed and map the gap. Of course, one needs for this a framework and a quantifiable approach. Having a support team that can provide training and help when needed can be beneficial for the effort. Exposure to projects that deal with data is probably a must. Organizations will need the resources to help in the process.

As a Senior Manager in Business Intelligence, I can't stress enough the importance of data literacy in today's data-driven world. It's like giving your team superpowers! ??♂???♀? By investing in training and resources, you're not only upskilling your employees but also creating a culture where data is as fluent as the morning coffee chat. And let's be real, who wouldn't want to be the data hero in the office? ?? #DataLiteracy #BeTheHero #DataDrivenCulture

A data literacy program can be combined with other methodologies like Six Sigma, TQM or Data Management and conduct common projects. No amount of theory can replace a real life example in which hopefully a deeper understanding of data and one's job is reached.

It's important to build a community of data literate folks who empower each other. You can't control all data literacy knowledge to the analytics and enablement teams, you need to identify your data 'power users' and elevate them to become champions amongst their peers and support enablement of every-day data encounters from those who need a bit more support.

Organizations need to ensure that the focus is on internal challenges and opportunities, respectively that the efforts don't have only a theoretical basis. Therefore, the training needs to be tailored to an organization's needs with examples focused on its problems. Unfortunately, too often the focus is on general topics and examples that have minor or no overlapping with those of the organization. Equally important is the diffusion of findings and further knowledge within the organization. Communication should have a networked and not a hierarchical structure.