Getting executives to back data projects means reaching middle managers and individual contributors too. AI's rapid rise creates urgency, but you need both top-down leadership support and bottom-up training tailored to different employee personas, not one-size-fits-all data literacy.
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Related to this is related to these conversations, right? Like adoption of data science, making sure business stakeholders use data tools. I think that requires, you know, some level of data culture within the organization, right? Not just buy in from leaders who are strategically aligned with the importance of becoming data driven, but also middle managers, individual contributors, you know, who may have, you know, years under their belt developing their own gut feeling and their own, you know, gut instinct when it comes to, like, how to approach business problems. How do you approach that buying component with your, you know, business stakeholders? Right. And what do you think is the most critical factor data leaders need to look at when trying to develop a data culture and their business counterparts?
So I think currently what helps a lot is this fast development of AI, because in this case it's much easier to convince that if we don't do anything in 10 years, we might simply not exist. So I think that that's a very strong argument we have. And obviously to approach any kind of data literacy effort is two ways and actually you have to do both. It's like top down and bottom up. So top down, that's very important because otherwise it's very difficult to do role modeling inside of organizations. But the bottom up actually requires much more work in sense that you have much bigger user base to actually train. And the easiest way to do that is to define Personas which you're going to train, because not everybody needs the same knowledge of data science or even data governance data in general.
