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say it with moxy

Five Myths About Enabling a Data Culture

I readily admit that enabling a data culture within an organization is tough work. It's like when everyone knows they need to be healthier, but there's no instant gratification and it's not always very fun so they put it off until next year, or the next year, or the next year. But just like getting healthier, enabling a data culture is far more about making small, incremental changes, and being consistent and persistent about it, rather than immediate gains.

Whether you're guilty of making those kinds of excuses or just looking for a bit of guidance on this subject, here's a list of myths about enabling data culture (and my thoughts about them) that you may find helpful:

Myth #1: You must have Executive support/sponsorship

Okay, I concede that this one is both true and false. It is false in the context of needing executive support to START a data culture enablement initiative. As a matter of fact, I highly recommend beginning with a grass-roots approach rather than spin your wheels waiting for the C-suite to see the light. This also gives you time to hone your message, your strategy, measure initial interest and identify potential evangelists. It's also much cheaper. You will eventually need executive support, but by then it should be a no-brainer for them.

You don't need fancy tools to have a data-enabled culture

Myth #2: You have to have all the fancy tools

Hopefully I'm not the first person to tell you that when it comes to changing a culture the tools don't really matter. Sure, you need to have something the masses can use to interact with the data, but it could literally just be Excel. Don't get me wrong; I am huge fan fancy tools like Tableau, Power BI, Alteryx, Collibra, Snowflake, Dataiku, etc... But you don't NEED them when your ultimate goal is to change processes and human behavior.

Myth #3: Generic data literacy programs will do the trick

No, no they won't. Trust me, every organization's data, tool stack, IT infrastructure, data security and risk tolerance is so different that generic data literacy programs are just not worth it. Any training you use to enable a data culture is far more effective when it's relevant to your organization's unique situation.

data governance is a team effort

Myth #4: Data governance is a separate thing

So, the whole point of enabling a data culture is to get your workforce in the habit of effectively using data to the benefit of the company, right? What happens when you have hundreds, thousands or even tens of thousands of people looking at your company's data? Well, some of those folks are going to to weird stuff with it, but that's not what I'm getting at here - they're going to find errors in the source data! And from a data governance standpoint, that a good thing. When data governance is embedded into your data culture or data literacy efforts, you've just created hundreds, thousands or even tens of thousands of little data stewards who can do the job no one person or small team could ever hope to do.

Myth #5: Success is hard to measure

If you agree the whole point of enabling a data culture is to get your workforce in the habit of effectively using data to the benefit of the company, then you shouldn't need to over-complicate how you measure it's success. It can be as simple as tracking the number of queries hitting your database(s), and/or activity on your reporting platform(s) like Tableau Server or Power BI Service. Anything to indicate that more people are using more data. This should be your early and primary measure of success.

Longer term indicators of successful data culture enablement efforts can be correlated with improvements in Profit, Employee Engagement and Employee Productivity, but be prepared to share credit with many other initiatives for these common key performance indicators.

You can learn more about data strategy, data governance literacy, and data culture enablement by downloading our free ebooks, available here!

Love what I said? Hate what I said? Have thoughts of your own to add? Let's start a conversation 😉


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Separating out the “church and state” of data governance will help organizations focus on better and faster access to data.


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