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How to get a Data Program to its Full Potential
The reason your data program isn't producing anywhere near its full potential is an operations problem, not a technology problem.
Here's how to fix that in three steps:
- STOP focusing on the newest technologies just because they're cool. Technology won't solve your pain on its own, and will likely ADD pain in the short-term. Do you really need a data catalog when you still haven't figured out how to connect to and ingest your data into a modern environment?
Spoiler: You don't. And it's 2023, so when you actually need one, you can add one in approximately 16 seconds.
New technology = new rules of engagement and new processes for a team already struggling with existing rules of engagement and existing processes.
- Sit down with your leadership team, agree on ONE (just one....seriously) use case, and quantify the business impact of that use case with numbers, either in terms of value produced (e.g. 10% efficiency gain, 4% revenue lift, etc.) or costs saved (e.g. 1% reduction in scrap, etc.). The smaller andmore specific you can begin, the better.
"Implement self-service analytics" is not a good use case.
"Understand sum of sales" IS a good use case.
- Build toward that business impact statement, and ignore everything else. Why? Because your people only have so many cycles, and context switching is destroying them.
Bonus: Outsource your undifferentiated data operations to a qualified team, so your internal team can do what they were hired to do: create value for the business. Your team will thank you.
