# “Let’s define a data strategy.” Translation: let’s argue about tools for 6 mo...
Canonical: https://social-archive.org/tgroenwals/DhpOaYA9hW
Original URL: https://www.linkedin.com/feed/update/urn:li:activity:7443296204207271936/?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAAUj9ABA6XwLJ3RcHE4FACjTijtAT4klvY
Author: sebastianhewing
Platform: linkedin
## Content
“Let’s define a data strategy.” Translation: let’s argue about tools for 6 months. Here’s the thing I don't like to admit openly: I've been a data leader for almost 20 years. In my first 6 years, I believed that data strategy was mostly about data stacks. Over those years, I realized (the hard way): If you want a strategy that survives the next reorg, AI hype wave, or exec sponsor change - start here: 1. Problem: What are we solving? 2. Users: Who are you serving? 3. UVP: What's our data team's secret sauce? 4. Solution: What are we building and what are we NOT building? 5. Distribution: How will we get this in front of users without chasing them down? 6. Systems: What helps this scale without breaking us? 7. Outcomes: What will users actually do differently? 8. Costs: What’s the real investment? (Spoiler: it’s not just the software) 9. People: How will we grow a team that wants to stick around? 10. Vision: What guides our decisions when priorities clash? Answer those 10? You’ve got a data strategy. Ignore them? You’ve got a dashboard backlog and a stack no one uses. I know because I've been there and lived through the pain... 👉 Follow me, Sebastian Hewing, for daily insights on data strategy. ♻️ Repost if you've ever watched a “data strategy session” turn into a Power BI vs Tableau debate.