Plenty of organisations invest time and energy into creating a shiny new data strategy, only for it to be quietly forgotten. Tucked away on the intranet, it gathers dust, referenced maybe once in a board paper, and never again. If you’re writing a data strategy because you need one for compliance or to tick a box, fine. But if you actually want it to shape decisions, priorities, and culture, you need to think beyond the PDF.
Here are a few things I’ve learned that help a data strategy stick, not just in theory, but in day-to-day use.
1. Don’t write it for the data team.
Yes, the data team will use it, and yes, they’ll probably help shape it. But the people you need to reach are the ones commissioning reports, collecting data from students or staff, making policy decisions, or approving tech spend. Your strategy needs to speak to them, in language that means something outside the data world. If it only makes sense to analysts and architects, it’s already too narrow.
2. Make it about what people do, not what they believe.
Too many strategies read like value statements: “We believe data is an asset” or “We aim to be data-informed.” That’s fine, but what are people meant to do differently as a result? Will they start capturing something new? Stop duplicating effort? Ask for evidence before approving a project? Turn those good intentions into specific expectations.
3. Make it visible in decisions.
The easiest way for a strategy to fail is for it to never be mentioned when something real is happening. If your organisation is choosing between two systems, prioritising a backlog, or building a new process—bring the strategy in. If you can’t use it to argue for one option over another, it might not be a strategy at all. It might just be a vision.
4. Bake it into onboarding and planning.
New starters should hear about the data strategy early, especially managers and decision-makers. And if you’ve got business plans, project templates, or risk logs, those are perfect places to reflect the strategy. You don’t need a whole section titled “Data Strategy”, just use the language and ideas where they naturally fit.
5. Review it with people, not for them.
A strategy that gets reviewed every year by a data steering group and then quietly republished isn’t really being used. Invite people from other teams to talk about what’s changed, what’s still hard, and what needs to go. If the strategy still describes the world as it was three years ago, it probably needs a rethink, or a retirement.
6. Align it with pain points.
If you want people to remember the strategy, connect it to the things they’re already struggling with. Can’t get hold of accurate learner data? Strategy. Wasting hours reconciling different reports? Strategy. Nervous about data breaches or regulatory risk? Strategy. If it helps solve actual problems, it will be used.
7. Make it a reference, not a relic.
This isn’t about pushing everyone to memorise the strategy. It’s about making sure they know it exists, know where to find it, and know how to use it. That might mean short explainers, recorded walkthroughs, or a few worked examples. However you do it, make it easy to grab when people need it.
So, those are some ideas to breath life into your shiny new data strategy – you got any other ideas?