Your data strategy is dead. That 40-page slide deck won't get adopted. Here is what you are missing.
Everyone knows they need a data strategy alignment on definitions, governance, all the fundamentals.
But if everyone knows it, why is data still a mess?
Here’s how it usually plays out:
A “new data strategy” gets announced.
A 40-page PPT, a few workshops, a roadmap that looks great in QBRs.
Something happens. Disrupts the roadmap.
Then six months later, nothing.
No ROI.
No adoption.
Data strategy is just a fancy document or a new "tool"
Here’s the truth:
DS is not a tool or 40-page doc.
Forget theory and planning.
Here are some tips to do it correctly:
1. Quarterly Strategy Reviews
Every roadmap needs a pulse.
You review, recalibrate, and re-fund every 90 days, not every year.
Each QSR forces three conversations:
Impact: What value did we actually deliver (dollars, hours, trust)?
Relevance: Do our priorities still match business goals what has changed?
Resourcing: Do we have the capacity to keep this alive?
Nobody cares about "pipelines" and an 18-month roadmap. Align to core OKRs, show core clear next steps, have clear champion.
2. Sequencing, Prioritizing
Sequence by readiness, not ambition.
Most roadmaps collapse because they chase shiny goals instead of sequencing by what’s actually ready.
Everyone wants AI, predictive models, “real-time everything.”
But if you can’t reconcile last quarter’s revenue or trust your CRM data, you’re not ready.
The question is not "What to do?" is "Is this the lowest hanging fruit?"
In data, you are always building up on the foundation.
Make sure every initiative is like building LEGO.
3. Staffing & Capacity Modeling
This is where 90% of strategies fail before execution even starts.
Most plans assume teams can “just do more.” They can’t.
Bandwidth, missing skills, and context switching kill delivery.
For every initiative, quantify:
-Hours required
-Roles needed
-Gaps to fill or outsource
If the capacity model doesn’t fit, the roadmap isn’t real.
The roadmap isn’t just a timeline, it’s a resourcing plan.
A lean-focused data team is better than, big team working all over the place.
4. Don't be static, be agile
New priorities will always show up AI pilots, ad-hocs, and leadership changes.
Without a process, every shiny request nukes your roadmap.
Update roadmap when priorities change, new initiatives, and if progress stalls (ad-hoc),
Build a change scoring model:
Value impact
Highlight readiness
Risk & Dependencies
Re-score quarterly, not weekly.
5. Share Timelines
Include timelines so business units can plan resourcing.
Be transparent about sequencing, why some priorities are put first
When business areas see what’s coming, when, and why → trust and engagement rise.
Celebrate small wins visibly.
🧬 Repost if you think disconnected systems are root issue of most problems orgs face.
