Data strategy · 2-minute video
How do you build a data strategy that actually gets finished?
Why does a data strategy create so much work and so little finished? Most are a list of things to build, chosen on instinct and stacked on everything already running. The fix is to start from what you already run, and what it costs.
First step of the €1,200 workshop. Invoiced after. Full refund if it wasn't useful.
or test it on your own numbers first ↓2 min 16 s · Captions on. Nothing loads until you press play.
Fifteen initiatives, no order, nothing finished
A leadership offsite produces a strategy document. It promises an attribution model, new dashboards and a dozen new pipelines by year end, on top of everything the team already keeps running.
Nobody can say which of the fifteen matters most, because each was chosen on instinct, with no estimate of what it would change. So the team works on whatever isn't blocked. By December there is a lot of work and almost nothing finished. Not a lazy team, and not a bad idea on the list.
Agile teams, product managers and quarterly goals make the work faster and clearer. They don't change what is on the list. The backlog is the same shopping list, cut into two-week slices.
Start from one board: the present, the future, success
What changes the outcome is where you start. Put the present, the future and how you will measure success on one page, and test each move before you commit the full budget to it.
The present
Who uses data today, and for what?
What is missing, what is broken, and what all of it costs to run, in euros. Most strategies skip this, so every new idea lands on top of it.
The future
What must the business be able to do in three years?
The capabilities first, then the data, tools, people and skills they need. Three or four moves, not fifteen.
Success
How will you know it worked?
A few measures, each tied to a decision someone makes, plus how people will be brought along. That is how you tell progress from being busy.
That page is a vision board. Not a document you file, but a map you steer by: each move gets a budget and room to work, is tested before full commitment, and what you learn goes back on the page.
Would you fund last year's initiatives again?
List what your last strategy started. For each one, answer three questions. Rough answers are fine. If nobody can say whether it was worth it, that's where to start.
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Answer the three questions for at least one of last year's initiatives. Three to five is enough to see the pattern.
Start your next plan from what you already pay for
A 30-minute call. We agree whether the session is worth it and who joins. A data lead can join if you want one.
The working session, on your numbers. Your list of initiatives with euros next to each, so the next plan has a floor, and what to stop before anything new goes on top.
What you leave with. A clear name for what's costing you, one number you can defend to the board, and a first list of what to stop, with the reason next to each.
In one e-commerce company, working around data was costing €930,000 a year in people's time and tools. €611,000 of it could be stopped. It took three weeks to measure, and the first cancellations were made before the engagement ended.
€1,200, invoiced after the session. Full refund if it wasn't useful. The fee is credited toward the Data Capital Audit if you continue.
Thirty minutes, no slides. If the session isn't worth it, you'll hear that on the call.
What happens in the workshopQuestions leaders ask about data strategy
What should a data strategy include?
Three things on one page: what you run today and what it costs, what the business must be able to do in three years, and how you'll know it worked. Most plans skip the first, so the next one has no floor.
How many initiatives should a data strategy have?
Fewer than most lists: a few moves, each tested before it gets the full budget. OKRs and agile make the work faster. They don't decide what's on the list.
Why do data strategies fail?
Rarely because of the team or the ideas. The list is chosen on instinct and stacked on everything already running, so nothing has an order. The longer read: Why a data strategy fails by month three
Can't we draw the board ourselves?
You can, and the check above is the start. The hard part from inside is pricing colleagues' projects and saying which should stop. Someone with no stake in any of them makes that shorter.
The right time to look is before next year's budget gets spent.
First step of the €1,200 workshop. Invoiced after. Full refund if it wasn't useful.
Want the longer read? Why a data strategy fails by month three · What your data already costs