When to hire a data analyst, and what to do until then
The honest math on what it actually costs to get executive dashboards — and how to bridge the gap while you hire.
Every CEO I talk to who is thinking about “doing something about data” eventually hits the same question. Should we hire a data analyst now, or bridge with a platform until we’re ready?
I have a strong bias, obviously — I run a data platform company. But I’m going to try to give you the honest version, because the timing of this decision matters more than most people realize, and the right answer depends on specifics I can’t know from a blog post.
The raw numbers
Hiring an analyst (fully loaded): €70-120K/year for a mid-level analyst in most European markets, more in London or Zurich. Add a laptop, software licenses, management overhead, recruitment cost, and 3-6 months of ramp-up. First-year real cost is closer to €110-160K.
Building a data platform team: Analyst + data engineer + possibly a BI developer. First-year loaded cost: €250-400K, plus the six months of project management before anything ships.
Buying a platform: €5-20K/year for most mid-market platforms, including ours.
But the raw numbers miss the point
Cost isn’t actually the interesting question. The interesting question is: what do you get from each, and how do they fit together?
What a great analyst brings that a platform can’t:
- Deep knowledge of your business, your quirks, your one-off decisions
- Custom analysis on demand — “show me what happened when we ran the Q3 promo”
- A human who will walk into the CEO’s office and say “something is wrong with last month’s numbers”
- Relationships with the heads of each department, understanding of what they actually need
What a platform brings that a brand-new hire can’t (yet):
- Dashboards that are live on day one, refreshing automatically from then on
- Pre-built views that work for 80% of standard business questions (MRR, retention, cash flow, funnel, etc.) out of the box
- Institutional memory that stays in the platform — models, metrics and docs in one place, so new hires onboard in days instead of months
- Time to value measured in hours, not quarters
The two are complementary. A platform is not a replacement for a great analyst — it’s a foundation they can build on the day they arrive.
The framework I’d actually use
Ask yourself three questions:
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Is data your competitive advantage? If yes (you run experiments, build ML models, do non-trivial analytics that differentiates your product), hire now. You need someone embedded in the business from day one. If no (you just need to see your numbers clearly and make good decisions), start with a platform and hire when you have a backlog of questions it can’t answer.
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Do you have 3-6 months to wait? If yes and you can afford the salary, start recruiting today and let a platform cover the gap while they ramp. If no, a platform ships this week and you start hiring when the timing is right for the business.
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Are you past €30M in revenue? Above that line, the economics flip — custom teams start making more sense because the marginal cost of a few more headcount is smaller relative to the benefit. Below that line, a platform-first approach usually wins, with a hire layered on when the business needs it.
What we usually see
Most of our customers end up hiring an analyst — but they do it two to three years later than they otherwise would have, and for a better reason. Instead of hiring to build the first dashboard, they hire because the business now has specific questions the pre-built packs can’t answer. When their first analyst arrives, they inherit a running platform, a clean data model, and living documentation. They spend day one on real questions — campaign analysis, forecasting, board-level deep dives — instead of wiring pipelines. That’s a better job for them and a better use of the budget.
If you’re at the fork right now and want to talk through the specifics, book a demo — happy to walk through your stack and your options, no sales pressure.