# What does a dashboard cost to build — and why it's usually not the dashboard

> Request quotes for a dashboard and you'll get numbers from €500 to well past €15,000. That spread isn't random: you're not paying for the charts, you're paying for what sits underneath them. An honest breakdown of the price tiers, when the cheap version is fine — and when you shouldn't buy a dashboard at all.

_August 19, 2026 · Business, Dashboards, Costs_

Ask three parties to quote "a dashboard" and you'll get numbers back from
€500 to well past €15,000. For the same word. Choosing on price then means
comparing apples to plumbing — because the spread isn't random. With a
dashboard, you barely pay for the charts. You pay for what sits underneath
them.

## What does it cost to have a dashboard built?

Having a dashboard built costs between €500 and €15,000+, depending on what
sits underneath it. Three price tiers, and each of them is sometimes the
right one:

| Price tier | What you're buying | When it's the right choice |
| --- | --- | --- |
| **€500 – €3,500** | The quick dashboard: straight on one clean source, standard visuals, you maintain it yourself | An operational overview on a system that's already correct |
| **€5,000 – €10,000** | The serious dashboard: a data model under the hood, one pinned-down definition per figure shown, and attention for the people who'll use it | Figures you steer on every month — my own package sits in this tier: [from €7,500](https://ruudjuffermans.nl/en/services/dashboards) |
| **€15,000 and (well) beyond** | Dashboard plus foundation: once figures from multiple systems have to agree, you're no longer really buying a dashboard but a data warehouse with reporting on top | Multiple sources that must form one truth — Dutch market research prices that scenario around €17,500, see [What does a data warehouse cost for an SME?](https://ruudjuffermans.nl/en/blog/wat-kost-een-datawarehouse) |

The charts themselves — colours, tiles, filters — are maybe twenty percent
of the work in all three tiers. The rest sits below the waterline.

## Where the money actually goes

**The data model.** Every serious builder puts a modelling layer between
source and dashboard: cleaning, logic, one calculation per figure. Skip it,
and every definition lives inside a chart formula — and a year later nobody
knows why two tiles on the same dashboard give different answers. (How that
happens, and what it costs, is worked out in
[Every department reports a different revenue figure](https://ruudjuffermans.nl/en/blog/elke-afdeling-een-ander-cijfer).)

**The decisions, not the wishes.** The standard question "which charts do
you want?" produces a wish list. The better question: which decision do you
make again every month? A dashboard view that doesn't trace back to a
recurring decision stops being opened after three weeks. That inventory is
thinking work, not clicking work — and it's exactly the difference between
the price tiers.

**Adoption.** Dashboards rarely die on technology; they die on disuse. A
manual by email doesn't work. A working session with the people who need to
use it, in their own calendar, does. In the cheap tier this is absent by
definition; in my package it's in scope by default, not an add-on.

> A dashboard nobody opens didn't fail on visualisation.
> It answers a question nobody asked.

## "We already have a dashboard, but nobody looks at it"

I hear this more often than "we have nothing yet". And the important thing
then is *not* to buy a prettier dashboard first, because that changes
nothing. Disuse almost always has one of three causes:

1. **It doesn't answer a decision.** It shows what there was to show, not
   what the team has to decide monthly.
2. **The figures aren't trusted.** Users double-check the numbers against
   the source system — that's a definition problem, not a visualisation
   problem.
3. **The depth is missing.** The overview exists, but "which customers,
   exactly?" requires an export to Excel. Then Excel always wins.

All three are fixable — but with modelling work and conversations, not with
a new colour scheme.

## What you can do yourself before hiring anyone

- **Build the decision inventory yourself.** One list: which decisions come
  back monthly, and which figures do they need? Everything you have built
  afterwards must trace back to that list. This costs an afternoon and makes
  every quote sharper — and cheaper.
- **Test the trust.** Ask three users whether they double-check the current
  report's figures against the source. If yes: you have a definition problem
  first, and a dashboard wish second.
- **Look at the usage.** Virtually every BI platform shows who opens a
  report. Ten users created, two active? That's your real starting point,
  not the feature list.

## What I charge

My package [A dashboard people actually open](https://ruudjuffermans.nl/en/services/dashboards) costs
**from €7,500** and takes two to three weeks: first the decision inventory,
then a clean documented model on the source you already have (with a
definition list per figure shown), then one to three dashboards with
drill-down — built iteratively, users looking along — and finally the
adoption session. No warehouse project: the build goes straight on your
existing source.

And the honesty that belongs with it: if week one shows your sources are too
fragmented to build on directly, I won't build on sand — you'll hear it,
with [the warehouse story](https://ruudjuffermans.nl/en/services/single-source-of-truth) as the honest
alternative instead of a dashboard that falls over three months later anyway.

*Not sure which price tier your situation falls into?
[Book an intro call](https://ruudjuffermans.nl/en/contact) — I'll gladly walk through the decision
inventory above with you in a first conversation.*