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Business Intelligence in New Zealand
Numbers you trust, in one place, without someone spending three days a month building them in Excel. The technology is the easy part — agreeing what a number means is not.
$40k+
Typical project value
2 min
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What people usually mean by business intelligence
Almost every reporting project discovers the same thing: two departments define revenue differently, and both have been right for years. The dashboards are quick. Deciding what goes on them is the work.
Reports off one system
Your ERP, accounting or job system, reported properly instead of exported to a spreadsheet.
Bringing several sources together
Sales, finance and operations in one place, which means agreeing how they join.
A warehouse and a model
A proper data layer with definitions everyone shares, so a new question does not mean a new project.
What it costs
Indicative ranges from projects posted here. Use them to sense-check a quote, not to budget precisely.
Reporting on one source
Dashboards and scheduled reports from a single system.
$20k – $45k
Multi-source reporting
Several systems combined, with cleaning and agreed definitions.
$45k – $120k
Data warehouse
A modelled warehouse, automated pipelines, self-service reporting.
$120k+
Questions worth asking a provider
·Who decides what a number means when two systems disagree?
·How fresh is the data on each dashboard — live, hourly, overnight?
·Can we build our own reports afterwards, or does every question need you?
·What happens when a source system changes a field?
·What will this cost per month in licences and hosting?
Common questions
How much does business intelligence cost?
Dashboards from one source system are $20,000 to $45,000. Combining several sources, with the cleaning and definitions that requires, is $45,000 to $120,000. A modelled data warehouse with automated pipelines starts around $120,000. Licences — Power BI, for example — are extra and per user.
Why is combining systems so expensive?
Because the data disagrees. The same customer exists three times with different spellings, one system counts revenue at order and another at invoice, and a product changed code in 2021. Reconciling that is most of the project, and no tool does it for you.
Power BI, Looker or something else?
For most New Zealand businesses Power BI is the pragmatic answer — you probably have Microsoft licences already and people who know Excel find it approachable. The tool matters far less than whether the underlying data is trustworthy.
How do we stop it becoming shelfware?
Build the first dashboard for one person who has an actual decision to make weekly, and watch whether they use it. Dashboards commissioned because management wanted visibility, without a specific decision behind them, are the ones nobody opens after a month.
How long does it take?
Four to eight weeks for reporting off one system. Three to six months for multi-source work, most of it spent agreeing definitions rather than building.
Related: Data Integration · Data Warehouse · Dashboard Development · Power BI · Data Migration · Database Design · Data Cleanup
Business Intelligence projects open right now
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The data is the hard part
Every reporting project has the same moment. Someone asks for revenue by region, two systems produce different numbers, and both are defensible. Sales counts an order when it is placed; finance counts it when it is invoiced. Neither is wrong and they will never agree.
Resolving that is not a technical task and no tool solves it. It needs someone with authority to say what the definition is, and it is the single biggest predictor of whether a BI project succeeds.
Decide who that person is before you commission anything.
Start with a decision, not a dashboard
The dashboards that get used are built for a person who makes a specific decision on a regular basis. Which jobs are running late this week. Which customers have stopped ordering. Whether we can take another contract this month.
Dashboards commissioned for "visibility" get opened enthusiastically for two weeks and then never again. Name the decision and the person before anything is built, and you will know within a month whether it worked.
Agree how fresh the numbers need to be
Live data costs meaningfully more than overnight, and most reporting does not need it. A monthly revenue dashboard refreshed each night is fine. Stock availability being shown to a salesperson on the phone is not.
Decide this per dashboard rather than for the whole project. It is one of the few choices that moves the price a lot and is entirely yours to make.
Ask what happens when a source changes
Someone will rename a field, add a status, or restructure a table in a system you do not control. A well-built pipeline notices and tells you. A fragile one produces a chart that is quietly wrong, which is worse than a chart that is obviously broken.
Ask each developer how a source change is detected. The answers separate the careful from the quick.
Comparing quotes
- Definitions. Who decides, and is that time in the quote?
- First dashboard. For whom, and for what decision.
- Self-service. Can your team build reports afterwards?
- Licences. Monthly cost per user, stated.
- Source changes. How they are detected.
Describe the numbers you cannot get today and where they live. Five developers will tell you what it takes — and the good ones will start by asking who gets to define them.
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