Power BI consultancy in Solothurn: what it costs, what breaks and what to build first
A practical guide to Power BI consultancy in Solothurn: the definition traps in precision engineering and instruments and medical devices, honest licensing arithmetic, hire-versus-engage costs, and the compliance position under the revised Federal Act on Data Protection (revFADP / revDSG), in force since September 2023.
Local view for Solothurn, Switzerland
If you are looking for Power BI help in Solothurn, the useful question is not who can build a dashboard. It is who will tell you which of your existing numbers is wrong.
Solothurn is a market of mostly owner-managed and mid-sized organisations, where analytics is one person's responsibility alongside three others. With around 17,000 people and an economy built on precision engineering and instruments, medical devices, and public sector, the reporting questions here are specific rather than generic, and so are the ways they go wrong. This page sets out what a Power BI engagement in Solothurn actually involves: the metrics we check first, what it costs, how licensing should be chosen, whether you would be better off hiring, and what the compliance position looks like under the revised Federal Act on Data Protection (revFADP / revDSG), in force since September 2023.
Why reporting breaks in Solothurn specifically
Generic advice about Power BI is not very useful, because the failure modes follow the industry rather than the tool. Solothurn's economy is weighted towards precision engineering and instruments, medical devices, and public sector, with precision engineering and medical device manufacturing and cantonal administration shaping much of the local employment base. That mix produces a predictable set of reporting problems, and we have seen each of them here more than once.
Medical devices
Device history records, complaint and vigilance data, and post-market surveillance obligations that require linking field events back to manufacturing batches.
The characteristic failure is this: distributor-held data breaks traceability at exactly the point where a field action needs it. Where that has already happened, the first deliverable is not a dashboard. It is a written reconciliation that establishes which number is correct and why. In practice we start by building a traceability and complaint model linking batch, shipment, customer and field event, which is the foundation of post-market surveillance reporting.
Typical source systems: ERP, QMS, complaint handling systems, PLM and distributor reporting. EU MDR post-market surveillance and vigilance reporting require a reproducible data trail from field event back to production batch.
Tourism, hospitality and events
Booking, channel and rate data with heavy seasonality, plus on-site spend and occupancy that only reconcile once channel commission is accounted for.
Here the recurring problem is different: gross booking value from online travel agents is compared with direct booking revenue, making the most expensive channel look like the best one. The fix is a stay-grain model joining rooms, ancillary spend and channel cost, which is where true channel profitability becomes visible. Guest data is personal data with cross-border transfer implications when group systems sit outside the region.
Public sector
Case and service data locked inside line-of-business systems with restrictive reporting modules, feeding statutory returns with precisely defined rules. Returns are assembled by hand each cycle by a small number of experienced staff, concentrating risk in individuals.
We would usually begin with a governed model that produces both the statutory return and internal performance reporting, so published and internal figures cannot diverge. Source systems to expect: case management systems, finance and ERP, HR and payroll, GIS and gazetteers and grant management.
The metrics we check first in a Solothurn engagement
Sector knowledge in analytics is mostly knowing which definitions destroy a number when they drift. Before we design anything we go through the measures that matter to you and establish, in writing, exactly how each one is calculated and who owns that definition. The table below is the starting list for Solothurn, derived from the industries that dominate here.
| Metric | Where it comes from | The trap that breaks it |
|---|---|---|
| process capability indices | precision engineering and instruments | Subgroup selection and measurement system error must be handled or capability is overstated |
| scrap cost per order | precision engineering and instruments | High unit values mean a count-based scrap rate hides the financial exposure entirely |
| CAPA cycle time | medical devices | Reopened actions must not reset the clock, or effectiveness looks better than it is |
| field action exposure | medical devices | Requires batch-to-customer traceability that distributor data frequently breaks |
| statutory timescale compliance | public sector | Clock-stop rules differ per duty and must be modelled individually |
| cost per case | public sector | Overhead allocation and the definition of an open case drive the figure and need written rules |
| installed base service attach rate | industrial machinery and engineering | The installed base register is almost always incomplete and needs reconciling first |
| first-time fix rate | industrial machinery and engineering | Multi-visit jobs need an explicit rule or field performance looks better than it is |
| booking lead time distribution | tourism, hospitality and events | Cancellations must be excluded or the distribution misleads revenue management |
| net average daily rate | tourism, hospitality and events | Channel commission and taxes must be stripped consistently to compare channels |
None of this is exotic. If a number can be calculated two reasonable ways, it eventually is, and the difference turns into a standing explanation rather than a decision. The output of this stage is a measure dictionary: every KPI, its business definition, its owner, and the DAX that implements it.
What a first Power BI engagement looks like
We work the same way whether the client is a mid-sized business with one overworked analyst: decisions first, sources second, model third, reports last. Reports built before the model are the single most common cause of rework.
- Decision inventory, week 1We start from the recurring decisions that need numbers, not from the data that happens to be available. Who decides, on what cadence, and what currently blocks them. For a Solothurn business in medical devices, that usually surfaces three or four decisions worth building for and a dozen reports nobody needs.
- Source profiling, weeks 1 to 2Each source system profiled for grain, volume, change tracking, quality and refresh window. ERP, QMS and complaint handling systems are the usual candidates here. This is where unpleasant surprises belong, not in week ten.
- Model build, weeks 3 to 7A star schema with conformed dimensions, measures written against the agreed definitions, and row-level security applied from the start. For medical devices the argument that has to be settled first is normally complaint rate per units shipped, where shipment timing versus implantation or use timing changes the denominator materially. Settle it before any report exists, not after two of them disagree.
- Report build and validation, weeks 6 to 10Reports built with the people who will use them and validated line by line against the source of record until the numbers tie out. Disagreements get resolved and written down, never averaged.
- Handover, weeks 10 to 14Workshops with your team, documentation in your own systems, and a thirty-day period where we fix what breaks while your people drive. Solothurn draws on the Bern and Biel catchments, with strong precision engineering skills locally.
What that costs
Build cost follows project size rather than report count, the number of source systems and their state drive almost all of it. These are the bands we quote in Switzerland, and we publish them because a buyer cannot start an approval chain without a budget figure.
| Project size | What that covers | Indicative cost | Elapsed time |
|---|---|---|---|
| Small | One or two source systems, one business area, three to five reports, a straightforward star schema | CHF 15,000 to CHF 40,000 | 3 to 6 weeks |
| Medium | Three to six sources, two or three business areas, several fact tables, non-trivial DAX, basic governance | CHF 40,000 to CHF 120,000 | 6 to 12 weeks |
| Large | Heterogeneous sources including ERP and CRM, multiple business areas, a dedicated data layer, formal governance | CHF 120,000 to CHF 400,000+ | 3 to 6 months |
Running it afterwards is a separate line: CHF 3,000 to CHF 8,000 a month for a small estate, CHF 8,000 to CHF 20,000 for a mid-sized one, CHF 20,000 to CHF 50,000+ for a large multi-domain platform. Microsoft licensing is separate again, and is covered next.
Licensing: what Solothurn organisations should actually pay
This is where money is most often wasted, in both directions. Power BI Pro is listed at around US$14 per user per month and Power BI Premium Per User at around US$24 following the 2025 price revision. Local list prices in sterling, euro and Swiss francs track those figures with regional adjustment, and enterprise agreements usually land below list.
| Option | Who it suits | Approximate list price | The catch |
|---|---|---|---|
| Power BI Free | One person exploring data with no sharing | No charge | Cannot share into a workspace, so it is not a business option |
| Power BI Pro | Small reader populations, typically under about 200 people | Around US$14 per user per month at list | Every reader needs a licence, so cost scales linearly with the audience |
| Premium Per User | Teams needing larger models, higher refresh rates or paginated reports | Around US$24 per user per month at list | Still per-user, so a large reader base gets expensive quickly |
| Fabric F2, F32 capacity | Data engineering workloads with a modest reader population | From roughly US$260 a month for an F2, pay-as-you-go | Readers still need Pro licences below F64, and small SKUs throttle under load |
| Fabric F64 capacity | Large reader populations and in-platform data engineering | Roughly US$8,400 a month pay-as-you-go, around US$5,000 reserved | Only pays for itself above roughly 350 to 600 readers, depending on your discount |
The arithmetic that matters: F64 only becomes cheaper than per-user licensing somewhere in the region of 350 to 600 readers, depending on the discount you actually pay and whether you reserve capacity. Below that, Pro or PPU per user is normally the right answer, and buying capacity for prestige is a straightforward waste of money.
For most organisations in Solothurn, per-user licensing is the correct answer and will remain so for years. We have told several clients here that the Fabric capacity they were quoted would be a straightforward waste of money, and we would rather do that than sell the larger number.
Always price from the current Microsoft rate card for your region and agreement. Any figure in an article older than a quarter should be treated as an order of magnitude, not a quote.
Hiring in Solothurn versus engaging a consultancy
This is a fair question and the honest answer is sometimes "hire". Solothurn draws on the Bern and Biel catchments, with strong precision engineering skills locally. Locally, a mid-level analytics engineer costs roughly CHF 110,000 to CHF 160,000, with Zurich and Zug at the top. An experienced external consultant runs at roughly CHF 1,300 to CHF 2,200 per day.
| Approach | When it is the right call | What it costs you |
|---|---|---|
| Hire internally | Steady ongoing demand, an existing platform to maintain, and a manager who can judge the work | Roughly CHF 110,000 to CHF 160,000, with Zurich and Zug at the top a year, plus recruitment time and the risk that one person holds all the knowledge |
| Engage a consultancy | A first platform, a migration, a specialist problem, or a deadline that cannot absorb a hiring cycle | Roughly CHF 1,300 to CHF 2,200 per day, for a defined scope with documentation and handover included |
| Both | The most common answer: internal ownership of business engagement, external depth for architecture and peak delivery | A smaller internal salary plus a modest retainer, which is usually cheaper than either extreme |
Where a Solothurn client has told us they intend to build an internal team, we design for it from the start. Everything is built to be handed over: scriptable models rather than click-built ones, a naming convention written down, documentation in the tools your team already uses, and a dictionary of measures that outlasts the engagement. Several clients have gone on to need us only for quarterly review, which is a perfectly good outcome.
Data residency and compliance for Solothurn organisations
Switzerland North and Switzerland West give in-country residency, which matters more here than almost anywhere else in Europe: banking secrecy, professional secrecy obligations and client expectation all push Swiss data to stay Swiss. Verify per service, because not every Azure or Fabric feature is available in both Swiss regions. In practice, Solothurn deployments normally use Switzerland North (Zurich), with Switzerland West (Geneva) as the paired region.
Regulatory oversight relevant to analytics comes from the Federal Data Protection and Information Commissioner (FDPIC / EDÖB) under the revised Federal Act on Data Protection (revFADP / revDSG), in force since September 2023, plus the sector bodies that matter here: FINMA for banking, insurance and asset management supervision, including outsourcing circulars, FDPIC for federal data protection oversight and ElCom for electricity market and grid reporting.
- The revFADP brought Swiss law closer to the GDPR but not identical to it: records of processing, impact assessments and breach notification follow Swiss rules, and an EU-shaped compliance pack needs adapting rather than copying.
- FINMA outsourcing expectations require documented control over cloud providers, including the right to audit and a tested exit plan.
- Article 321 of the Criminal Code and sectoral secrecy duties restrict who may see client-identifying data, which has direct consequences for row-level security design.
We cover this properly on the data governance and compliance page, and in more depth in our article on data governance for Solothurn organisations.
How we deliver into Solothurn
- Swiss engagements are precise about scope and documentation, and tolerate fewer surprises than UK projects.
- Multilingual stakeholder groups are normal: German-speaking head office, French-speaking region, English-language group reporting.
- Expect strict supplier onboarding, including security questionnaires and in some cases background checks before any data access.
Delivery is remote-first with on-site workshops at the points where being in the room genuinely helps: definition sessions, validation and go-live. We work in German, French, Italian and English, and stakeholder sessions run in whichever of those the room prefers.
How a Solothurn organisation actually buys this
Most consultancy pages stop at what the work is and leave the buying process to email. Relationship-led but heavily documented, with supplier due diligence that goes further than anywhere else in our markets, particularly in banking and pharmaceuticals.
In the private sector: A relationship and a reference open the door; a formal supplier onboarding then decides whether the work can proceed. Expect a security questionnaire, financial checks and, in financial services, an outsourcing assessment against the FINMA circular with documented audit rights and a tested exit plan. Background checks on individual engineers are routine in banking, and some clients require that named staff never move data outside Switzerland.
In the public sector: Federal and cantonal bodies publish on SIMAP under BöB at federal level and IVöB at cantonal level, with WTO/GPA thresholds determining the procedure. Cantonal rules differ, and language requirements follow the canton.
| Stage | Who is involved | What they need from a supplier |
|---|---|---|
| Qualification | Fachstelle, the business owner | A clear statement of what would be built, in what order, with an indicative price range |
| Technical review | IT security, with a questionnaire and frequently an architecture review | An architecture position that survives questioning, and references in a comparable sector |
| Risk and compliance | Datenschutz, against the revFADP rather than an EU-shaped pack and Einkauf for commercial terms | Handelsregisterauszug, current commercial register extract, Betreibungsregisterauszug, a debt enforcement register extract, requested more often than people expect and Insurance certificates including professional indemnity, in CHF cover levels |
| Commercial | Geschäftsleitung, for anything touching client-identifying data | Contract shape, payment terms and liability. German, French or Italian depending on the canton; English is common in banking, pharmaceuticals and international groups. |
Documents you should expect to request, and that any supplier worth shortlisting will have ready, are handelsregisterauszug, current commercial register extract, betreibungsregisterauszug, a debt enforcement register extract, requested more often than people expect, insurance certificates including professional indemnity, in chf cover levels and data processing agreement drafted against the revfadp, not a translated eu template.
Our own entity details, insurance, processing agreements and contracting shapes are published on the procurement page, so your buying team can start without waiting for a reply.
Signals it is time to call someone
The usual triggers are two reports disagreeing on a headline number, an overnight refresh someone re-runs by hand each morning, a largest model that is one file owned by one person who also looks after three other systems, finance still rebuilding the board pack in a spreadsheet, a legacy BI renewal whose price no longer makes sense, or a question about who can see a sensitive dataset that took a week to answer honestly. If two or more are true, a two to three week paid discovery will tell you what to do about it, and you keep the output whether or not you engage us further. Book a technical review, or read what we actually build:
We work across Switzerland and deliver into neighbouring markets regularly. Nearby pages worth reading if your group has sites elsewhere: Thun, Fribourg, La Chaux-de-Fonds, Yverdon-les-Bains, Rapperswil-Jona and Geneva.
Frequently asked questions
Do you have an office in Solothurn?
We are deliberately a distributed consultancy rather than a network of nameplate offices, so we will not claim a Solothurn address we do not occupy. We deliver into Solothurn remotely with on-site workshops at the stages where presence matters, definition sessions, validation and go-live, and we are explicit about travel in the statement of work rather than burying it.
How much does a Power BI project cost for a Solothurn business?
Discovery is a fixed fee in the low five figures. Build cost follows project size: CHF 15,000 to CHF 40,000 for a small project of three to six weeks, CHF 40,000 to CHF 120,000 for a medium one of six to twelve weeks, and CHF 120,000 to CHF 400,000+ for a large platform running three to six months. What moves a project between bands is the number of source systems and their state, not the number of reports. Running it afterwards costs CHF 3,000 to CHF 8,000 a month for a small estate, CHF 8,000 to CHF 20,000 for a mid-sized one, CHF 20,000 to CHF 50,000+ for a large multi-domain platform. We give a written estimate range before discovery and a fixed price after it, because an estimate based on an average rather than on your data is worth very little.
Which industries in Solothurn do you work with?
The local mix means most of our Solothurn work sits in precision engineering and instrument makers, medical device manufacturers, and public bodies and agencies. We publish what we expect to find in each sector, the metrics, the source systems and the specific traps, so you can judge whether we understand your business before the first call.
Can you work with the Power BI estate we already have?
Yes, and it is usually the cheaper route. We begin with an estate review: which models are worth keeping, which should be consolidated into a shared semantic model, and which can be retired because nobody has opened them in six months. A full rebuild is occasionally correct, but it should be a conclusion rather than a starting assumption.
Do we need Fabric capacity, or will Power BI Pro do?
The arithmetic that matters: F64 only becomes cheaper than per-user licensing somewhere in the region of 350 to 600 readers, depending on the discount you actually pay and whether you reserve capacity. Below that, Pro or PPU per user is normally the right answer, and buying capacity for prestige is a straightforward waste of money. For most organisations of the size typically found in Solothurn, per-user licensing is cheaper and will stay cheaper. We model your actual reader mix and give you the break-even point in writing.
How long does it take to get a project started in Switzerland?
Eight to twenty weeks. Financial services onboarding alone can take two to three months before any work starts. The variable is rarely the commercial negotiation. It is supplier onboarding, security review and, where it applies, works council or outsourcing committee consultation. We publish our entity details, insurance, processing agreements and contracting shapes on the procurement page so your buying team can begin that in parallel rather than afterwards.
Who owns the work when the project ends?
You do, in a form you can change without us. Everything is scriptable and versioned, the naming is documented, the measure dictionary records intent, and the enablement sessions happen during delivery rather than as a handover event at the end. Exit assistance is written into every agreement rather than negotiated at an awkward moment.
Read next
Data governance and GDPR for Solothurn organisations: controls that produce evidence
Practical data governance for analytics estates in Solothurn: what the Federal Data Protection and Information Commissioner (FDPIC / EDÖB) expects under the revised Federal Act on Data Protection (revFADP / revDSG), in force since September 2023, the sector rules that bite locally, Microsoft Purview in practice, and a 90-day plan.
Microsoft Fabric and Azure data platforms in Solothurn: architecture, capacity and cost
How to build a Microsoft Fabric or Azure data platform for a Solothurn organisation: medallion layout for precision engineering and instruments and medical devices, honest capacity sizing, Direct Lake trade-offs and the Switzerland residency position.
Power BI licensing in 2026: Pro, Premium Per User or Fabric capacity, with the break-even arithmetic
The honest comparison of Power BI Pro, Premium Per User and Fabric capacity: what each one actually includes, where the break-even point sits, and the four ways organisations overspend.