Foundation • Activation • Acceleration

Four products. You decide after every step.

Each one is scoped to a single department, a single data model and a single report. That is the size at which figures can be reconciled, owners can be named and your own team can take over. Everything we build stays in your tenant and is yours to run and change. The free readiness check below takes twelve questions and tells you which of the four to start with.

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The progression

Each package ends somewhere you could stop.

  1. Step 1

    Foundation

    Know where the numbers stand.

    An expert review of the metrics, the model and the reports you already have: what holds, what does not, and what to fix first.

  2. Step 2

    Activation

    Turn them into a decision.

    One governed model with agreed definitions, and reporting aimed at a question someone has to answer rather than at the data that happened to be available.

  3. Step 3

    Acceleration

    Put AI on top of both.

    An assistant reading a model whose definitions are fixed, so the same question returns the same answer.

Most engagements start at Foundation and some stay there, which is the right outcome rather than an unfinished one. What the tier above inherits is not a licence or a platform, it is a clear account of which figures hold and which need work.

Readiness check

Is your reporting ready for what you want to do next?

Twelve questions about how your data actually works today. No email and no sign-up: the result appears on this page and goes nowhere else.
Questions
12
Minutes
10
Stages
3

Part one of three

Foundation: is the ground solid?

Whether a number means one thing, and whether anyone owns that meaning.

  • Question 1 of 12

    Do revenue, margin and headcount mean the same thing in every report your leadership sees?

  • Question 2 of 12

    Can you name the person, not the department, who is allowed to change the definition of a core KPI?

  • Question 3 of 12

    Can every report showing financial figures be reconciled to the statutory accounts without a manual step?

  • Question 4 of 12

    If a number looks wrong, can someone trace it back to the source system and the load that produced it within an hour?

Part two of three

Activation: is any of it being used?

Whether the reports you built change what anyone does on a Monday.

  • Question 5 of 12

    Do you know how many of the reports in your workspace were opened in the last ninety days?

  • Question 6 of 12

    Can you name a decision that was made differently last quarter because of a report?

  • Question 7 of 12

    When someone in the business needs a new view, can they build it themselves from a governed model, without raising a ticket?

  • Question 8 of 12

    Does a refresh failure reach a named person rather than a shared mailbox?

Part three of three

Acceleration: could AI safely touch this?

Whether an assistant answering from your data would be right, and whether you would know if it were not.

  • Question 9 of 12

    Is there one semantic model per steering area, rather than one per report?

  • Question 10 of 12

    Are your KPI definitions written down somewhere a person, or a machine, can read them, outside the DAX?

  • Question 11 of 12

    Would an AI assistant querying your model be bound by the same access rules as the person using it?

  • Question 12 of 12

    If an AI answered from your data today and was confidently wrong, would anyone notice before the decision was made?

01/03

Foundation Review

A second opinion on the reporting you already have.

In two weeks you know what is right, what is wrong, what is risky, and what to do first.

  • What you have
  • What you get back
The fix-first list: ten items in order, each with the area it touches, what to fix, an effort in days and an owner on your own team.A spreadsheet of record for quarterly revenue, with three disagreeing revenue columns, formula errors, hidden rows, a total typed by hand, seven competing source files and two different answers for the same quarter.
The reporting as it stands, and the list it ends in. Every owner on the right is someone on your team.

Who it is for

Teams where people do not fully trust the reports, where two reports show two different numbers for the same thing, and where nobody can say who owns the definition of a key figure. It also fits when you are planning a larger investment or an AI initiative and want to know whether the foundation carries it, or when you have just inherited reporting from a consultant or a colleague who left.

At a glance

Duration
2 weeks
Our effort
5 days of our time
What it costs

What you receive

Findings report
What is right, what is wrong and what is risky, written for your team rather than for us.
Reconciliation evidence
Three to five key figures compared with their source, with every difference explained.
KPI definition check
Which figures are defined twice, which ambiguously, and which nowhere at all.
Model, refresh and security check
Structure, performance, how reliably the refresh runs, and who is able to see what.
Takeover readiness score
How easily your own team could change and maintain what exists today.
Fix-first list
At most ten items, each with an effort, an owner and a how-to, so it can be worked without us.

What is in scope

  • One department’s reporting: one data model, the reports built on it, up to five, and the sources feeding it, up to three.
  • Read-only throughout. We change nothing in your environment.
  • Interviews with three people: the report owner, one KPI owner, and your IT or data contact.

How the 2 weeks run

  1. Before · order and accessRead-only access is requested and confirmed on day zero. The clock starts when it is confirmed, not when the order is signed.
  2. Week 1 · read and reconcileThree to five key figures are compared with their source and every difference is explained, which is what turns an opinion into evidence.
  3. Week 2 · findings and readoutThe findings report, the fix-first list and the roadmap, walked through with your sponsor in the room.

What you bring

  • Read-only access on day zero, arranged before we start rather than during.
  • A report owner, one KPI owner and an IT or data contact, about two hours in total in week one.
  • The report you trust most, which is what we reconcile against.
  • A sponsor at the readout in week two.

What follows

You can act on the report yourself, since every finding carries an owner and a how-to. Or an Activation Sprint fixes the first thing properly, or Reporting Stewardship keeps what already works from drifting. Stopping here is a real option and some do.

Talk about a Foundation Review

02/03

Activation Sprint

One department, one data model, one report your team runs its meeting on.

Six weeks, with a clickable prototype in week one so you react to something you can open rather than to a description.

  • The KPI brief
  • The runbook
A runbook: five numbered steps for a failed morning refresh, and an escalation table naming who acts on what and within how long.A KPI brief for gross margin: definition, formula, source, owner, threshold and the reaction the threshold should trigger.
Two of the things that stay behind: every figure defined, and the procedure your own team runs it on.

Who it is for

A department drowning in Excel, where a decision needs numbers nobody trusts. It also fits when you want to start with BI properly but small, and see a result before committing further, or when a Foundation Review has told you what is wrong and you want the first thing fixed properly. Either way, your own people should be able to run and change the result afterwards.

At a glance

Duration
6 weeks
Our effort
about 18 days of our time
What it costs

What you receive

A governed data model
In your tenant, in your repository, documented.
One production report
Up to five pages, with a page explaining how to read the report.
KPI briefs
One per figure in your KPI Library: definition, formula, source, owner, threshold and the reaction it should trigger.
Reconciliation evidence
Every KPI against its source or the report you trusted before, differences explained.
Documentation
Model, sources, refresh and permissions, plus a runbook for the three situations that come up most.
Enablement
One recorded thirty-minute session per user group, so a new joiner next year still gets it.

What is in scope

  • One department, one decision and the questions underneath it.
  • One governed data model, in your tenant and in your repository.
  • One report of up to five pages, up to ten KPIs, up to three source systems and up to two user groups.

How the 6 weeks run

  1. Week 0 · prepareThe charter and the kickoff date: goal, scope, roles, and what each side provides, written down before anything is built.
  2. Week 1 · decide and sketchA two-page requirements sign-off and a clickable prototype on made-up numbers with real structure.
  3. Week 2 · connectAccess is issued and each KPI brief is confirmed by the person who owns that figure.
  4. Week 3 · real numbersThe second version of the prototype, now running on your data rather than on samples.
  5. Week 4 · proveEvery KPI compared with its source or with the report you trusted before, and every difference explained in writing.
  6. Week 5 · acceptA guided hour with your signatory: the test cases, the findings, the decision, confirmed by email.
  7. Week 6 · go live and hand overThe report goes live in your tenant, and your report owner makes a real change with us watching before we call it done.
  8. After · hypercare and checkResponse times for a short period, then a call about how the report is actually being used, and a close-out report.

What you bring

  • A sponsor who decides scope, budget and dates, from week zero.
  • A project contact for the day-to-day questions, from week zero.
  • Your IT contact issues access by day three of week two.
  • One owner per KPI, a person rather than a department, ten minutes each in week two.

What follows

Reporting Stewardship keeps the numbers right and extends the report within a monthly budget while your team owns it. Or the next department gets its own sprint, which is shorter and cheaper because the access, the standards and the client pack already exist.

Talk about an Activation Sprint

03/03

Acceleration Pilot

One AI use case on a data model you trust.

Tested with your own people, measured rather than estimated, and at the end you decide whether to scale.

  • The guardrails
  • The measurement
An illustrative results table: answers correct, refused and wrong against a fixed test set, time to answer before and after, and users still using it in week eight, each with the method beside it.A guardrail configuration in three columns: what the assistant may query, what it refuses, and what is logged.
What the pilot is held to, and how it is measured. The figures on the right are an example rather than a client’s result.

Who it is for

Organisations whose management is asking what AI can do with their data and who want an answer with numbers rather than a demo. It also fits when users already ask an AI assistant questions and the answers do not match the reports, or when you have a governed model from a sprint or a clean review and want to put it to work.

At a glance

Duration
8 weeks
Our effort
about 20 days of our time
What it costs

What you receive

A working pilot in your tenant
For the named users, on the guardrails you agreed.
Pilot brief
Use case, success criteria, guardrails, users and licences, agreed in week one.
Test set and results
Accuracy, time saved and adoption, measured rather than estimated, and the test set stays with you to measure again.
Guardrail configuration
Documented: what the assistant may query, what it refuses, and what is logged.
Pilot results report
What worked, what did not, and what it would cost to scale.
Recommendation and scale plan
With a price on it, so the decision is yours to make rather than to ask for.

What is in scope

  • One use case, on one governed model that already exists.
  • Five to ten named pilot users, who are the ones who judge whether it works.
  • Guardrails: the assistant sees what the user may see and no more, what it must refuse, and what is logged.

How the 8 weeks run

  1. Week 1 · frameThe pilot brief: use case, success criteria, guardrails, users and the licences it needs. Agreed before anything is built.
  2. Weeks 2–3 · buildA working pilot in your tenant, ready for internal testing.
  3. Weeks 4–5 · test with your peopleFive to ten pilot users, two hours each, and their findings rather than ours.
  4. Weeks 6–7 · measure and hardenAccuracy, time saved and adoption, measured against the test set, and the guardrails tightened where the test found a gap.
  5. Week 8 · decideThe results report, a recommendation with a price on it, and the handover pack. The decision is yours and “no” is a legitimate one.

What you bring

  • A governed model before the order: a completed sprint, or a review without open blockers.
  • A sponsor, an IT contact and a data-protection contact in week one, about two hours.
  • Five to ten pilot users, two hours each in weeks four and five.
  • The licences listed in week one, in place before week two.

What follows

Scale-out, one department at a time, planned and priced in the results report. Or Reporting Stewardship runs alongside the pilot and keeps the model it reads from drifting while your team owns it. Where the pilot does not clear the bar, the report says so and names what would have to change first, which is Foundation work and is quoted in stages.

Talk about an Acceleration Pilot

Runs alongside

Reporting Stewardship

Your team owns the reports. We keep the numbers right.

A fixed monthly budget, response times in writing, and changes planned and released once a month.

Who it is for

Teams whose review, sprint or pilot is finished and who want it to stay right. It fits a BI team that is small, or that is one person, and cannot cover peaks, second opinions and change requests at the same time. It also fits anyone who wants a fixed monthly cost and response times in writing rather than a consultant on call by the hour.

At a glance

Duration
monthly, 3-month minimum
Our effort
8, 16 or 32 hours a month
What it costs

What you receive

Response times in writing
A blocker gets a response the same working day, a major issue within two working days, and a minor one lands in the next monthly release.
Monthly health check
One page: refresh, reconciliation spot check, usage, open items and hours used.
Changes released once a month
Planned with your report owner, and delivered within the hours of your tier.
Second line for your report owner
Your person stays first line and keeps learning, which is the point rather than a side effect.
Quarterly review
Backlog, roadmap, and whether the tier still fits what you actually use.
Documentation kept current
Every change updates the handover pack and the KPI Library, so leaving never needs a project of its own.

What is in scope

  • The models and reports named in your client pack, rather than everything you own.
  • Change requests: a new measure, a page, a filter, or a field from a source that is already connected.
  • A monthly health check: refresh success, a reconciliation spot check of three key figures, usage and open items, on one page.

How a month runs

  1. Week 1 · set upThe stewardship agreement: which models and reports are covered, who your report owner is, and what counts as a blocker.
  2. Each month · requestsChanges are planned once a month with your report owner and delivered within the hours of your tier.
  3. Each month · health checkOne page on refresh, a reconciliation spot check, usage, open items and the hours used.
  4. Last week · releaseOne release a month with a release note, so nothing changes under your users without warning.
  5. Quarterly · reviewThe backlog, the roadmap, and an honest look at whether the tier still fits. Moving down is as normal as moving up.

What you bring

  • A report owner on your side who stays first line, from week one.
  • Priorities once a month, which takes about twenty minutes.
  • Access kept current, so a blocker is not waiting on a permission.

How it ends

Monthly, after the minimum term, with thirty days’ notice, and the handover pack is brought up to date at exit at no cost. A retention product that is hard to leave is a retention product nobody should sign.

Talk about Reporting Stewardship

Handover by design

Built to be taken over.

Most reporting projects end with a vendor who is the only one who understands how the thing works. We treat that as a defect and design against it from day one. These six commitments are in every offer and every charter, so your team can take over after any of the four products rather than only at the end.
Everything lives in your tenant.
Models, reports and data stay in your Microsoft environment, under accounts you issue. We host nothing of yours.
You receive the source of everything.
Model and report files in your repository, the KPI Library, the documentation. Nothing sits only on our side.
Standard Microsoft features only.
No custom tooling you would depend on us for. Anyone who knows Power BI or Fabric can pick it up.
Documentation is a deliverable.
Model documentation, KPI briefs, a runbook and a guide to reading the report, each with its own acceptance.
Your report owner makes a real change before we leave.
A measure changed, a page published, a user added, by your person, with us watching. If they cannot, we are not done.
Leaving is free.
Reporting Stewardship cancels monthly after the minimum term, and the handover pack is brought up to date at exit at no cost.

Selected engagements

Five engagements that ran this way.

These five name the tiers they went through, so you can read the case that matches the product you are considering. They are anonymised by sector and size, each is written out in full on a page of its own, and seven further engagements sit alongside them under case studies.

  • Retail

    Foundation then Activation then Acceleration alongside Stewardship

    Store revenue, executive questions and forecasting on one set of definitions

    A retailer with Microsoft Fabric already in production, semantic models over Direct Lake and store revenue streaming in, who wanted forecasting, Copilot questions and anomaly detection on top of it.

    • Microsoft Fabric
    • Power BI semantic models
    • Direct Lake
    • Copilot in Power BI
    • Fabric AI Functions
    • Activator

  • Industrial manufacturing

    Foundation then Activation then Acceleration

    Governed reporting across a production network

    An industrial manufacturer reporting across a production network of sites, each with its own view of what was running.

    • Microsoft Fabric
    • OneLake
    • OneLake Security
    • Direct Lake
    • Spark
    • MES
    • OPC UA
    • Power BI
    • DAX
    • Azure Key Vault
    • Purview
    • Azure DevOps

  • Hospitality and real estate

    Foundation then Activation

    A CFO cockpit over a group that closed its books separately

    A holding group across hospitality and real estate, with entities that each closed their own books and a CFO who had to answer for all of them.

    • Microsoft Fabric
    • OneLake
    • Direct Lake
    • Databricks Mirrored Catalog
    • Fabric Data Factory
    • Power BI
    • DAX
    • Calculation groups
    • Row-level security
    • Azure DevOps
    • Azure Key Vault
    • Purview

  • Multi-brand retail

    Foundation then Activation

    One governed model across a multi-brand retail group

    A retail group running several brands, each with its own systems, its own reporting habits and its own answer to what a margin is.

    • Microsoft Fabric
    • Direct Lake
    • Databricks
    • Eventstream
    • KQL Database
    • Power BI
    • DAX
    • SAP
    • Salesforce
    • Azure DevOps

  • Omnichannel e-commerce

    Foundation then Activation

    Finance reporting that keeps up with the day

    An omnichannel retailer whose finance leadership was steering on yesterday’s numbers in a business that changes within the day.

    • Microsoft Fabric
    • OneLake
    • Direct Lake
    • Fabric Data Factory
    • Eventstream
    • Power BI
    • DAX
    • REST APIs
    • ERP integration
All case studies

Who does the work

I spent five years defending these numbers myself.

Before the BI years I spent five years inside controlling, closing books and defending the numbers in them, which is where you learn that a reporting problem is almost never a reporting problem. It is a definition nobody owns. Two people build the same figure from the same system, both are right under rules neither of them wrote down, and the meeting that was meant to decide something opens with a reconciliation instead.

Eleven years of BI consulting across Europe came after that, in Power BI, DAX, Microsoft Fabric and the architecture underneath them. Plenty of people can write the DAX. The part that is scarce is knowing what the number is supposed to mean before anyone writes any, and that is the part I was hired for long before I was hired to build models.

So that question comes first in every engagement, and we run each one end to end, from the first call through to handover, so you are never explaining your business twice.

Niklas Hoeppener

Niklas Hoeppener

Founder • Ariavor

Eleven years
BI consulting across Europe
Power BI • DAX • Microsoft Fabric
And the data architecture underneath them
Remote, worldwide
For companies in Europe and beyond
English and German
Engagements run in either

Scope and price

The questions that come up first.

Is the price really fixed?

The Foundation Review is a fixed figure and it does not move. The Sprint and the Pilot start from a figure and are fixed after a 60-minute scoping call, after which they do not move either unless you change the scope, and then you see the effect before you decide. Every figure, and every condition attached to one, is written out on the pricing page rather than discovered later.

What if we want to stop afterwards?

Then you stop. Each package ends in a document and a staged plan you can hand to your own team or to another firm, everything we built sits in your tenant under your accounts, and Reporting Stewardship cancels monthly after the minimum term. That is the design rather than a concession.

What if our data turns out to be a mess?

It usually is somewhere, and none of the packages can be blocked by that. Finding out precisely where is the deliverable, which is why the work that genuinely depends on your data gets quoted after we have looked rather than before.

Free consultation

Know where your data stands in an hour.

A free 60-minute consultation. No pitch, no invoice. You’ll leave knowing whether your data is ready for AI, and whether we’re a good fit.

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