MultiBase GmbH

MultiBase GmbH MultiBase GmbH
Business Intelligence Consultancy Es kommt darauf an, sich von anderen zu unterscheiden; ein Engel im Himmel fällt niemanden auf." Unmöglich!

(George Bernard Shaw)
Die „MultiBase“ GmbH lässt sich einfach nicht zu einem 0-8-15 Unternehmen, auf dem Business Intelligence Markt von morgen, degradieren! Utopisch! Indiskutabel! Warum?! Darum:..Unsere Mitarbeiter geben stets ihr Bestes! Nicht nur für die Firma, auch für die Kollegen steht Man(n) hier gerne ein!
…Unser Motto: „MultiBase: working together to win“..21 dynamische, kreative u

nd jederzeit hilfsbereite sowie engagierte Mitarbeiter, das ist MultiBase! We already won the war for talents:

Das Patentrezept für unser TOP Unternehmen:
• Man nehme ein großes Stück von unorthodoxem: eine Kleiderordnung? Fehlanzeige! Zumindest intern gilt: geht nicht, gibts nicht! Hier gibt es beinahe alles: Steckdose, Metall, Lacoste, Baggy & Co
• 500 gramm flache Hierarchien
• eine große Scheibe von Weiterbildungangeboten sowie Trainingsmöglichkeiten
• einige, mehrere cubes, bevorzugt in den Farben: hell türkis bis dunkelblau
• 2 attraktive Standorte, wie Gilching und Timisoara mit ebenso attraktiver deutsch- rumänischer Traumbesetzung
• gänzjährige, zumeist sehr amüsante Zusammenkünfte und tolle Firmenevents
• ein hohes Maß an Heterogenität, Interkulturalität
• 1 Päckchen ethisches Engagement in Form einer Weihnachtsspendenaktion
• Und ein großes Packet randvoll gefüllt mit Kooperationsbemühungen zur Hochschule München
• einen Schwung tiefschwarzer Kettlebells (Gewicht kann dabei leicht variieren), sowie eine hochfrequentierte Dartscheibe lassen und unter der Woche schwitzen!
• Gemischt mit einer Prise Empathie und einem etwas größeren Hauch von Offenheit und Humor..ensteht das, was uns einzigartig macht: das BI Unternehmen MultiBase GmbH

Die MultiBase GmbH steht für so viel mehr, als schnöde Imperative, die auf einer schimmernden Webside annonciert werden, überzeuge dich! Wir machen uns stark für unsere Mitarbeiter und deren Familien UND befinden uns seit geraumer Zeit wirtschaftlich auf einem aufsteigenden Ast! Wir, die Geschäftsleitung, wissen...
Ganz gleich was für ein großer Krieger er ist, ein Häuptling kann die Schlacht nicht gewinnen ohne seine Indianer.

07/08/2026

Your reporting can be completely accurate and still let a problem go unnoticed for weeks.

Accuracy is not always the hard part. Attention is. Seeing a number and recognizing its significance are not the same thing, and the gap between them is expensive.

Picture a standard Monday. The numbers are all there, revenue, margin, cost, sales, every figure correct. A dip in one region is sitting in plain view. Nobody notices, because a report built to show everything often struggles to highlight what matters.

The cause is structural. They try to answer every question at once and therefore direct attention to none in particular. The signal is present and invisible at the same time.

A technically correct dashboard that you scroll past has done little to support your decision.

This is where attention-directing reporting changes the outcome. Instead of waiting for someone to spot the pattern, the system flags what changed, where it changed, and when it needs attention, so the decision gets made on time instead of a month late.

06/08/2026

Put your finance lead and your sales director in front of the same numbers, and they may describe two different versions of the same problem.

This is usually not a people problem. Each person is looking at the business from a legitimate angle. The difficulty is that the report shows the result without helping you locate the cause.

The meeting debates which version of reality is correct instead of deciding what to do about it. Margin is down, but was it pricing? Product mix? Supplier cost? One region falling behind?

Attention-directing reporting does that first piece of work before the meeting begins.

Plan versus actual. Trends over time. Comparisons between teams, regions, products. The conversation then starts with the decision rather than an argument over the numbers.

Increasingly, AI can support this first pass by surfacing likely drivers before anyone has to make the case for them.

When BI produces one shared picture, the meeting gets shorter and decisions are made faster.

See how good reporting can settle the question instead of starting it.

05/08/2026

Most reporting problems do not look dramatic.

They look like a meeting ending with “Let’s come back to this next week.”

The margin change is visible. The unusual account activity is visible. The operational delay is visible. But nobody has enough context or confidence to make the call.

A week later, the same issue returns with a larger number attached.

This is why the value of reporting is not measured only by accuracy. It is also measured by how quickly you can move from noticing something to deciding what to do about it.

The OODA Loop provides a practical way to examine where that speed breaks down.

29/07/2026

If you priced a Business Intelligence project a few years ago and walked away, you did the math right.

Half a million for implementation. Twelve months before anything useful appears. Licensing fees on top, internal people tied up, and a result nobody would guarantee. For a mid-sized company, that was not hesitation. It was sound judgment.

The problem is that verdicts have expiry dates.

AI has collapsed the economics of reporting and analytics, and the collapse did not take a generation. It started about a year ago, and the pace is still increasing, week by week rather than year by year. The project you declined and the project available to you today share a name and almost nothing else.

So the question is no longer, can we afford BI. It is, is our information about BI still true.

28/07/2026

Somewhere in your operations, a pattern is repeating that has never appeared on a report.

It might be small. A fraction of a percent in defects. A schedule that quietly produces rework. A cost that lands in the same place every single week. Small enough that the totals absorb it, regular enough that it compounds year after year.

Monthly reporting is not built to catch this. Totals and averages smooth over exactly the patterns that cost you money, so the numbers look fine while the damage spreads thin across years of data.

Nobody notices, because nobody knows there is a question to ask.

This week's video tells the story of a manufacturer that lived with one of these patterns for five years. No report flagged it. No dashboard showed it. Then proper reporting was introduced, and one signal changed the maintenance schedule of an entire plant.

Most mid-sized companies have never seen what Business Intelligence finds in data they already own. That is the real reason so many still run without it.

22/07/2026

Somewhere in your numbers is a product line you are underselling and a customer who costs more than they pay you.

Both sit in the data you already have. Neither surfaces on its own.

This is the part of Business Intelligence that gets lost in the tooling conversation. A dashboard that does not lead to a decision is not a harmless extra. It absorbs effort and budget and changes nothing, which is a quiet form of damage.

Data turns into profit in exactly two ways: it reveals where you can earn more revenue, or where you can take out cost. That is the whole job.

Your reporting is only the tool that makes these decisions obvious: push this product, step back from a customer who is not profitable to serve.

The gap between seeing a number and acting on it is where profit quietly stays trapped.

So the real test is simple. Which decision did the report change? If the answer is none, the report did not earn its place, however polished it looks. It just became another dashboard that cost you something to build.

21/07/2026

Before you build anything, one question decides whether the project is worth starting. Which part of the data you already hold can actually be turned into profit?

Most BI projects skip that question and spend six to twelve months building anyway. There is a faster way to answer it.

Insight Discovery is a rapid, fixed-scope service that takes one existing dataset and returns decision-ready profit drivers in two to four weeks. It does not begin with a data warehouse. It begins with data you can export today.

The method combines human expertise with AI. From a single decent dataset, that pairing surfaces 50 to 100 potential use cases.

Then it filters honestly. 70 to 80 percent are what we call “so what”: real signals, but nothing you would act on. The value sits in the 20 to 30 percent that make you stop and say, "very interesting.”

These are the golden nuggets, and finding them takes weeks, not quarters.

You find out whether the data holds profit before you commit to building, not a year after.

See how Insight Discovery works and whether your data qualifies: https://offer.multibase.de/insightdiscovery-en

17/07/2026

The most expensive moment in a reporting project is the day you finally reveal the finished dashboard.

In a typical BI project build, the business waits months to see anything real. By then the data is wired, the architecture is set, and the cost of changing direction is enormous. If the report answers a question nobody actually asks, you find out far too late to fix it cheaply.

We solve this with a mockup.

Before a single pipeline is built, the decision-maker gets a PDF of what the final reports will look like, with no real data behind it.

That preview does two things. It surfaces "that's not what I need" in days instead of months, while a change still costs nothing. And it turns a skeptical stakeholder into someone who says "I want this" before the work even starts.

That second part is the quiet one. Reporting only creates value if people use it, and people use what they helped shape.

A mockup costs a day. Building the wrong dashboard costs months.

15/07/2026

15 years ago, if you asked me to define dashboards and reports, I would have said: they visualize data.

That definition is the reason most reporting projects fail.

Think about it. If the goal is to "visualize data" - then a beautiful chart showing last month's revenue by region is a success. Job done. Everyone nods.

But did anyone in that room make a different decision because of what they saw? Did anything change?

My definition today is different. Dashboards and reports are tools to sharpen decisions, drive actions, and monitor the impact of both.

Three words changed everything: decisions, actions, impact.

Because once you define it that way, you stop asking "what data do we have?" and start asking "what decisions need to be made?" You stop building reports that look good and start building reports people actually act on.

The old definition gave us technically perfect projects where nothing changed. The new one gave us projects where the CFO calls after the first month and says: finally, I can prove what I already knew.

Nikolai and I discuss this in this week's video. Link in the first comment.

Agree or disagree?

14/07/2026

When was the last time a report actually changed what you decided?

For years, Business Intelligence was graded on engineering.

Did the pipelines run, did the architecture hold, did the numbers refresh on time, did the reports look right?

By that standard, the work was excellent. The deliverable looked flawless, and clients signed off with a handshake.

Then came the silence. No new questions, no changed meetings, no different actions. Reporting was just used to confirm what everyone already knew.

Cost was visible on the invoice. The real loss was invisible: a business that invested heavily in BI and ran exactly as before.

A report that is technically perfect and operationally ignored is not a neutral result. It is capital spent for no real change in behavior.

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