Most companies today have no shortage of data. What they lack is clarity about what that data means — and what to do next.
Analyses are produced, dashboards are filled, reports are sent out. But when it comes to making a concrete decision — steering a campaign, prioritizing a product, shifting a budget — the question remains open: what is the data really telling us?
Closing this gap between analytical output and decision is the core of my consulting work.
What is decision support through data analysis?
Decision support means backing a specific business decision with analysis — using the right method, the right data and a clear interpretation of the results.
This typically includes:
Analyzing a concrete business question (pricing, customer segmentation, resource allocation, market entry strategy).
Preparing and evaluating relevant datasets.
Assessing courses of action based on the analysis.
Communicating the results in a form that decision-makers can understand.
When is this the right service?
Decision support makes sense when:
an important decision is coming up that has so far been based on intuition or unstructured information;
an analytical project is complete, but it is unclear what the results actually mean;
you need an external, methodologically independent perspective on a question;
internal analytical capacity is missing or limited in time.
My approach
1. Define the decision frame
What exactly is being decided? Who decides? What are the alternatives, and which information would genuinely change the decision? These questions come before the analysis — not after.
2. Analysis
Depending on the question: exploratory data analysis, statistical modeling, segmentation, scenario calculation or experiment evaluation. The method is determined by the problem, not by the available tools.
3. Interpretation
Results are not presented as isolated numbers but interpreted in the context of the original question: What does this mean? What does it not mean? Where are the limits of the analysis?
4. Recommendation
Where the data allows, I formulate a concrete, actionable recommendation — with reasoning and explicit assumptions. When the data does not provide a clear answer, I say so plainly — and explain which information would increase confidence in the decision.
Typical use cases
Customer segmentation: Which customers are most valuable? Which segments are growing, which are eroding?
Price analysis: How does demand respond to price changes? Where is the optimal price for a product or segment?
Resource allocation: Where is further investment worthwhile? Which channels, products or regions are performing below their potential?
Ad hoc analysis: A one-off assessment of a specific data question — fast, structured, action-oriented.
Who I work with
My clients are managing directors, division heads and strategic decision-makers in mid-sized companies and startups in the EU who need analytical support for a specific question — without a long-term consulting contract. I work project-based or hourly — remote or on-site in Berlin.
Further reading
The 7-Step KPI Blueprint from Business Intelligence Analytics Perspective — how metrics and decision frames are built systematically.
BI System Blueprint — an overview of the architecture of a complete decision support system.
Let’s discuss your project
Are you facing a concrete decision and want to back it with analysis — or do you have analyses in hand and want to know what they mean?
Pricing & Packages
- Fixed scope, defined in advance
- 1–2 weeks duration
- 1 revision round
- Summary deliverable document
- Post-delivery support
- Iterative collaboration
- Complete project with iterations
- 3–6 weeks duration
- Unlimited revisions within scope
- Full documentation & handover
- 2 weeks post-delivery support (async)
- Ongoing monthly support
- Monthly, min. 3 months
- Continuous iterations
- Living documentation
- Priority access
- €90/h for additional work
- Monthly review call
Hourly rate for ad hoc requests: €90/h. All prices plus VAT.