Data modelling
We bring data from your shop, ERP, accounting and CRM into one shared model – with unambiguous definitions, so that “revenue” means the same thing in every report.
Data-driven decision models and strategies
Business Analytics
Before AI can make good suggestions, you need clean numbers. As a business analyst, senior business analyst and pricing manager in e-commerce, I spent years building reporting systems, forecasting models and dynamic pricing systems. I bring that experience to your company.
In detail
What this service actually covers
Predictive analytics
Forecasting models for revenue and inventory, demand estimates and early-warning signals. Not as a black box, but with transparent assumptions you can challenge.
Decision support and KPI tracking
Dashboards and automated reports showing exactly the metrics you steer by – complemented by AI-generated summaries that explain anomalies in plain language.
Process
How we work together
- 1
Define questions
Which decisions should the numbers support?
- 2
Data foundation
Connect, clean and define your sources.
- 3
Model & report
Build and validate forecasts and KPIs.
- 4
Automate
Reports run on their own, with AI commentary.
From practice
Where I have built this myself
FAQ
Frequently asked questions
How much data do we need for forecasts?
For robust revenue or inventory forecasts, one to two years of history is usually sensible. More important than volume, though, is that the data was captured consistently – which is what we check first.
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Ready to streamline your processes with AI?
In a no-obligation first call we look at how your business runs today and identify the two or three places where AI pays for itself fastest.