Use your data to see what is coming.
We build predictive models for demand, pricing, maintenance and churn, and put them where decisions are made.
Planning still relies on last year plus a percentage.
Demand is forecast in spreadsheets, maintenance follows the calendar and price changes are based on experience. It works, until the market moves.
The data to do better is usually there; the models and the skills to use them are not.
A good model is not the most advanced one. It is the one people trust and use.
Data science creates value when the prediction lands in the right process: the planner's screen, the price tool, the service schedule. And when people understand why the model says what it says.
We start simple, prove the value on real decisions and only add complexity where it pays.
From one valuable decision to a model in daily use.
- 01
Pick the decision
The planning or pricing decision where a better prediction is worth most.
- 02
Prepare the data
Historical data collected, cleaned and enriched with relevant external data.
- 03
Build and test the model
Models tested against what actually happened, explained in plain language.
- 04
Put it in production
Predictions delivered into daily tools, monitored and retrained over time.
What you hold at the end
- 01
A working model
Predictions tested on your own history.
- 02
Predictions in daily tools
Where planners, sellers and service teams work.
- 03
Ongoing monitoring
Models kept accurate as conditions change.
Talk to a partner, not a sales team
Bring the forecast you would most like to improve. Marco Bjørslev Jensen, Founding Partner, takes the call.
Marco Bjørslev Jensen
- 01Tell us where you are
A few lines are enough. No brief needed.
- 02Marco gets back to you
Personally, not through a sales team.
- 03A first conversation
About where you are and where to start.