Analysis process

Operational data preparation

This view shows how raw company data is checked before forecasting and anomaly analysis. Date alignment, missing periods, KPI definition and data availability are verified before any model result is published.

Operion AI first determines whether data is suitable for decision-making, then compares a simple reference method with model results for the selected KPI.

01

Define the operational question

02

Check the historical record

03

Compare against a reference

04

Publish only validated findings

Target KPI definition

The outcome to be forecast or reviewed is explicitly defined.

Time alignment

We check whether records were genuinely available during the relevant period.

Missing-data review

Empty, duplicate and inconsistent periods are identified.

Model publication threshold

Only validated results that exceed the reference method are shown.

Private data pilot

Start with one operational KPI.

A read-only pilot begins with a structured data review and a documented evaluation boundary.

Discuss a private-data pilot