Melanie L.

Implementation of an artificial intelligence tool to reconcile sell-out data with a product repository, using semantic analysis and language models (LLM).

This project served as the foundation for defining, in collaboration with architects, the future target architecture to support and industrialize upcoming AI projects.

Scoping of a matching project between sell-out data and the product repository: requirements gathering, analysis of incoming data, and definition of the functional and technical framework for the model.

I participated in a strategic project within Airbus Helicopters aimed at standardizing, automating, and ensuring the reliability of performance indicators (KPIs) used in the group's highest decision-making committees.

Project Objective:

The main objective was to build a common repository of approximately 200 strategic indicators, shared across Airbus's different production units. This involved ensuring a consistent calculation methodology, reliable data quality, and comparability between entities, while meeting monthly trend and annual objective requirements for each KPI.

Role Played:

- Definition of KPIs in direct collaboration with operational business units

- Identification and extraction of source data in a complex environment

- Implementation of calculation rules and indicator refresh frequency

- Monitoring of evolution requests and change management support for users

- Implementation of security rules to ensure data confidentiality according to access levels

Results Achieved:

- Standardization of indicator calculation methods across Airbus units

- Transition from a manual, scattered, and error-prone process to an automated and centralized system

- Over 200 strategic KPIs developed, now used by hundreds of employees, up to the highest levels of management

- Improved reliability, transparency, and responsiveness in industrial activity management

- Successful adoption of new digital tools by business teams