Decision Support for Interoperability readiness in Networked Enterprises

The obligation to become more competitive and effective in providing better products and services requires enterprises to transform from traditional businesses into networked businesses. The project deals with transformations related to enterprise interoperability. The objective is to help organizations planning their interoperability transformations in order to facilitate the transition from an AS-IS situation to a TO-BE one; and prevent interoperability and transformations problems before they occur. The objective of this PhD research aims to focus on providing a foundation for understanding, designing and planning transformations with regards to interoperability within a network of enterprises. Transformations in this context are driven by interoperability problems that an enterprise may face. In light of these, various issues remain open and will be the subject of research in this project:
– How to help an enterprise to plan interoperability transformations in the context of networked enterprises? In other words, how to help an enterprise to increase its interoperability readiness and its capacity to adapt within a changing environment?
– One of the implications of the previous research question touches upon the capacity of the enterprise to solve interoperability issues and raises one new question: How to diagnose or predict interoperability potential problems and plan transformations in networked enterprises (NE)?

The major contribution of the PhD project, beyond the current state of the art, can be summarised as follows:
• Definition of a new framework for enterprise transformation interoperability, which will support stakeholders, architects and engineers of business services in their understanding, design, assessment, decision making and engineering tasks.
• Development of a prototype for the monitoring and decision support for enterprise interoperability transformation in networked enterprises.

The candidate must demonstrate motivation, self-structure and responsibility as well as ability to work independently. He/she should have (or soon receive) a Master’s degree in computer science/engineering, informatics, or related fields. Programming skills are mandatory. Excellent education in decision support and reasoning engines is considered as an asset. Fluency in English for scientific exchanges is mandatory.