Curriculum
Computer Science and Innovation for Societal Challenges, XXXVI series
Grant sponsor
Estilos S.r.l.
Supervisor
s
Fabio Aiolli
Co-supervisor
s
Anna Spagnolli
Contact
andrea.montagna@studenti.unipd.it

Project description
The current market situation does not provide solutions capable of generating value through the information and data collected by an Enterprise Collaborative Network. Social network analysis solutions exist but are not part of the business enterprise context: the specificity of these solutions dedicated to general-purpose architectures sometimes preclude the benefit of tailor-made analysis. Finally, it is not possible to have an objective and analytical vision of the company's internal processes without exploiting unstructured data: elements such as goal setting, team composition, deadlines, plans and KPIs establish interactions between people. The project aims to create a technological and process model for increasing the efficiency rate within an enterprise collaborative network by extracting value from all the interactions that take place within projects, teams, meetings. The data obtained will allow the creation of a model that will be able to analyze bottlenecks and delays, intervening before they have a chance to repeat. This model will use structured and unstructured relationship data to feed artificial intelligence algorithms and train neural networks. The information will be immediately usable by company management and decision-makers through an analytical platform: the easy-to-use software will reduce the time to access these data and information to make better and informed decisions. Management people will access to analysis and monitoring tools to manage different aspects such as process and team-work efficiency, skills detection, analysis of sentiment and discussion topics.