The application of Artificial Intelligence (AI) algorithms is becoming more and more widespread in a variety of fields. While at the beginning it was matter of purely academical research, in the last twenty years it has become source of development and competitive advantage for companies and industries. Previous searches have already shown the effectiveness of the AI application in project management (PM) and more specifically in project portfolio management (PPM). In a world of limited resources, the ability of selecting and managing the most appropriate projects to achieve desired outcomes is becoming fundamental. As a consequence, being able to forecast successful options from a bucket of candidate projects becomes source of sustainable competitive advantage for businesses and firms. Other than the aforementioned skills, this study is concerned with the understanding of the real meaning of the word “success” depending on the different stakeholders’ views existing in project-based industries. At the same time, this study will propose a literature review concerning those factors able to link projects with final successful outcomes. These critical success factors (CSF) will be implemented in a case study realized thanks to the partnership with a simultaneous multi-projects company (Capgemini). In this application, qualitative judgements given by experts, will be assessed to create a reliable model of success prediction. The subjectivity that by nature is associated with qualitative opinions will be managed through the application of fuzzy logic. Being aware of the importance of the figures used to model AI algorithms, an innovative data-augmentation process will be proposed, transforming fuzzy logic evaluation in probabilistic distributions. The final objective of this study is to understand whether it is possible to implement a new project portfolio development model able to integrate potentials of AI algorithms, standard PM processes (PPM) and Fuzzy logic.
L'applicazione di algoritmi di Intelligenza Artificiale (AI) è sempre più diffusa in una varietà di campi. Se all'inizio si trattava di ricerca puramente accademica, negli ultimi vent'anni è diventata fonte di sviluppo e vantaggio competitivo per aziende e industrie. Studi precedenti hanno già dimostrato l'efficacia dell'applicazione di AI nella gestione dei progetti (Project Management) e più specificamente nella gestione del portfolio di progetti (Project Portfolio Management). In un mondo di risorse limitate, la capacità di selezionare e gestire i progetti più appropriati per raggiungere i risultati desiderati diventa fondamentale. Di conseguenza, essere in grado di prevedere opzioni di successo da un insieme di progetti diventa fonte di vantaggio competitivo sostenibile per le imprese. Oltre alle competenze di cui sopra, questo studio riguarda la comprensione del vero significato della parola "successo” quando diverse opinioni delle parti interessate si incontrano in industrie project-based. Allo stesso tempo, questo studio proporrà una revisione della letteratura riguardante quei fattori in grado di associare progetti con risultati finali di successo. Questi fattori critici di successo (Critical Success Factors) saranno implementati in un case-study realizzato grazie alla partnership con una società simultaneous multi-projects based (Capgemini). In questa applicazione, verranno valutati i giudizi qualitativi forniti da esperti al fine di creare un modello affidabile di previsione del successo. La soggettività che per natura è associata alle opinioni qualitative sarà gestita attraverso l'applicazione della logica Fuzzy. Consapevoli dell'importanza delle figure utilizzate per modellare gli algoritmi di AI, verrà proposto un innovativo processo di data-augmentation trasformando la valutazione della logica fuzzy in distribuzioni di probabilità. L'obiettivo finale di questo studio è capire se sia possibile implementare un nuovo modello di sviluppo del portfolio di progetti in grado di integrare le potenzialità di algoritmi di intelligenza artificiale, processi di gestione di progetti standard (PPM) e logica Fuzzy.
Project portfolio development and artificial intelligence : a new framework applied in simultaneous multi-project based companies
Rossi, Francesco;Palmieri, Luca
2020/2021
Abstract
The application of Artificial Intelligence (AI) algorithms is becoming more and more widespread in a variety of fields. While at the beginning it was matter of purely academical research, in the last twenty years it has become source of development and competitive advantage for companies and industries. Previous searches have already shown the effectiveness of the AI application in project management (PM) and more specifically in project portfolio management (PPM). In a world of limited resources, the ability of selecting and managing the most appropriate projects to achieve desired outcomes is becoming fundamental. As a consequence, being able to forecast successful options from a bucket of candidate projects becomes source of sustainable competitive advantage for businesses and firms. Other than the aforementioned skills, this study is concerned with the understanding of the real meaning of the word “success” depending on the different stakeholders’ views existing in project-based industries. At the same time, this study will propose a literature review concerning those factors able to link projects with final successful outcomes. These critical success factors (CSF) will be implemented in a case study realized thanks to the partnership with a simultaneous multi-projects company (Capgemini). In this application, qualitative judgements given by experts, will be assessed to create a reliable model of success prediction. The subjectivity that by nature is associated with qualitative opinions will be managed through the application of fuzzy logic. Being aware of the importance of the figures used to model AI algorithms, an innovative data-augmentation process will be proposed, transforming fuzzy logic evaluation in probabilistic distributions. The final objective of this study is to understand whether it is possible to implement a new project portfolio development model able to integrate potentials of AI algorithms, standard PM processes (PPM) and Fuzzy logic.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/183832