polito.it
Politecnico di Torino (logo)

The Influence of PMIS-IT System Integration on Project Efficiency and Collaboration

Negar Nazari

The Influence of PMIS-IT System Integration on Project Efficiency and Collaboration.

Rel. Alberto De Marco, Massimo Rebuglio. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management), 2024

[img]
Preview
PDF (Tesi_di_laurea) - Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives.

Download (1MB) | Preview
Abstract:

This thesis explores project management information system (PMIS) when integrated into other available software tools and information technology (IT) systems to enhance overall effectiveness in project management, communication, and data flow, particularly in com-plex and multi-stakeholder projects. A systematic literature review (SLR) was carried out for the present study using the Preferred Reporting Items for Systematic Reviews and Me-ta-Analyses (PRISMA) framework to ensure completeness and a structured approach in analysis. The integration categories that are emphasized include collaboration and commu-nication platforms, integrated analytical and decision-making support tools, and integrated resource and process management systems. The integration of these features can improve project coordination and interoperability among remote or geographically dispersed teams through real-time data sharing. This reduces data re-entry, allows for informed decisions based on insights from data, hence giving the teams options that lead to optimized resource allocation and risk mitigation. The findings show that PMIS integrations organize data and eliminate information bottle-necks, allowing increased transparency for project teams. Even with such advantages, a couple of those limiting factors have been indicated in the present literature, which apparently fails to engage with the studies concerning the longer-term impact of PMIS integration. Secondly, even with the new functionalities introduced by the smart project management information system (SPMIS) solutions (van Besouw & Bond-Barnard, 2021), very little integration of AI and ML is found, which can elevate the capabilities of PMIS. The integration of artificial intelligence (AI) and machine learning (ML) with PMIS opens up new possibilities for predictive analytics and automation capabilities. Such develop-ments have the potential to aid project managers in determining various risks, optimizing resource distribution, and making readjustments with a view of meeting very dynamic pro-ject demands and continuous change. This study gives industry practitioners practical in-sights on how to leverage integrations for PMIS in order to enhance project performance, especially in those sectors where effective coordination, data management, and timely de-cision-making are crucial for success.

Relatori: Alberto De Marco, Massimo Rebuglio
Anno accademico: 2024/25
Tipo di pubblicazione: Elettronica
Numero di pagine: 44
Soggetti:
Corso di laurea: Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management)
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-31 - INGEGNERIA GESTIONALE
Aziende collaboratrici: NON SPECIFICATO
URI: http://webthesis.biblio.polito.it/id/eprint/34192
Modifica (riservato agli operatori) Modifica (riservato agli operatori)