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Improving SCRUM Project Duration Forecasting through Learning Curve Theory

Elisa Alfieri

Improving SCRUM Project Duration Forecasting through Learning Curve Theory.

Rel. Alberto De Marco, Filippo Maria Ottaviani. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management), 2022

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Abstract:

In the first chapter of my thesis, I speak about the theoretical notions of Project Management, from the traditional methodologies to the more recent ones applied for software development projects, focusing my attention on the SCRUM framework. The second chapter underlines the main different techniques to manage and predict the costs and the duration of a software. Later, I will detail how I applied them in my working experience and I will report the conclusion obtained in their application. In particular: the Earned Value Model, the Burndown charter and the Putnam model. In the chapters regarding the analysis and the results, I’m reporting the direct application of the Scrum methodology during my curricular internship in an IT company, Alten fr. The internship research focuses on the data collected in 6 months of work, in which I was part of an Agile team with the purpose of developing an internal project for the company. The product delivered is a web application used by Business Managers and Human Resources of the company to manage consultants. In this thesis I am not speaking in detail about the end product but about the data I have collected in these months and the application of the Scrum theory in a real working environment. Thanks to these data was possible to study the projects performance in an Agile environment. I apply the different techniques listed before to forecast duration and cost in the project I worked on. In addition, I propose a model based in the Putnam theory but that takes into consideration the Learning Curve. In the Conclusion, comparing this latter with the actual data collected until the end of the project I demonstrate that the revised model improves the forecasting and seems to be the best method to foresee the duration in a SCRUM environment.

Relatori: Alberto De Marco, Filippo Maria Ottaviani
Anno accademico: 2022/23
Tipo di pubblicazione: Elettronica
Numero di pagine: 65
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: ALTEN fr
URI: http://webthesis.biblio.polito.it/id/eprint/25261
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