The SAGA approach to automated project management

Campbell, Roy H.; Terwilliger, Robert B.

doi:10.1007/3-540-17189-4_95

Cited by 5 publications

(3 citation statements)

References 13 publications

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“…Automated project management (APM) is the automation of software development tasks, typically organised as software projects (Campbell and Terwilliger, 1986). In general terms, APM contains all approaches for automating project management tasks and activities (Auth, Jokisch and Dürk, 2019).…”

Section: Ai In Projectsmentioning

confidence: 99%

Application of machine learning to limited datasets: prediction of project success

Bang¹,

Aarvold²,

Hartvig³

et al. 2022

ITcon

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Much research is conducted on the importance of success factors. This study contributes to the body of knowledge by using artificial intelligence (AI), specifically machine learning (ML), to analyse success factors through data from construction projects. Previously conducted studies have explored the use of AI to predict project success and identify important success factors in projects; however, to the extent of the authors’ knowledge, no studies have implemented the same method as this study. This study conducts quantitative analysis on a sample of 160 Norwegian construction projects, with data obtained from a detailed questionnaire delivered to relevant project team members. The method utilises ML through a Random Forest Classifier (RFC). The findings obtained from the analysis show that it is possible to use AI and ML on a limited dataset. Furthermore, the findings show that it is possible to identify the most important success factors for the projects in question with the developed model. The findings suggest that a group of selected processes is more important than others to achieve success. The identified success factors support the theoretically acknowledged importance of thorough and early planning and analysis, complexity throughout the project, leadership involvement, and processes supporting project success.

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Section: Ai In Projectsmentioning

confidence: 99%

Application of machine learning to limited datasets: prediction of project success

Bang¹,

Aarvold²,

Hartvig³

et al. 2022

ITcon

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show abstract

“…This ENCOMPASS prototype has been used to develop about twenty programs, including specification, prototyping, and mechanical verification. At present, all the programs developed have been less than one hundred lines in length, but some have included more than one module, allowing demonstrations of the ENCOMPASS configuration control [4] and project management [1] systems.…”

Section: System Statusmentioning

confidence: 99%

An overview and bibliography of ENCOMPASS

Terwilliger

1990

SIGSOFT Softw. Eng. Notes

Self Cite

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“…From the available literature, we identified two different meanings of APM: as part of the related term Automated Project Management System (APMS) it focuses on special software systems supporting project scheduling and controlling in terms of time, resources and cost (Nicols, 1986). A second, narrower meaning of APM can be located in software engineering where it describes the automation of software development tasks, which are typically organized as a software project (Campbell & Terwilliger, 1986). In parallel, expert systems had evolved and become popular, leading to a growing supply of commercial software solutions (Liebowitz, 1997).…”

Section: Introductionmentioning

confidence: 99%

Revisiting automated project management in the digital age – a survey of AI approaches

Auth

Jokisch

Dürk³

2019

OJAKM

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In this decade, remarkable progress has been made in the field of artificial intelligence (AI). Inspired by well-known services of cognitive assistance systems such as IBM Watson, Apple's Siri or Google Duplex, AI concepts and algorithms are widely discussed regarding their automation potentials in business, politics and society. At first glance, project management (PM) seems to be less suitable for automation due to the inherent uniqueness of projects by definition. However, AI is also creating new application possibilities in the PM area, which will be explored in this contribution by involving an extensive literature review as well as real-world examples. The objective of this article is to provide a current overview of AI approaches and available tools that can be used for automating tasks in business project management.

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The SAGA approach to automated project management

Cited by 5 publications

References 13 publications

Application of machine learning to limited datasets: prediction of project success

Application of machine learning to limited datasets: prediction of project success

An overview and bibliography of ENCOMPASS

Revisiting automated project management in the digital age – a survey of AI approaches

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