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The illusion of control = project da...

Vanhoucke, Mario.

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The illusion of control = project data, computer algorithms and human intuition for project management and control /

Record Type:	Electronic resources : Monograph/item
Title/Author:	The illusion of control/ by Mario Vanhoucke.
Reminder of title:	project data, computer algorithms and human intuition for project management and control /
Author:	Vanhoucke, Mario.
Published:	Cham :Springer Nature Switzerland : : 2023.,
Description:	xiv, 330 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Project management - Data processing. -
Online resource:	https://doi.org/10.1007/978-3-031-31785-9
ISBN:	9783031317859

The illusion of control = project data, computer algorithms and human intuition for project management and control /
Vanhoucke, Mario.

The illusion of controlproject data, computer algorithms and human intuition for project management and control /[electronic resource] :by Mario Vanhoucke. - Cham :Springer Nature Switzerland :2023. - xiv, 330 p. :ill., digital ;24 cm. - Management for professionals,2192-810X. - Management for professionals..

This book comprehensively assesses the growing importance of project data for project scheduling, risk analysis and control. It discusses the relevance of project data for both researchers and professionals, and illustrates why the collection, processing and use of such data is not as straightforward as most people think. The theme of this book is known in the literature as data-driven project management and includes the discussion of using computer algorithms, human intuition, and project data for managing projects under risk. The book reviews the basic components of data-driven project management by summarizing the current state-of-the-art methodologies, including the latest computer and machine learning algorithms and statistical methodologies, for project risk and control. It highlights the importance of artificial project data for academics, and describes the specific requirements such data must meet. In turn, the book discusses a wide variety of statistical methods available to generate these artificial data and shows how they have helped researchers to develop algorithms and tools to improve decision-making in project management. Moreover, it examines the relevance of project data from a professional standpoint and describes how professionals should collect empirical project data for better decision-making. Finally, the book introduces a new approach to data collection, generation, and analysis for creating project databases, making it relevant for academic researchers and professional project managers alike.

ISBN: 9783031317859

Standard No.: 10.1007/978-3-031-31785-9doiSubjects--Topical Terms:

879398
Project management
--Data processing.

LC Class. No.: HD69.P75

Dewey Class. No.: 658.4040285

The illusion of control = project data, computer algorithms and human intuition for project management and control /
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520 $a This book comprehensively assesses the growing importance of project data for project scheduling, risk analysis and control. It discusses the relevance of project data for both researchers and professionals, and illustrates why the collection, processing and use of such data is not as straightforward as most people think. The theme of this book is known in the literature as data-driven project management and includes the discussion of using computer algorithms, human intuition, and project data for managing projects under risk. The book reviews the basic components of data-driven project management by summarizing the current state-of-the-art methodologies, including the latest computer and machine learning algorithms and statistical methodologies, for project risk and control. It highlights the importance of artificial project data for academics, and describes the specific requirements such data must meet. In turn, the book discusses a wide variety of statistical methods available to generate these artificial data and shows how they have helped researchers to develop algorithms and tools to improve decision-making in project management. Moreover, it examines the relevance of project data from a professional standpoint and describes how professionals should collect empirical project data for better decision-making. Finally, the book introduces a new approach to data collection, generation, and analysis for creating project databases, making it relevant for academic researchers and professional project managers alike.
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