Book Review
Book Title: Data Analytics in Project Management
Author: Edited Seweryn Spalek
Publisher: CRC Press
List Price: $59.95
Format: Softcover, 236 pages
Publication Date: June 2021
SBN: ISBN 9781032094526; 9781138307285
Reviewer: Charlotte McKenzie
Review Date: February 2024
Introduction
The saying “Information is the lifeblood of all organizations” resonates deeply within the realm of project management. Indeed, effective project management hinges on the availability of pertinent data for analyzing past, present, and future performance. In the book “Data Analytics in Project Management,” edited by Seweryn Spalek, the crucial importance of identifying and leveraging the right data elements in project management is underscored. This emphasis serves to enhance decision-making processes and overall project performance.
The integration of data analytics into project management is gaining increasing traction due to its potential to revolutionize decision-making, elevate project outcomes, and streamline resource allocation. Within the context of project management, data analytics finds application across multiple domains, including risk assessment, resource management, schedule optimization, and performance monitoring.
Overview of Book’s Structure
The book comprises 10 chapters authored by a diverse group of subject matter experts, each delving into specific facets of data analytics within project management. These chapters present a mix of essays, case studies, and research papers, thoughtfully arranged according to the table of contents for easy navigation. Covering a broad spectrum of topics, the chapters are as follows:
Chapter 1: Introduction – Recognizing Data Analysis as Integral to Successful Project Management.
Chapter 2: Why Data Analytics in Project Management? – Exploring the Imperative of Data Analysis.
Chapter 3: Data Analytics Risk: Lost in Translation? – Unraveling Risks and the Role of Data Analysis.
Chapter 4: Analytical Challenges of a Modern PMO – Addressing the Role and Hurdles of Data Analysis within the PMO.
Chapter 5: Data Analytics and Project Portfolio Management – Emphasizing Decision-Making Metrics.
Chapter 6: Earned Value Method – Analyzing EVM for Project Management.
Chapter 7: How to Manage Big Data Issues in a Project Environment – Strategies for Navigating Big Data Challenges.
Chapter 8: IT Solutions of Data Analytics as Applied to Project Management – A Detailed Case Study.
Chapter 9: Conventional and Unconventional Data Mining for Better Decision Making – Harnessing Data Mining for Enhanced Decision Making.
Chapter 10: Agile Project Management and Data Analytics – Exploring Agile Values and Processes.
More…
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How to cite this review: McKenzie, C. (2024). Data Analytics in Project Management, book review, PM World Journal, Vol. XIII, Issue V, May. Available online at: https://pmworldlibrary.net/wp-content/uploads/2024/05/pmwj141-May2024-McKenzie-data-analytics-in-project-management-book-review.pdf
About the Reviewer
Charlotte McKenzie
Washington, DC, USA
Charlotte A. McKenzie, CPLP®, PMI-ACP, PSM, ITILv3 is a Technical Trainer, Instructional Designer, Agile Project Manager and Online Professor. She lives and works in the Washington D.C. Metro Area in the United States. Charlotte can be contacted at cam@charlottemckenzie.com
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