This handbook is a unique, comprehensive resource for professional project managers and students in project management courses that focuses on the integration between baseline scheduling, schedule risk analysis and project control, also known as Dynamic Scheduling or Integrated Project Management and Control. It contains a set of more than 70 articles. Each individual article focuses on one particular topic and features links to other articles in this book, where appropriate. Almost all articles are accompanied with a set of questions, the answers to which are provided at the end of the book. This book is accompanied by and is based on the Project Management Knowledge Center (www.pmknowledgecenter.com), an online learning platform for Integrated Project Management.

This handbook is a unique, comprehensive resource for professional project managers and students in project management courses that focuses on the integration between baseline scheduling, schedule risk analysis and project control, also known as Dynamic Scheduling or Integrated Project Management and Control. It contains a set of more than 70 articles. Each individual article focuses on one particular topic and features links to other articles in this book, where appropriate. Almost all articles are accompanied with a set of questions, the answers to which are provided at the end of the book. This book is accompanied by and is based on the Project Management Knowledge Center (www.pmknowledgecenter.com), an online learning platform for Integrated Project Management.

Meant to complement rather than compete with the existing books on the subject, this book deals with the project performance and control phases of the project life cycle to present a detailed investigation of the project's time performance measurement methods and risk analysis techniques in order to evaluate existing and newly developed methods in terms of their abilities to improve the corrective actions decision-making process during project tracking. As readers apply what is learned from the book, EVM practices will become even more effective in project management and cost engineering. Individual chapters look at simulation studies in forecast accuracy; schedule adherence; time sensitivity; activity sensitivity; and using top-down or bottom-up project tracking. Vanhoucke also offers an actual real-life case study, a tutorial on the use of ProTrack software (newly developed based on his research) in EVM, and conclusions on the relative effectiveness for each technique presented.

Discover solutions to common obstacles faced by project managers. Written as a business novel, the book is highly interactive, allowing readers to participate and consider options at each stage of a project. The book is based on years of experience, both through the author's research projects as well as his teaching lectures at business schools. The book tells the story of Emily Reed and her colleagues who are in charge of the management of a new tennis stadium project. The CEO of the company, Jacob Mitchell, is planning to install a new data-driven project management methodology as a decision support tool for all upcoming projects. He challenges Emily and her team to start a journey in exploring project data to fight against unexpected project obstacles. Data-driven project management is known in the academic literature as "dynamic scheduling" or "integrated project management and control." It is a project management methodology to plan, monitor, and control projects in progress in order to deliver them on time and within budget to the client. Its main focus is on the integration of three crucial aspects, as follows: Baseline Scheduling: Plan the project activities to create a project timetable with time and budget restrictions. Determine start and finish times of each project activity within the activity network and resource constraints. Know the expected timing of the work to be done as well as an expected impact on the project's time and budget objectives. Schedule Risk Analysis: Analyze the risk of the baseline schedule and its impact on the project's time and budget. Use Monte Carlo simulations to assess the risk of the baseline schedule and to forecast the impact of time and budget deviations on the project objectives. Project Control: Measure and analyze the project's performance data and take actions to bring the project on track. Monitor deviations from the expected project progress and control performance in order to facilitate the decision-making process in case corrective actions are needed to bring projects back on track. Both traditional Earned Value Management (EVM) and the novel Earned Schedule (ES) methods are used. What You'll Learn Implement a data-driven project management methodology (also known as "dynamic scheduling") which allows project managers to plan, monitor, and control projects while delivering them on time and within budget Study different project management tools and techniques, such as PERT/CPM, schedule risk analysis (SRA), resource buffering, and earned value management (EVM) Understand the three aspects of dynamic scheduling: baseline scheduling, schedule risk analysis, and project control Who This Book Is For Project managers looking to learn data-driven project management (or "dynamic scheduling") via a novel, demonstrating real-time simulations of how project managers can solve common project obstacles

Earned Value Management (EVM) is a project management technique for measuring project progress in terms of cost, schedule and scope, and has developed into a very effective way to uncover performance problems at an early and correctible stage in any given project. From its earliest days as a financial analysis tool in the US in the early 1960 s, it steadily grew in use through the US Department of Defense until it was made the standard measurement for all DoD, NASA, and Department of Energy projects, and was widely adopted by publicly-traded companies trying to comply with the 2002 Sarbanes-Oxley ruling calling for greater transparency and accountability. It has also long been used in software engineering projects.

Winning the 2008 Research Award from IPMA for his research leading to this proposed book, author Mario Vanhoucke has surveyed the published literature to find and evaluate the effectiveness of the latest developments (and established practices) in EVM. After first explaining the fundamentals and terminology of the practice, he explores all the latest research trends and then tests them against a group of fictitious projects to gauge their effectiveness, offering general results applicable to a wide set of project types that researchers and practitioners can use to expand their work in EVM-managed projects. With a focus on the simple calculations behind EVM systems, Vanhoucke shows how they can often lead to misinterpretation and frustration and how to avoid common mistakes.

Meant to complement rather than compete with the existing books on the subject, the proposed book deals with the project performance and control phases of the project life cycle to present a detailed investigation of the project s time performance measurement methods and risk analysis techniques in order to evaluate existing and newly developed methods in terms of their abilities to improve the corrective actions decision-making process during project tracking. As readers apply what is learned from the book, EVM practices will become even more effective in project management and cost engineering. Individual chapters look at simulation studies in forecast accuracy (under nine different scenarios); schedule adherence; time sensitivity; activity sensitivity; and using top-down or bottom-up project tracking. Vanhoucke also offers an actual real-life case study, a tutorial on the use of ProTrack software (newly developed based on his research) in EVM, and conclusions on the relative effectiveness for each technique presented. This will be an important read for anyone researching, using, or studying EVM and will certainly help to push the field forward in the coming years.

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The topic of this book is known as dynamic scheduling, and is used to refer to three dimensions of project management and scheduling: the construction of a baseline schedule and the analysis of a project schedule s risk as preparation of the project control phase during project progress. This dynamic scheduling point of view implicitly assumes that the usability of a project s baseline schedule is rather limited and only acts as a point of reference in the project life cycle. Consequently, a project schedule should especially be considered as nothing more than a predictive model that can be used for resource efficiency calculations, time and cost risk analyses, project tracking and performance measurement, and so on.

In this book, the three dimensions of dynamic scheduling are highlighted in detail and are based on and inspired by a combination of academic research studies at Ghent University (www.ugent.be), in-company trainings at Vlerick Business School (www.vlerick.com) and consultancy projects at OR-AS (www.or-as.be). First, the construction of a project baseline schedule is a central theme throughout the various chapters of the book, and is discussed from a complexity point of view with and without the presence of project resources. Second, the creation of an awareness of the weak parts in a baseline schedule is discussed at the end of the two baseline scheduling parts as schedule risk analysis techniques that can be applied on top of the baseline schedule. Third, the baseline schedule and its risk analyses can be used as guidelines during the project control step where actual deviations can be corrected within the margins of the project s time and cost reserves.

The second edition of this book has seen corrections, additionsand amendments in detail throughout the book. Moreover Chapter 15 on "Dynamic Scheduling with ProTrack" has been completely rewritten and extended with a section on "ProTrack as a research tool.""

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.