Winner of the IIE Book of the Month for June 2012 A project can be simple or complex. In each case, proven project management processes must be followed. In all cases of project management implementation, control must be exercised in order to assure that project objectives are achieved. Statistical Techniques for Project Control seamlessly integrates qualitative and quantitative tools and techniques for project control. It fills the void that exists in the application of statistical techniques to project control. The book begins by defining the fundamentals of project management then explores how to temper quantitative analysis with qualitative human judgment that makes project control nebulous but also offers opportunities to innovate and be creative in achieving control. The authors then discuss the three factors (time, budget, and performance) that form the basis of the operating characteristics of a project that also help determine the basis for project control. They then focus on computational network techniques for project schedule (time) control. Although designed as a practical guide for project management professionals, the book also appeals to students, researchers, and instructors.

Winner of the IIE Book of the Month for June 2012A project can be simple or complex. In each case, proven project management processes must be followed. In all cases of project management implementation, control must be exercised in order to assure that project objectives are achieved. Statistical Techniques for Project Control seamlessly integrate

This book systematically examines and quantifies industrial problems by assessing the complexity and safety of large systems. It includes chapters on system performance management, software reliability assessment, testing, quality management, analysis using soft computing techniques, management analytics, and business analytics, with a clear focus on exploring real-world business issues. Through contributions from researchers working in the area of performance, management, and business analytics, it explores the development of new methods and approaches to improve business by gaining knowledge from bulk data. With system performance analytics, companies are now able to drive performance and provide actionable insights for each level and for every role using key indicators, generate mobile-enabled scorecards, time series-based analysis using charts, and dashboards. In the current dynamic environment, a viable tool known as multi-criteria decision analysis (MCDA) is increasingly being adopted to deal with complex business decisions. MCDA is an important decision support tool for analyzing goals and providing optimal solutions and alternatives. It comprises several distinct techniques, which are implemented by specialized decision-making packages. This book addresses a number of important MCDA methods, such as DEMATEL, TOPSIS, AHP, MAUT, and Intuitionistic Fuzzy MCDM, which make it possible to derive maximum utility in the area of analytics. As such, it is a valuable resource for researchers and academicians, as well as practitioners and business experts.

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

This book gathers the best papers presented at the International Congress on Project Management and Engineering, in its 2017 and 2018 editions, which were held in Cádiz and Madrid, Spain. It covers a range of topic areas, including civil engineering and urban planning, product and process engineering, environmental engineering, energy efficiency and renewable energies, rural development, information and communication technologies, and risk management and safety.

There is often a deep disconnect between the project team's goals and those of the organization. Senior management wants "profitable" projects, but is only able to quantify its wishes in terms of the traditional project management elements: schedule and cost. To operate smoothly, the entire organization must be driven by the single goal of project

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.

NeoPopRealism Journal and Wonderpedia founded by Nadia Russ in 2007 (N.J.) and 2008 (W.). Wonderpedia is dedicated to books published all over the globe after year 2000, offering the books' reviews.

This book presents an integrated approach to monitoring projects in progress using Earned Value and Earned Schedule Management combined with Schedule Risk Analysis. Monitoring and controlling projects involves processes for identifying potential problems in a timely manner. When necessary, corrective actions can be taken to exploit project opportunities or to get faltering projects back on track. The prerequisite is that project performance is observed and measured regularly to identify variances from the project baseline schedule. Therefore, monitoring the performance of projects in progress requires a set of tools and techniques that should ideally be combined into a single integrated system. The book offers a valuable resource for anyone who wants to understand the theory first and then to use it in practice with software tools. It is intended for students, professionals and academics with an interest and/or experience in running projects as well as for newcomers in the area of project control with a basic grasp of the Earned Value, Earned Schedule and Schedule Risk Analysis concepts.

The goal of the new edition is to continue with a systems view of the world. For a more robust and worldwide market dissemination, the new edition has changed to a reference book. The project systems approach to project management, is needed in executing projects across countries and across cultures, which is a crucial requirement in today's globalized and intertwined economics. The book uses ample graphical representations to clarify the concepts and techniques presented. The case examples help to reinforce the topics covered. Several illustrative examples and practice exercises are included. Each chapter is updated and new chapters include Project Simulation and Project Templates. A new chapter on managing complex projects in an age of artificial intelligence adds a unique value to the book. Features Highlights contemporary best practices of project management Uses a systems framework to integrate quantitative and qualitative tools Offers illustrative examples and practice exercises Covers project schedule performance appraisal techniques Discusses the knowledge areas contained in the Project Management Book of Knowledge (PMBOK) Presents software applications for project management, as well as case examples