Leading Complex Projects takes a unique approach to post-mortem analysis to provide project managers with invaluable insight. For the first time, individual PM characteristics are quantitatively linked to project outcomes through a major study investigating the role of project leadership in the succ
The Data-Driven Project Manager
β Scribed by Mario Vanhoucke
- Publisher
- Apress
- Year
- 2018
- Tongue
- English
- Leaves
- 164
- Edition
- 1st ed.
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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 βdynamic schedulingβ or βintegrated project management and control.β 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 projectβs time and budget objectives.
- Schedule Risk Analysis: Analyze the risk of the baseline schedule and its impact on the projectβs 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 projectβs 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
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
β¦ Table of Contents
Front Matter ....Pages i-xiii
Background (Mario Vanhoucke)....Pages 1-3
Plan (Mario Vanhoucke)....Pages 5-27
Risk (Mario Vanhoucke)....Pages 29-60
Buffer (Mario Vanhoucke)....Pages 61-82
Monitor (Mario Vanhoucke)....Pages 83-110
Control (Mario Vanhoucke)....Pages 111-139
Exciting Times Ahead (Mario Vanhoucke)....Pages 141-143
Afterword (Mario Vanhoucke)....Pages 145-152
Back Matter ....Pages 153-158
β¦ Subjects
Business and Management; Project Management; Careers in Business and Mangagement; Business Strategy/Leadership; Market Research/Competitive Intelligence; Consumer Behavior
π SIMILAR VOLUMES
In the traditional view of project management, if a project manager completed a project and had adhered to the triple constraints of time, cost, and performance, the project was considered a success. Today, in the eyes of the customer and the parent or sponsoring company, if a completed project did
The average data warehouse takes three years to build and costs $3-5 million -- yet many data warehouse project managers are thrown into the position with no clear idea of their roles, authority, or even objectives. It's no wonder that 85% of all data warehouse projects fall short of their objective
The average data warehouse takes three years to build and costs $3-5 million -- yet many data warehouse project managers are thrown into the position with no clear idea of their roles, authority, or even objectives. It's no wonder that 85% of all data warehouse projects fall short of their objective
The average data warehouse takes three years to build and costs $3-5 million -- yet many data warehouse project managers are thrown into the position with no clear idea of their roles, authority, or even objectives. It's no wonder that 85% of all data warehouse projects fall short of their objective
<p><span>Getting Data Science Done</span><span> outlines the essential stages in running successful data science projects.</span></p><p><span>Data science is a field that synthesizes statistics, computer science and business analytics to deliver results that can impact almost any type of process or