This new edition of Risk Management: Concepts and Guidance is a contemporary look at project risk while still covering well-established and time-proven practices. Integrating agile concepts with new chapters on artificial intelligence applications, the text breaks new ground on the need for project risk management in adaptive environments, as it remains focused on classic approaches and applications. Taking a holistic approach, it examines risk as a blend of environmental, programmatic, and situational concerns. Supplying comprehensive coverage of risk management tools, practices, and protocols, the book presents powerful techniques that can enhance organizational risk identification, assessment, and management—all within the project and program environments.
Aligned with the seventh edition of the Project Management Institute’s A Guide to the Project Management Body of Knowledge (PMBOK® Guide), the sixth edition of this classic text is an ideal resource for those seeking Project Management Professional (PMP®) and Risk Management Professional (PMI-RMP®) certifications. Emphasizing greater clarity on risk practice, this edition maintains a focus on the ability to apply "planned clairvoyance" to peer into the future.
The book begins by analyzing various systems that can be used to apply risk management. It provides a fundamental introduction to the basics associated with risk management techniques and clarifies essential concepts of risk and how they apply to projects. The second part of the book presents the specific techniques necessary to successfully implement the systems covered in the first part. The text addresses project risk management from the project manager’s perspective. Adopting the perspective that risk is both a threat and an opportunity, the book acknowledges that any effective risk management practice must look at the potential positive events that may befall a project, as well as the negatives.
Providing coverage of the concepts that many project management texts ignore, such as the risk response matrix and risk models, the book includes appendices filled with additional reference materials and supporting details that simplify some of the most complex aspects of risk management.
This new edition views risk in light of current systems but is still grounded in the history of risk practice. Updated to reflect such emerging trends as machine learning and genAI, the book features an in-depth case study from the bio-research arena but applicable to any organization wrestling with its ability to peer into the future.
