Don't Tell the Boss! : How Poor Communication on Risks Within Organizations Causes Major Catastrophes
Langue : anglais
Edité par Springer, 2024
- Livre broché
- Occasion

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- Titre
- Don't Tell the Boss! : How Poor Communication on Risks Within Organizations Causes Major Catastrophes
- Auteur
- Chernov, Dmitry; Sornette, Didier; Sansavini, Giovanni; Ayoub, Ali
- Éditeur
- Springer
- Année de publication
- 2024
- État de l'article
- As New
- Reliure
- Couverture souple
- Langue
- anglais
- ISBN à 10 chiffres
- 3031052080
- ISBN à 13 chiffres
- 9783031052088
After a major disaster, when investigators are piecing together the story of what happened, a striking fact often emerges: before disaster struck, some people in the organization involved were aware of dangerous conditions that had the potential to escalate to a critical level. But for a variety of reasons, this crucial information did not reach decision-makers. So, the organization moved ever closer to catastrophe, effectively unaware of the possible threat—despite the fact that some of its employees could see it coming.
What is the problem with communication about risk in an organization, and why does this problem exist? What stops people in organizations or project teams from freely reporting and discussing critical risks? This book seeks to answer these questions, starting from a deep analysis of 20 disasters where the concealment of risks played a major part.
These case studies are drawn from around the world and span a range of industries: civil nuclear power,coal, oil and gas production, hydropower energy, metals and mining, space exploration, transport, finance, retail manufacturing and even the response of governments to wars, famines and epidemics.
Together, case studies give an insight into why people hesitate to report risks—and even when they do, why their superiors often prefer to ignore the news.
The book reviews existing research on the challenges of voice and silence in organizations.
This helps to explain more generally why people dread passing on bad news to others—and why in the workplace they prefer to keep quiet about unpleasant facts or potential risks when they are talking to superiors and colleagues.
The discussion section of the book includes important examples of concealment within the Chinese state hierarchy as well as by leading epidemiologists and governments in the West during the novel coronavirus outbreak in Wuhan in 2019-2020. The full picture of the very early stage of the COVID-19 pandemic remains unclear, and further research is obviously needed to better understand what motivated some municipal, provincial and national officials in China as well as Western counterparts to obfuscate facts in their internal communications about many issues associated with the outbreak.
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À propos de l’auteur
Dr. Dmitry Chernov is a senior researcher at the Chair of Entrepreneurial Risks and at the Chair of Reliability and Risk Engineering at the Swiss Federal Institute of Technology in Zurich (ETH Zurich). He has more than 15 years of experience as a crisis communication and disaster management consultant for large corporate clients working in oil and gas, electric power, metals and mining, chemical, telecommunication, transport, utilities, retail manufacturing, etc. He first recognized the importance of intra-organizational risk concealment in 2007 during one of his seminars for a critical infrastructure company. Since then, he has focused on researching solutions to improve intra-organizational risk communication, in order to enable timely decision-making before and during industrial disasters. Additional information: www.riskcommunication.info
Dr. Didier Sornette is Chair Professor and co-Dean of the Institute of Risk Analysis, Prediction and Management (Risks-X) at the Southern University of Science and Technology (SUSTech) Shenzhen, China. He is professor emeritus of ETH Zurich since 31st July 2022, where he was a founding member of the Risk Center at ETH Zurich. Since 1s August 2022, he has taken an active role in the private sector, applying his energy to develop socially important business products associated to earthquake forecasts and financial crises, as well as in medical applications. He is a Fellow of the American Association for the Advancement of Science, a member of the Swiss Academy of Engineering Sciences and of the Academia Europaea. He uses rigorous data-driven mathematical statistical analyses combined with nonlinear multi-variable dynamical models with positive and negative feedbacks to study the predictability and control of crises and extreme events in complex systems, with applications to all domains of science and practice.
Dr. Giovanni Sansavini is an associate professor of Reliability and Risk Engineering at the Institute of Energy and Process Engineering, ETH Zurich. Currently, he is the chairperson of the ETH Risk Center and of the Technical Committee on Critical Infrastructures of the European Safety and Reliability Association (ESRA). His research focuses on the development of hybrid analytical and computational tools suitable for analyzing and simulating failure behaviors of engineered complex systems, with focus on physically networked critical infrastructures and sustainable energy systems. He aims to quantitatively define reliability, vulnerability, resilience and risk within these systems using a computational approach based on physical system modeling, advanced Monte Carlo simulation, soft computing techniques and optimization.
Dr. Ali Ayoub is a postdoctoral researcher at the Department of Nuclear Science and Engineering at the Massachusetts Institute of Technology. He received his Ph.D. and M.Sc. in nuclear engineering from the ETH Zurich after finishing his undergraduate training at the American University of Beirut. Dr. Ayoub is a member of the European Commission ESReDA "Risk, knowledge, and management" project group. Besides his interests in tackling the problems of risk communication and risk information transmission in critical industries, his research interests include: risk analysis and nuclear safety, uncertainty quantification and model-data integration, atmospheric dispersion, resilience engineering and timely decision-making.
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