Risk and uncertainty may sound scary, but todays best business leaders are navigating both to gain strategic advantage over competitorsand you can, too. This guide for business leaders examines risk and opportunity through the lens of some of the worlds most respected visionaries, including Howard Schultz, Andy Grove, Peter Huntsman, John Krafcik, Peter Leibinger, Doug Hepper, and many more. These visionaries looked beyond financial performance to see opportunitiesand they did so by understanding uncertainty. Then, they decisively acted to create measurable results that coincided with the future they envisioned. Find out how they did it, and learn how to: identify, define, and convert uncertainty into value; become more opportunistic when facing uncertainty; develop the skill to spot where advantages are likely to emerge; and create an environment where managers and leaders complement each other. Filled with case studies on companies such as Hyundai, Starbucks, Roche, and Intel, this guide delivers proven ways to create value and leverage uncertainty. It is the culmination of a decade of research and interaction with dozens of companies and growth leaders who prove that pursuing a market driven strategy to navigating uncertainty will gain measurable market advantage.

Despite the extensive body of evidence that informs regulatory decisions on pharmaceutical products, significant uncertainties persist, including the underlying variability in human biology, factors associated with the chemistry of a drug, and limitations in the research and clinical trial process itself that might limit the generalizability of results. As a result, regulatory reviewers are consistently required to draw conclusions about a drug's safety and efficacy from imperfect data. Efforts are underway within the drug development community to enhance the evaluation and communication of the benefits and risks associated with pharmaceutical products, aimed at increasing the predictability, transparency, and efficiency of pharmaceutical regulatory decision making. Effectively communicating regulatory decisions necessarily includes explanation of the impact of uncertainty on decision making. On February 12 and May 12, 2014, the Institute of Medicine's Forum on Drug Discovery, Development, and Translation held public workshops to advance the development of more systematic and structured approaches to characterize and communicate the sources of uncertainty in the assessment of benefits and risks, and to consider their implications for pharmaceutical regulatory decisions. Workshop presentations and discussions on February 12 were convened to explore the science of identifying and characterizing uncertainty in scientific evidence and approaches to translate uncertainties into decisions that reflect the values of stakeholders. The May 12 workshop presentations and discussions explored tools and approaches to communicating about scientific uncertainties to a range of stakeholders in the drug development process. Characterizing and Communicating Uncertainty in the Assessment of Benefits and Risks of Pharmaceutical Products summarizes the presentation and discussion of both events. This report explores potential analytical and communication approaches and identifies key considerations on their development, evaluation, and incorporation into pharmaceutical benefit- risk assessment throughout the entire drug development lifecycle.

Knight (1921) defines uncertainty as an informational market failure that, while being detrimental to most existing businesses, presents possible profitable opportunities for others. This book builds upon that classic work by providing an analysis of the alternative approaches to strategic decision-making under such uncertainty. It covers what uncertainty is, why it is important, and what connections it has to business and related fields, culminating in a new and comprehensive typology and a valuable guide for how to appropriately address various types of uncertainties, even under AI. It clarifies the current terminological and categorical confusion about ‘unknowns’ while complementing the mathematical, probability-based approaches that treat uncertainty as ‘knowable’ (i.e., as risk). It corrects the mistaken approaches that treat ‘unknowables’ as ‘shapeable’ or ‘discoverable’. This book widens the perspective for viewing uncertainty, in terms of its impacts across humanity, by offering a shrewder understanding of what roles uncertainties play in human activity. It will appeal to academics across business, economics, philosophy, and other disciplines looking for approaches to apply, test, and hone for dealing with decision-making under uncertainty.

This book provides a new point of view on the subject of the management of uncertainty. It covers a wide variety of both theoretical and practical issues involving the analysis and management of uncertainty in the fields of finance, management and marketing. Audience: Researchers and professionals from operations research, management science and economics.

Praise for the First Edition "...a reference for everyone who is interested in knowing and handling uncertainty." —Journal of Applied Statistics The critically acclaimed First Edition of Understanding Uncertainty provided a study of uncertainty addressed to scholars in all fields, showing that uncertainty could be measured by probability, and that probability obeyed three basic rules that enabled uncertainty to be handled sensibly in everyday life. These ideas were extended to embrace the scientific method and to show how decisions, containing an uncertain element, could be rationally made. Featuring new material, the Revised Edition remains the go-to guide for uncertainty and decision making, providing further applications at an accessible level including: A critical study of transitivity, a basic concept in probability A discussion of how the failure of the financial sector to use the proper approach to uncertainty may have contributed to the recent recession A consideration of betting, showing that a bookmaker's odds are not expressions of probability Applications of the book’s thesis to statistics A demonstration that some techniques currently popular in statistics, like significance tests, may be unsound, even seriously misleading, because they violate the rules of probability Understanding Uncertainty, Revised Edition is ideal for students studying probability or statistics and for anyone interested in one of the most fascinating and vibrant fields of study in contemporary science and mathematics.

Stephen Tallman has put together an excellent tome by high-quality emerging scholars that provides cutting edge knowledge on the field of international strategy. The coverage is thorough, including more traditional topics such as the outcomes of internationalization (e.g., performance, innovation, risk reduction) and market entry modes of cross-border M&As and alliances, while also exploring unique and important topics such as investment in global cities and the development of new organizational forms. It is a must read for graduate students and scholars interested in international strategy. Michael A. Hitt, Texas A&M University, US This book comprises eighteen cutting edge chapters by emerging scholars in international strategy, offering a variety of fresh perspectives on critical issues that the field will face in the near future. These young scholars have unique and innovative thoughts about international strategy, which are well ahead of the mainstream of international business academics. Various topics are addressed, including the rise of outsourcing and the global spread of research and development activities; structural innovations by multinational firms, with particular attention to organizing for the efficient transfer of knowledge resources within networks of alliances; and new ways of considering the effects of location, focusing on the relative importance of regional clusters and countries and the impact of geographical and cultural distance on international strategies. Stephen Tallman has geared the book to an academic audience, specifically faculty and graduate students in international business, international management, and global strategy. Sophisticated international business practitioners will also find it an interesting read.

Uncertainty Quantification of Stochastic Defects in Materials investigates the uncertainty quantification methods for stochastic defects in material microstructures. It provides effective supplementary approaches for conventional experimental observation with the consideration of stochastic factors and uncertainty propagation. Pursuing a comprehensive numerical analytical system, this book establishes a fundamental framework for this topic, while emphasizing the importance of stochastic and uncertainty quantification analysis and the significant influence of microstructure defects on the material macro properties. Key Features Consists of two parts: one exploring methods and theories and the other detailing related examples Defines stochastic defects in materials and presents the uncertainty quantification for defect location, size, geometrical configuration, and instability Introduces general Monte Carlo methods, polynomial chaos expansion, stochastic finite element methods, and machine learning methods Provides a variety of examples to support the introduced methods and theories Applicable to MATLAB® and ANSYS software This book is intended for advanced students interested in material defect quantification methods and material reliability assessment, researchers investigating artificial material microstructure optimization, and engineers working on defect influence analysis and nondestructive defect testing.