Based on policy makers’ limitations in solving real-life problems and the fact that information is rarely available in a pure quantitative form, enhancements and new approaches to remedy this are proposed by Mark Hürlimann. He introduces simple and more sophisticated static and dynamic methods to analyze complex topics. In addition a semi-quantitative approach is presented that integrates quantitative and qualitative variables in a feedback system. The author, finally, illustrates on the basis of a case study the advantages and limitations of the various approaches in a didactically sound and easily understandable way.
Contents 11. 2. 2. Four Main Areas of Dispute 247 11. 2. 3. Summary . . . 248 11. 3. Making Sense of the Issues . . 248 11. 3. 1. Introduction . . . . 248 11. 3. 2. The Scientific Approach 248 11. 3. 3. Science and Matters of Society . 249 11. 3. 4. Summary . 251 11. 4. Tying It All Together . . . . 251 11. 4. 1. Introduction . . . . 251 11. 4. 2. A Unifying Framework 251 11. 4. 3. Critical Systems Thinking 253 11. 4. 4. Summary 254 11. 5. Conclusion 254 Questions . . . 255 REFERENCES . . . . . . . . . . . . . . . . . . . 257 INDEX . . . . . . . . . . . . . . . . . . . . . . 267 Chapter One SYSTEMS Origin and Evolution, Terms and Concepts 1. 1. INTRODUCTION We start this book with Theme A (see Figure P. I in the Preface), which aims to develop an essential and fundamental understanding of systems science. So, what is systems science? When asked to explain what systems science is all about, many systems scientists are confronted with a rather daunting task. The discipline tends to be presented and understood in a fragmented way and very few people hold an overview understanding of the subject matter, while also having sufficient in-depth competence in many and broad-ranging subject areas where the ideas are used. Indeed, it was precisely this difficulty that identified the need for a comprehensive well-documented account such as is presented here in Dealing with Complexity.
The essays and lectures collected in this book center around knowledge transfer from the complex-system sciences to applications in business, industry and society, as viewed from a broad perspective. The contributions aim to raise awareness across the spectrum to meet the increasing need to integrate lessons from complexity research into everyday planning, decision making, logistics or optimization procedures and forecasting. The writing has been largely kept non-technical.
Recognizing that complexity calls for innovative, conceptual, and methodological solutions, Dealing with Complexity in Development Evaluation by Michael Bamberger, Jos Vaessen, and Estelle Raimondo offers practical guidance to policymakers, managers, and evaluation practitioners on how to design and implement complexity-responsive evaluations that can be undertaken in the real world of time, budget, data, and political constraints. Introductory chapters present comprehensive, non-technical overviews of the most common evaluation tools and methodologies, and additional content addresses more cutting-edge material. The book also includes six case study chapters to illustrate examples of various evaluation contexts from around the world.
Despite growing concern with the effects of concurrent task demands on human performance, and research demonstrating that these demands are associated with vulnerability to error, so far there has been only limited research into the nature and range of concurrent task demands in real-world settings. This book presents a set of NASA studies that characterize the nature of concurrent task demands confronting airline flight crews in routine operations, as opposed to emergency situations. The authors analyze these demands in light of what is known about cognitive processes, particularly those of attention and memory, with the focus upon inadvertent omissions of intended actions by skilled pilots. The studies reported within the book employed several distinct but complementary methods: ethnographic observations, analysis of incident reports submitted by pilots, and cognitive task analysis. They showed that concurrent task management comprises a set of issues distinct from (though related to) mental workload, an area that has been studied extensively by human factors researchers for more than 30 years. This book will be of direct relevance to aviation psychologists and to those involved in aviation training and operations. It will also interest individuals in any domain that involves concurrent task demands, for example the work of emergency room medical teams. Furthermore, the countermeasures presented in the final chapter to reduce vulnerability to errors associated with concurrent task demands can readily be adapted to work in diverse domains.
Why we don't really want simplicity, and how we can learn to live with complexity. If only today's technology were simpler! It's the universal lament, but it's wrong. In this provocative and informative book, Don Norman writes that the complexity of our technology must mirror the complexity and richness of our lives. It's not complexity that's the problem, it's bad design. Bad design complicates things unnecessarily and confuses us. Good design can tame complexity. Norman gives us a crash course in the virtues of complexity. Designers have to produce things that tame complexity. But we too have to do our part: we have to take the time to learn the structure and practice the skills. This is how we mastered reading and writing, driving a car, and playing sports, and this is how we can master our complex tools. Complexity is good. Simplicity is misleading. The good life is complex, rich, and rewarding—but only if it is understandable, sensible, and meaningful.
This book is about dealing with messes. Sometimes known as 'wicked problems', messes (or messy situations) are fairly easy to spot:it's hard to know where to startwe can't define them everything seems to connect to everything else and depends on something else having been done first we get in a muddle thinking about them we often try to ignore some aspect/s of themwhen we finally do something about them, they usually get worse they're so entangled that our first mistake is usually to try and fix them as we would fix a simple problem.
Managing Complexity is the first book that clearly defines the concept of Complexity, explains how Complexity can be measured and tuned, and describes the seven key features of Complex Systems: ConnectivityAutonomyEmergencyNonequilibriumNon-linearitySelf-organisationCo-evolution The thesis of the book is that complexity of the environment in which we work and live offers new opportunities and that the best strategy for surviving and prospering under conditions of complexity is to develop adaptability to perpetually changing conditions. An effective method for designing adaptability into business processes using multi-agent technology is presented and illustrated by several extensive examples, including adaptive, real-time scheduling of taxis, see-going tankers, road transport, supply chains, railway trains, production processes and swarms of small space satellites. Additional case studies include adaptive servicing of the International Space Station; adaptive processing of design changes of large structures such as wings of the largest airliner in the world; dynamic data mining, knowledge discovery and distributed semantic processing. Finally, the book provides a foretaste of the next generation of complex issues, notably, The Internet of Things, Smart Cities, Digital Enterprises and Smart Logistics.
Outlines an approach to high-performance problem solving and decision making that draws on insights from survival guides, pop culture, and other sources.
Today's managers, business owners, and public relations practitioners grapple daily with a fundamental question about contemporary crisis management: to what extent is it possible to control events and stakeholder responses to them, in order to contain escalating crises or safeguard an organization's reputation? The authors meet the question head-on, departing from other crisis management texts, and arguing that a complexity-based approach is superior to the standard simplification model of organizational learning.
