The motivation for this book is to provide, in a concise format, account of the explorations and integration of the lessons learned from experimental decision support system implementation. This book considers the various aspects of developing decision support systems in a way which is accessible to the full range of participants in the process.
Decision support systems (DSS) are widely touted for their effectiveness in aiding decision making, particularly across a wide and diverse range of industries including healthcare, business, and engineering applications. The concepts, principles, and theories of enhanced decision making are essential points of research as well as the exact methods, tools, and technologies being implemented in these industries. From both a standpoint of DSS interfaces, namely the design and development of these technologies, along with the implementations, including experiences and utilization of these tools, one can get a better sense of how exactly DSS has changed the face of decision making and management in multi-industry applications. Furthermore, the evaluation of the impact of these technologies is essential in moving forward in the future. The Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering explores how decision support systems have been developed and implemented across diverse industries through perspectives on the technology, the utilizations of these tools, and from a decision management standpoint. The chapters will cover not only the interfaces, implementations, and functionality of these tools, but also the overall impacts they have had on the specific industries mentioned. This book also evaluates the effectiveness along with benefits and challenges of using DSS as well as the outlook for the future. This book is ideal for decision makers, IT consultants and specialists, software developers, design professionals, academicians, policymakers, researchers, professionals, and students interested in how DSS is being used in different industries.
"A very rich book sprinkled with real-life examples as well as battle-tested advice.” —Pierre Haren, VP ILOG, IBM "James does a thorough job of explaining Decision Management Systems as enablers of a formidable business transformation.” —Deepak Advani, Vice President, Business Analytics Products and SPSS, IBM Build Systems That Work Actively to Help You Maximize Growth and Profits Most companies rely on operational systems that are largely passive. But what if you could make your systems active participants in optimizing your business? What if your systems could act intelligently on their own? Learn, not just report? Empower users to take action instead of simply escalating their problems? Evolve without massive IT investments? Decision Management Systems can do all that and more. In this book, the field’s leading expert demonstrates how to use them to drive unprecedented levels of business value. James Taylor shows how to integrate operational and analytic technologies to create systems that are more agile, more analytic, and more adaptive. Through actual case studies, you’ll learn how to combine technologies such as predictive analytics, optimization, and business rules—improving customer service, reducing fraud, managing risk, increasing agility, and driving growth. Both a practical how-to guide and a framework for planning, Decision Management Systems focuses on mainstream business challenges. Coverage includes Understanding how Decision Management Systems can transform your business Planning your systems “with the decision in mind” Identifying, modeling, and prioritizing the decisions you need to optimize Designing and implementing robust decision services Monitoring your ongoing decision-making and learning how to improve it Proven enablers of effective Decision Management Systems: people, process, and technology Identifying and overcoming obstacles that can derail your Decision Management Systems initiative
In today's rapidly changing educational and business climate, organizational transformation has become a key area of development for many different and varied environments, both commercial and academic. This book addresses issues related to developing Decision Support Systems (DSS) which are sensitive and adaptable to different contexts and evolving technical and work environments. In addition to addressing the various cultural/social, organizational/individual, task/technology contexts of DSS, the book also anchors these discussions in a practical context, drawing on case studies to illustrate the theoretical dimensions stressed. This book includes the following issues: Frameworks for understanding the contexts and environments of decision support; Cases and issues in decision support and organizational transformation in context; An inter-disciplinary analysis of DSS, covering a wide variety of situations; and Real-world applications of DSS . It contains selected papers presented and discussed at the International Conference on Context-Sensitive Decision Support Systems, which was sponsored by the International Federation for Information Processing (IFIP) and held in Bled, Slovenia in July 1998. The book will prove invaluable to anyone working in information and decision support systems development, management, implementation and evaluation, as well as to researchers/practitioners in organizational analysis and development, management and business administration, sociology and psychology of organizations, human relations and human factors management.
Presents the advances in decision support theory and practice with a focus on bridging the socio-technical gap. This book covers a wide range of topics including: Understanding DM, Design of DSS, Web 2.0 Systems in Decision Support, Business Intelligence and Data Warehousing, Applications of Multi-Criteria Decision Analysis, and more.
The main purpose of this paper is to contribute to the discussion about the design of computer and communication systems that can aid the management process. 1.1 Historical Overview We propose that Decision Support System can be considered as a design conception conceived within the computer industry to facilitate the use of computer technology in organisations (Keen, 1991). This framework, built during the late 1970s, offers computer and communication technology as support to the decision process which constitutes, in this view, the core of the management process. The DSS framework offers the following capabilities: • Access: ease of use, wide variety of data, analysis and modelling capacity. • Technological: software gel)eration tools. • Development modes: interactive and evolutionary. Within this perspective, computer and communication technologies are seen as an amplification of the human data processing capabilities which limit the decision process. Thus, the human being is understood metaphorically as a data processing machine. Mental processes are associated with the manipulation of symbols aOO human communication to signal transmission.
This book will be bought by researchers and graduates students in Artificial Intelligence and management as well as practising managers and consultants interested in the application of IT and information systems in real business environment.
As the most comprehensive reference work dealing with decision support systems (DSS), this book is essential for the library of every DSS practitioner, researcher, and educator. Written by an international array of DSS luminaries, it contains more than 70 chapters that approach decision support systems from a wide variety of perspectives. These range from classic foundations to cutting-edge thought, informative to provocative, theoretical to practical, historical to futuristic, human to technological, and operational to strategic. The chapters are conveniently organized into ten major sections that novices and experts alike will refer to for years to come.
Data mining deals with finding patterns in data that are by user-definition, interesting and valid. It is an interdisciplinary area involving databases, machine learning, pattern recognition, statistics, visualization and others. Decision support focuses on developing systems to help decision-makers solve problems. Decision support provides a selection of data analysis, simulation, visualization and modeling techniques, and software tools such as decision support systems, group decision support and mediation systems, expert systems, databases and data warehouses. Independently, data mining and decision support are well-developed research areas, but until now there has been no systematic attempt to integrate them. Data Mining and Decision Support: Integration and Collaboration, written by leading researchers in the field, presents a conceptual framework, plus the methods and tools for integrating the two disciplines and for applying this technology to business problems in a collaborative setting.
