Ralph H. Sprague

A framework for the development of decisoin support systems

This article proposes a framework to explore the nature, scope, and content of the evolving topic of Decision Support Systems (DSS). The first part of the framework considers (a) three levels of technology which have been designated DSS, (b) the developmental approach that is evolving for the creation of a DSS, and (c) the roles of several key types of people in the building and use of a DSS. The second part develops a descriptive model to access the performance objectives and the capabilities of a DSS as viewed by three of the major participants in their continued development and use. The final section outlines several issues in the future growth and development of a DSS as a potentially valuable type of information system in organizations.

1001 Unanswered research questions in GSS

Robert O. Briggs is the Research Coordinator in the Center for the Management of Information at the University of Arizona, where he conducts theoretical and empirical investigations on the use of collaborative technology to support teams working under high cognitive load. He has focused his work on technology-supported learning and crisis planning and response. He received his Ph.D. in Management Information Systems from the University of Arizona in 1994 and his B.S. and M.B.A. from San Diego State University.

Information Systems Success

ROBERT O. BRIGGS is Research Coordinator at the Center for the Management of Information at the University of Arizona and Associate Professor of Collaboration Engineering at Delft University of Technology in the Netherlands. He is also Director of Research and Development for GroupSystems.com. As a researcher, he has published more than 60 scholarly works on the theoretical foundations collaboration, and he applies his findings to the development and deployment of collaborative technology to enhance team productivity, team creativity, and team satisfaction. His work on organizational transition to collaborative technology led to new insights about how to conceive of and deploy group support systems so as to create self-sustaining and growing communities of users. He received his Ph.D. from University of Arizona in 1994.is Research Coordinator at the Center for the Management ofInformation at the University of Arizona and Associate Professor of CollaborationEngineering at Delft University of Technology in the Netherlands. He is also Directorof Research and Development for GroupSystems.com. As a reseiu-cher, he has pub-lished more than 60 scholarly works on the theoretical foundations collaboration,and he applies his findings to the development and deployment of collaborative tech-nology to enhance team productivity, team creativity, and team satisfaction. His workon organizational transition to collaborative technology led to new insights abouthow to conceive of and deploy group support systems so as to create self-sustainingand growing communities of users. He received his Ph.D. from University of Arizonain 1994.

Hitting the wall: errors in developing and code inspecting a 'simple' spreadsheet model

Abstract Field audits and experiments have found substantial error rates when students and professionals have built spreadsheet models. In this study, 102 undergraduate MIS majors and 50 MBA students developed a model from a word problem that was relatively simple and free of domain knowledge. Even so, 35% of their 152 models were incorrect. There was no significant difference in errors per model between undergraduates and MBAs. Even among the 17 MBAs with 250 h or more of experience, 24% of the models contained errors. The cell error rate (CER)—the percentage of cells with errors—was 2.0%. When 23 undergraduates attempted to audit their models through code inspection, only three with incorrect spreadsheets (15%) produced clean spreadsheets when they finished the audit.

Bit by Bit: Toward Decision Support Systems

Alias Decision Support System or DSS, the use of information technology to support upper-level management is receiving much attention. Is DSS just another buzz word-or will it become the system that performs in data storage, access, and handling; analytic model creation, use, and manipulation; and manager-system interface ?

A decision support system for banks

Just recently, information systems with rather unique characteristics have begun to emerge. These systems usually referred to as Decision Support Systems, feature decision models, a data base and the decision maker as subsystems and are specifically oriented to supporting decision making. This article examines Decision Support Systems and their application to banks.

Special Issue: Enhancing Organizations' Intellectual Bandwidth: The Quest for Fast and Effective Value Creation

Jay F. Nunamaker Jr. is Regents and Soldwedel Professor of MIS, Computer Science, and Communication, and Director of the Center for the Management of Information at the University of Arizona, Tucson. He has over forty years of experience in developing collaborative information systems. He has served as a test engineer at the Shippingport Atomic Power facility, as a member of the ISDOS team at the University of Michigan, and as a member of the faculty at Purdue University prior to joining the faculty at the University of Arizona in 1 974. Dr. Nunamaker received his Ph.D. in systems engineering and operations research from Case Institute of Technology, an M.S. and B.S. in engineering from the University of Pittsburgh, and a B.S. from Carnegie Mellon University. He has been a registered professional engineer since 1965.

Toward a new framework for office support

Office automation is the outgrowth of one form of corporate information technology—the office products category. If we are really to enhance the total office function, however, we will need a much broader concept of office information systems. This paper proposes one such concept, which we call office support.

The financial planning system at louisiana national bank

In 1974 Louisiana National Bank designed and implemented a Financial Planning System. For the past five years, it has been the primary reporting, analysis, and decision support tool for the Budget Committee and the primary source of the financial reports for the Board of Directors. Top management of the bank believes that, as a direct result of the use of this system, Louisiana National Bank: 1. reversed a decreasing profit trend by increasing profits more than 92% in one year, 2. creatively managed the banks liquidity during severe market pressures, 3. restructured the banks asset/liability management policies to better align with newly perceived market and investment potential, and 4. sharply reduced th cost and management burden of reporting to regulators. In addition to the quantifiable benefits cited above, use of the system resulted in several other improvements, including 1. a reduction in the amount of time required to meet periodic management reporting requirements, 2. increased understanding of financial reports by the Board of Directors, 3. improved communications between bank executives and regulator examiners, and 4. a discipline and structure within which the Budget Committee could establish goals and action plans. The Financial Planning System supports financial decision making at both the tactical and strategic levels. It is an integrated system which includes reporting and analysis of historical data, long and short range forecasting, and modeling.

Natural technologies for knowledge work: information visualization and knowledge extraction

This paper ‘looks” into one of the most novel knowledge management technology products that has been brought to the market in the recent years. The authors describe two technologies, information visualization and knowledge extraction, for leveraging our natural abilities of vision, language and memory. They discuss a way for exploiting structure that is available in the information system in one case (traditionally called structured) and easily perceived by humans in the other (traditionally called unstructured). The two technologies focus on the two sides of this goal, respectively. They demonstrate the value of these technologies in supporting interaction with much larger amounts of information than was possible with previous graphical interfaces and in guiding access and use of the information and often for automating portions of the work.