Context in Decision Support Systems Development

Context in Decision Support Systems Development

Alexandre Gachet (University of Hawaii at Manoa, USA) and Ralph Sprague (University of Hawaii at Manoa, USA)
DOI: 10.4018/978-1-59904-843-7.ch011
OnDemand PDF Download:
List Price: $37.50
10% Discount:-$3.75


Finding appropriate decision support systems (DSS) development processes and methodologies is a topic that has kept researchers in the decision support community busy for the past three decades at least. Inspired by Gibson and Nolan’s curve (Gibson & Nolan 1974; Nolan, 1979), it is fair to contend that the field of DSS development is reaching the end of its expansion (or contagion) stage, which is characterized by the proliferation of processes and methodologies in all areas of decision support. Studies on DSS development conducted during the last 15 years (e.g., Arinze, 1991; Saxena, 1992) have identified more than 30 different approaches to the design and construction of decision support methods and systems (Marakas, 2003). Interestingly enough, none of these approaches predominate and the various DSS development processes usually remain very distinct and project-specific. This situation can be interpreted as a sign that the field of DSS development should soon enter in its formalization (or control) stage. Therefore, we propose a unifying perspective of DSS development based on the notion of context. In this article, we argue that the context of the target DSS (whether organizational, technological, or developmental) is not properly considered in the literature on DSS development. Researchers propose processes (e.g., Courbon, Drageof, & Tomasi, 1979; Stabell 1983), methodologies (e.g., Blanning, 1979; Martin, 1982; Saxena, 1991; Sprague & Carlson, 1982), cycles (e.g., Keen & Scott Morton, 1978; Sage, 1991), guidelines (e.g., for end-user computer), and frameworks, but often fail to explicitly describe the context in which the solution can be applied.

Key Terms in this Chapter

End-User DSS Development: Refers to people developing decision support applications for themselves or for others even though they are not trained IS professionals.

Design Cycle: DSS development methodology introduced by Keen and Scott Morton in 1978 (Keen & Scott Morton, 1978) which can be considered as the ancestor of most of the other DSS development processes and as an authoritative model. The global cycle is made of several steps focusing both on the decision support functionalities and their implementation in the actual system.

DSS Development Phases: DSS development methodology proposed by Sprague and Carlson in 1982 (Sprague & Carlson, 1982). The methodology can be broken down into two broad parts: an action plan and the ROMC methodology, a processing dependent model for organizing and conducting systems analysis in DSS.

DSS Design and Development Life Cycle: DSS design and development methodology proposed by Sage in 1991 (Sage, 1991) as a phased life-cycle approach to DSS engineering. Its basic structure is very close to the software development life cycle (SDLC) methodology. However, it tries to avoid the drawbacks of the SDLC by embedding explicit feedback loops in the sequential life cycle and by promoting prototyping during system implementation in order to meet the iterative requirements of a DSS development process.

Decision Graph: DSS development methodology introduced by Martin in 1982 (Martin, 1982) as a modification of the descriptive system dynamics model. The methodology emphasizes graphic rather than computer simulation results, changes terminology from an engineering to a decision oriented context, and allows the use of a standard computer template. The methodology is purely graphical and uses symbols inspired by system dynamics structures. Decision graphs are used to create the decision model, with the purpose of identifying pertinent decisions.

Functional Mapping (sometimes referred to as functional category analysis): DSS development methodology introduced by Blanning in 1979 (Blanning, 1979) as a DSS design approach mapping the functions of a DSS with the organizational units of the company. The methodology clearly identifies the responsibilities and/or benefits of the various organizational units vis-a-vis the DSS.

Decision Support Engineering: DSS development methodology proposed by Saxena (1991) as a comprehensive methodology based on a life cycle model of DSS development, which encompasses an engineering approach to DSS analysis and design. Prototyping is also an important part of the methodology.

DSS Prototyping (also known as evolutive approach): DSS development methodology defined by Courbon in 1979 (Courbon et al., 1979, 1980) as a methodology based on the progressive design of a DSS, going through multiple short-as-possible cycles in which successive versions of the system under construction are utilized by the end-user.

Decision-Oriented DSS Development Process: DSS development process introduced by Stabell in 1983 (Stabell, 1983) in reaction to the technocentric, system oriented development methodologies proposed at the beginning of the 1980s. The development process relies on interrelated activities collectively labelled decision research. Emphasis in this decision-oriented, normative methodology is placed on changing the existing decision process to increase decision-making effectiveness.

Complete Chapter List

Search this Book: