Chapter Sixteen - Summary

The study of organizational computing is a vast endeavor, beyond the scope of a single chapter or perhaps even a single book. The organizational computing field is also rapidly growing and changing, with new concepts and technologies appearing every year. Of particular interest here are those parts of the OC field related to decision support systems. They form an important basis for achieving an organization-wide perspective on DSSs and for beginning to appreciate multiparticipant DSS possibilities.

In connection with the first of these, four types of DSSs were identified, characterized, compared, and contrasted: corporate planning systems, functional decision support systems, executive information systems, and local decision support systems. These were integrated into a framework that relates them along three dimensions: organizational level/scope, degree of system formality, and user class (individual versus multiparticipant). The organization-wide view provided by this framework is a good starting point for beginning to think about planning for and managing an organization's DSSs.

In connection with the second point, not only does the OC field overlap with the DSS field, it encompasses several subject areas that have strong relationships with multiparticipant decision support. The OC-DSS overlap consists of multiparticipant DSSs, which can be classified into those that support group decision makers (GDSSs) versus those that support more complex kinds of organizational decision makers (ODSSs). Cutting across these two classes is a type of multiparticipant DSS called a negotiation support system.

Four OC subject areas that contribute to the study of multiparticipant DSSs are groupware, computer-mediated communication, computer supported cooperative work, and coordination technology. A survey of each of these areas indicates that they are related to each other and they offer technologies that can be adapted for decision support purposes. Continuing advances of researchers in these four areas are likely to help shape the multiparticipant DSS landscape for years to come. In Chapter 17, we look at GDSSs, ODSSs, and NSSs in greater detail.

DECISION SUPPORT SYSTEMS A KNOWLEDGE-BASED APPROACH

This chapter has examined computer-based systems that support the decision-making efforts of decision makers composed of multiple participants. These multiparticipant decision support systems (MDSSs) can be categorized into those that support groups (GDSSs) and those that support more complex organizations of decision-making participants (ODSSs). Cutting across these two categories are MDSSs specifically oriented toward supporting negotiated decisions (NSSs). Depending on the organization infrastructure of a decision maker, one or another of these MDSS types will be most appropriate. The appropriateness of a MDSS's fit with a particular decision maker can be gauged in terms of the natures of the roles, relationships, and regulations that make up its infrastructure.

MDSSs do have various traits in common. All fit into one or more of the time/place categories. That is, every MDSS is oriented toward some arrangement of decision-maker participants in time and space. All MDSSs adhere to the generic DSS architecture introduced in Chapter 6. However, we can elaborate on that framework to get a more detailed architecture that is common to MDSSs. With this architecture, four potential kinds of users are identified. The PPS and/or KS can be distributed across multiple linked computers. The LS and PS can have public and private messages. The KS can hold system knowledge, domain knowledge, and relational knowledge. The KS can hold public and private knowledge. The PPS has a participant coordination ability in addition to knowledge acquisition, selection/derivation, and presentation abilities. Some PPS abilities may be exercised by individuals doing individual work, while others involve joint work.

Group decision support systems have been the most extensively studied and widely implemented type of MDSS. Relative to individual work, group work has the potential for certain gains and losses. GDSSs are intended to help the potential gains from group work to become actual gains, while helping prevent potential losses due to group work. GDSSs can be classified into various types based on their architectural features, the time/place categories into which they fit, levels of support they offer to a decision maker, or available technologies that can be applied.

Tools for building GDSSs encompass a considerable variety of processors that are ready-made for inclusion in a PPS. Choosing an appropriate tool(s) is one of a variety of factors that have been found to be important for GDSS success. Unlike DSSs for individuals, usage of a GDSS often involves a facilitator who can strongly influence group performance with the GDSS. Researchers have discovered that effects of GDSS usage depend on situational factors as well as the technology itself.

Organizational decision support systems are for multiparticipant decision makers that are more complex than groups. ODSS research and practice are not as well developed as in the case of GDSSs. Yet, different types of ODSSs have been identified, specialized ODSS architectures have been advanced, development guidelines have been recommended, and candidate technologies for use in ODSS development have been identified. In the case of negotiation support systems a wide range of support possibilities have been recognized, and a number of them have been implemented and studied in NSSs. Also, a way for categorizing NSSs has been advanced. Exploration of the diverse kinds of ODSSs and NSSs that are possible is still in an early stage, but is likely to mature rapidly in the years ahead.

DECISION SUPPORT SYSTEMS A KNOWLEDGE-BASED APPROACH

Executive information systems are increasingly important means for supporting the decision making of top executives. An EIS allows an executive to directly request information that portrays trends, highlights exceptions, and stimulates insights as a basis for high-level decision making. The EIS responses are presented in ways attuned to an executive's individual needs and tastes. Because it is designed specifically to support executives, an EIS permits executives to review information needed for decision making in a faster and more focused way than pouring through conventional reports provided by management information systems.

As a basis for building an EIS, various approaches can be used to discern what information a top executive needs. These include the by-product, null, total study, key indicator, and critical success factor methods. Critical success factors are those areas of activity where satisfactory results will ensure that organizational performance is competitive. To support decision making, executives need to continually receive information about the current status of performance in these areas. Generally, this involves information from both internal and external sources, held in multiple MISs and on multiple computers, much of which is short-term and subject to rapid change, oriented toward monitoring current performance and/or building for the future.

In being created to meet such information needs, today's EISs tend to have several common traits including sufficient ease-of-use to be used directly by top executives; ability to draw on a wide variety of data sources; able to deal with critical success factor information; can present information in ways customized to executive desires; can perform reporting of status, trends, and exceptions; and allows drill-down investigation. Emerging trends in EIS characteristics include broadening accessibility to managers below the top executive level, increasing abilities for electronic communication and automated analysis of information, and provision of EIS access for executives in certain external organizations (e.g., customers, suppliers).

Executive information systems are usually built by professional developers, with general oversight by an executive sponsor. The development task can be greatly facilitated by various commercial software offerings specifically designed to function as EIS development tools. Rapid EIS prototyping, quickly traversing a life cycle of system analysis and design, and evolutionary improvement are advocated in the development of EISs. Evolutionary EIS development requires the ongoing availability of development personnel to implement EIS extensions. There are various technical limitations on what an EIS can do.

There are potential organizational liabilities that can limit the value of an EIS. There is also the possibility of outright EIS failure. Preventing such failure depends on a variety of factors including enthusiastic sponsorship, cultivation of executive users' interest, a skilled developer, appropriate development tool(s), accessible data sources, and ongoing developmental support. Successful EIS development efforts pay close attention to such factors. As an organization and its environment become increasingly complex and dynamic, the pressure for successful implementation of this kind of decision support system grows.

DECISION SUPPORT SYSTEMS A KNOWLEDGE-BASED APPROACH

The design, construction, and ongoing management of an effective infrastructure presents challenges to each of the traditional functional areas of management. Each area can make important contributions to the realization of viable knowledge-based organizations. The focal point for study and research into these such organizations will be a new field, referred to as knowledge management, which transcends the more narrow interests of fields such as MIS and DSS. Its mission involves the identification and creation of concepts, methods, and tools for maximizing the global knowledge worker productivity in an organization.