A Knowledge Worker Desktop Model (KWDM) Applied to Decision Support System

A Knowledge Worker Desktop Model (KWDM) Applied to Decision Support System

Camille Rosenthal-Sabroux (Dauphine University, France), Michel Grundstein (Dauphine University, France) and Fernando Iafrate (Euro Disney SCA, France)
DOI: 10.4018/978-1-59904-843-7.ch065
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The concept of information system covers two notions: on the one hand, the reality of the evolving organization that collects, communicates, and records information; and, on the over hand, the digital information system, artificial object conceived by humans to acquire, process, store, transmit, and restore the information allowing them to carry out their activities within the context of the organization (Reix, 1995). We shall refer hereinafter to the digital information system. In the first part of this article, we present the knowledge worker desktop’s model (KWDM). This model highlights three types of data: “main-stream” data, shared-data, and source-of- knowledge-data. In the second part, we describe a group decision and negotiation system (GDNS) for operational performance management (OPM) implemented in an entertainment company based in France. This GDNS addresses a zero latency organization problem that is to provide decision makers, both strategic and operational, with the insight they need to interpret multiple and complex operational data, and take immediate decision close to the action. In the third part, in order to validate the KWDM model, we present the methodology that consists to match each system’s component with each model’s element, and the study’s outcomes. This analysis leads to highlight the formalization of the different data flows, the impact of the system on the organization, and to confirm the importance of human factor in the group decision and negotiation process. Furthermore, it opens new, perspectives particularly the influence of the intention, the importance of shared-data system and the role of the system in the organizational learning process to insure the business continuity plan.

Key Terms in this Chapter

Expert Systems: A field of research within artificial intelligence that seeks to design systems that can perform tasks equal to the reasoning ability of experts in a chosen field.

“Main-Stream” Data: The flow of information that informs us on the state of a company’s business process or working information needed by each individual to act.

“Shared” Data: Information processed by the technologies of communication exchange.

“Source-of-Knowledge” Data: Are the result of a knowledge engineering approach that offers techniques and tools for identifying, acquiring, and representing knowledge.

Common Sense Reasoning: A field of research in the artificial intelligence community that seeks to endow a computer with “common sense.” Many applications of artificial intelligence are highly successful. As an example, consider the fact that IBM’s “Big Blue” has defeated the world chess champion on multiple occasions. Yet, all computer applications perform miserably when required to perform outside of the realm for which they were designed. Put differently, the performance of humans degrades gracefully while the performance of computers plummets rapidly when performing unanticipated tasks.

Knowledge Management: The management of activities and processes that enhance creation and utilization of knowledge within an organization. It aims at two strongly interlinked goals: a patrimony goal and a sustainable innovation goal with their economic and strategic, organizational, socio-cultural, and technological underlying dimensions.

Logic Programming: A field of research within artificial intelligence that seeks to use logic to represent and reason about knowledge. Initially, pure mathematical logic was used (“first order logic”). However, as the need to mimic human thought processes became prevalent (such as “rules of thumb,” or “jumping to conclusions”), the field broke away from first order logic. The field still has a very strong relationship to first order logic. However, the field employs nonmonotonic techniques and higher orders of logic.

Knowledge Representation: A field of research within artificial intelligence that seeks to methodically identify ways in which to represent and reason about knowledge of a particular domain.

Artificial Intelligence: The field of research aimed at getting a computer to perform tasks which one would normally associate with intelligence. Mathematician Alan Turing proposed what is now called “the Turing test” to define artificial intelligence. Loosely speaking, place a computer in one secluded room and a human in another secluded room. If an observer queried these two entities and could not identify which entity was the computer, then the computer had achieved intelligence on a par with a human.

Knowledge Worker: A knowledge worker is a worker whose job depends on the processing and use of knowledge and information in work situations that require decision making, and demand his initiative and responsibilities

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