The Evolution from Data to Wisdom in Decision-Making at the Level of Real and Virtual Networks

Introduction

The purpose of this chapter is to provide the theoretical background for the computer-driven applications in problem-solving and decision-making in practice of real and virtual networks. The main premises of this study are as follows:

• 1.

  So far Knowledge Management systems (KMS) were limited to data and information processing, but with the dawn of data mining, they should be very useful in elaborating rules of knowledge of a given business or organizational unit, which should enhance problem solving and decision-making in practice.

• 2.

  The KMS can be useful but is not the ultimate feature in problem-solving and decision-making, since the ultimate factor is wisdom, which is very difficult to automate. Hence the wisdom-oriented approach towards problem solving and decision-making is defined in this chapter.

• 3.

  The evolution approach towards knowledge and wisdom applications in problem-solving and decision-making is applied in this study in order to understand stages (and their possible success/failure factors) of information technology applications in applying these units of cognition.

The decision-making process is predominantly a cognition-oriented process. Cognition as a process is mostly associated with thinking, which processes information either stored in human memory or just fed into it from external sources. The “source material” in cognition-oriented processes is information. However nowadays, information can be treated as a colloquial term, which must be decomposed into more elementary, quanta kind of units, which will be called cognition units, such as; data, information, concept, knowledge, and wisdom. They convey the essence of thinking and decision-making under the form of message semantics. Of course there is a question of how do they sent it through several gates of mind, and external channels of communication. This flow reflects the syntax aspect of cognition units processing and handling. In this study this aspect is limited to networks, either real or virtual. Another aspect of messaging in decision-making is the pragmatic aspect of cognition which deals with the question: Why is a decision made? This aspect is not considered in this study. These three cross-sections of cognition are treated under the framework of Knowledge Management systems as shown in Figure 1.

Figure 1.

The cross-sections of knowledge management systems

Knowledge management systems’ technological tools are closely related to information technology as well as to organizational learning initiatives. Knowledge management may be distinguished from organizational learning by its greater focus on the management of specific knowledge assets and development and cultivation of the channels through which knowledge flows for the purpose of decision-making, supported by information technology.

This study will look how cognition units can be applied in the problem-solving/decision-making processes in order to make these processes more information-concept-knowledge intensive. The evolution of KMS will provide some suggestions for the limits of technology applications in management. This technology will be allocated in various processes taking place in real and virtual networks in order to evaluate its usefulness for decision-makers.

Since the potential of KMS seems to be endless, there is a question: How far can this technology automate decision-making? The answer will be provided after reviewing a concept of wisdom, which is one of the cognition units with the highest complexity. Based on these considerations some suggestions for practitioners and researchers as well as for developers will be provided.

The Semantic Ladder Of Cognitive Units

The process of communication in decision-making, as the main process of KMS, conveys meaning through five units of cognition:

• •

  Datum (D)