DECISION SUPPORT SYSTEMS:KNOWLEDGE MANAGEMENT FOR DECISION SUPPORT

KNOWLEDGE MANAGEMENT FOR DECISION SUPPORT

There can be no doubt that contemporary developments in information technology have changed engineering and business practices in many ways. The information revolution has, for example, created entirely new ways of marketing and pricing such that we now see very changed relationships among producers, distributors, and customers. It has also led to changes in the ways in which or- ganizations are managed and structured, and deal with their products and services. In particular, it creates a number of opportunities and challenges that affect the way in which data is converted into information and then into knowledge. It poses many opportunities for management of the environment for these transfers, such as enhancing the productivity of individuals and organizations. Decision support is much needed in these endeavors, and so is knowledge management. It is fitting that we conclude our discussions of decision support systems with a discussion of knowledge management and the emergence in the 21st century of integrated systems to enhance knowledge management and decision support.

Major growth in the power of computing and communicating and associated networking is fun- damental to the emergence of these integrated systems and has changed relationships among people, organizations, and technology. These capabilities allow us to study much more complex issues than was formerly possible. They provide a foundation for dramatic increases in learning and both indi- vidual and organizational effectiveness. This is due in large part to the networking capability that enables enhanced coordination and communications among humans in organizations. It is also due to the vastly increased potential availability of knowledge to support individuals and organizations in their efforts, including decision support efforts. However, information technologies need to be appropriately integrated within organizational frameworks if they are to be broadly useful. This poses a transdisciplinary challenge (Somerville and Rapport 2000) of unprecedented magnitude if we are to move from high-performance information technologies and high-performance decision support systems to high-performance organizations.

In years past, broadly available capabilities never seemed to match the visions proffered, especially in terms of the time frame of their availability. Consequently, despite these compelling predictions, traditional methods of information access and utilization continued their dominance. As a result of this, comments something like ‘‘computers are appearing everywhere except in productivity statistics’’ have often been made (Brynjolfsson and Yang 1996). In just the past few years, the pace has quick- ened quite substantially, and the need for integration of information technology issues with organi- zational issues has led to the creation of related fields of study that have as their objectives:

• Capturing human information and knowledge needs in the form of system requirements and specifications

• Developing and deploying systems that satisfy these requirements

• Supporting the role of cross-functional teams in work

• Overcoming behavioral and social impediments to the introduction of information technology systems in organizations

• Enhancing human communication and coordination for effective and efficient workflow through knowledge management

Because of the importance of information and knowledge to an organization, two related areas of study have arisen. The first is concerned with technologies associated with the effective and efficient acquisition, transmission, and use of information, or information technology. When associated with organizational use, this is sometimes called organizational intelligence or organizational informatics. The second area, known as knowledge management, refers to an organization’s capacity to gather information, generate knowledge, and act effectively and in an innovative manner on the basis of that knowledge. This provides the capacity for success in the rapidly changing or highly competitive environments of knowledge organizations. Developing and leveraging organizational knowledge is a key competency and, as noted, it requires information technology as well as many other supporting capabilities. Information technology is necessary for enabling this, but it is not sufficient in itself. Organizational productivity is not necessarily enhanced unless attention is paid to the human side of developing and managing technological innovation (Katz 1997) to ensure that systems are designed for human interaction.

The human side of knowledge management is very important. Knowledge capital is sometimes used to describe the intellectual wealth of employees and is a real, demonstrable asset. Sage (1998) has used the term systems ecology to suggest managing organizational change to create a knowledge organization and enhance and support the resulting intellectual property for the production of sus- tainable products and services. Managing information and knowledge effectively to facilitate a smooth transition into the Information Age calls for this systems ecology, a body of methods for systems engineering and management (Sage 1995; Sage and Rouse, 1999a,b) that is based on analogous models of natural ecologies. Such a systems ecology would enable the modeling, simulation, and management of truly large systems of information and knowledge, technology, humans, organizations, and the environments that surround them.

The information revolution is driven by technology and market considerations and by market demand and pull for tools to support transaction processing, information warehousing, and knowledge formation. Market pull has been shown to exert a much stronger effect on the success of an emerging technology than technology push. Hardly any conclusion can be drawn other than that society shapes technology (Pool 1997) or, perhaps more accurately stated, that technology and the modern world shape each other in that only those technologies that are appropriate for society will ultimately survive.

The potential result of this mutual shaping of information technology and society is knowledge capital, and this creates needs for knowledge management. Current industrial and management efforts are strongly dependent on access to information. The world economy is in a process of globalization, and it is possible to detect several important changes. The contemporary and evolving world is much more service oriented, especially in the more developed nations. The service economy is much more information and knowledge dependent and much more competitive. Further, the necessary mix of job skills for high-level employment is changing. The geographic distance between manufacturers and consumers and between buyers and sellers is often of little concern today. Consequently, organizations from diverse locations compete in efforts to provide products and services. Consumers potentially benefit as economies become more transnational.

Information technology-based systems may be used to support taking effective decisions. Ideally, this is accomplished through both critical attention to the information needs of humans in problem solving and decision making task and provision of technological aids, including computer-based systems of hardware and software and associated processes, to assist in these tasks. There is little question but that successful information systems strategies seek to meaningfully evolve the overall architecture of systems, the systems’ interfaces with humans and organizations, and their relations with external environments. In short, they seek to enhance systems integration effectiveness (Sage and Lynch 1998).

Although information technology and information systems do indeed potentially support improve- ment of the designs of existing organizations and systems, they also enable fundamentally new ones, such as virtual corporations (DeSanctis and Monge 1999), and they also enable major expansions of organizational intelligence and knowledge. They do this not only by allowing for interactivity in working with clients to satisfy present needs, but also through proactivity in planning and plan execution. An ideal organizational knowledge strategy accounts for future technological, organiza- tional, and human concerns to support the graceful evolution of products and services that aid clients. Today, we realize that human and organizational considerations are vital to success in using infor- mation technology to better support decisions. A major challenge is to ensure that people gain maximal benefit from these capabilities. This is why information technology must be strongly as- sociated with information ecology, knowledge management, and other efforts that we discuss here and that will ultimately lead to an effective systems ecology (Sage 1998).

There are three keys to organizations prospering in this type of environment: speed, flexibility, and discretion (Rouse 1999). Speed means rapid movement in understanding a situation, such as a new product development or market opportunity; formulating a plan for pursuing this opportunity, such as an intended joint venture for the new product; and deploying this plan so as to proceed through to product availability in stores. Flexibility is crucial for reconfiguring and redesigning or- ganizations, and consequently reallocating resources. Functional walls must be quite portable, and generally the few of them the better.

Discretion transforms flexibility into speed. Distributed organizations must be free to act. While they may have to play by the contemporary and evolutionary rules of the game, they need to be able to adapt rapidly when things are not working well. Resources can thus be deployed effectively and speedily and results monitored quickly. Resource investments that are not paying off in the anticipated time frame can be quickly redeployed elsewhere, thereby ensuring adaptive and emergent evolution of the organization.

A major determinant of these organizational abilities is the extent to which an organization pos- sesses intellectual capital, or knowledge capital, such that it can create and use innovative ideas to produce productive results. The concept of intellectual capital has been defined in various ways (Brooking 1996; Edvisson and Malone 1997; Stewart 1997; Klein 1998; Roos et al. 1998). We would add communications to the formulation of Ulrick (1998), representing intellectual capital to yield:

Intellectual capital = Competence X Commitment X Communications

Other important terms, such as collaboration and courage, could be added to this generic equation.

Loosely structured organizations and the speed, flexibility, and discretion they engender in man-

aging intellectual capital fundamentally affect knowledge management (Myers 1997; Ruggles 1997;

Prusak 1997; Albert and Bradley 1997; Liebowitz and Wilcox, 1997). Knowledge workers are no longer captive and hence know-how is not ‘‘owned’’ by the organization. What matters most is the

ability to make sense of market and technology trends, quickly decide how to take advantage of these

trends, and act faster than other players. Sustaining competitive advantage requires redefining market-

driven value propositions and quickly leading in providing value in appropriate new ways. Accomplishing this in an increasingly information-rich environment is a major challenge, both fo rorganizations experiencing contemporary business environments (Allee 1997; Stacey 1996) and for those who devise and provide decision support systems for supporting these new ways. The major

interactions involving knowledge work and intellectual capital and the communications-driven information and knowledge revolution suggest many and profound, complex, adaptive system-like changes in the economy of the 21st century (Hagel and Armstrong 1997; Shapiro and Varian 1999; Kelly 1998; Hagel and Singer 1999). In particular, this has led to the notion of virtual enterprises and virtual communities and markets where customers make the rules that enhance net gain and net worth.

All of this creates major challenges for the evolution of knowledge organizations and appropriate knowledge management. One of the major challenges is that of dealing in an appropriate manner with the interaction among humans, organizations, and technologies and the environment surrounding these. Davenport and Prusak (1998) note that when organizations interact with environments, they absorb information and turn it into knowledge. Then they make decisions and take actions. They suggest five modes of knowledge generation:

1. Acquisition of knowledge that is new to the organization and perhaps represents newly created knowledge. Knowledge-centric organizations need to have appropriate knowledge available when it is needed. They may buy this knowledge, potentially through acquisition of another company, or generate it themselves. Knowledge can be leased or rented from a knowledge source, such as by hiring a consultant. Generally, knowledge leases or rentals are associated with knowledge transfer.

2. Dedicated knowledge resource groups may be established. Because time is required for the financial returns on research to be realized, the focus of many organizations on short-term profit may create pressures to reduce costs by reducing such expenditures. Matheson and Matheson (1998) describe a number of approaches that knowledge organizations use to create value through strategic research and development.

3. Knowledge fusion is an alternative approach to knowledge generation that brings together people with different perspectives to resolve an issue and determine a joint response. Nonaka and Takeuchi (1995) describe efforts of this sort. The result of knowledge fusion efforts may be creative chaos and a rethinking of old presumptions and methods of working. Significant time and effort are often required to enable group members to acquire sufficient shared knowl- edge, work effectively together, and avoid confrontational behavior.

4. Adaptation through providing internal resources and capabilities that can be utilized in new ways and being open to change in the established ways of doing business. Knowledge workers who can acquire new knowledge and skills easily are the most suitable to this approach. Knowledge workers with broad knowledge are often the most appropriate for adaptation as- signments.

5. Knowledge networks may act as critical conduits for innovative reasoning. Informal networks can generate knowledge provided by a diversity of participants. This requires appropriate al- location of time and space for knowledge acquisition and creation.

In each of these efforts, as well as in much more general situations, it is critical to regard technology as a potential enabler of human effort, not as a substitute for it. There are, of course, major feedbacks here because the enabled human efforts create incentives and capabilities that lead to further enhanced technology evolution.

Knowledge management (Nonaka and Takeuchi 1995; Cordata and Woods 1999; Bukowitz and Williams, 1999) refers to management of the environment for knowledge creation, transfer, and sharing throughout the organization. It is vital in fulfilling contemporary needs in decision support. Appropriate knowledge management considers knowledge as the major organizational resource and growth through enhanced knowledge as a major organizational objective. While knowledge manage- ment is dependent to some extent upon the presence of information technology as an enabler, infor- mation technology alone cannot deliver knowledge management. This point is made by McDermott (1999), who also suggests that the major ingredient in knowledge management, leveraging knowledge, is dramatically more dependent upon the communities of people who own and use it than upon the knowledge itself.

Knowledge management is one of the major organizational efforts brought about by the realization that knowledge-enabled organizations are best posed to continue in a high state of competitive ad- vantage. Such terms as new organizational wealth (Sveiby 1997), intellectual capital (Brooking 1996; Edvinsson and Malone 1997; Klein 1998; Roos et al. 1998), the infinite resource (Halal 1998), and knowledge assets (Boisot 1998) are used to describe the knowledge networking (Skyrme, 1999) and working knowledge (Davenport and Prusak 1998) in knowledge-enabled organizations (Liebowitz and Beckman 1998; Tobin 1998). Major objectives of knowledge management include supporting organizations in turning information into knowledge (Devin 1999) and, subsequent to this through a strategy formation and implementation process (Zack 1999), turning knowledge into action (Pfeffer and Sutton 2000). This latter accomplishment is vital because a knowledge advantage is brought to fruition only through an action advantage. Appropriate information technology and knowledge man- agement tools (Ruggles 1997) are necessary but not at all sufficient to enable knowledge creating organizations or knowing organizations. The result of appropriate creation of knowledge in organi- zations (Prusak 1997) leads to a very important result, a knowing organization in which organizations use information to construct meaning, to create knowledge, and to use this knowledge in taking decisions. The term fourth generation R&D has been given to the efforts necessary for management of knowledge, technology, and innovation. A framework to enable this is described in Miller and Morris (1999).

The major increase in interest in knowledge management in recent years has been brought about by the reality that contemporary engineering and business success are progressively more linked to abilities associated with the management of data, information, and knowledge. Knowledge manage- ment is concerned with knowledge creation, knowledge acquisition, knowledge packaging, knowledge transfer, and knowledge use and reuse by humans and organizations. Knowledge management and decision support each support a common purpose: making decisions and actions taken on the basis of information and knowledge more effective. Thus, it is reasonable to suggest that an objective of knowledge management is to make appropriate knowledge available in a timely and cost-effective manner to decision makers. It seems very safe to predict that computer-based decision support systems will increasingly employ or be associated with various knowledge management techniques to enhance the representation and processing of information such that it can be best associated with contingency task structures to become the beneficial knowledge that is absolutely needed for effective decision support.

The development of intellectual capital such as to optimize organizational value is of particular importance in effective decision support. This is accomplished by using information to construct meaning and create knowledge and thereby enable appropriate decision and action. Such an organi- zation has been called a ‘‘knowing organization’’ (Choo 1998). The major challenge in all of this is

very often that of making sense of a wealth of opportunities concerning alternative schools and strategies. These include dramatic increases in available data, as well as an ever-growing set of potentially useful methods and tools—and the major need to convert data into information and thence into knowledge—and to manage knowledge successfully in the networked economy. Sage and Rouse (1999a,b) identifies 10 important challenges and paradigms: systems modeling, emergent and complex phenomena, uncertainties and control, access to and utilization of information and knowledge, infor- mation and knowledge requirements, information and knowledge support systems, inductive reason- ing, learning organizations, planning and design, and measurement and evaluation. Ongoing trends in information technology and knowledge management pose substantial challenges for information systems frontiers. Addressing the 10 key challenges elaborated here requires a new, broader per- spective on the nature of information access and utilization, as well as knowledge management. Satisfactorily addressing these 10 key challenges, will require that decision support systems engi- neering efforts move beyond structure-bound views of the world and the natural tendency to nail down requirements and constraints before proceeding. The current dynamics of information technol- ogy and knowledge management make such ‘‘givens’’ obsolete almost as quickly as they are envi- sioned. These appears to be the major decision support systems engineering challenges today, and in a very real sense they are challenges for all of engineering and engineering management. In large part, they provide a major motivation for this Handbook.