ORGANIZATIONS AND GROUPS FORM to create value that cannot be created by individuals [7]. Value means anything that someone might consider useful, important, or desirable. As such, value can only be defined and measured from the point of view of a particular entity: a person, a group, an organization, or a society. Because people have many different kinds of needs, wants, and desires, organizations may create value along many dimensions, including economic, physical, emotional, social, cognitive, and political dimensions.
In the pursuit of value creation, people are limited by the capacity of their attention resources. When trying to achieve a goal (create value), one person can assimilate and understand only so much, reason so much, and take only so many actions in a day. Over the years, several avenues have been explored to overcome these limitations. First, systems professionals and researchers have developed technology to support discovery and understanding. As we consider understanding in organizations, the question arises: understanding of what? Many authors, such as Ackoff [1], Bellinger [2], and Davenport and Prusak [4], have framed hierarchies of knowledge or information with data as the lowest level, followed by information, knowledge, and wisdom. In last year's special issue of JMIS, Ilkka Tuomi [9] made the provocative and rather persuasive argument that the familiar hierarchy might, in fact, be upside down, with wisdom as the bottom layer and data as the top layer.
Upside down or right side up, the definitions of these layers have always been problematic. What is data? What is information? What is knowledge? Definitions abound, but they do not always satisfy. Data, information, and knowledge are related, but how can one express that relationship? And what is the hierarchy? Can we conceive of the whole hierarchy in terms of one of its intermediate layers? The knowledge hierarchy? The information hierarchy?
It may be useful to frame this hierarchy as a hierarchy of understanding. We can then define each layer in terms of what can be understood.
• Data-understanding of symbols
• Information-understanding of relationships among data
• Knowledge-understanding of patterns, processes, and context
• Wisdom and judgment-understanding of the principles, causes, and consequences that give rise to intellectual and ethical positions
Many of the technologies developed by systems professionals, such as semantic database queries, data mining systems, or knowledge representation systems, reduce the amount of scarce attention required for organizational members to find and understand that which is buried-in vast data stores, and in the minds of their colleagues.
Second, with the realization that decision-making and problem solving in organizations can no longer be a task carried out by individuals alone [6, 7] came the focus on collaboration and participative problem solving. Collaboration is the degree to which people in an organization can combine their mental efforts so as to achieve common or congruent goals. People in organizations work together on at least three levels: collective, coordinated, and concerted. In collective work, like sprinters at a track meet, organizational members make uncoordinated individual efforts. Group productivity is simply the sum of their individual outputs. In coordinated work, people make individual efforts, but like members of a relay team, they have critical points where they must carefully coordinate hand-offs of deliverables. With concerted work, like the members of a sailboat racing crew, all members must perform their tasks in con-cert for the team to be productive. Be it collective, coordinated, or concerted collaboration [8], in order to combine the power of many minds, a group must be able to create, sustain, and change effective patterns of interaction. To this end, considerable research and development effort has been spent on collaboration technologies, such as e-mail, team databases, workflow automation, and GSS tools like electronic brain-storming, group outlining, and voting tools, to name but a few.
However, the effective application of such technologies does not depend on the technology alone, but on the combination of tool and technique [9]. As a result, the development and evaluation of various facilitation techniques are found high on research agendas around the globe. In order to facilitate value creation, organizations apply methodologies, or repeatable work processes. A methodology is a predefined set of steps and guidelines for attaining a particular goal, either focusing on reasoning (problem solving) or action (solution implementation). While they often appear sequential and orderly, methodologies are seldom executed as if following a cookbook recipe [10]. Their main purpose is to provide overall guidance to organizational groups and support repeatable effective reasoning processes to assure that teams reach their goals consistently and with predictable quality [3].
Taken together, understanding and collaboration are the building blocks of what we call an organization's intellectual bandwidth. The intellectual bandwidth of a team or an organization represents its potential to do meaningful work through the minds of its members. Intellectual bandwidth can be increased either by increasing a team's ability to understand or by increasing the ability of its members to collaborate. However, multiplicative gains may be obtained by increasing both. Figure 1 illustrates a conceptual model of intellectual bandwidth. This model may be used to plot the intellectual bandwidth of an organizational unit. Indeed, it may also be used to plot the potential contribution a particular technology might make to the productivity of an organization. The effectiveness with which an organization can create value is bounded by its intellectual bandwidth, which is its collective potential to acquire information, make sense of it, and take action with respect to a goal.
Therefore, in order to create value, groups must have sufficient intellectual band-width. That bandwidth derives from (1) their ability to discover and understand, and (2) their ability to create, sustain, and then change their patterns of collaboration. This special issue presents you with eight papers, each of which addresses various aspects of organizational value creation and intellectual bandwidth. These papers were selected from among the best at the 32nd and 33rd Hawaii International Conference on System Sciences. The first four papers address issues relating to the hierarchy of understanding. The following two deal with issues of collaboration. The final two papers address topics central to information systems research. One is a case study of a large systems development project, and the other offers a taxonomy of IS development methodologies.
The lead paper in this volume, "Leveraging Tacit Organizational Knowledge," by Stenmark, addresses one of the great challenges of organizational understanding: how to capitalize on tacit knowledge. Most approaches in this area focus on making such knowledge explicit, which is an expensive and long process. However, the author shows that organizations and their workers can take advantage of the available tacit knowledge without making it explicit. Stenmark argues that the professional interests of users in a corporate setting are examples of tacit knowledge. He shows that a so-called recommender system that is based on this premise can seek out documents of interests to its users. In addition, a recommender system may support the forming of communities of interest.
One of the most critical activities in problem solving methodologies concerns the creation and comparison of alternative solutions. In his paper "An Experiment to Assess the Performance of a Redesign Knowledge System," Nissen evaluates the effectiveness of an automated business process redesign tool as compared to novice business process reengineering consultants. The results of his study are encouraging in that they show how groups of problem solvers could move more efficiently toward effective options for organizational redesign using KOPeR-lite, a knowledge-based process redesign system.
Figure 1 omitted.
In their paper, "Workflow-Centric Information Distribution Through E-mail," Zhao, Kumar, and Stohr address issues relating to the hierarchy of understanding by exploring effective ways to electronically distribute only appropriate information through the organization. Taking a workflow perspective on information distribution, the authors identify two distribution methods-dynamic mailing lists and automatic profile matching. They show that in workflow environments, intelligent distribution approaches can be used to reduce information overload.
In order to effectively collaborate, people have to be able to make sense of what information is exchanged. This is a challenge in situations where people exchange thousands of messages-so-called very-large-scale conversations. In his paper, "Conversation Map: An Interface for Very-Large-Scale Conversations," Sack addresses this problem. He demonstrates the conversation map system, which draws from social and semantic network theory. The system assists in understanding and critically reflecting on histories of very large-scale conversations. This is especially useful for conversation analysis researchers and practitioners who need to gain a rough under-standing of past communication without spending a lot of effort.
Much research has shown that people using GSS to brainstorm exchange more information than people using standard means. However, there was some indication that people who receive more information do not necessarily use that information to support their decisions. In their paper, "Stimulating Thinking: Cultivating Better Decisions with Groupware Through Categorization," Hilmer and Dennis demonstrate that when individuals use GSS-like capabilities to categorize the information from a brainstorming activity, they attend to that information more thoroughly. They appear to incorporate it into their reasoning processes, and they make measurably better decisions. Because the authors were investigating questions of individual cognition in a group setting, rather than group productivity, they used a GSS simulator to generate what appeared to be contributions from other group members. This reduced the number of required subjects and increased the experimental control. The results have implications both for individual and group decision-making techniques.
In the paper, "Group Support Systems: A Descriptive Evaluation of Case and Field Studies," Fjermestad and Hiltz present a sequel to their landmark Winter 1998-1999 paper in this same journal. In their previous work they summarized the findings of more than 200 GSS experiments. In this follow-on paper, they present an overview of 54 GSS case and field studies that have occurred over the past two decades. Among other things, their review suggests GSS has had a positive effect on team collaboration in the field. This paper will be an invaluable resource for GSS researchers and practitioners who wish to "know what we know, and know what we don't know" about GSS experiences in the field.
The paper titled "The Propagation of Technology Management Taxonomies for Evaluating Investments in Information Systems," by Irani and Love presents a case study that addresses two approaches that organizations can use to support IT/IS investment decisions. These approaches address a plethora of tangible and intangible benefits that may ensue from implementing IT/IS. Their work is useful for researchers to focus future inquiries into IT/IS implementation and for practitioners to guide IT/IS implementation projects. Moreover, the paper demonstrates how much can be learned just by building systems, and how useful it is to have case studies of development projects to inform the research.
In the final paper in this volume, Iivari, Hirschheim, and Klein focus on information systems development in their paper, "A Dynamic Framework for Classifying Information Systems Development Methodologies and Approaches." They introduce a four-tier framework that can be used to classify various ISD methodologies and approaches, which they illustrate with 11 well-known ISD approaches. Iivari et al.'s work is especially useful, since there is no single development approach that is universally applicable. Their framework will support practitioners in the selection of complimentary approaches and educators in teaching students to critically evaluate various aspects of known ISD approaches.
The lessons that can be drawn from the work presented in this volume are many, and apply to researchers and practitioners alike. They address ways to assimilate in-formation more easily and effectively. They show how tools and meeting techniques can enhance collaboration in teams. They address issues in the area of organizational problem-solving and implementation methodologies. In doing so, the authors of these papers showcase a variety of research methods and approaches, ranging from theoretical and developmental to experimental and field study methods. We commend these papers to your attention and hope they will facilitate your own understanding and trigger and fuel collaboration with research colleagues.
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