Knowledge that Transforms

The Bank of America literally changed the banking industry during the 1950s by means of its ERMA and IBM 702 computer systems. These innovations in information technology resulted in a dominate design that helped keep the Bank of America in the lead for over a decade and a half. They were the collective work of a leader, Clark Beise, a maestro, Al Zipf, and a group of supertechs, all of whom became the prototypes for these crucial roles. Bank of America was the first organization, among a selected few, to successfully negotiate the innovation cascade leading from crisis to a dominant IT design. Due in large part to IBM’s failure to deliver a fully operational operating system for its 360/65, however, coinciding with the leadership’s attention toward international markets, in the late 1960s the Bank of America lost its lead. After several decades “in the trough, ” as a result of aggressive investment and leadership, the bank re-emerged as a strong competitor. This story of achieving alignment in strategy and structure by means of technological innovation, of the almost tragic breaking of that alignment, and of fervent efforts made to gain realignment illuminates some of the most important lessons of IT management that can be learned from the field’s relatively recent, but dramatic, history.

The lack of theories and methodological weakness have been pointed out as two distinct but related problems in empirical management information systems (MIS) research. Reinforcing the existing belief that too much attention has been devoted to “what" as opposed to “why” or “when” relationships exist, this paper focuses on a subset of model building and methodology issues involving the systematic discovery and representation of causal relationships. Our analysis of the existing empirical MIS literature reveals the need to build richer causal models, to increase the flexibility of model representation, to integrate the isolated worlds of pure latent and pure manifested variables, and to provide a tighter linkage between the exploratory and confirmatory research phases. Based on philosophy of science and advances in the fields of experimental economics and sociology, we propose a foundation for developing richer models by explicitly considering the exogeneity and endogeneity of constructs and a manipulative account of causality, and by recognizing the role of incentives, agent, and organizational characteristics in MIS models. Since richer models require more flexible tools and techniques, the paper describes the representational shortcomings and statistical pitfalls of factor-analytic methods commonly deployed in empirical research. We suggest that weak exploratory phase tools and approaches may allow violations of causal assumptions to pass undetected to the confirmatory phase. Since confirmatory tools like LISREL also make factor-analytic assumptions, these violations are not likely to be detected at the confirmatory phase either. We propose using TETRAD, a non-parametric tool, at the exploratory phase for its ability to accommodate a wide variety of causal models. The findings are summarized within an integrated framework, which enhances the likelihood of discovering relationships through richer theoretical support and powerful exploratory analysis.

MIS as a discipline has not yet developed a tradition of historical research. Historical analyses broaden our understanding of the processes by which information technology is introduced into organizations and of the forces that shape its use. Paramount among these processes are those Schumpeter called “creative destruction.” These are events that change entire organizations and industries. The end product of a Schumpeterian process is called a “dominant design,” a new configuration of an organization’s technology, strategy, and structure. A dominant design is manifested in several ways: a new organizational infrastructure, new functionality, new products, new services, new production functions, or new cost structures. By changing the basis of competition in the industry, a firm that institutes a dominant design secures an initial competitive edge. Although the understanding of these processes is central to the concerns of many researchers and practitioners in the field, the information systems research literature contains very few examples of historical analyses of this type. A contingency framework is developed for conducting a class of information technology-based historical studies that focuses on innovation and competition within an industry.

There is strong evidence that data items stored in organizational databases have a significant rate of errors. If undetected in use, those errors in stored data may significantly affect business outcomes. Published research suggests that users of information systems tend to be ineffective in detecting data errors. However, in this paper it is argued that, rather than accepting poor human error detection performance, MIS researchers need to develop better theories of human error detection and to improve their understanding of the conditions for improving performance. This paper applies several theory bases (primarily signal detection theory but also a theory of individual task performance, theories of effort and accuracy in decision making, and theories of goals and incentives) to develop a set of propositions about successful human error detection. These propositions are tested in a laboratory setting. The results present a strong challenge to earlier assertions that humans are poor detectors of data errors. The findings of the two laboratory experiments show that explicit error detection goals and incentives can modify error detection performance. These findings provide an improved understanding of conditions under which users detect data errors. They indicate it is possible to influence detection behavior in organizational settings through managerial directives, training, and incentives.

This paper provides insights for redesigning IT- enabled customer support processes to meet the demanding requirements of the emerging electronic economy in which fast response, shared knowledge creation, and internetworked technologies are the dynamic enablers of success. The paper describes the implementation of the TechConnect support system at Storage Dimensions, a manufacturer of high-availability computer storage system products. TechConnect is a unique IT infrastructure for problem resolution that includes a customer support knowledge base whose structure is dynamically updated based on adaptive learning through customer interactions. The paper assesses the impacts of TechConnect and its value in creating a learning organization. It then draws insights for redesigning knowledge-creating customer support processes for the business conditions of the electronic economy.

Change-readiness is the ability of an information systems (IS) organization to deliver strategic IT applications within short development cycle times by utilizing a highly skilled internal IS workforce. This paper examines two important questions: What are the design elements of a change-ready IS organization? How can transformations to such designs be effectively managed? Insights to these questions are generated through a case study of the conceptualization and implementation of an innovative organization design within a large IS unit at Bell Atlantic, a Regional Bell Operating Company. First, a rich description is provided of the components (strategy, structure, processes, people skills, reward systems) of a centers of excellence (CoE) design that has yielded measurable gains in IS performance. Then, an analysis of the two-year implementation of this CoE design is provided in terms of anticipated and unanticipated change actions, as well as a summary of “lessons learned.” The conclusion describes the design as a model worthy of consideration by other IS managers for developing change-readiness IT capabilities. Comparisons with other models for the IS organization are then drawn.