Rethinking Information Systems in Organizations

Integrating Organizational Problem Solving

John Paul Kawalek

• Publisher: Routledge
• Year: 2008
• Print ISBN: 9780415403047
• eBook ISBN: 9781134141999
• Topic: Business
• Subtopic: Business General
• Index: Business

In Rethinking Information Systems in Organizations John Paul Kawalek challenges the current orthodoxy of information systems and proposes new alternatives. Bold and ambitious, this book tackles the thorny issues of integration of disciplines, cross over of functions, and negotiation of epistemological divides in IS. Historically, the IS discipline has struggled to embrace and integrate technical as well as organizational knowledge, skills and methods. Kawalek argues that there are now a new set of imperatives that will irrecoverably change IS, affecting the way many organizations deploy and access their information and technology. This book defines how the traditional practices of Information Systems are required to integrate into a process of organizational problem-solving.

An essential read for students of business information systems, organizational theory and research methods, Kawalek's work also provides core methodological principles on organizational change and problem solving, and presents an effective rationale for their use in Information Systems contexts.

Part I
The discipline of information systems

This part discusses some of the current challenges of the discipline. First, it presents an interpretation of the history and emergence to date of the discipline of IS, and how it evolved as a response to meet the needs of practice. In order to do so, this part will outline a potted history and context of the discipline, and its past and future raison d’être. We will discuss the development of the discipline, and its current problems and challenges.

Second, this part questions how far it could be said that the modern discipline, as we know it today, can be considered a ‘success’ or otherwise. We will discuss this in terms of some of the problems and challenges in curricula design and the problems in the research activities of the discipline.

Although there have been huge successes in the field of practice, these have largely been achieved in large organizations, with significant budgets. The challenge in today’s context is to replicate these successes in smaller organizations, particularly in contexts where resources are not available for bespoke application development and complex software builds.

This discussion aims to provide the basis and rationale for the conceptual rethink of some of the core principles and elements of method to be discussed in Parts II, III and IV.

1
Emergence

Abstract

This chapter outlines a potted history of the discipline of information systems. The reason for doing so is that an historical account can provide insight into the present and future. This account of the history of the discipline of information systems is intended to help explain and contextualize the current challenges of the discipline, in terms of (i) the nature and raison d’être of the discipline, (ii) how the discipline has emerged to date, (iii) the nature of the discipline as it currently serves the field of practice, and (iv) the future of the field of practice, and the way the discipline will be required to change in serving practice.

Introduction

In order that a thorough analysis of the information systems discipline can take place, it is necessary to explore some of its most basic definitions, assumptions and why it has evolved in the first place. Inevitably, this requires a ‘potted history’ of sorts; also inevitably, such a ‘potted history’ is an imperfect human interpretation, but serves as a basis for exploring the most fundamental aspects the information systems discipline. It is imperfect, because of the significant ambiguity in the discipline and in the field of practice, which require making some significant generalizations. Exploring some of these ambiguities is certainly not a simple exercise because it involves an interpretation of sorts about some of the most fundamental constructs that are used within the discipline and in the field of practice, over a period of time.

For example, the term ‘information’ itself is ambiguous. Liebenau and Backhouse (1990) quote a number of different definitions of ‘information’, each of which reflects the interests, assumptions and assertions of their creators. For example, early ‘information systems’ work did not differentiate between data and information. The interest for Shannon and Weaver (1964) was in the coding and communication of ‘information’. They used the word ‘information’ to mean an ‘artefact’ that can be represented and communicated, and therefore take on physical characteristics. Generally speaking, within the field of information systems, data is commonly considered to be a record of events, activities, observations etc., while information is considered to be the relevance and use of that data in a given context. For instance Wilson (1984) discusses the human meaning attribution that converts data into information. Thus, commonly, data is considered an artefact, and information is purposefully constructed via human interpretation of the data. As such, the verb ‘to inform’ indicates a process that is intricately tied to human cognition (via a process of human interpretation), and can have both an implicit and explicit purpose e.g. to enable informed decision making to take place, to stop decisions being made, to obfuscate, to confuse, or to constructively ‘inform’ etc. A further important implication is that the meaning attribution of ‘information’ for one person is likely to be different for another user in some circumstances; but this does not mean that there are other circumstances where there may be a degree of ‘shared meaning’ attribution to the same data (see also Winograd and Flores 1986).

Since the process of converting data into information is full of implicit and explicit human purpose and cognitions, tied to the political, power and ambiguities of practice, information systems, as a discipline and as a field of practice, must be concerned with that process (e.g. the purposefulness inherent in the conversion of data into information). Millions of data can be recorded on physical media (paper, computers, books, internet, in the Library of Congress, information systems textbooks). Conversion of data into a meaningful and usable form may very well involve considerable processing and, in the field of information systems, terms such as ‘information processing’ or ‘data processing’ are used to describe that activity. Nonetheless, it should not be assumed that ‘information’ is a human act (i.e. by attaching meaning to data), and that ‘data’ is in some way devoid of human purpose. Data cannot be considered devoid of humanly constructed purpose. For example, data is not ‘God-given’ (at least in most circumstances!). It is humanly constructed, collected (or not collected) for specific human purpose; it is stored in a particular way, based on an assumption about its utility for human use and the process of ‘meaning construction’. In that sense, data itself is not ‘objective’ as might sometimes be assumed.

History

In organizations, information is generally seen as being central to the job tasks, politics and culture of everyday human activity, and of organizational processes. As such, both data and information are always highly integrated with the activities that they serve (e.g. for decision making, coordination of actions, power games, to justifying actions). Information and its use is an intrinsic part of organizational activities. It makes no sense in the field of practice, and in the discipline, to consider information to (i) completely separate the information processing activities from a given organizational process, or to, (ii) consider that data is in some way ‘independent’ or ‘objective’ – it is purposely humanly constructed, as is the information processing that is served by it. The organizational process, the information and the data are all inextricably linked together, although in some situations it is possible to conceptually separate them.

In craft production, it is quite impossible to separate the information processing from the human actions that are involved. That is to say, the information that is used to perform the task cannot be separated from the task itself. The information to undertake the task are deeply embedded in the task, and implicitly absorbed within the activity. An outsider who might want to acquire a given set of craft skills will typically work as an apprentice for a period of time. In these contexts, there is often little need of a separate ‘information processing’ activity because the information processing is often completely integrated with the task, and mostly carried out in the mind.

In other organizational processes, however, it can be more meaningful to conceptually (and temporarily) separate the ‘information processing’ oriented activities from the ‘physical’ oriented activities that use it. The conceptual separation enabled the creation of separate data processing tasks, e.g. in the process of bookkeeping there is a data processing component. The bringing together of similar data processing activities led to the creation of specialized roles such as accountants, statisticians and clerks. The industrial revolution sharpened the divisions between those who were engaged in data processing activities and those who were engaged in the execution of tasks, based on the information, i.e. white and blue collar workers (see Braverman 1974; Scarborough and Corbett 1992). The emergence of the white collar worker was, in a sense, a movement from physical activities to those that focus on recording and processing data. It is in this separation of the physical actions and activities in human organizations from the information processing activities that provided the raison d’être of the information systems discipline.

The arrival of computers marked the beginning of the automation of data processing activities. The perception of the computer as a calculating machine resulted in computing technology being allocated a home in the accounts departments of commercial organizations. In universities the same basic reasoning helped them to locate their computers in mathematics or applied mathematics departments. However, the power of computers to operate with program instructions enabled a new discipline to emerge from the mathematics departments, in the form of computer science. The ability to handle non-financial activities helped data processing to emerge as a ‘sub-department’ within the accounts departments in many organizations, e.g. to handle stock control, order processing etc. The primary role of computers within organizations was to handle large volumes of data, storage of that data, and the output, but with simple processing requirements; whereas computers used in the applied mathematics or computer science departments typically handled fewer data inputs and outputs, but vast amounts of processing and computations.

It was the extension of the use of the computers by mainframe and minicomputer manufacturers (IBM, Honeywell, Hewlett Packard, ICL, DEC) into diverse business domains, especially into non-financial activities (e.g. manufacturing, logistics, workflow), which enabled the data processing functions in accounting departments to grow and break away to form departments of their own. These created demand for a large number of specialists with knowledge of computers (e.g. with programming skills in languages such as COBOL), combined with knowledge of organizational functions. These were a new breed of individuals who had specific technical skills but who could operate in organizational contexts.

These changes also led to the popularity and use of the term ‘information technology’. In essence the terms ‘information technology’ and ‘computer technology’ usually refer to the same technology. However, the term ‘information technology’ is used to emphasize the use of computers for information processing, storage and presentation to satisfy perceived needs for converting data into usable and purposeful information, given particular sets of perceived organizational and human needs. The term ‘computer technology’, on the other hand, is used to emphasize the experimentation and exploration of the computational power of the technology with a very different purpose. Its purpose is focused on the capabilities of the technology, its architecture etc., without consideration of the specific needs of a given human

In commercial organizations	First computers were most commonly located in accounts departments. Generally, there was a large volume of data which required relatively simple processing tasks, e.g payroll. A typical early language used was Cobol
In universities	First computers were typically located in mathematics departments. Volumes of data were often quite small, but required large processing capacities, i.e. ‘number crunching’ applications such as multiple regression and linear programming. Typical early languages were Fortran and Algol, and a little later Pascal

Figure 1.1 Early adoption of computers

organizational context. Broadly speaking, in the former, information technology is considered only to be a means to an end whilst in the latter, computer technology is often considered to be an end in itself (see Jayaratna 1994). This dichotomy continues to exist in both academic institutions and in non-academic institutions. Although there remains much overlap and many fuzzy lines, ‘computer science’ has emerged to reflect the advancement of the technology as a primary objective whereas ‘information systems’ is largely concerned with the application of that technology by humans in human organizations, for information processing purposes.

University contexts

The pressure to produce graduates to meet the new demands of commercial applications of computers led to the formation of information systems groups within computer science departments, or of separate information systems departments in universities. Where there was strong resistance in the computer science departments to the introduction of knowledge areas on computer applications in organizations, business schools responded by opening their own information systems or management information systems departments. It might be argued that the birth of information systems as a discipline can be attributed to the failure of computer science to deal with emerging organizational problems. The scientific paradigms, with which computers were associated, were not appropriate for solving many of the emerging organizational problems. The ‘engineering’ principles that are involved in building computers, did not easily port to the building of organizations. Commonly, early computer scientists treated COBOL and associated business-related activities with contempt and predicted the death of COBOL (for over three decades!). In situations in which information systems remained a part of computer science departments, academics who were teaching information systems topics (or ‘management information systems’) sometimes found themselves alienated by their colleagues because of their closeness to organizational, business or commercial applications. Equally, academics who worked in information systems departments in business schools sometimes found themsel...

Table of contents

• Contents
• Illustrations
• Preface
• Acknowledgements
• Part I The discipline of information systems
• Part II Principles of organizational problem solving
• Part III Inquiring activities in organizational problem solving
• Part IV Whither inquiring activities?
• Notes
• Bibliography
• Index