Data in Organization Studies

Data in Organization Studies

Organization studies (OS) is about understanding the social world we organization students inhabit. It is not a closed system of study like logic or mathematics. OS is necessarily an empirical study, exploring attitudes, behaviours, experiences, artefacts, symbols, documents, texts, feelings, beliefs, meanings, measures, facts and figures. Even the armchair/conceptual theorists must muse on empirical data.

But what is to count as data of organizational life? There is no clear consensus on an answer among the community (or is it communities?) of scholars who study organizations. Some organizational students (OSers) run well-controlled experiments to produce data which others claim ‘have little or nothing to say about the realities of organizational behavior’ (Lawler 1985: 4). Some spend months ‘in the field’ reporting their data as ethnographic tales that others dismiss as mere anecdotes (Martin 1990). Some ask hundreds and thousands of people to answer carefully chosen questions producing data which others disparage as simplistic, distorted reflections of the respondents’ organizational reality, unrelated to their organizational behaviour.

Can we reconcile these paradigm-laden positions and arrive at an acceptable definition of data for OS? The advantages of a common position are clear. If the field can establish a common paradigm, resources will flow more freely, and research will accumulate more ‘successfully’ (Pffefer 1993). We could all use the money! However, will the accumulation of knowledge reflect the variety and complexity of organizational reality? Many argue that accumulation is an illusion (see Canella and Paetzold 1994 and Jaros 1994 for specific responses to Pfeffer). These critics rely on contemporary philosophy of science (Kuhn 1970) and the sociology of scientific knowledge (Ashmore 1989) to support their position. The arguments applied to OS are well developed (Burrell and Morgan 1979; Morgan 1983; Hartman 1988).

A more recent challenge comes from postmodern and poststructural theorizing in the humanities (Zald 1994). Cooper (Cooper and Burrell 1988; Cooper 1989) and Burrell (1988) have written extensively on the implications of postmodernism for organizational studies. Hassard and Parker (1993) provide a sampler of views on the utility and significance of postmodernism for organization studies. Postmodern theorizing challenges the very notion of a common ground. In particular, postmodernists warn against any totalizing narrative (e.g. Jeffcut 1994a), i.e. an attempt to provide an all-encompassing explanation. They would argue that any attempt to develop a universal definition of data for OS is doomed.

Yet, my strategy in this review will be to offer such a definition of data in organization studies. However, I make no claim to absolute truth in doing so. Instead, I offer this grand narrative, bracketed as a heuristic for OS. I believe we can self-consciously use modernist writing techniques to forge temporary consensus, to create the shared tacit knowledge and assumptions required to do OS. Thus I do not write in opposition to the postmodern. As Deetz has noted in discussing competing research programs, they can be seen not as ‘alternative routes to truth, but as specific discourses which, if freed from their claims of universality and/or completeness, could provide important moments in a larger dialogue about organizational life’ (1995: 5). Though I cannot promise the beauty of Kubla Khan, I join Coleridge in asking you, the reader, for the suspension of your disbelief.

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