Advancing Empirical Research
Edited by Markus C. Becker and Nathalie Lazaric
Chapter 4: Using Workflow Data to Explore the Structure of an Organizational Routine
4. Using workﬂow data to explore the structure of an organizational routine Brian T. Pentland, Thorvald Haerem and Derek W. Hillison INTRODUCTION Empirical study of organizational routines poses many diﬃculties for the researcher. Routines are typically distributed in time, space and throughout an organization’s structure. Short of ‘stapling yourself to the paperwork’, it is diﬃcult to observe even a single performance of an organizational routine from beginning to end. In addition, the natural variability in performances can make it diﬃcult to identify a single representative pattern. Time, money and patience often limit us to observations of a few performances, or parts of performances or interviews with a subset of participants. Workﬂow systems provide an unprecedented opportunity to gather data about the patterns of action generated by routines (van der Aalst et al., 2003). With the proliferation of computer network technology, more and more organizations have adopted workﬂow systems to support their routines (Basu and Kumar, 2002). These systems typically involve a mixture of human and automatic processing – they are like the ‘glue’ that holds together other, more common applications (Becker et al., 2002). Typical workﬂow systems generate ‘event logs’ that include time-stamped records of each event or action that occurs in the system, making it possible to collect large numbers of performances at very low cost. Computer scientists have made tremendous progress in analysing event logs for a range of purposes, such as the recovery of formal process models (van der Aalst et...
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