| Abstract | This paper reports on findings resulting from our research conducted for the 2014 Business Process Intelligence (BPI) Challenge. The goal of this year's challenge was to identify predictive patterns in the data, provided by Rabobank's ICT operations unit, that could be used to determine whether service calls and incidents were likely to increase or decrease as a result of any change implemented in their systems. We took two approaches: a macro approach where conclusions were drawn via analysis of aggregated data from the entire set, and a micro approach where sequence classification was used to uncover predictive patterns in the data for individual configuration items. Each approach addresses the challenge questions from different levels, and offers insight on the findings from each point of view that can be applied to improve company business processes and decision making in the future. |
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