Exceptions and Other Rare and Irregular Events: Two Modes of Learning in Business Intelligence (Research in Progress)

Irregular and unpredictable events are increasingly important design elements of several of the latest business intelligence technologies, such as complex event processing (CEP), business performance management (BPM), and the real-time enterprise (RTE). Theories of individual and organizational learning from irregular events - exceptions, interruptions, surprises, accidents, and so on - tend to conform to one of two contradictory patterns. I draw these theories together to understand the complementary processes by which learners derive knowledge and insight from irregular events. I identify contingency factors that bias learners toward one of the two cognitive modes - incorporation of multiple events into a generalized understanding, or expansion of individual events into rich analytical conversations - and propose "exception design" levers by which BPM dashboard implementers can adjust these factors and influence the way users create knowledge in business intelligence. A pilot experiment lends some support to the hypothesis that frequency and ambivalence are designable aspects of exceptions that affect learning. The author seeks feedback and suggestions for a more effective research design.