AbstractActionable knowledge has been qualitatively and intensively studied in the social sciences. Its marriage with data mining is only a recent story. On the one hand, data mining has been booming for a while and has attracted an increasing variety of increasing applications. On the other, it is a reality that the so‐called knowledge discovered from data by following the classic frameworks often cannot support meaningful decision‐making actions. This shows the poor relationship and significant gap between data mining research and practice, and between knowledge, power, and action, and forms an increasing imbalance between research outcomes and business needs. Thorough and innovative retrospection and thinking are timely in bridging the gaps and promoting data mining toward next‐generation research and development: namely, the paradigm shift from knowledge discovery from data to actionable knowledge discovery and delivery. © 2012 Wiley Periodicals, Inc.This article is categorized under: Application Areas > Data Mining Software Tools Fundamental Concepts of Data and Knowledge > Key Design Issues in Data Mining Fundamental Concepts of Data and Knowledge > Motivation and Emergence of Data Mining