Rethinking BPM in a Cognitive World: Transforming How We Learn and Perform Business Processes

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9850)


If we are to believe the technology hype cycle, we are entering a new era of Cognitive Computing, enabled by advances in natural language processing, machine learning, and more broadly artificial intelligence. These advances, combined with evolutionary progress in areas such as knowledge representation, automated planning, user experience technologies, software-as-a-service and crowdsourcing, have the potential to transform many industries. In this paper, we discuss transformations of BPM that advances in the Cognitive Computing will bring. We focus on three of the most signficant aspects of this transformation, namely: (a) Cognitive Computing will enable “knowledge acquisition at scale”, which will lead to a transformation in Knowledge-intensive Processes (KiP’s); (b) We envision a new process meta-model will emerge that is centered around a “Plan-Act-Learn” cycle; and (c) Cognitive Computing can enable learning about processes from implicit descriptions (at both design- and run-time), opening opportunities for new levels of automation and business process support, for both traditional business processes and KiP’s. We use the term cognitive BPM to refer to a new BPM paradigm encompassing all aspects of BPM that are impacted and enabled by Cognitive Computing. We argue that a fundamental understanding of cognitive BPM requires a new research framing of the business process ecosystem. The paper presents a conceptual framework for cognitive BPM, a brief survey of state of the art in emerging areas of Cognitive BPM, and discussion of key directions for further research.


Business Process Cognitive Agent Business Process Management Process Instance Unstructured Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors wish to than several IBM colleagues for numerous inspirational discussions on the topics presented in this paper, including Currie Boyle, Robert Farrell, Janet Hunter, Matthias Kloppmann Rong Liu, Mike Marin, Manoj Mishra, Nirmal Mukhi, Jae-eun Park, Karthikeyan Ponnalagu, Michael Oland, Eniko Rozsa, Stuart Strolin, and John Vergo. The authors also thank members of the working group [2] on Knowledge-intensive Processes (KiP’s) at the Dagstuhl workshop on “Fresh Approaches to Business Process Modeling” held in April, 2016, where the discussions were very stimulating and informative.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.IBM T.J. Watson Research CenterNew YorkUSA
  2. 2.IBM Almaden Research CenterSan JoseUSA

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