Abstract
This work focuses on the execution of knowledge-intensive business processes by harnessing collective intelligence without codification. Trying to automate processes that are neither completely predictable regarding pre-defined structure and activities but instead require the decisions of experts, traditional workflow management reaches its limits. Having recognized this deficit, several new business process management concepts and techniques arose, drawing upon the advantages of Enterprise 2.0 and social software to face the complexity of knowledge-intensive processes. These elements offer cooperative coordination but always require linguistic codification to enable the knowledge transfer. This article untangles the various terms and concepts, derives requirements and develops a set of metrics that lead to a social, design-by-doing, machine-learning tool that harnesses the collective intelligence without the need for codification.
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Fink, A., Vogt, S. (2014). Managing Knowledge-Intensive Business Processes by Harnessing Collective Practical Experience without Codification. In: Zehbold, C. (eds) S-BPM ONE - Application Studies and Work in Progress. S-BPM ONE 2014. Communications in Computer and Information Science, vol 422. Springer, Cham. https://doi.org/10.1007/978-3-319-06191-7_7
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DOI: https://doi.org/10.1007/978-3-319-06191-7_7
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