Abstract
Hunches are important tools for executives making time-critical highly complex decisions in turbulent environments. However, hunches are also elusive and exist below the surface when not being used for immediate decision making. These latent hunches can be useful for developing analytical models. This paper coins the term “hunch mining” to describe the process of surfacing latent hunches from corporate decision makers as well as workers and using them as models for data analytics. We present the Organizational Hunch Matrix and show how organizations can make the leap from time-consuming manual cognitive analysis to artificial intelligence and analytics driven analysis facilitated by Cognitive Computing Engineers.
Cite
CITATION STYLE
Nelson, H. J., Clark, T., & Stewart, I. (2018). Hunch mining: Intuition augmented with cognitive computing, analytics, and artificial intelligence. In Proceedings of the Annual Hawaii International Conference on System Sciences (Vol. 2018-January, pp. 5065–5074). IEEE Computer Society. https://doi.org/10.24251/hicss.2018.633
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