Abstract
Successful companies understand and respond to the latent demands of customers. “Chance discovery” means, as stated previously, the discovery of events essential for making decisions (Ohsawa and McBurney 2003). In this chapter, we describe a method of chance discovery in which visual/touchable tools for data-based decision making are positioned in the spiral of human–machine collaboration in a business environment. We present a case of an actual business using this method to choose the most promising textile products for production and sale in the real market. The results are evaluated on the basis of the subjective criteria of business people rather than the objective criteria of a computer, and the evaluation is then passed on to the next cycle in the process of chance discovery, thereby improving the business performance.
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Notes
- 1.
KeyGraph®; is registered trademark of Yukio Ohsawa of the University of Tokyo, Japan.
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Ohsawa, Y., Nishihara, Y. (2012). Using Maps for Scenario Externalization. In: Innovators' Marketplace. Understanding Innovation. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25480-2_3
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DOI: https://doi.org/10.1007/978-3-642-25480-2_3
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