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Genetic Algorithms A |
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| A significant challenge in managing today��셲 enterprise is quickly and effectively choosing among a large number of complex options and alternatives with subtle trade-offs. Fortunately, new computer applications using genetic algorithms can do a much better job at making these choices than a person using traditional analytical techniques. |
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Businesses Get a "Se |
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| Like animals, companies have always monitored changes in their environments. Historically, companies have moved slowly in response to changes. For example, if a retailer��셲 sales of red sweaters outpaced sales of green sweaters during the Christmas shopping season, the results would not be noticed until months later. By the time the retailer could react, the holiday season was over, and the insights might not be relevant to the following year. |
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Tracking the Experts |
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| Regardless of whether we��셱e talking about open or closed innovation, building open source or proprietary systems, or discussing operating under a product-centered business model, a customer-centered model, or a co-creation model, companies can��셳 effectively compete unless they can locate and organize the available expertise. But, expertise can be surprisingly difficult to find, even in businesses that have spent millions to attract and retain world-class experts. The problem isn��셳 that the company doesn��셳 have the expertise; it��셲 that no one knows who has it or how to find it. |
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Open Innovation |
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| At the same time that the open source movement is accelerating, the trend of open innovation is also picking up speed. This makes perfect sense because at a time when innovation is essential to the success of every business, few companies can afford to follow the traditional ��쐁losed innovation��� model that rejects any ideas that were ��쐍ot invented here.��� |
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The 6 Types of Worki |
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| 저자 | Patrick M. Lencioni |
| 출판사 | Matt Holt |
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[62]권 
