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In fact, most of the content that AI repurposes from online resources is explicit knowledge. The hidden treasure of organizational knowledge is tacitknowledge that is deeply rooted in people, their experiences, skills, insights and judgements. That’s all tacit and invaluable at the same time.
Despite the media coverage of Boomers and how a tidal wave of retirements could impact business, many senior managers are kicking the can down the road, putting off the job of creating a system and process for capturing knowledge. Will younger workers have the knowledge and skills to run our organizations when they do? But your [.]
Many leaders see organizational learning simply as sharing existing knowledge. This isn’t surprising given that this is the primary focus of educational institutions, training programs, and leadership development courses. In an organization focused on scalable efficiency, the focus of learning is on sharing explicit knowledge.
Developing a diverse leadership pipeline can benefit companies in all sectors. To increase diversity at senior executive levels, more must be known about one group in particular: women of color in midlevel leadership, who successfully developed and progressed beyond individual contributor and first-line management.
What’s more, the subsidiaries operated more or less autonomously, each with separate organizational cultures and norms. This type of orientation can be incredibly valuable to cultivate for anyone working for multinationals or in other global careers, and can also be used by managers to develop employees.
Further, algorithms cannot (yet, anyway) tap intuition — the soft factors that are not data inputs, the tacitknowledge that experienced managers deploy every day, nor the creative genius of innovators. Algorithms only operate on the inputs they’re provided. So what should managers, especially leaders, do? They are not.
Most of the absorbed knowledge — local contacts and relationships, intelligence, insights, and so on — left with them. The company no longer has any operations at all in Silicon Valley. Some of the outpost team were hired by local companies or joined startups.
The only person not applauding was Wang Xiguo, the engineer who had led the development of Prime's power train technology. For another, Prime had embedded a great deal of "tacitknowledge" into some of the components — knowledge that was more "know why" than pure know-how. The workers standing near him applauded.
However, we don’t need to learn with others in formal training or development programs: we can architect our own opportunities to gain insight, knowledge, and skills that move us on an upward trajectory. Take charge of your own development. Don’t let the word “love” scare you. You and Your Team.
Further, algorithms cannot (yet, anyway) tap intuition — the soft factors that are not data inputs, the tacitknowledge that experienced managers deploy every day, nor the creative genius of innovators. Algorithms only operate on the inputs they’re provided. So what should managers, especially leaders, do?
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