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Humble Leadership

Leading Blog

Edgar Schein and Peter Schein call this Level 1 based leadership. But it comes at a cost. I T NEVER HURTS TO BE REMINDED of the need for humility. We tend to fall back on transactional relationships and rule-based leadership. That is relationships that are intentionally personal, cooperative, and trusting.

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Peter Senge on the Creation of a Post-Industrial Theory and Practice of Education

Deming Institute

Edgar Schein, “Culture are the assumptions we cannot see”. Within Toyota there are no standardized measures for cost control. A human being, a “you,” only exists in relationships. The Zulu greeting, “hello,” meaning, “I see you”. Hard to know what fish talk about, but you can be damn sure it isn’t water. It’s the water we live in.

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It’s About What You Add to the Interaction

Lead Change Blog

In his book Humble Inquiry , Edgar Schein (2013) makes the argument that a good relationship is based on your inquisitiveness and your ability to ask the right questions, rather than how much information you give the other. Defuse the obligation issue. Then you have those with just a modicum of self-esteem (level 1).

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How Digital Natives Are Changing B2B Purchasing

Harvard Business Review

It reduces cost, saves time, integrates sources of information, connects, organizes, informs and provides access to previously hard-to-find data and expertise — all “elements of value” that have direct application to both consumer and B2B purchasing and product usage.

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What Tops Your 2011 Agenda?

Harvard Business Review

We found Ed Schein, for example, still working hard in his "emeritus" days, and hoping to discover keys to getting increasingly diverse teams to click fast and work as one in high-pressure conditions. The first, we will admit, is a self-inflicted pattern: Several of our thinkers are setting their sights on aspects of managing people.

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If Your Data Is Bad, Your Machine Learning Tools Are Useless

Harvard Business Review

Alan Schein Photography/Getty Images. Possible objectives for using machine learning include: Lowering the cost of the existing decision process. Poor data quality is enemy number one to the widespread, profitable use of machine learning. Consider a mortgage-origination company that wishes to apply machine learning to its loan process.

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