• High Reliability - Myth or Possibility?

  • De: DNV
  • Podcast
High Reliability - Myth or Possibility?  Por  arte de portada

High Reliability - Myth or Possibility?

De: DNV
  • Resumen

  • DNV presents High Reliability - Myth or Possibility? Highly Reliable Organization. Just Culture. What do these terms really mean to executives seeking sustainable operational excellence? Delve into the history and current socio-technical science to define and explain the concepts surrounding High Reliability and Just Culture. We'll explore the relationship between the two terms, the principles that shape them, and how they are related. You'll hear examples of how any company in any industry can - and should - work toward becoming a Collaborative Highly Reliable Organization.
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Episodios
  • 11 - Exploring the what, why, and how of Collaborative Just Culture®
    Apr 2 2024

    By understanding the what and the why, we can move forward with determining the how. In this episode, Scott Griffith and Tammy Allen explain why we must understand what Collaborative Just Culture® is and why it is important for people and organizations. They also outline in detail how to attain Collaborative Just Culture®.

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    45 m
  • 10 - Can collaborative just culture programs improve labor relations?
    Feb 6 2024

    In this first episode of 2024, host Tammy Allen and guest speaker Scott Griffith investigate the question: can collaborative just culture programs improve labor relations? Whether or not you have a collective bargaining organization representing your employees, the frontline workers are vital to your culture and your ability to see, understand, and manage risk.

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    38 m
  • 9 - Are Biases a Risk in Your Organization?
    Sep 28 2023

    Are biases a risk in your organization? There are good and bad biases and problems can arise when they are not examined and considered as potential risks. In this episode, guest speaker Paul LeSage, founding partner and analyst at SGCS, joins us again to explain - with real-life examples - how to address biases as risks.

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    30 m

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