2.2 Chaos Theory

Rachel Dolechek

Up to this point, we have discussed the importance of career development and both linear and non-linear career beliefs. The non-linear approach to career development accepts unplanned events and unpredictable conditions that will be endured throughout a career. Chaos theory embraces the non-linear aspects of career development. Chaos theory is the “study of the behavior of complex dynamical systems” (Kaufman, 1995 as cited in Pryor & Bright, 2011). It originated as a way to develop a better weather-predicting model. In practical terms, the further out we are in time, the harder it is to predict the weather. By using chaos theory in careers, you may see the connection between predicting the outcome of a future career. The greater the distance in time, the harder it is to be accurate in predicting career paths. There are too many variables, unplanned events, and unpredictable conditions in your life and in industry to accurately predict the outcome (Brooks, 2017).

We can use chaos theory to think about the potential disruptions you may have along your career journey. You can also utilize chaos theory to reframe how you think about career planning. Mesaros (2019) suggests:

  •       Place an emphasis on preparation instead of planning
  •       Focus on adaptation, not deciding (de-emphasize the finality of choices)
  •       Develop short-term, flexible goals
  •       Grow self-awareness and build transferrable skills

Being realistic about your career journey and how you prepare for this journey will set you on a path to adaptability and employability. Moving forward in this text, we take the perspective that the skills for self-managing one’s career are relevant to those looking to enter into the workforce or those looking to change careers. We will be focusing on helping you develop and maintain your employability through communication-based skills essential for the modern workplace.

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Introduction to Professional Development Copyright © 2022 by Rachel Dolechek & Rose Helens-Hart is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted.

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