Exploring the Gati model

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Career decision-making can be thought of as a process flow, where we logically step through gathering and analysing information, comparing options, and finally selecting our optimal choice (Gati & Kulcsár, 2021).

Earlier work by Gati was the PIC model (Gati & Asher, 2001; read more here), which begins by sifting our information, narrowing the vast "universe" of potential career options to a more manageable group of "promising" options in the Pre-screening (P) step (Gati & Asher, 2001). We purge options which don't fit our pre-screening criteria. Then we look at our "promising" options in more detail, checking them for our specific preferences, abilities, and personality in the In-Depth Exploration (I) step (Gati & Asher, 2001). From there we then systematically compare all options for advantages and disadvantages to create a rank-ordered list in the Choice (C) step, finally identifying our optimal option (Gati & Asher, 2001).

While the Gati and Kulcsár paper (2021) uses the PIC model (Gati & Asher, 2001) as a suggested process flow to follow, it formalises the readiness element as part of the PIC process - see the image accompanying this post - by making it a frame to go around the PIC framework. Our ideas about career are made clear, as is the type of information we may need to consider when making career decisions.

We should not be approach career decision-making as a way to find a 'dream job'; but as a cooler, more adaptive and informed career decision-making process which lowers the stakes, makes outcomes more flexible, and so - hopefully - avoids potential irreversibility (Gati & Kulcsár, 2021). In considering these elements, we need to inject a dose of realism that 'ideal' jobs rarely exist; we must compromise on certain job aspects; bridge the gap between what is desirable and what is attainable by settling for "good enough". We need to seek the optimal, or satisfice. But in saying that, we can find "good enough" options during Pre-screening (P), then move to a more maximising approach - identifying the "best" - during the Choice (C) step (Gati & Kulcsár, 2021).

However. It is my view that this model should be slightly amended, as follows, to show how PIC fits with this frame:

Why the update from Gati and Kulcsár (2021)? Our world has grown increasingly complex, and the process must allow for uncertainty, unplanned events and unexpected opportunities. Our decision-making structures must be flexible enough to be supported by AI-synthesis of big data when Pre-screening, and which may provide some level of guidance during In-depth exploration (Gati & Kulcsár, 2021). If this frame helps the PIC process stay flexible and intuitive enough, it may help us be more confident in our choices, improve satisfaction, and - hopefully - reduce regret. Worthy aims indeed.

While this is better, I still find this model too complicated. Maybe iteration three might spring it into focus for me!

Sam

References:

Gati, I., & Asher, I. (2001). Prescreening, in-depth exploration, and choice: From decision theory to career counseling practice. The Career Development Quarterly, 50(2), 140–157. https://doi.org/10.1002/j.2161-0045.2001.tb00979.x

Gati, I., & Kulcsár, V. (2021). Making better career decisions: From challenges to opportunities. Journal of Vocational Behaviour, 126(1), 103545. https://doi.org/10.1016/j.jvb.2021.103545