Much as Barry Johnson is describing a process of optimization that is based on the ongoing and dynamic assessment of two polarities and modification of one’s decisions based on this assessment, I am describing a process that incorporates “reasonable and flexible set points” alongside “optimal responses” that are “repeatedly redefined.” A simple, mechanistic model of human behavior can’t contain the dynamic processes described by Johnson. Most importantly, a behavioral model that relies on a desire for return to a stable state (homeostasis) is inadequate for addressing the challenges inherent in Johnson’s polarities. Only a model that allows for flexible and changing “set-points” (baselines) and the search for ‘optimal responses” (effective actions based on valid predictions) can operate in an adaptive manner when faced with polarities—and the even more pervasive presence of volatility, uncertainty, complexity, ambiguity, turbulence and contradiction (VUCA-Plus) (Bergquist, 2020).
Susan’s Optimization
I turn back to case studies that I offered in one of the previous essays (Bergquist, 2024d) in this series. These case studies concerned two protagonists (Susan and Rick) and center on the Trust-based polarity that exists between Home (safety and security) (which I have labeled S²} and Quest (opportunity and openness) (O²) (Bergquist, 2024d). Susan is coming from a position of safety and security (S² /Home) and considering a move to a position of greater opportunity and openness (O² /Quest). Conversely, Rick is currently in a position of O² and considering the move back home to a position of greater S².
We find that Optimization for Susan might begin with her review of the want ads in her local newspaper—or nowadays her looking on the Internet for job postings in her own community. For what type of job might she be eligible? How would the pay for a specified posted job compare with what Susan is now making? Most importantly, is there something about this advertised job that stirs up Susan’s aspirations? Susan takes on the task of predicting how likely it is that she will be able to secure a “better” job. As she reviews several job postings, Susan will find that her prediction is changing, as is her baseline. She gains greater clarity regarding what kind of jobs might be in her skill-range and what kind of compensation she might anticipate.
Critically, Susan’s aspirations are likely to change given this feedback regarding jobs in her community and her modified prediction regarding job success. Her subsequent actions are likely to change based on this new baseline and prediction. She might decide to look at job postings in other nearby communities or might decide that she is making too much money as a long-time receptionist to consider any entry-level position. Instead, she might decide that job change is a viable option. And she begins to prepare a resume.
Yet another action might be taken. There are jobs that she might be able to take in her local community—how about a job in Chicago? She returns to the Internet and looks for job postings in Chicago. Obviously, there are many more postings. Her review of jobs in her own community enables Susan to do some sorting out of jobs in Chicago. Susan adjusts her baseline regarding compensation, knowing that the cost-of-living in Chicago will be higher than in her own suburban community. She has begun the process of optimization. Rather than swinging from one polarity to another, Susan is eliciting feedback from the Internet and adjusting her expectations and further actions.
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