The Jobs Churn Rate

Americans are quitting their jobs like crazy.

The latest monthly “Job Openings and Labor Turnover Survey” (JOLTS) showed that in December, the total number of quits was 3.1 million, the highest level in a decade, while the quits rate was 2.1%, the highest since April 2008. The rate takes the number of quits divided by the number of employees who worked or were paid for work.

If people are quitting their jobs, it may suggest that they are confident in the labor market and are receiving better-paying opportunities elsewhere. However, it may suggest a higher level of mismatch between opportunity and ability.

The report also showed that there were 5.6 million job openings during December, the second-highest ever, and more than the expectation for 5.41 million. The hires rate was 3.7%, and the layoffs and discharges rate was 1.1%.

The Enterprise and Placement Improvements

My previous posts titled Evaluating Placement Information (Parts 1 – 3) prompted a request for me to read an article by Don Fornes, CEO of Software Advice which sponsors The New Talent Times blog. I was asked by Software Advice to opine on the article.

The article, titled “The Psychological Profiles of the Dream Team”, was published on BusinessInsider and refers to a commissioned project by Mr. Fornes to analyze the high-performers at his company, to see what drives and motivates them. The research concluded with four distinct personality profiles which describes what makes their top players tick, the management style they respond best to, and how to identify and hire more people like them.

The following is my opinion about the problem the article addresses but in a more expansive view.

First, let’s define the problem. The problem is that an increasing number of people in the world are miserable, hopeless, suffering, and unhappy because they don’t have a good job—one that is a best-fit. The United States is no exception and, in fact, may be the poster child for workplace unhappiness.

Second, in almost all the content relating to ability placement there always seems to be an embedded assumption that we need to rely on the enterprise to make improvements. What if that assumption is wrong? What if the future of work is more about coordinating distributed work activity versus aggregated? Then, as solution providers, I think we need to design for the individual as a work network node, rather than designing for the enterprise as the work center, to realize the improvements we are looking for.

Third, we can look at the financial services industry for an analog to better understand how psychological profiles are used to help place capital at best-fit. After all ability is human capital. My experience tells me that psychological profiling of investors to facilitate the placement of financial capital at best-fit is more art than science. This is because the ongoing decision-making environment is extremely dynamic with very many variables. More specifically, in this space, best-fit knowledge may depend on tacit information held by individuals, distributed in a community network. If you accept this as a constraint and embrace it as such then you’ll be able to see the futility of trying to optimize the art of placing capital at best-fit.

So, in my opinion, psychological profiles can not be relied upon with a high degree of confidence to complete the job-to-be-done successfully. This is not to say that they are not an improvement but rather should be viewed as a sustaining innovation. It is my belief that to make the improvements we are looking for we need disruptive innovation.