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I am curious if you or any other group is studying the current shutdown effects on pay and motivation and the long term effects (if any) on attracting, retaining, and motivating people who are working without immediate pay now. Obviously higher earning people are better able to weather this financially but there are a lot of people working who are lower wage and they are still coming to work. What is driving this? Pride? Fear? Lack of Other Opportunity? Retirement? I would LOVE to see an article on this!


Here is my hypothesis: The continued influx of AI/ML/RPA into the workplace will help usher in a rethinking of how we think about paying for positions. One impact of AI/ML/RPA is that is seldom eliminates whole jobs, usually only portions of jobs. This theoretically frees the individual to focus on other work, other duties, etc. It also creates a challenge since organizations may find themselves with a slew of "partial" jobs whose remaining duties and responsibilities cannot readily be combined in predictable ways. Instead, those jobs may become flexible "general practitioner" roles able to be surged when and where exigencies demand.

From a compensation lens, the challenge will be pricing "jobs" that do not have static duties/responsibilities. The value of a position may become less about the on-paper position and more about the capabilities of the incumbent in the position.

In short, Chris, my prediction is that AI/ML/RPA will help usher in more person-centric vice position-centric compensation (more rank-in-person pricing) than we have been used to seeing.

Oh, and a second big-picture prediction: better data science will trigger more granularity and more targeted salary increase data. Instead of the "salaries are expected to rise by 2.9%," we'll see forecasts which are much more specific with respect to industry/occupation/location than we get today.

For Katherine, that's a good suggestion. We're certainly not conducting any such type of study, since that role resides with other federal agencies. In more than a slight tinge of irony of course, those same agencies charged with performing such a study - are themselves currently furloughed. I'll assume that some of the quasi-governmental entities (Partnership for Public Service) will undertake a post-mortem study (sorry, it's the only word that seemed appropriate), when the shutdown concludes.

From past experience though, I know our organization has generally experienced an uptick in turnover and an increased difficulty in attracting new hire candidates in some period after prior shutdowns (at least until memory fades ...).

For Joe, I think your predictions synch up surprisingly well with what I previously speculated on, now almost eight years ago.

The slew of remaining partial jobs dovetails with my guess about the rise in the need for more broadly-knowledgeable generalists - and the wane of specialists (at least in HR and Compensation . . . but probably in other disciplines/domains as well).

You'll recall that on the market pay granularity, we've repeatedly pitched the exact shift in salary data collection and reporting you hint at, to a couple of the survey data providers - to target market pay trends by discipline/domain/function. So far, nobody has signed-up to that being a good idea.

The only point that we slightly diverge on, is your perhaps overly-optimistic perspective on the future of jobs. We're a little more pessimistic about this, and while we'd like to envision both the changes in work and the hoped for altruistic predisposition by employers - we think that's woefully unrealistic. Given the increased ability to automate both routine and increasingly complex jobs - we don't see any set of circumstances that would predispose employers to do anything except eliminate people from the work equation, as that becomes increasingly possible to do so.

Since I received a sidebar question, it might be beneficial to clarify it here - since I can see how what was written in the article might have been unclear.

The total worldwide workforce is estimated to be around 2.8 billion people (the U.S. workforce is around 158 million). So, in the reference above, automation might be anticipated to effect about 40 percent of these populations, respectively, in the next ten years.

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