Good news: I got a new job! In the very near future I’m going to be joining a large utility company (a different one than the one I’m currently at) as a staffing/selection specialist. Implementing selection systems, validation research, project management, integration with other HR systems, all that kind of thing. Essentially the same kind of things I’m currently doing, only moreso. As much as I loved the people and work at Sempra Energy, this is definitely a good move for my career.
The job, however, is kind of halfway across the country. So the bad news is that Selection Matters is going on hiatus for about a month. In the next few weeks I’ll be on house hunting trips, packing up my things, and driving a minivan many hundreds of miles across several states and climates. And can I just say how much I’m going to miss Southern California? I now get depressed every time I go out into the warm sunshine and clear skies. At any rate, through all this I’ll have little or no access to the Internet, which means that updating the site won’t be too practical.
But I will be back after SIOP, and I’m sure I’ll see plenty of interesting things there to ponder and make silly blog posts about. Hope you come back, and see you then!
I’m always fascinated by the varied approaches that different branches of science tackle the same problems. There’s an interesting report on research done by economists (found via Strategic HR Lawyer) that lays out some of the drivers of job satisfaction and their value relative to increases in pay. This isn’t directly related to selection and assessment, but job satisfaction and tenure are often criteria that we’re interested in when deciding if a selection system has value.
Here’s the meat of the piece:
Trust in management is by far the biggest component to consider. Say you get a new boss and your trust in management goes up a bit at your job (say, up one point on a 10-point scale). That’s like getting a 36 percent pay raise, Helliwell and Huang calculate.
In other words, that increased level of trust will boost your level of overall satisfaction in life by about the same amount as a 36 percent raise would.
Conversely, if you lose some trust in management, the decline in your job satisfaction is like taking a 36 percent pay cut.
Having a job that offers a lot of variety in projects, Helliwell and Huang found, is the equivalent of a 21 percent hike in pay.
Having a position that requires a high level of skill is the equivalent of a 19 percent raise.
Interesting stuff. I’d love to see the original research to see how it compares to how psychologists typically go about looking at job satisfaction –self-report data on ordinal scales, measuring theoretical constructs.
I have no objective. What’s the point when cold death is the final destination for us all? Can you explain that to me? I know I’m supposed to put something here, though, so here goes: Your objective is to hire me into a challenging position in a computer-applications-based field within which you feel I can “make a difference” and “contribute” in a team environment.
Bachelor of “Science” in Computer Applications, University of Washington
B.S., all right. It tickles me greatly that vapid, hornswoggled employers place so much emphasis on scholastic aptitude and higher education, as if knowing the Pythagorean theorem could shield me from the stygian pointlessness of mortality or the lurid abyss of imminent nonexistence. Of course, I use the word “tickles” figuratively, since I feel absolutely nothing.
And they say Nietzsche-related humor as applied to selection systems is dead…
The official Google Research blog has an interesting blurb about their “Lake Wobegon” hiring strategy –that is, hire only people who are of above average ability. They went so far as to put up a Googletastic graph showing how this approach is, theoretically, better than the “hire if they’re better than the worst person here” approach.
I’ve written before about how the rules change out of necessity when your business moves at insane speeds. I have first-hand experience with this, too. But the Google Research entry strikes me as a little nonsensical. What exactly is being graphed? What “ability” is being discussed here. Knowledge of computer science? Intelligence? Fit with the Google culture? Given that businesses of any complexity have a division of labor that creates diversity in its jobs and thus diversity of the skills, knowledges, and abilities needed for those jobs, trying to plot “ability” on one axis seems more like a bizzare exercise than proof that your particular hiring strategy works.
That being said, I do wonder what the medium-term and long-term results would be for applying this kind of reasoning to test cut scores if you were talking about a single ability or a composite of several abilities for a particular job or job family. Say you knew that customer service orientation, as measured by a personality test, was important for a job. The job of Customer Service Representative (CSR), for example. And the pass/fail decision for each applicant was made by comparing his/her score to the mean score of the existing CSRs. Would the trend in job performance look like what the Google Research post describes?
I’d guess so. It’d be pretty easy to find out by creating a Monte Carlo type of experiment with hypothetical data given a number of different starting conditions and assumptions about test validity. In fact, this is close to what the Google Research blogger says he did. I also wonder if this would be a defensible cut score strategy –improving the ability of the workforce is often cited as an adequate reason for setting cut scores higher than the average ability of your current job incumbents. Where things would probably break down, though, is when you can’t find anyone with a high enough customer service orientation to hire after your group’s mean passes some threshold. So you have to either alter your cut score strategy or not hire anybody. Still, interesting to consider if your goal were to improve the quality of your incumbents over some temporary period of time.