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When the Hiring Boss Is an Algorithm
Hugh Pickens writes "Joseph Walker writes at the WSJ that although personality tests have a long history in hiring, sophisticated software has now made it possible to evaluate more candidates, amass more data and peer more deeply into applicants' personal lives and interests. This allows employers to predict specific outcomes, such as whether a prospective hire will quit too soon, file disability claims, or steal. For example after a half-year trial that cut attrition by a fifth, Xerox now leaves all hiring for its 48,700 call-center jobs to software. Xerox used to pay lots of attention to applicants who had done the job before. Then, an algorithm told the company that experience doesn't matter. It determined what does matter in a good call-center worker — one who won't quit before the company recoups its $5,000 investment in training. By putting applicants through a battery of tests and then tracking their job performance, Evolv has developed a model for the ideal call-center worker (PDF). The data recommend a person who lives near the job, has reliable transportation and uses one or more social networks, but not more than four. He or she tends not to be overly inquisitive or empathetic, but is creative. 'Some of the assumptions we had weren't valid,' says Connie Harvey, Xerox's chief operating officer of commercial services. However, data-based hiring can expose companies to legal risk. Practices that even unintentionally filter out older or minority applicants can be illegal under federal equal opportunity laws. If a hiring practice is challenged in court as discriminatory, a company must show the criteria it is using are proven to predict success in the job."
tends not to be overly inquisitive or empathetic
Well, if the bean counters consider the lack of those qualities to be what makes for a good callcenter worker then it's no wonder that the quality of support has gone down as fast as it has. Six or seven years ago when I called into support there was about a 50% chance of reaching someone who was smart and could solve my problem without relying on a script (which never solve my problem because if it can be found in available documentation I've already tried it before calling support), today there's maybe a 5% change if that.
There are 4 boxes to use in the defense of liberty: soap, ballot, jury, ammo. Use in that order. Starting now.
http://marshallbrain.com/manna1.htm
One massive computer controlled database that marks you hireable or not hireable.
I had a hell of a time landing a federal position in the department that I had been working for years as a contractor because the automated system at OPM kept kicking my resume out of the candidate pool. If you fail to get past that, then local hiring managers aren't even aware you have applied, and have no recourse. A co-worker finally gave me pointers on "faking out" the word filters, and I went from "unqualified" to "highly qualified" overnight.
Since it doesn't guarantee success, it's a heuristic...and I wouldn't trust anybody trying to sell me one, who doesn't know the difference
Meh. I consider it a heuristic that I use to filter out the employer if they require read access to my Facebook. My Facebook is locked the fuck down; they'd find my name but not much more. If that's a problem, well, I have recruiters emailing me every day, so good luck with your search.
It's better to vote for what you want and not get it than to vote for what you don't want and get it.
- E. Debs
There's a growing trend of hiring intelligent Japanese, Chinese and Indian workers at a fraction of cost to U.S. ones
You think labor rates are cheap in Japan? GDP per-capita in Japan is about 4X that of China and about 10X that of India. Japan has plenty of talent but it isn't particularly cheap or abundant talent. Japan, like the US, relies heavily on automation. Labor intensive industries left Japan years ago just like they did in the US.
The U.S. ranks 23rd among developed nations in the percentage of students with undergraduate degrees in science or engineering who are employed in related fields
Now figure out what that means. It's not at all clear what significance is in having a lower percentage of engineers at a portion of the population. The US is also the third largest country in terms of population so even if they produce a lower percentage of engineers than some other countries they still will produce larger absolute numbers than most of them. You seem to be implying that graduating a lower percentage of engineers/scientists will result in negative consequences. While that might be true you have to back it up with more than just vague implications.
Funny how our education ranking has dropped considerably once the 'No Child Left Behind' bill went into service.
Enforcing everyone passes education at the detriment of our more intelligent children does us no good.
No article on hiring algorithms is complete without mentioning the secretary problem.
In brief, how do you decide that you've interviewed enough people and select a candidate, even though that means ignoring anyone you have yet to interview?
Use of the words "good", "bad" or "evil" is almost invariably the result of oversimplification.
That couldn't possibly be due to years of massive overproduction of American STEM graduates, now could it.
Of course not, there's a slashdot article every semester about how we need more people in STEM degrees, especially women.
Especially hot women.
Especially hot women with a fetish for nerdy men, and possibly a tendency for bisexuality.
That $5k is an average number for call center training. For professional positions, it's between 1 and 1.5x annual salary.
Sadly, your brother needs to adopt better parents, because that's how you get jobs. Do you think Mitt Romney, son of a Mexican immigrant who was a migrant farmer and never made more than a subsistence wage and never interacted outside of the migrant community would have had job offers in big firms or ready-made partnerships with well-connected businessmen? Of course not. Take your brother, add in a network of hundreds of friends and colleagues in various fields, have someone prominent in the community and in business vouch personally for his abilities, and I can almost guarantee him a job in under a month, and a 6 figure job in under 5 years - far less if it turns out your brother is both personable and responsible. Add in some ability (numbers, management skills, sales ability) - it doesn't even need to be technical in any way, and he'll be on his way to a very comfortable lifestyle.
Can you claw your way up from the bottom? Yes, but you have to be exceptionally lucky in finding a job with growth and a manager who sees ability and is not threatened by it. Or you have to just be downright good and start your own enterprise from the ground up. The latter generally requires the moral flexibility to spend a lot of time in the gray area of the law (skirt regulation as much as you can) and personal relationships (be a ruthless backstabbing sonofabitch).
Is it just my observation, or are there way too many stupid people in the world?
As usual, most of the respondents either did not RTFA, or simply did not understand it because many of the respondents have got it exactly backwards.
Management did not just make up a set of characteristics they thought would be good (in this case hire local drone) and hire those after doing a drone-test. That's the way it had been done for the last few thousand years.
So here's what happened.
A company tests applicants for a very broad set of characteristics.
They track the performance of the hires.
They compare the success of the hires back to the characteristics found in the test.
They make a model of the successful hires and then use that model to select future hires.
Scientific model:
Construct hypotheses
Gather data
Conduct test
compare result to hypotheses
refine hypotheses
Anyone that is complaining about the algorithmic process and it's outcome has no idea how most people are typically hired.
For the most part, It still boils down to 1: being someone's buddy/relative and 2: looking like someone the HR boss would like to hang out with.
So I, for one, welcome our new algorithmic masters. ( having neither buddy nor looking like someone you would want to hang out with)
Also, this is very far from being new. I know of one upscale hotels started doing this a couple or three decades ago.
They gave all their employees a variety of tests and observed what characteristics were associated with the successful ones in the various positions.
Then, when people apply, they assign them to the position they'll be successful in. The end result is that successful floor-cleaners are happy and productive floor-cleaners, and people whose profile fits the front desk are happy and successful there. And it should be obvious that swapping those two people might create two very resentful employees. It really shows, too, if you ever stayed in a place like that how the good moods of the employees is almost Stepford-spooky.
I'm an industrial/organizational psychologist at Evolv. I help build assessment content and I work closely with our predictive algorithms. A few clarifications from the WSJ article & responses to /. comments:
Yes, creativity and empathy are important for some positions, even in call centers! We're not looking for hateful drones who will hang up on you when you call in. In addition to staying longer, our recommended hires perform better as well. That means increases in both customer satisfaction and efficiency (we call it "average handle time"). But it's a curvilinear relationship - somebody who is too inquisitive is going to tend to waste your valuable time (and their employer's) while trying to resolve your issue. There's a balance.
Most test vendors put a test in place and walk away. At Evolv we take all the post-hire data from our clients and continually feed it back into our algorithms. The content, scoring, and weighting adjust over time to be more predictive.
At Evolv, we don't pair obvious responses when we create questions. So no "I like to steal office supplies" vs "I always show up to work on time" questions. Coupled with the continual refresh & validation of the content, there is no "answer key" that will get you a job. One of the neat things about this approach that we've found is that people applying to entry level positions often don't know what they're good at. Either they've bounced around a few jobs or they're just out of high school. So when somebody applies to a call center job that's hiring for both customer service and sales positions, and we can recommend the position for which they're likely to be "fitter, happier, and more productive"... that's kind of cool. Their employer will make more money off a more stable employee, and the employee ends up doing something they will enjoy just a little bit more. I know some folks will see it from the Radiohead point of view, as creepy (and I respect that), but we think it's better than dumping somebody into a position they're not going to enjoy just because they had the right keywords on their resume or they BS'd their way through an interview.
Science & statistics help eliminate some crazy gut-based hiring decisions. Some hiring managers want to ask call center applicants what they'll be doing in 10 years with an expected response of "I'll be working at this call center". But let's be realistic - while some people enjoy them and thrive, call center jobs are typically not where you plan to be in 10 years. We've also found that resume experience for entry level positions is less important than basic skills and attitude. It's easy to look at that and say "duh" but you'd be surprised how many people hiring & screening for these roles want to exclude applicants who don't have prior experience. So we can cut things out of the interview and hiring process that just don't mean anything.
Evolv doesn't just do employment screening. We periodically follow up with people after they're hired. We find out what information wasn't communicated well during the hiring process, get their feedback on how their training is going, their thoughts on their supervisor, that sort of thing. We feed all of this back in to improve the process. In some cases, that means identifying the trainers whose students perform poorly when they start working. Other times it could be flagging a tenured stellar performer whose numbers are starting to dip for a new position to help reinvigorate them. We strive to improve profitability across the workforce, and do so in an employee-friendly way.
Last but not least, we're still expanding through Xerox, so if you've called their customer service and had a bad experience it must not have been one of our hires. Joking aside, agents are people too, and even our top recommendations have a bad day. We're working hard to to make it better though!
Hope that helps! Yes, there definitely are risks with employment testing, but we try to avoid them and build solutions that make everybody's life a little better.
Cheers,
Tim
I was sought out specifically by a government agency because of some research work I had done and some tools I had developed - they basically had a position that was an EXACT match for my skills, just in a broader scope.
I had to submit my CV to their automated system and was rejected because there was a typo in one of the filter criteria for their automated screening system. Then when they fixed it and I resubmitted, because I was found unqualified previously I was booted out.
They reset the job listing, triple checked the criteria, had me re-format my resume and submit it from a different email address just to make sure it wouldn't reject, but then when a human HR manager looked, she noted I had been rejected previously (but not why) and rejected it again.
Bottom line, you need smart people handling your hiring, and you need to make damn sure your automated systems are helping rather than hindering getting good people in there.
What's funny is that they wound up hiring me as a consultant (costing them at least 3x as much as hiring me on staff would cost) for the work, which worked out great for me since I was able to keep my old job and do the new work telecommuting with only the occasional trip to various sites.
Since I can't tell them apart, I treat all ACs as the same person.
I was once asked (on a formal test, the last hoop) in a job interview for a big box store whether I would turn my mother in if I caught her stealing.
I was entirely unsure of what answer they were looking for. On one hand you would think they would want employees to be that dedicated to protecting their assets. But lets be real, is ruining your family worth your part time job, over a petty theft? Bitch at them and return the item to the store, yes...
I can't imagine anyone (who is 100% sane) would. This would indicate that anyone who answers yes is either a damned liar or not mentally stable. But by saying "no" means you may be immoral (yet, honest?).... so... which was correct? I answered "no" for the sake of honesty. And did not get the job. Not sure if that is why or not, but still wonder.
Japanese workers are extremely hard working and incredibly unproductive. I hope they serve as a warning on the importance of work/life balance.
I have worked in Japan, this is VERY true. During much of the work day, and especially the late afternoon/early evening was almost official goof-off time. Then everyone buckled down and got to work in the overtime hours. And if you left before 9pm you were supposed to apologize to everyone. It was weird.
Also, many Japanese Engineers are still paid hourly instead of being salaried, so it is to their advantage to work long hours. Plus, white collar workers wore "uniforms" of some sort everywhere. Often it was just the same color pants and shirt for everyone. And it was a different color for females.
And then there was always the morning "chant" meeting where everyone gathered and did the weird company chant. Of course when I asked my co-workers about any of these things I was always told "It's a Japanese thing."
A common misconception. The actual phrase is "To all in tents and porpoises", meaning that it addressed to everyone who doesn't care that it's raining.