(Over-)Measuring the Working Man
HughPickens.com writes: Tyler Cowen writes in MIT Technology Review that the improved measurement of worker performance through information technology is beginning to allow employers to measure value fairly precisely and as we get better at measuring who produces what, the pay gap between those who make more and those who make less grows. Insofar as workers type at a computer, everything they do is logged, recorded, and measured. Surveillance of workers continues to increase, and statistical analysis of large data sets makes it increasingly easy to evaluate individual productivity, even if the employer has a fairly noisy data set about what is going on in the workplace. Consider journalism. In the "good old days," no one knew how many people were reading an article, or an individual columnist. Today a digital media company knows exactly how many people are reading which articles for how long, and also whether they click through to other links. The result is that many journalists turn out to be not so valuable at all. Their wages fall or they lose their jobs, while the superstar journalists attract more Web traffic and become their own global brands.
According to Cowen, the upside is that measuring value tends to boost productivity, as has been the case since the very beginning of management science. We're simply able to do it much better now, and so employers can assign the most productive workers to the most suitable tasks. The downsides are several. Individuals don't in fact enjoy being evaluated all the time, especially when the results are not always stellar: for most people, one piece of negative feedback outweighs five pieces of positive feedback.
According to Cowen, the upside is that measuring value tends to boost productivity, as has been the case since the very beginning of management science. We're simply able to do it much better now, and so employers can assign the most productive workers to the most suitable tasks. The downsides are several. Individuals don't in fact enjoy being evaluated all the time, especially when the results are not always stellar: for most people, one piece of negative feedback outweighs five pieces of positive feedback.
This metric would seem to be encouraging authors that write the clickbaitiest titles. Sounds wonderful.
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Now wait a second. Management, generally speaking, doesn't understand data. They like to look at a nice Powerpoint slide with people ranked from best to worst. this means that all measures taken relative to workers' productivity get aggregated/coalesced into one, which will most likely be skewed because the aggregation algorithm would never take all variables into consideration.
Management won't look at 15 metrics per worker and try to understand the data; they want one value and that's it. Not good.
Consider journalism. You have Worker A and Worker B. You give A an assignment about work effectiveness evolution through history, and B gets to write about Kim Kardashian's choice of panties colors. A writes a 5000 word article, well documented, with references and shit, with a serious title. B writes a 300 word article filled with generic panties pictures with a clickbait title. A gets 300 views, B gets 5 million views. The algorithm generates a value based on efficiency and ROI, and A gets a score of 5/100 while B gets a score of 100/100. You look at the values, fire A and promote B.
Now you know why most articles out there are about Kim Kardashian and panties. Incidentally, you know why automatically measuring productivity can go tits up very quickly.
...gis sdrawkcab (usually not responding to ACs; don't bother posting as AC)
Sounds like a regurgitation of Taylorism and time-and-motion studies, for the digital worker. Will people never learn? You get what you measure, and if you aren't extremely careful, you'll cause dysfunction because the measurement goal isn't aligned with the organizational goal. (It always looks like it should be, but it rarely is.)
In any case there's nothing new here, just another well-meaning nitwit looking for the magic bullet.
statistical analysis of large data sets makes it increasingly easy to evaluate individual productivity, even if the employer has a fairly noisy data set about what is going on in the workplace.
This is only true if you know what to measure. Otherwise you are measuring activity. For example one programmer may type out lots of quick lines to empirically discover the format of a string a library returns for a given inputs, another might go directly to the documentation. One will press more keys, but which is more productive? I don't think you can always expect the correct answer if the statistic you use is average key presses per hour.
If someones job is to paint unpainted widgets in bin A and paint them and put them in bin B, that we can pretty accurately measure their productivity by determine how many widgets are in bin B each day and comparing them with others who do the same work, or can we? What about the defect rate? Measuring is hard, knowing what to measure is harder.
How do measure the productivity of a corporate staff attorney? What about route / switch admin? Is one who puts in more change requests more productive or does that just mean (s)he fails to plan ahead?
Be careful what you measure you will probably get favorable results, but its the side effects that will hurt you.
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the pay gap between those who make more and those who make less grows
That line clearly comes from someone supporting the insane wages of top executives in this country under the illusion that they are actually productive. They rarely make anything in terms of actual productivity - they are paid a lot primarily in reward for being well-connected.
Damn_registrars has no butt-hole. Damn_registrars has no use for a butt-hole.
A similar assessment of CEOs and other board positions.
"But there’s another fundamental driver of income inequality: the improved measurement of worker performance. As we get better at measuring who produces what, the pay gap between those who make more and those who make less grows."
This assumes people who produce more get paid more. This has not been the case for the past 30 years. That's why there is an income inequality. Wages have not kept pace with Productivity. So the issue has nothing to do with measuring productivity. This has to do with companies keeping worker pay low in order to increase dividends and CEO pay, which is a consequence of lower rates. If companies had to reinvest in the company, worker pay would keep pace with productivity.
Slashdot moderation system used to measure us as a total of karma over all posts to measure the contribution to Slashdot.
Slashdot had to stop using those because of karma whores.
Even meaningless numbers are a strong motivators to cheat a system. You have to be very careful about what you do. Improving those metrics will triumph over quality and ethics.
Case in point.
I can spend the time to manually type in a few hundred lines of configuration data for a Router / Switch for every device I manage.
or
I can spend the time to build an app or program that will effectively build the same configuration for me, guaranteed error free. I need
only change the unique data for the site which can be done prior to the program launching.
So, if my employer is tracking how much I type or how many windows I click on in a day*, which of the two above scenarios is the more
efficient methods of getting a job done ? Because I didn't sit for three days straight and manually configure these systems, then I'm not
as productive ?
Heh. I'll say again, metrics are rarely accurate enough to base decisions on by themselves.
*Which is really easy to fudge with a simple script or program.
99.9999999% of organizations will choose to measure something more concrete in hopes that it will be a reasonable proxy for productivity. It won't be.
And that is the real problem. There is no known way to overcome it. But MBA bean-counters that lack any understanding of reality will go for metrics every time, regardless of how misleading they are, because these cretins are unable to do anything else.
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FTA: "The result is that many journalists turn out to be not so valuable at all. Their wages fall or they lose their jobs, while the superstar journalists attract more Web traffic and become their own global brands."
So at least in journalism, only the most popular will have a subsidized voice, and the rest will have to pay their own way if they want to share their insights. Since when is popularity the ultimate measure of value in a society, especially when it comes to news? Sometimes people really need to hear the stuff that's scary, uncomfortable, guilt-inducing, etc., even though it's not popular. If we continue down this road then I hope everyone enjoys having Fox-style reporting as the only available news source.
Yes, I realize I've used a 'reductio ad absurdum' argument, but I don't think I've gone very far into absurdity here. It strikes me that in a lot of ways this kind of 'metric' is merely measuring quantity when its purveyors seem to think that it measures quality. Maybe that's because quantity is so much easier to measure. But like a drunk searching for his keys under a streetlight because 'the light's better there', it's probably counterproductive.
'The Economy' is a giant Ponzi scheme whose most pitiable suckers are the youngest among us and the yet-unborn.