What if every critique you could make about the modern workforce was briefly disproven? I happened upon one shining example in a recent article in the New York Times.
It’s opposite land in Moraine, Ohio. A Chinese glassmaker named Fuyao put a half-billion dollars into an abandoned General Motors plant and created over 1,500 jobs producing windshields for the North American auto sector. The investment narrowed the physical distance between the investor and clients, which presumably lightened the load on the environment. The plant has been unionized by the United Auto Workers who would normally think of this as their turf. Health and safety conditions fall squarely under US law. There are more visible minorities in executive positions.
Some people have a problem with all of this. White male executives lost jobs to make space for Chinese managers who were brought in, triggering at least one lawsuit. The drive to unionize was successful but really difficult. There is a debate about how hard the employees should work. The investor is operating just one inch inside the law on health and safety, spurred into action by a hefty fine. (Who knew that kind of thing worked?) On Weibo, a popular microblogging site in China, someone called out the owner as a traitor for out-sourcing jobs to the US.
I can barely think of what to say. It’s just one of those things you hope would happen, until you realize you are suddenly deprived of any legitimate reason to complain or criticize. Maybe we should decide we don’t have to chase reassuring opinions, and get comfortable with contradiction?
How do you really know if someone is trying to fool you? Sometimes it’s easy. You know the kid took the cookie. You know the employee wasn’t sick. You know corporate is just cutting costs. But big data makes it harder to know what to believe. The raw data takes hours to read and is in a specialization that is not your area. Everyone who works with the data is beholden to an interest. And what if that cool thing the data scientists have figured out his how to scam you as a target? Thankfully, there is help.
A recent article from the New Yorker advises on How to Call B.S. on Big Data. It’s a great summary of a course at the University of Washington which became available in January 2017. In the spirit of public education, you can access a large amount of the materials in the course’s web site with videos, tools, and case studies.
There are some simple protective measures that are known to those in the number-crunching fields. Watch out for unfair comparisons; remember that correlation doesn’t imply causation; and beware of the hubris of those making bold claims. On average you need to keep information in context and ask for a plausible theory about why a fact would be true. The plausible theory is your hypothesis, and the scientific method is to test the hypothesis. No plausible theory; no science.
Amongst the precautions is that data taken from the general public will often re-create prejudice. I see this all the time when looking at inequalities in women’s promotions and salaries. Superficially it does appear that many women are self-selecting into less onerous careers. Deeper into the analysis, you tend to find that women do more than their share of the caring (in all of its forms) and that it’s a pervasive imposition, a subtle stereotype, and just about everyone is causing this to happen.
I’m glad to know that there is a growing desire among non-quants to consume information in a more sophisticated manner. For my own work, this doesn’t worry me. I’m honest and my motives are transparent [about stuart] If anything, I’m intimidated by the volume of work ahead of me. I used to have a clear sense of the amount of work required to seek the truth in the data and share what I found with a sincere audience. Since the rise of fake news and the increasing complexities of social media, a Pandora’s Box has been opened people like me are obliged to investigate ten times as many topics. We may be asked to fact-check nonsensical statements, defend controversial findings that were created in a neutral setting, or spend excess hours establishing credibility.
The most unsettling concept raised in the article is the BS Asymmetry Principle coined by Alberto Brandolini: the amount of energy needed to refute BS is an order of magnitude bigger than that needed to produce it. And so begins the new hybrid skill set of doing good math, and then talking about it properly.
The world is complicated. Do corporate leaders think this is a good thing? No, they do not. There is an emerging effort to put a greater priority on keeping things simple, while human resources leaders get their people to adapt to changes in the nature of work.
In June of 2014, Josh Bersin developed a fresh opinion that simplicity is the next big thing. (You’ll need to click past the Forbes pop-up screen, but then you’re in) Large global corporations were at the time expanding their business, organizing mergers and restructuring efforts, and putting talent management ahead of cost reduction. There was also a pre-existing struggle to redesign performance management, reduce workload for overwhelmed employees, and create a stronger and more integrated workplace culture.
Bersin notes “We have inadvertently become far too enamored with our technology, mobile phones, social networks, photos, video sharing tools, and all the various competency models, frameworks, process diagrams, and workflows we design in HR.” Indeed.
By contrast, some organizations have put a lot of effort into simplifying their approach. This could include reducing the number of competencies they encourage from seven to four, or reducing the performance management process to three simple steps, or creating apps that attach to their HRIS where the apps accomplish just one thing. Solutions become smaller items that almost belong on Etsy.
For those of you who have written a one-sentence email to an executive it is obvious that keeping it simple is more work, not less. Designing simple things for a lay audience also requires a special perspective and a devotion to good design. Yet concentrating effort and attention to just one thing has obvious payoffs in focus and effectiveness. I don’t have data. In this case, you can go on instinct.
Human resources departments and those who handle their data are expected to guard the best secrets. But one of the biggest secrets is ironically an anti-secret. Did you know you’re allowed to talk openly about your own pay? Don’t tell HR. It’s embarrassing (for them).
This article in Atlantic.com by Jonathan Timm from July 2014 draws attention to the dubious practice of pay secrecy. I’m not talking about the employer’s obligation to keep your pay information confidential. Rather it’s an article about employees being obliged to keep their pay a secret from one another. These obligations are referred to as “gag rules.”
For the uninitiated, there is no meaningful moral obligation for employees to refrain to talking about their salary with each other. On the contrary, in the United States there are regulations that protect employees’ rights to discuss working conditions with one another. It’s on the edges of the legislation that allows employees to collectively discuss their lot in life, bargain for improvements, and possibly unionize.
In that context the moral judgement should be obvious. Those handling the file at human resources desks are not allowed to advance anti-union behavior, and as professionals they should always advise against such policies.
The article describes personal experiences of people struggling with these fake rules. What is notable is how people presume these gag rules are legitimate, employers and employees alike. Gag rules create a sense of guilt about whether we should put ourselves ahead of the employer. They make us self-consciousness about whether we’re being greedy. We’re embarrassed to talk about whether we’re losers for being the lowest paid person. Raising the topic with colleagues is “akin to asking about their sex life.”
These emotions are powerful stuff. But then, that’s how bullying is done, isn’t it?
Above and beyond beef-and-taters union issues, gag rules are also wrapped up in discriminatory pay practices. That is, it is easier to under-pay women and visible minorities or play favorites if employees don’t talk about their pay. A woman named Lilly Ledbetter complied with the gag rule at Goodyear for nearly three decades and ultimately found out she was under-paid. Ms. Ledbetter sued and lost because she did not complain about being under-paid within the first 180 days of her first paycheck.
Ironically, employers share pay information with each other all the time. They’re called compensation surveys. They happen on an annual basis (if not monthly), and they are delivered through specialized consulting services. The work is done under careful checks and balances that ensure data privacy and keep the whole process fair and legal. Those who have worked on such surveys are proud of their work. I used to do compensation surveys myself, and I was good at it.
One of the reasons why compensation professionals love doing this work is because it helps make pay fair and equitable. Looking down from the ivory tower, human resources people know that perceived unfairness in pay creates discord. So “good” employers put some work into getting it right, behind the scenes, in a kind of lab environment where social justice is organized by experts. But really we’re just trying to stay one step ahead of the riff-raff.
Let’s face it, employees and the social justice movements they created are the rightful owner of this dialogue. Gag rules and compensation surveys are just the cultural appropriation of working class politics.
Too much knowledge can turn you into an idiot. The curse of knowledge is that problem where experts in a field are unable to explain their great knowledge to a lay audience, because they can’t bring it down to earth. The speaker might have good information about the base knowledge of their audience, but they just don’t “get” that their audience hasn’t taken the introductory course in their subject area. It’s odd that someone can be highly esteemed for their knowledge, yet get short-tempered with the very people who hold them in high regard. I think this is why it’s so hard for experts in two different fields to communicate with one another. There is a special skill set in talking to intelligent people who don’t understand what it is that you do.
The real reasons millennials are described as different is that people are jealous of their courage and freedom. I can prove it.
There is an interesting report available online at the University of British Columbia (UBC). In their 2014-15 Benchmark Report to the Board of Governors, UBC Human Resources developed insights about staff turnover that were new at the time. In particular, they identified that staff turnover was mostly about career advancement.
One of the things this report straightens-out is turnover amongst new people and young people. The challenge is that there is a large overlap. A lot of the new employee are young, and vice versa. To untangle these two populations the report shows a simple 2×2 diagram with subtotals and labels on the outside edge of the grid. The results on pages 8-9 of the report look like this:
1-3 Years in Job
4+ Years in Job
Total (All Lengths of Service)
Age 34 & Under
Age 35 & Over
Total (All Ages)
It takes a minute to get used to it, so look at it carefully. Look at the (vertical) columns for years of service, and compare the percentages side-by-side between the 1-3 Years and 4+ Years length of service categories. For younger staff (the top row) there’s only a 2% spread by years of service, and for older staff (one row down) the spread is 3%. The total at the bottom shows that new staff quit at a rate that is 5.6% higher for all ages combined. But that difference is skewed by a large number of younger-and-newer people in the upper-left corner. When we look at it carefully, there is a very small difference in turnover according to length of service.
Then look horizontally at the rows. Those age 34 and under have a quit rate of 13.5% in total, and in this case the number is relatively similar by years of service (13.8% for new people and 11.8% for those with longer service). One row down, you see that those age 35 and over have a quit rate of 4.4% in total, and once again it’s relatively similar by age category.
This means the important information is the totals by age category. Those aged 35 and over have a turnover rate of 4.4%, while those who are younger have a turnover rate of 13.5%, nine percentage points higher. Simply put, younger people have a high quit rate. This phenomenon is not unique to UBC, as the external benchmark provider had similar findings.
Why are young people quitting? The report looks to three additional data sources and finds that young people largely resign from their jobs for reasons of career advancement.
However, it’s not entirely accurate to say that young people resign because of career advancement. The problem is that everyone is concerned about career advancement, and it is a major workplace frustration. What makes those under 35 different is that they are getting frustrated about career advancement and then quitting. Think about the different home lives of those over the age of 35. There are things that keep older people in place. There is home ownership, mortgage payments, the obligation to support kids, spouses who have a job in the same city, and the commitment to their current profession.
It turns out that millennials did not have career expectations that were different from that of others. They were just more likely to express their opinions in a display of freedom. Millennials are the gregarious friend at the pub who says out loud what everyone else is thinking. You can’t really scold them when you’re jealous they have the guts to tell it like it is.