Workplace Incivility Drags Workplaces Back to Stone Age

Neanderthal Museum. Photo courtesy of Clemens Vasters.

How important is good manners?  Really, really important.  And it extends much further than knowing what an oyster fork looks like.

Incivility weakens health in areas such as cardiovascular disease, cancer, diabetes, ulcers, and of course mental health.  For reasons of reducing health care claims alone, mistreatment of staff should be curtailed.  However, preventing workplace incivility is actually a bigger deal than originally thought.

In fact, there is significant research that shows being outright rude to colleagues is a major killer of workplace productivity.

In my jurisdiction, there was legislation brought in a few years ago that obliged employers to curtail bullying and harassment.  The legislation goes beyond the long-standing human rights legislation preventing harassment on prohibited grounds, such as sexism or racism.  The new rules say that if we are to compel others to action we must not be aggressive, humiliating, or intimidating.

Uncivil Workplace Culture Adversely Affects Productivity

According to her research, Christine Porath found that for those treated rudely by their colleagues:

  • 47% intentionally decrease the time spent at work
  • 38% deliberately decrease the quality of their work
  • 66% report that their performance declined
  • 78% said their commitment to the organization declined
  • 80% lost time worrying about the uncivil incident
  • 63% lost work time in their effort to avoid the offender

In addition to the reduced productivity of those who stick around, there is also the consideration of those who quit.  Twelve percent of those treated poorly leave the job because of the incident and, by contrast, those who are treated well by their manager are more likely to stick around.  What is interesting from an analytics perspective is that those treated poorly don’t tell their employers why, making it a blind spot in the data.  We know this from other sources; it’s always okay to say that you’re leaving for a better opportunity elsewhere.  But employees usually quit because of their manager and refuse to talk about it in exit interviews.

In addition to those directly treated in an uncivil manner, those who observe someone else being treated in such a manner are also affected.  “You may get pulled off track thinking about the incident, how you should respond, or whether you’re in the line of fire.”  Those who witness incivility see their performance halved and they “weren’t nearly as creative on brainstorming tasks.”  It makes sense that behavior is social and contagious, and that we feel for those around us.  That includes emotional pain.

The impact is not just contagious between employees, but it also spreads to customers.  In research conducted with two colleagues form the University of Southern California, Porath found that “…many customers are less likely to buy from a company they perceive is uncivil, whether the rudeness is directed at them or other employees.”  When customers witness an uncivil episode between employees, that customer makes generalizations about the company.  This has happened with Uber; customers who perceive a toxic environment have turned to competitors.

It’s more evidence of an emerging business model I refer to as double engagement.  That is, that it is engaged employees who attract and retain engaged customers, causing the revenue flow that marketing and finance want so desperately.  The days of investors and marketing teams driving a product or service into the hands of witless customers is long gone.  We live in a world where being human dictates business strength.

But before we put this all in the hands of the worker, we should note that the main source of an organization’s emotional tone comes from its leadership.  Simply put, when leaders treat their team fairly and well, they are more productive.  The team goes above and beyond.  They have more focus, better engagement, more health and well-being, more trust and safety, and greater job satisfaction.

For leaders, the new bottom line must also now include compassion, emotional sensitivity, and engagement.  You must step away from individual heroics and reverse your sense of who is important.  Why? Because way down at the bottom of the pecking order there may be someone who is not treated so well.  Whether you’re a caveman or a gentleman, if you are stronger and more powerful it is your job to carry them.

Where’s Waldo in the Job Applicant Pool?

Where's Waldo. By David Trawin
Where’s Waldo. Photo courtesy of David Trawin.

How do you find that one special thing in the middle of all this big data?  It depends on what you’re looking for.  Machines can help you find things, but first you have to teach the machine to understand what you want.  With recruiting data, a few simple formulas evolve into something far more complex.

This article from, by Sharon Florentine summarizes how Artificial Intelligence is revolutionizing recruiting and hiring.  Long story short, if you have really good data about who your high-performers are and what the process was like to recruit them, you can reverse-engineer the recruiting to predict which applicants will perform well after hire.

I hate to imply that it’s so-last-month, but the basic concept is straightforward.  Collect large amounts of data, fine-tune its quality, run a statistical analysis to determine causation, and make a forecast.  That’s what it looks like in a lab environment.  But the good stuff is in the war stories of how this kind of experimental analysis plays out.  The article names a few hot-points worthy of more discussion.

Where’s Waldo: Finding the Best-Fit Candidate in the Middle of Big Data

Citing Glen Cathey of Randstad, the new job search is similar to the “Where’s Waldo?” book series.  “…it’s not difficult to search anymore, what’s of greater importance now is a data problem.”  That is, you have good applicants, but you have to identify that one great fit.  Cathey describes three types of search that make this viable.

  • Semantic Search, which seeks to understand a searcher’s intent and the context in which the search is being made. (Remember, good fit is circumstantial and conceptual)
  • Conceptual Search, which creates a basic concept from just a few key words.
  • Implicit Search, which pushes information to you making assumptions about what you’re trying to accomplish “…much like how Google automatically pushes restaurant recommendations in your local area…” I have to admit, I’m always impressed when Google knows that I only want local

Dark Matter: The Missing Job Applicant You Don’t Know You’re Missing

In spite of his faults, former Defense Secretary Donald Rumsfeld did pioneer an important concept called “unknown unknowns.”  That is, there are unknowns that you are somewhat aware are a risk factor, but there are deeper unknowns where you just have no idea information was lacking in the first place.

As it relates to recruiting, Cathey notes that “…you’re excluding people with those [machine-driven] searches.  Doing it this way means you’re actually looking only for the best of the easiest candidates to find.”  So, they use Artificial Intelligence and machine learning to find overlooked candidates.  A strong candidate might have done a mediocre job customizing their resume to your posting, but still have exceptional virtue.  They might use the wrong key words.   They might have special skills that your organization needs but it’s not on the job posting.  And your recruiting expectations might be biased towards a certain type of white male, or white males generally.  The modified formulas can open-up the under-used areas of the candidate pool.

So, while it’s great if the machine gets you to a great candidate quickly, you can also get the machine to do the tedious exercise of finding the diamonds-in-the-rough.

While it’s true that some of this work can be done with basic statistical tools and a good data set, that’s actually an ambitious starting-point to get to in the first case.  The advanced class is that you must create new data from scratch, revise the model on an iterative basis, and eventually run the model off live data such that the predictions change as the ground underneath the data shifts.

But that’s only if your attempt to do this kind of thing matches the business context.  The big challenge is when the work is incompatible with organizational strategy, or the initiative needs a compelling business case to shift resources, or you need to win-over new people who are in the middle of a leadership change.  At that point you will get sucked back into the complex world of humanity and empathy.  So much for robots making our lives easier!

Data Will Drive Your Car. Oil, Not So Much

Oil Rig. By Soliven Melindo.
Oil Rig. Photo courtesy of Soliven Melindo.

Are cars no longer fueled by gasoline because they are now fueled by data?  Consider how driverless cars, electronic vehicles, and Uber are changing the outlook for the future.  And reflect on how the in-vehicle computer has increasingly changed you safety, your comfort, and your ability to manage the vehicle’s maintenance.  Gasoline is so last century; today it’s all about the data.

A Financial Review article from July 2017 by Mark Eggleton plays with the idea of data as the fuel of the future.  For a century oil ruled our world, influencing geopolitics, urban design, and decisions about where to work and travel.  Today, it is data that is significantly changing our world.  However, we cannot just obey data on blind faith.  We need to look up from the GPS, so to speak, and decide for ourselves if the data we are being fed is relevant and appropriate.

We need to consider data in the context of trust.  Take banks for an example.  Although banks could do lots of things with our personal financial information, they operate within the context of trust that has built over centuries.  Regardless of whether we trust their profit motives in society overall, we do indeed trust that the information they hold will be handled in a responsible and diligent manner.  Banking is deeply immersed in a human context, regardless of whether it always seems that way.

I personally think that in workforce analytics, there is a similar concern about trust.  We have at our fingertips sensitive information that could be used for good or evil.  So let’s ask, are human resources departments actually good? Perhaps we need some time establishing ourselves, to give a better sense that when we’re wrapped up in industrial conflict and individual terminations, that we’re sincerely doing what is expected of us.  If we collect accident statistics and attendance lists for mental health workshops, do employees bank on us only using this information to make people well?  Have we truly established that the employment equity data we collect will be used exclusively for its intended purpose?  When we survey employees on their engagement experience, is the information used to create a better workplace, or are there attempts to punish those who express low motivation?  While we closely guard peoples’ confidential pay data, do we have the correct attitude towards employees discussing their pay amongst themselves?

I think it’s high time we subordinate data to the human context.  After all, if big data peaks, we are probably into the human economy.   If data is going to change the world, we need to ensure it dovetails with our history, the geography, the people and their culture.  If we get this wrong, it will be a dystopian science fiction movie come true.  That’s kind of what happened with oil.  So let’s get it right this time.

(Hat tip to KPMG’s Hugo van Hoogstraten for sharing the original article with me)

Boxes Without Humans: What Will Fill the Gap?

Amazon cat. Photo courtesy of Stephen Woods.

It’s been couple of days since the latest social disruption.  I wonder what’s going to be turned upside-down this week?  Flat on the heels of online shopping ravaging the conventional retail sector, warehouse and trucking jobs might be the next to go. holds contests every year entitled the Amazon Robotics Challenge, where academics and graduate students compete for prize money to help automate warehouse jobs with robots.  The technology gets a little more clever each year.  “They now use neural networks, a form of artificial intelligence that helps robots learn to recognize objects with less human programming.”  The good news is that there might be lots of work for technologists.

The bad news is that this could take a bite of decent-paying warehouse jobs.  In the US, there are about 950,000 warehouse and storage-industry jobs with an average wage of about $20 per hour.  Those jobs are threatened.

But a more pressing concern would be trucking.  Self-driving cars are already starting to make an appearance on the roads.  For trucking, the change will happen more quickly according to a Guardian article.  The decision to go driverless with trucking is a corporate decision, not a consumer decision like with driverless personal automobiles.  The financial motivation is extremely favorable to use self-driving trucks. “The potential saving to the freight transportation industry is estimated to be $168bn annually… [including savings from] labor ($70bn), fuel efficiency ($35bn), productivity ($27bn) and accidents ($36bn)…”  The trucker’s wage is similar to that of warehouse workers, but there are far more jobs at stake.  There are 3.5 million truckers in the United States, and the drivers themselves spend a lot of money at road stops, hotels, and diners.

Now, if you work in finance or information technology this might not concern you so much.  Technologies are created, investments made, money saved, and we’re better off on average.  But in human resources we know that the unemployed are our people.  We terminate them, we screen them when they apply for jobs, we help them with problems if we know them personally, and occasionally the we ourselves are the unemployed.  We think about them a lot.  We don’t always show it, but frankly we have to care or we die inside.

Thankfully, people have started to talk more openly about the broad-based social disruption that Artificial Intelligence may have.  In the Guardian article on trucking, there are calls for a Universal Basic Income, direct payments to everyone regardless of how well they have fared in a disrupted labour market.  There may be other policy concerns as well, such as improved access to training and education.  Of course, these are government-funded solutions which seem obvious to me.

There is still a persisting risk that the disruption will be misattributed to an outside factor.  If the technology-based job losses are blamed on immigrants, environmental regulations, or the abandonment of tradition, I can’t foresee broad democratic support for government solutions or the embracing of change.  And this spells trouble for the very business interests whose success relies on the rule of law, stable diplomacy, and a diverse workforce who are engaged to stay productive.

Loving Math, Caring About Peers

Nerd. by David Nichols
Nerd. Photo courtesy of David Nichols

Some time has passed, so let’s calmly reflect on the anti-diversity manifesto that got a software engineer fired from Google in August of 2017.  James Damore, the author, has to be the unluckiest person on earth.  Not only did he lack the genetics and environmental upbringing to be compassionate about the emotions of others (he might be on the autism spectrum), but he also wrongly attributed his career difficulties to the ascent of workplace diversity initiatives.

He delivered his critique via the alt-right media one week prior to the deadly neo-Nazi rally in Charlottesville.  That incident provoked corporate executives, top-ranking generals, and mainstream Republicans to denounce the rally and distance themselves from Donald Trump’s muddled sympathies in the aftermath.  Damore and his fans have left no opening for a nuanced discussion about the effects of diversity initiatives on those with developmental disorders, a potentially meaningful topic of debate.

In this article in the New York Times, author Claire Cain Miller proffers a critique of the role of emotional intelligence in the modern world of information technology.  It turns out that technology has a massive overlap with social and emotional context.

Emotional Intelligence in Workforce Analytics and Computer Programming

For deep evidence, the article cites 2015 research from David Demming that finds job growth and wage growth are highest among roles that use both math skill and social skills.  The idea is that workers “trade tasks” with one another, to allow specialization of talents and improved efficiency when work duties are shuttled back and forth.  Those who trade tasks more effectively through the use of social skills are more productive; hence more jobs and higher pay.

This double-barreled skill set is abundantly obvious to those in workforce analytics.  We spend half our day figuring out cool formulas and novel discoveries.  But the other half of our day is spent interpreting client need, negotiating resource priorities, wordsmithing data definitions, developing interpretations that are suitable to context, and showing compassion while we advance disruption.  However, my field is new.

When computer programming was new it was originally considered highly social work.  There was an abundance of women working in the field.  Through some office-culture twists and turns, things changed.  Boys and men who weren’t as clever at the social skills self-selected into programming.  It worked out for a lot of people.  But there’s a problem; at some point in someone’s career their next chance for a promotion is contingent on social skills.  Those who are lacking in this area see their careers stalled.

Examples abound of coding projects with male-dominated teams who lacked context, who missed an important detail about women’s perspectives.  Apple’s original health app tracked everything except menstrual cycles, the most-tracked health data point amongst women.  Google Plus obliged users to specify their gender and provide a photo, exposing women to harassment.

The Times article also cites research from 2010 by Stanford sociologist Shelley Correll showing that gender stereotypes about skills and performance are a kind of self-fulfilling prophecy.  It’s not true that women are naturally bad at math, but it is abundantly true that women who are told they are bad at math will under-perform and rate themselves more harshly.  The struggle about this stereotype has played out in dramatic ways over the years.

How to Improve Workplace Culture to Ensure Equality for Women

In terms of what to do about this, Correll advises that we:  1) ensure there are no negative gendered beliefs operating in the organization, 2) ensure performance standards are unambiguous and communicated clearly so that sexism does not fill the vacuum, and 3) hold senior management accountable for gender disparities in hiring, retention, and promotion.  That third item is metrics-based accountability, which means that business performance, diversity, and workforce analytics are fundamentally entwined.

The times article notes that “one way to develop empathy at companies is by hiring diverse teams, because people bring different perspectives and life experiences.”  While we might perceive that equity and inclusion efforts come from an activist base, there is a corporate interest in fostering inclusion.  High-performance workplaces need an environment where tasks and diverse views are shuttled back and forth, with ease and good manners.

As for white white males who desperately struggle with emotional intelligence, their voice will have to wait another day.  And probably wait for another leader.

How to Become Strong By Understanding Disadvantage

2012 Marine Corps Trials Day 2.  Photo courtesy of DVIDSHUB.

We hear lots about excellence these days.  So what are the opportunities for persons with disabilities and disadvantages to drive excellence?  It may be that those who are in the throes of disadvantage might not have a fair shot at success.  But there are opportunities for everyone to aspire to excellence, through the cultivation of empathy for those who are disadvantaged.

This is a touching article about a doctor who was concerned about his own mother during her  disabling illness.  The illness was Parkinson’s disease, a degenerative disorder that affects movement.  In the Times article, Dr. Sandeep Jauhar is rigged with a device that allows him to personally experience the sensation of his muscles turning to jelly, like those who have Parkinson’s, like his mother.

Why would he do such a thing?  Because he always wanted to understand his mother’s perspective during the illness.  Devices are also available that replicate the effects of emphysema, psychiatric illness, and nerve disease related to diabetes.

While I haven’t experienced it yet, I have also heard rave reviews about a similar effort called Dark Table.  Dark Table is a restaurant in Vancouver where food is served and eaten in a room which is completely dark.  The servers are blind or visually impaired, and the guests commit to keeping their gadgets off and eating their meals in the dark.  The dark dining experience increases the awareness of other senses such as hearing, touch, and taste.  It creates jobs for persons with disabilities.  And it also helps people empathize with the perspective of the visually impaired.

Emotional Intelligence in Workplace Conflict

On the human resources side of the fence, it’s possible to develop greater empathy for those we are in conflict with.  The nurturing of empathy is important for industrial relations, the professional development of managers, performance conversations, and the general growth of all staff.  How do you teach workplace empathy?  I have been involved in complex roleplay scenarios called Conflict Theatre.  The theatre scenes are designed so that each scenario is integrated into well-developed back stories and emotional perspectives of the actors.

The theatre is presented so as to invite audience members to step into the shoes of an individual actor and attempt to change the course of the conflict.  It’s one thing to sit back and observe from and armchair, and develop an opinion about how things should be done.  But the real expertise is to understand the full emotional context of each player in a conflict, an understanding which is far more vivid when experienced directly.

Empathizing with diverse perspectives turns out to be a key attribute of those who face conflict with dignity and grace.  It takes you beyond the negotiations that resembles bartering for trinkets, and even beyond the interest-based bargaining of those vying for a win-win solution.  You have to learn how to understand people as individuals based on their perspective and story, not their category or “type.”  This includes understanding their perspective when they struggle with ability, whether it’s professional ability or impairments.

Using Emotional Intelligence to Improve Workplace Culture

The thing I find fascinating about these initiatives is their scientific and cultural back-story.  The Parkinson’s device was built in response to well-documented complaints that patients perceive their nurses and doctors lack empathy for their hardships.  Blind dining is traced back to Switzerland by a man named Jorge Spielmann, whose concept was imitated in restaurants in London, Paris, and New York.  Conflict Theatre in Vancouver comes out David Diamond’s Theatre for Living, which itself comes out of Theatre for the Oppressed, created by Augusto Boal in Brazil in the 1970’s.  Theatre for the Oppressed, as you might guess from the name, arises from social critiques and movements to overcome repression, with an intellectual legacy dating well back into the 50’s.

To affect society on the larger scale we need to reach into the emerging science, the social experiments in many countries, and the lessons learned many decades into the past.  The knowledge and confidence of those with power and privilege can pale in comparison to the universe of individual experiences.  In order to take full advantage of the best information when advancing ourselves in this world, we need humility about how right we truly are, curiosity for knowledge that is new, and sensitivity to the lessons from other cultures and other moments in time.  Only then can each of us aspire to excellence.