Costco Toilet Paper is Soft on the Math

Bathroom. By Dean Hochman.
Bathroom. Photo courtesy of Dean Hochman.

Denominators make everything feel better, including toilet paper.  A really good denominator can help you figure out that you should not buy the bulk package of toilet paper from Costco.  That’s because the real estate you are storing it on is way too expensive.

To understand this, consider your cost of housing.  If you haven’t done so already, you should probably figure out how much you’re paying every month for each square foot of living space in your home.  For example, if your living expenses are $3,000 per month on 1,500 square feet, you’re spending $2 per month for each square foot.

The bulk package of toilet paper occupies four square feet of floor area, which represents $8 per month of storage costs.  The package costs $20 for 30 rolls that will last a family of four about two months.  That’s $10 per month for toilet paper, which seems like a bargain compared to about $15 per month you would pay for the package at a regular grocery store.  But your $5 of savings is sitting on top of $8 worth of real estate.  The unit-cost savings is less than the cost of real estate that it’s occupying.  The Costco toilet paper is just too expensive to forgive real estate cost that it’s imposing on you.

So, how does this relate to workforce analytics?

Appropriate Denominators in Workforce Analytics

Throughout the analysis of the value of your workforce, it is common to talk in numerators.  Number of people.  Salaries.  Benefits costs.  But what is usually more meaningful is to match up the numerators with appropriate denominators.  Number of people this year divided by number of people ten years ago (it’s usually not what you think).  Salaries per month during unfilled vacancies (actually a lot of money).  Executive compensation divided by organizational revenues (a drop in the bucket).  Numerators become more meaningful when you divide them by the right denominator.  And you must experiment and choose wisely.

With truly strategic business analytics, the biggest opportunity for novel insights is the blending of numbers from different strategic pillars.  You could have a finance metric divided by a human resources metric, such as capital invested per employee.  You could take a sales and marketing metric and divide it by people, such as revenues per salesperson.  Ratios from within a VP portfolio are often really easy to pull together because you can usually get them from a single database.  Once you have those easier in-house numbers figured out, it’s vital to get into the difficult metrics.

With the toilet paper example, it is the price of consumer goods are familiar to us as shoppers.  Then unit price is the next level of complexity, looking at price-per-roll.  You need to then seek information that is outside of the shop where the question was first posed, and in this example it’s housing cost.

The Story Changes When Better Denominators Are Chosen

One of my favorite experiences was a health & safety statistic about back injuries from over-exertion.  We knew that a large number of men over age 55 were pulling their backs from over-exertion.  But we discovered that there was a larger denominator of men over age 55, and that their percentage frequency of injury was lower than expected.  By contrast, those entering middle-age at age 45-54 had the highest frequency of these types of injuries.

When I was helping the client figure this out, I had personally pulled my own back at the gym at the age of 46.  I was in defiance about the fact that I was getting older, and trying to prove myself by lifting something that I should not.  I proposed to the client that those age 55+ are too wise for such foolishness, and those under age 45 can handle the challenge because they’re younger, fitter, happier.  I proposed a new interpretation; over-exertions are not about stand-alone physical vulnerability, they are about the disconnect between actual ability and self image, particularly in the social context.  The client liked it.

In order to rock it, each database had to be high quality, allow apples-to-apples comparisons, and have enough fields to break out the data by ten-year age cohorts.  These are critical intermediate steps, and not every organization is there yet.  What is important to notice is that as you improve your numbers, opportunities abound.  You can get stronger each time.  Nothing is so trivial that you can’t make it better with analytics.  And yes, you can afford the good stuff.  If you earn it.

Don’t Hate Mayhem. Love Complexity Instead.

You Better Hold On. By Jane Rahman
You Better Hold On. Photo courtesy of Jane Rahman.

The strongest defense against a bewildering world is a love of complexity and ambiguity.

Elif Shafak, Turkey’s most popular female novelist, has provided a brilliant critique of our modern times.  In her TED Talk from September 2017, she expresses concerns about economic uncertainty, the impact this uncertainty has on our emotional bewilderment, and knock-on effect this has on the appeal of demagogues.

“Ours is the age of anxiety, anger, distrust, resentment, and I think lots of fear.  But here’s the thing:  Even though there’s plenty of research about economic factors, there’s relatively few studies about emotional factors.  …I think it’s a pity that mainstream political theory pays very little attention to emotions.  Oftentimes, analysts and experts are so busy with data and metrics that they seem to forget those things in life that are difficult to measure, and perhaps impossible to cluster under statistical models.”

Speaking as a workforce analyst, these are my sentiments exactly.  People like me often try to figure out what is happening inside the workplace while thinking of employees as livestock or machines.  But then the people talk, and their souls come through.  Their context and their lives prevail over objective definitions of effectiveness.  Workplace culture overpowers the declarations of those with authority.

Emotional Complexity Amidst Demographic Over-Simplification

Nowhere do I see this more than when I split a dataset into demographic categories.  The categories are usually either-or scenarios, such as age bracket, binary sex, or length of service.  And just as we find the definitive behaviors and opinions of a certain category of people, with a little more digging we find that there is a deeper human story that defies categories.  I see men taking parental leaves, older workers expressing career ambitions, and high-school dropouts with unmet educational needs.  Putting people into categories only helps find a demographic that best gives voice to the human story.  But that human story will usually speak for everyone.

Shafak, who understands human stories, notes that demagogues “…strongly, strongly dislike plurality.  They cannot deal with multiplicity.  Adorno used to say, ‘Intolerance of ambiguity is the sign of an authoritarian personality.’  …that same intolerance of ambiguity, what if it’s the mark of our times, of the age we are living in?  Because everywhere I look, I see nuances slipping withering away.  …So slowly and systematically we are being denied the right to be complex.”

To Shafak, it is the bewilderment imposed upon us by change that makes us susceptible to the simple ideas offered by demagogues.  “…In the face of high-speed change many people wish to slow down, and when there is too much unfamiliarity people long for the familiar, and when things get too confusing, many people crave simplicity.  This is a very dangerous crossroads, because it is exactly where the demagogue enters into the picture.”

Emotional Intelligence, Embracing Complexity, and Building Resilience to Organizational Change

Shafak suggests that “…we need to pay more attention to emotional and cognitive gaps worldwide.”  Those who struggle with complexity and ambiguity need our help.  We’re not at liberty to define non-complex people as the “other,” as people whose opinions we can reject in yet another polarizing simplification.

I felt this concern when I followed the James Damore incident at Google.  A programmer on the autism spectrum was fired for writing an anti-diversity manifesto, and his memo showed that he struggled with sensitivity training in a culture of diversity.  He attempted to attribute the onus of emotional intelligence to a liberal bias and the imposition of allegedly feminine social concerns.  The true lesson was not so much that bigotry sucks; it is that simplified emotions make us prey to extreme opinions.  I think we need to devote more time and energy to empathizing with the perplexed.

Shafak is insistent that we must cherish complexity.  We must value ambiguity.  We must allow ourselves to carry multiple identities and become the cosmopolitan people who can adapt to the world.  For me, I felt reassured that a deep curiosity for new information and enthusiasm for diverse views is the ultimate resistance against bad ideas.

With complexity we can have a meaningful society, meaningful work, and a resilient sense of self that allows us to move forward.  Only then can we get back to work and do our jobs well.

Big World, Small Wages

the shrinking dollar, by frankieleon
The shrinking dollar.  Photo courtesy of frankieleon.

We are now in an era when unemployment is low, but wages are not increasing.  This is unusual.  Normally when unemployment is low, wages increase.  Even the meanest of bosses would look over their shoulder and increase wages to “stay competitive with market,” when they’re actually just worried about losing key people and unions making inroads.  But the rules of business have changed.

According to the New York Times article Plenty of Work; Not Enough Pay the reasons why wages are staying low are incredibly varied.  Long story short: It’s a dog-eat-dog world and we’re in a big, hot mess.

  • Unions have less power than in the past. Last year only 11% of the American workforce was unionized, down from 20% in 1983.  This decline coincides with American wages largely breaking-even since 1972 on an inflation-adjusted basis.
  • The article interviews Lawrence Mishel from the Economic Policy Institute, who notes that “people have very little leverage to get a good deal from their bosses…” and this reduces expectations to the point where “People who have a decent job are happy to just hold down what they have.”
  • It’s not just workers and unions, businesses are anxious, too. In Japan, companies “mostly sat on their increased profits rather than share with employees.”  Businesses are still spooked from the popping of the real estate bubble in the early 1990s, which was a prequel to the larger subprime mortgage fiasco in the USA around 2008.  In Norway, wages increased as a result of their oil riches in the run-up to 2008.  Their higher cost structure put them at a competitive disadvantage during that same recession and business in Norway don’t want to make the same mistake.
  • Employers who are experiencing good business results are trying to get more work done by hiring temporary employees. After all, if a business can get a large fraction of their work done by contractors, it’s easier to shed the contractors during a downturn.  While temporary work is a negative experience for those forced into it, it is also something business leaders need to do out of fear that they themselves could be in trouble at any time.
  • In Norway and Germany, unions have negotiated special deals to keep wages low, ensure businesses stay cost-competitive, and save local jobs. This arrangement puts pressure on lower-cost jurisdictions, such as Italy and Spain.
  • Globalization is connecting developing-world factories more closely to the individual consumer. After “eliminating the middle-man,” there are fewer bottlenecks in getting goods to market.  With fewer middle players, there is not the same opportunity for employment in these roles.  Factories have fewer hurdles to dropping goods right at your doorstep.  Online leaders, such as Amazon, continue to ravage physical retail.  Meanwhile, warehouse operations and trucking goods across continents are increasingly prone to automation by robots and artificial intelligence.
  • In addition to buyers purchasing goods from developing countries, immigrants are often brought in from those same countries, keeping wages down. It is virtuous to be sympathetic to the plight of immigrants, but there is also truth to the complaint that businesses are using immigrants as pawns. In Norway, the social democratic system that shares wealth with the unionized workforce is being undermined by start-up businesses employing immigrants from Eastern Europe at wages that are below the agreed standard.  The unions are struggling to ensure these immigrants get the same rights as others.  Labour’s biggest struggle is to break even.

The supply-and-demand mantra that the market will correct itself has simply become a falsehood.  This raises the possibility that for our gains, we can’t let the market take care of us.  The possible solutions are varied and the solutions you lean towards probably match the opinions of those around you.

Perhaps families and churches will help us, or maybe it will be unions and the government.  But the emerging consensus is that market forces are nobody’s friend.

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 CIO.com, 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!

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.