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)
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.
Amazon.com 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.
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.
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.
Are we still living in the information age? Maybe not. Here’s an interesting article from Harvard Business Review on the Human Economy, from November 2014. Societies have evolved from agrarian economies to industrial economies to service economies to knowledge economies. At this point, there’s such a glut of food and goods and services and information, the next bottleneck is humans. Businesses that do well in this new era will be those with a greater sense of humanity. Those that have a poor sense of humanity shall be sunk!
“In the human economy, the most valuable workers will be hired hearts.” It is what makes us different from robots and artificial intelligence (i.e. emotions) that will make us special as employees. Many of the examples in the article are from the perspective of a customer whose heart was won over. Noticeably there’s always and employee whose empathy and enthusiasm closed the deal (so to speak). The article cites several studies where CEOs place a higher priority on social skills than analytics.
This is what it feels like at my desk. I spend half of my time getting the formulas right, and the rest of the time helping people become happy about the numbers. They can’t use workforce analytics unless they trust us. The analytics influence the decision making. Clients get better because we help them develop patience. They come back for more the data is addictive. We persevere through inevitable errors and mistakes, being honest about having made best efforts.
Beyond customer engagement, employee engagement is increasingly recognized as having a major impact on productivity behind closed doors. People are not monkeys at a keyboard sending customer service complaints in circles. Or rather, sometimes it seems that way but it sure looks bad in the news.
At their best, people are the embodiment of the discretionary effort that dictates if a service or product gets to market, and they make every capital investment matter (or not).
The wall of plexiglass. Photo courtesy of ebt47563.
Exactly how do you change organizational culture? This is a good HBR article from June 2017 about attempts to change corporate culture from the bottom-up. It’s a story about Dr. Reddy’s, a global pharmaceutical company based in India and led by G.V. Prasad. The authors are Bryan Walker from IDEO and Sarah A. Soule from Stanford Business School.
Dr. Reddy’s process of culture change began with significant ground research to find out what their staff, providers, and investors needed when dealing with customers. They brought their goals down to four simple words that brought it all together: good health can’t wait. Instead of selling the slogan through posters and speeches they chose to demonstrate their purpose through actions. The initiative named projects in packaging, sales, and internal data to advance the new vision. There were some immediate impacts. One scientist broke a number of company rules and produced a new product in 15 days, having prioritized new efforts to match the vision.
The comparison to social movements is important, because movements start with an emotion rather than a call to action. Movements start small, “with a group of passionate enthusiasts who deliver modest wins.” Momentum builds through networks, penetrating power structures and leadership.
There are also “safe havens,” places where activists can behave differently from the dominant culture and discuss their goals. In innovative organizations, research labs are often built as separate mico-organizations that cultivate change as prep-work for the larger organization. This story resonates with me, because disruptive workforce analytics will occasionally fall of deaf ears. The analysis needs to be created in a manner which partially ignores pre-existing agendas or presumptions of how things would normally be done. The decision of whether to apply new ideas might belong within a more formal process, but when experimenting with messy new ideas, to be sequestered is ideal.
Beyond the HBR article two additional models are appropriate to discuss the nature of change.
Innovating Technology and Trends Through Social Networks
The first model is the diffusion of innovations as described by Everett Rogers. In this model, there is a small avant-garde of weirdos who just get into stuff that is new and interesting. That crowd of innovators will not have the full opportunity to make money or make it big. But their new findings diffuse through social networks, based on peoples’ network connections and their readiness to consider new ideas.
There are several hold-outs, such as the laggard crowd who resists change until it is impossible to do so. The biggest difficulty is the early-stage challenge of “Crossing the Chasm” where the new idea has won-over a small crowd of early-adopters who are about 13.5% of the population. The challenge is that sometimes there’s something about the new idea that doesn’t mesh with the next crowd, the early majority. Some examples might be that the new technology has a difficult user interface, or the social trend is incompatible with the conventional lifestyle of those in the burbs.
In my opinion, the classic example of this challenge is the hands-free bluetooth headset that you see people wearing when they’re talking on the phone while walking down the street. The technology has been in public for more than fifteen years and our first instinct is still that we want the caller to get professional help. And that’s even when you’re not also angry at them about a misunderstanding.
Using Social Disobedience Tools to Change Workplace Culture From Within
Another compelling cultural change model is the Spectrum of Allies model from George Lakey of Training for Change. Lakey is highly experienced in training social justice activists in civil disobedience. I attended a couple of workshops with Lakey when I was part of the labour movement, and his spectrum model is eye-opening.
The key diagram is a semi-circle, kind of like a half-order of a large pizza with six or eight slices. The idea is that everyone can be categorized according to their level of enthusiasm for, or resistance to, an agenda or new idea. Then you lay these wedges out in order, with the most supportive categories on the left and the most resistant on the right. Your goal is to shift all of society one wedge to the left. That is, the biggest hold-outs still get your attention, you’re just trying to convince them to become only moderately opposed to your goals. Those in the middle, you can tip towards you slightly. Those who are with you from the start, those are your strongest advocates and you can start giving them more work.
What really holds the model together is that you are shifting the entire social culture towards your way of thinking, resulting in culture change. Everyone is a big deal, everyone receives the attention they deserve. It’s very different from that us-against-them stuff that we’re accustomed to seeing during elections. And it is very different from the notion that the main difference in the key players is their place on the org chart.
What this means for workforce analytics, is that you will require several different vehicles to bring meaningful information into human resource decision-making. While there will be those who are hungry for the information, there will be others who need to simply be sold on the notion that it is not a threat. While innovative findings might be compelling amongst an in-crowd, getting the information through cliques and interests will require bridging links and data translation. You can build new ideas in self-imposed isolation, but at some point you step into public and advance it your ideas through the audience.
But before you step out, please put away your Bluetooth headset.
Stuart Murray Speaks 