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.
There is increased speculation that artificial intelligence (AI) will increasingly replace the work of humans over the medium to long term. Already, AI is performing well at the world-class tournament levels in such games as Chess and Go, the latter of which was a major breakthrough. What about actual jobs?
At University of Oxford, a survey from the Future of Humanity Institute asked several leading experts how long it will take for machines to outperform humans. Here is the average forecast for a couple of skill sets:
2023 – Folding laundry
2027 – Truck driving
2031 – Retail sales
2049 – The writing of best-selling books
2053 – Surgery
In the long game, they think all human tasks will be out-performed by machines in 45 years. All human jobs would be replaced in about 125 years. So we’re kind of safe for a decade or so. However, there are major concerns about what this change will mean for humanity, as this change may increase economic inequality.
In my opinion, as this relates to workforce planning, the challenge seems most interesting in the transition period. That is, people will get new jobs designing new technologies, and people will make themselves more productive by using technology in the workplace. But there will be more frequent changes, more dramatic changes, and things will happen more quickly.
These changes mean that human resources will be the key party delivering change management, knowledge management, hiring, learning and development, and employee communications. The pace at which people adapt to change will determine success in investment decisions and the retention of engaged customers. But only if you get the metrics right. Anything else, and your organization is sunk.
Do you know how you’re going to benefit from this screwy economy? There are lots of opportunities to win or lose. How do you make sure you get something out of this world? How do you make sure you land one of the good jobs, and avoid the pitfalls of a fiercely competitive market?
Workforce Data and Inequality by Education
Jeffrey Sachs, the noted economist from Columbia University, wrote a brief overview of the jobs market in the US. Unemployment is near a ten-year low in the United States. This is getting into the news because it kinda looks like Trump’s policies are having a positive impact. But it’s tricky.
What is interesting is the great divide between those with a university degree and those without. Sachs diverts our attention to the more-accurate employment-to-population (EP) ratio which is currently 60.1% “meaning close to three of every five adults is working, still down sharply from the peak rate of 64.6% in early 2000.”
The EP ratio is varied by education level, at 72.1% for those with a degree and 54.9% for those with only a high school diploma.
Sachs notes that job losses in the past decade have been mostly caused by automation and not globalization. He cites the self-serve kiosks at McDonald’s as an example. Policies aimed at saving and creating jobs through restrictions of trade and immigration are “doomed to fail.”
Sachs recommends that America prioritize quality education and job skills, preserving and improving the vital role of public schools. He also recommends America boost the incomes of lower-skilled families through government transfers to break the multi-generational cycle of poverty that discourages skill attainment by the kids. Sachs also points to countries that provide a higher quality of life through better government spending in health care, child care, and other programs, which boost the quality of life regardless of job success.
Public Policy and the Political Divide
I personally agree with Sachs, but I lean that way anyway. I’m well-educated, I come from a union family, and I live in an urban area. I also work in the public sector, and I’m Canadian.
I think the hardest thing for liberals to understand is the opinions of those who are locked-down by hardship and who decline this “expert” help. It’s true at the aggregate level that we should ensure people get help. But at the individual level, people who have actually been poor perceive that overcoming hardship is a case of perseverance, getting out to look work, staying away from high-risk habits, and keeping an eye out for the occasional physical threat. If there are millions of people who have this individual opinion, it bundles together into a block of pro-market voters. The prescription of public-policy solutions seems policy-correct but off-target in the messaging.
Meanwhile, new technologies will disrupt every sector and make billions for those who create or innovate these new solutions, leaving everyone else in the dust.
It’s hard to make sense of it all. To understand this, you need to know that there are secret whispers amongst all economists that “everything causes everything else” in a big hot mess. It’s still possible to have a thriving economy for strange reasons. Trump could still cause the economy to grow by accident. To what we attribute our personal success or failure is frothy right now, and it’s reasonable to not take anyone’s judgments to seriously, including your own.
The simple question we should ask when a few big winners bring in the gold, is will you get your cut? The winners think they get to keep it all. We’ll see.
Discomfort of Innocence. Photo by Mohammed Alalawi
Why do you hang out with people like you? Because you have to be friends with your friends’ friends. Society does not give you permission to dislike (or not know) your friends-of-friends. It’s called the forbidden triad. There is a complex quantitative puzzle involving triangles with plus and minus signs, all coded and ready for an elaborate statistical analysis. You can peek at the math in this October 2016 overview of the research by Dustin Stoltz, a PhD candidate at University of Notre Dame.
But back to people. The main problem is cognitive dissonance, that feeling you get when you are obliged to maintain two contradictory opinions at the same time. An example may be that you both love and hate a particular family member, politician, or manager in your workplace. Cognitive dissonance makes you uncomfortable, and you aspire to greater comfort. Therefore, you will choose between contradictory opinions and let one prevail over the other. So, you decide that you like that complex person. If you then meet a third-party who dislikes that person, you have to even-out the triangle. You will be motivated to change the third person’s mind, change your own mind, or just stop hanging out with the third party. If everyone does this, friendships and world views will evolve within cliques that are internally consistent, comfortable, and smug. But that’s not so clever.
That is because social networks are held together by people who choose to maintain contradictory opinions. They foster civil dialogue, cultivate plurality, and agree to disagree. It’s not so much that they are smarter, although that may still be the case. It’s that the exploration of the best information and the most diverse opinions guarantees contradiction. You will find attributes that seem contradictory but not mutually exclusive, such as sensitivity and courage. You will find rival facts, such as the prevailing research on global warming and colder winters in your own locale. And there will be facts that change quickly, such the price of oil or a change of government.
Workforce Analytics and the Workplace Culture of Curiosity and Discomfort
If you place comfort ahead of maximum information, then you have to insulate yourself from contradiction. Yet this can be a big mistake in the modern world. How could you possibly choose a stable mindset when the amount of information is exploding, technology is disrupting everything, and ideas and opinions go round the world in a heartbeat. It’s a wild and crazy world we live in. You must choose discomfort, and reject the allure of smug.
In workforce analytics, there is a great divide between colleagues and clients who are curious about new information and those who are not. It often feels like I exclusively support those hungry for the new, who like the challenge, who want to pick up a few tricks. Yet those who are more settled in their views or slower to change need to be brought along for the ride. That is because at the center of the social network people are obliged to commit to, and support, prevailing views. They tend to agree with one another just like you might do with your own friends. Looking outward to the fringes of the network, you might see a wider variety of irregular opinions, trends, and opportunities. The fringe is full of people who are removed from the network in some way, be it marginal legal status, geographic isolation, exclusion, or just looking different. To bring diverse views from the fringe to the center (and vice-versa) obliges us to maintain contradictory opinions.
The prescription that we must become uncomfortable applies equally to social trends, new technology, and disruptive workforce analytics. In your workplace, you may have had one opinion for a very long time. When you are presented with change or new evidence, it is one thing to simply obey orders or comply with the data. But if you really want to be clever, it is far better to hold onto that moment of discomfort for a while to get a sense of what everyone else is going through. Only then can you talk to diverse people who think and live in different worlds. And only then can you fine-tune new evidence to make it presentable to a broader audience.
If we are to disrupt normal ways of doing things through emerging information, we must stand at the bridge between two worlds, be prepared to disrupt ourselves, and get used to discomfort.
Do you want to get promoted? Here’s a quick tip… you probably don’t want to get promoted. It’s extremely common for people to attribute their hopes and dreams to the single most common solution to their woes, which is a promotion into a higher-paying job. But that’s not how our souls really work.
The “long tail” is a theory attributed to Chris Anderson of Wired and TED fame. The long tail theory is that for many cultural products – books, movies, and music – we over-rely on a small number of great works that are immensely popular. But there is also a very large amount of product that you might have enjoyed, if only you knew about it, it was easy to access, and you didn’t care that much what others thought about your taste. If you want to get geeky, the long tail web site describes this concept using a power law distribution (1/x), where the popular goods are at the peak on the far left, constituting the “big head,” and the lesser-known goods tail off to the right, going on forever into smaller and smaller numbers, hence the “long tail.”
Bricks-and-mortar storefronts prefer to sell large volumes of popular goods, in order to reduce production and storage costs. By contrast, things sold over the internet can be stored at low cost and sold in low volumes at reasonable profit. The internet opens up your access to a greater diversity of concepts, allowing you to bypass overly-popular mainstream content.
It’s important to keep our eyes on consumer data, because consumer-based big data is about one decade ahead of human resources analytics in terms of maturity.
For those in human resources the long tail phenomenon is a good metaphor for career advancement concerns of employees. Consider our societal obsession with vertical career movement and the opportunity to make more money by working longer hours and enduring greater stress. Contrast that mainstream goal with the possibility of thousands of careers to choose from, a wide range of work-life balance concerns and solutions, and unusual combinations of hours of work and locations of work.
When people meet with career coaches, the employee will often name career advancement as their primary goal, typically to the rank of Director. But after some inquiry, it often turns out that there is a deeper personal objective which is more important to them. It could be energy level, the challenge, pride in craftsmanship, helping others, or greater independence. But each of these individual objectives can be achieved through more targeted efforts. Promotion is only one way to make life better, and in some cases it makes life worse if it takes us further away from the deeper goal.
Career decisions and deeper goals will occasionally line up with the mainstream. For example, it’s usually an all-round good idea to get a degree. But if your motivations are unique, think of your life choices as the equivalent of an obscure garage band with a cult following of two hundred people. Sometimes it doesn’t matter if everyone else is doing it. But it always matters if you’re doing what’s right for you.
Stuart Murray Speaks 