Unbundling Work: Learning to Thrive in Disruptive Times

Gary A. Bolles, eParachute.com & Charrette LLC

#4 in the Fulcrum Series

Work is becoming “unbundled,” fueled by the combination of automation and globalization, and driven by the rapid pace of change.

We need dramatically new strategies to help people to become adaptive workers — today.

Technology & Globalization Are Unbundling Work…

“Unbundling” is a concept advanced in a 1999 Harvard Business Review article by John Hagel of Deloitte’s Center for the Edge, with Marc Singer. The premise is that former “vertically-integrated” companies that held market power due to their interlocked business components are dramatically reshaped by the impact of automation and globalization. I’ve detailed the effects of unbundling in articles like Unbundling Media and Unbundling Higher Education. And I’ve offered some insights about the impact of unbundling on the the U.S. economy in Unbundling the Middle Class.

Technology has had a profound impact on work in the past. As Futurist Ross Dawson has said, “Human history is all about the automation of work… Right from the plough through to the spinning Jenny through to the automobile, through to any number of other inventions. They all destroy jobs. And at the same time we have always created more jobs than we have destroyed.”

In the past, over time, economies have been resilient enough — and innovation widespread enough — that those who lost work in a disrupted field were ultimately likely to find work again. So why is it different this time? How are automation and globalization changing the very nature of work?

…But Our Greatest Challenge is the Pace of Change

In the past, the pace of change has usually been stretched out over decades or centuries. But information technology is unlike any other kind of technology that has come before it. With the advent of machine learning (often called Artificial Intelligence, or AI) and robots, technology has the ability to create technology in ways that were previously the realm of science fiction. According to the University of Virginia’s Philip Zelikow, we are undergoing a shift as fundamental as the transition from an agricultural to an industrial economy — and it’s happening in a blindingly short period of time.

As economist Jeffrey Sachs says, the inevitable conclusion is that many of our greatest challenges are coming from the pace of change. It’s entirely possible that robots and software will have a long-term, large-scale impact on the available amount of compensated work. But what matters most is that the pace of change is accelerating, driven by increasing automation and globalization, and it’s impacting both workers and hirers — today.

Many of our greatest challenges are coming from the pace of change.

It’s therefore our responsibility to do three things:

• First, we must gain a collective understanding of the likely ways that work (and learning) are being impacted, and are likely to be in the near future.
• Second, we must do everything we can to help affected populations to adapt to the new rules of work, so they can have meaningful and productive lives.
• Third, we must come up with dramatically new strategies — in our personal lives, our organizations, and our economies — to allow us to continually adapt to relentless change, so that we all can thrive in disruptive times. In other words, we must all become adaptive workers.

(How hard can that be?)

I’ve detailed below a wide range of ideas, sources and influences, trying to be as comprehensive as possible. If you’re short on time, try reading this brief [link], listing the key takeaways (but no sources).

Since the “new work” arena is a constantly-changing landscape, the specific examples, statistics and articles below will inevitably become old news. My hope is to treat this as a living document, and to update it on a regular basis.

Let’s start with a brief look at the ways in which work has changed in the past, and how we can think about the essence of what work and jobs really are.

Part I: How Did We Get Here?

In 1800, almost three quarters of the nearly 2 million workers in the U.S. worked on farms. (In a telling sign of the times, that number included anyone over 10, and a quarter of all workers were slaves.) By 1840, U.S. population had tripled, yet nearly two thirds of workers remained in agriculture. But by 1920, when the country’s population had increased by a factor of seven, only about a quarter of the workforce was on a farm. By 1960, farm work had dropped below eight percent, while about one quarter of all workers in America worked in manufacturing. Today, under four percent of American workers are on farms.

That fundamental shift in the American workforce over two centuries was driven by the combination of automation and, to an increasing extent, globalization. More technology meant that more food could be produced and distributed for lower cost, a trend which occurred in parallel to the rise of factories, mass production, and a substantial increase in the income of the average American worker. Crops could be grown in higher density and for longer seasons. And globalization meant that food could be sent to markets around the world — and could come from them as well. (Today, the U.S. exports slightly more food than it imports.)

As U.S. farm employment declined, factory employment rose. In the early 1900’s, factories needed workers who could perform Reading, Writing and Arithmetic with reasonable proficiency. That meant that the one-room schoolhouse was no longer up to the task of educating a factory-ready workforce, so the Federal Government took on the task of providing a national system that could deliver the workers that factory owners needed, which led to the creation of such institutions as high schools.

The Three Boxes of Life

This industrial-era construct inevitably led to the three-stage structure for our lives that persists today. In 1978, Richard N. “Dick” Bolles wrote a book called The Three Boxes of Life, and How To Get Out of Them. His thesis: We start our lives with a massive glut of learning; then a massive glut of work; then a massive glut of leisure (in what I call “the period formerly known as retirement”), when you could do all the things you didn’t have time to do when you were younger.

At the time of the transition to an industrial economy, this approach was a huge leap. The U.S. government ensured that everyone — not just the elite — would get a basic education. But it helped to bake into our culture and our economy a Three Boxes model, and encouraged the creation of the mass-production education system we have today.

As detailed in Unbundling Higher Ed and in Unbundling the Middle Class, here are some of the ancient holdovers from that shift to the Three Boxes model:

• Students start school early in the morning — even though studies show again and again that most youth aren’t mentally productive before mid-morning.
• Daylight savings time still exists — despite the fact that few kids need to rise in the dark due to lack of electricity.
• We group kids together by age — even though studies show that kids learn differently at different ages.
• We teach kids with a production-model, pedagogical approach — a teacher at the front of the room — despite years of studies that show kids learn best when they’re the stewards of their own learning, and despite advances in technology that allow them to learn at their own pace.
• We teach all kids the same way — even though studies prove that there are significant differences in the ways kids process, retain and use information.

In the same way that we continue to follow the old rules of education, we follow the old rules of work, as well.

The Old Rules of Work: Understanding Employment

In the past, the rules of work were fairly straightforward. Go to school. Choose and learn a trade or profession. Get a job. Stay in that industry for decades, if not your entire career. Do what your boss told you. If you did those things, you got to have a family, buy a car, buy a house, put your kids through school, and make sure they had a better life than you did. That’s the American Dream.

That’s not to say that change didn’t happen during that period. Throughout the latter half of the 20th century, there were constant shifts in the job market. An oversimplified way to think about these dynamics is to make a circle with the forefinger and thumb of your left hand. That’s the total amount of worker ability in our economy. Now, make another circle with your right hand. That’s the total amount of work need — you can call those “jobs” if you want, but it’s more accurate to think of it as “the total amount of available compensated work.” Now, make the two circles mostly overlap. That’s what economists call “full employment” — most people who want to work, can work. And most employers have workers to meet their needs. Wages are typically high in these periods, and the power dynamic typically shifts to the worker’s favor: Employers have to pay more to get qualified workers.

Now, move the circles so they don’t overlap as much. That’s a “skills gap.” There’s more “supply” than demand for certain skills, and many employers either don’t need as many workers as they used to, or they complain they can’t find workers with the skills they actually need. In times such as these, the power dynamic mostly shifts to the employer, and wages are typically lower, as more workers compete for a smaller amount of paid work. (It’s the opposite in the “work opportunity” segment, because employers are willing to pay more for scarce skillsets.)

Understanding Unemployment

As Dick Bolles makes clear, at any point there are three to five million job openings, even in the toughest times. But national media tend to focus on the delta between hiring and job loss — how many jobs were added or subtracted from the total number of jobs — which is a much smaller number.

Some amount of asymmetry in the work market can be geographic. In its first Workforce Report in February 2017, LinkedIn published its findings about the markets in the U.S. with the greatest asymmetry.

As you’ll notice, though, these are largely concentrated in urban areas. It’s the places in between — the rural areas of the U.S. — that are what a February 2017 Bloomberg article called “the new face of unemployment.” Workers in these areas tend to be older, less trained in the use of technology, and less mobile in their ability to find new work. The article includes a chart that illustrates the changing dynamics of rural workers over time.

Our economy has gone through shifts between high employment and high unemployment repeatedly, such as the massive transition from an agricultural to an industrial economy, or the transition from a wartime to a post-wartime economy. In the past, the workforce eventually recalibrated. Unemployed people got trained in needed skillsets, and eventually filled the need of the new economy.

The Great Recession clearly washed out a huge number of jobs. From 2005 to 2015, employers slowly added back about 10 million “jobs,” eventually bringing the unemployment rate to 4.7% in January 2017. However, that simple metric hid a set of large-scale structural changes that were deeply affecting workers.

According to CNN Money, here are the actual numbers, as of February 2017. Of the 254.5 million Americans age 16 and up:

152.2 million had a job. Of these…

• 7.2 million were “in the labor force,” but without a job (likely self-employed or gig workers)
• 95.1 million Americans were not in the labor force
• 44.1 million were retired
• 15.4 million were disabled and not working
• 12.9 million were taking care of a family member, and not employed
• 15.5 million were in college or job training
• 5.5 million had looked for a job in the past year, or wanted a job but had given up searching for over a year
• 1.7 million “not known” — but many of these were likely to be a combination of young people who had moved back home, spouses not currently working, and workers with part-time but unreported work

Those 95 million who are “not in the labor force” aren’t counted in the unemployment percentage. The most easily forgotten are those who are “discouraged from looking” — they haven’t sought work for more than six months. (For more detail, see Unbundling the Middle Class.)

If you want to better understand the reported numbers for employment, check out the monthly Bureau of Labor Statistics’ JOLTS report, which provides detailed information about what the federal government believes has happened. But as we’ll see, those numbers can be highly misleading.

Understanding Under-employment

The numbers get even more complicated when we factor in part-time and temporary work. A late 2016 study by Harvard University’s Lawrence Katz and Princeton University’s Alan Krueger showed that 94% of the 10 million jobs added from 2005 to 2015 were in “alternative work” — where a worker was working either part-time or temporary. In that time, the percentage of American workers engaged in such alternative work jumped from about 1 in 10 to about 1 in 6.

Did this grow due to workers’ choice? As reported by CNN Money in 2014, “the number of people working part-time involuntarily is more than 50% higher than when the recession began” — bringing the national average of involuntary part-time workers to nearly 5% of the workforce. In 2015, 6.6 million workers were estimated to be in this situation.

According to a Carsey Institute study, “involuntary part-time employment (or underemployment) is concentrated among relatively disadvantaged groups, such as African Americans and Hispanics, recent immigrants, and high school dropouts.” About three quarters of part-time workers are either low income, and part-time workers are five times more likely to live in poverty than full-time workers, says the study’s author, Rebecca Glauber of the University of New Hampshire. Part-time workers tend to be paid less than full-time workers, even for the same work. And nearly 30% of involuntary part-time workers go without work for at least three months each year.

Another kind of involuntary work is the kind of under-employment that comes from a worker doing work that requires less than their skillset. A study by Payscale.com found that 46% of all workers believed they were under-employed. To the respondents, under-employment included doing work beneath their education and experience, as well as those working involuntary part-time or temporary. 52% of high school graduates, and 57% of those with some college, reported being under-employed. 41% of MBA degree holders said they were under-employed — and a whopping 90% said their current job didn’t use their education or training.

A study by Payscale.com found that 46% of all workers believed they were under-employed.

Some of the self-reporting about being under-employed may have to do with engagement — how much (or little) workers feel they are connected to the work they’re performing. According to an annual Gallup survey, in 2015 only 32% of U.S. employees were engaged in their work. Gallup says that over half were “not engaged” (“just showing up” at work), and more than a sixth were “actively disengaged” — sabotaging the work environment. The report goes on:

“Gallup categorizes workers as ‘engaged’ based on their ratings of key workplace elements — such as having an opportunity to do what they do best each day, having someone at work who encourages their development and believing their opinions count at work… Engaged employees are involved in, enthusiastic about and committed to their work.”

Some workers might be disengaged because they’re not using their favorite skills and knowledges in their work. Others may feel it’s the lack of cooperation from co-workers, or the lack of a supportive supervisor.

Again, using your fingers as circles: If your left hand circle is all of the skills, knowledges, and work environment characteristics that make you happy in your work, and your right hand circle is your current job, how much of an overlap do the two circles have?

Of course, in an earlier age, our parents or grandparents might have told us that “engagement” is a useless term. After all, they didn’t necessarily have to love what they did for work: They just did it, put food on the table, and a roof over their family’s heads. But from the employer’s perspective, that world no longer exists. The Gallup report continues:

Gallup’s extensive research shows that employee engagement is strongly connected to business outcomes essential to an organization’s financial success, such as productivity, profitability and customer engagement. Engaged employees support the innovation, growth and revenue that their companies need.

For employers who realize that a retained worker is more valuable than a lost worker, that means it’s not an option to allow more than two thirds of workers to be disengaged at work: Increasingly, employers will need to find ways to help workers to be more actively engaged.

Why are the dynamics of unemployment and under-employment so important? We need the best possible understanding of what’s happening to our economy, so we can make the best possible decisions, as the very nature of work changes before our eyes.

Part II: What’s Work?

The Oxford Dictionary tells us that work is “…[an] activity involving mental or physical effort done in order to achieve a purpose or result.” That doesn’t necessarily mean we’re paid for it, though. So Oxford continues, “Mental or physical activity as a means of earning income.” (Of course, not all work is paid. But to the worker, even volunteer work is often still work.)

From a hirer’s perspective, the building blocks of work looks like this:

We’re paid to deliver results. This is true whether the result is a clean floor, or a profitable transaction.

To achieve results, a worker usually has to solve a set of problems. This is true whether the problem involves a dirty floor, or a complex series of financial calculations.

To solve problems, a worker performs a set of tasks. Because related tasks are often linked together in a series of steps, they’re often aggregated into processes.

To perform tasks, a worker uses one or more skills.

From the worker’s point of view, the sequence is the opposite: We use our skills to perform tasks in processes to solve problems and generate results.

For example:

• A fast-food company has problems like getting food into the hands of happy customers. Tasks such as taking orders and making change are performed using skills like listening, handling money, making change, and so on. And the result should be that food is delivered into the hands of a happy customer, and money is deposited in the cash register.
• A consulting company has problems like helping clients develop complex market strategies. Tasks such as conducting research programs and engaging in strategy design are performed using skills like analyzing, interviewing, synthesizing, and writing. And the result is a happy client who has a new strategy.

Of course, this is an oversimplification: In a lot of work situations, the sequence from skills to results isn’t linear, with a constant cycling through a variety of tasks and problem-solving until a desired result is generated. At times, the exact results that a worker is generating may seem opaque. And in some situations, the specifics of problems to be solved, or the results to be generated, may be opaque.

But for most workers, the general building blocks of work remain: Results, Problems, Tasks & Processes, and Skills.

What’s a Skill?

In the same way that “friend” has been redefined in the age of Facebook, “skill” no longer means what it used to. In the past, many people defined a skill as an occupation, like being a lawyer or a programmer. But we need a more granular way of looking at skills, if we want to understand how work really works.

It turns out that the most effective skills definition goes back to the 1950s, when Sidney Fine, the “father of the Dictionary of Occupational Titles,” offered a fundamental insight. According to Fine’s work, there are three categories of skills: Special Knowledges (or Work Content); Transferable (or Functional) Skills, and Self-Management skills (often thought of as Traits).

• Knowledges are bodies of information that we possess, which help us to know what tasks to perform to solve specific problems. These are sometimes called Work Content skills, because they are comprised of the information (content) associated with a particular kind of work. Knowing how to perform brain surgery, or how to repair a car engine, is an example of a knowledge.
• Transferable Skills are skills that we can use in a variety of situations. When you were a kid, if you were good with people then, you’re probably good with people now — and you’re good with them in a variety of situations. Analyzing data, taking things apart with your hands, problem-solving — these are all transferable skills. These are also called Functional skills, because they allow us to perform certain functions under a variety of conditions.
• Self-Management Skills, often called Traits, are skills we apply to ourselves. How well we can follow through on a task, or manage our inevitable frustrations, or arrive on time for an appointment, is determined by our self-management skills.

In other words, what you Know, what you Do, and How you use what you know and can do.

It may be helpful to think of a skill as energy applied to a task. The process of calling up Knowledge in our brains takes energy. Applying a Transferable Skill, such as writing with a pen, takes energy. And using Self-Management Skills to guide our own actions takes energy.

Each kind of skill is energy applied to something different. With Knowledges, we apply our energies to bodies of information. With Transferable Skills, we apply energy to people, data or things. And with Self-Management Skills, we apply energy to ourselves.

Each of us has many skills. There are hundreds of transferable skills, and a virtually unlimited number of knowledges — from simple knowledge, like boiling a pan of water, to deep knowledge, like the steps in brain surgery.

Skills can be thought of as existing on a sliding scale, from zero ability, knowledge or training, to complete mastery. (That may make you think of Malcolm Gladwell’s reported 10,000 hours of practice — which is questioned by a 2014 Princeton study). Our engagement in the use of that skill, or in the study of a body of knowledge, can also be thought of as a scale, from no interest, to the conviction that this arena is our purpose in life.

From an individual’s standpoint, skills are the most important elements of our work — and are therefore the most important parts of a job.

What’s a Job?

As Dick Bolles talks about in What Color Is Your Parachute?, jobs have seven important parts. In addition to our skills and knowledges, jobs also include a people environment (including co-workers, and customers or clients), a workplace environment, one or more geography locations, compensation (salary and benefits), and the values of the individuals and the organization.

The various components of a job have traditionally been bundled together, like this:

As Dick Bolles points out in Parachute, these are also the components of what we as individuals care the most about in our work. There’s a raft of literature that explains the connection between the work we do, our jobs, and our feelings of importance and purpose in our lives. For many people, the greater the overlap between all of the elements we love in our work and the jobs that we perform, the greater our happiness.

Unbundling Work

Since work is skills performing tasks in processes to solve problems and deliver results, how does automation change this formula?

Skills

• For workers, automation can enhance our skills, allowing us to perform tasks we might never have been able to do otherwise. Most of us couldn’t perform complex calculations without a spreadsheet program, if our lives depended on it. Software and robots have the potential to enhance our skills in a range of ways, “up-skilling” workers to perform increasingly-harder tasks.
• For hirers, up-skilled workers are easier to find, and can be paid potentially less, than workers with extensive training in an arena. It’s also easier to move workers around in larger organizations when up-skilling tools are readily available.

Tasks

• For workers, software also allows tasks to be split apart. Suppose you needed an audio recording to be transcribed. You could use software to find a transcriber, transmit the audio recording, and receive the transcribed results, and the actual task of transcription would be performed by someone who might be halfway around the world. What that means is that, as with classic outsourcing, the work becomes unbundled, allowing tasks to be performed elsewhere by cheaper workers. If you’re that remote worker, you benefit.
• For hirers, automation increasingly performs the task itself. Today, you’re far more likely to submit an audio recording to an online transcription service, which can often provide a transcript usable for editing. This is the typical concern about software and robots eating our jobs, as technology replaces an increasing amount of human activity. But software and robots don’t usually eat jobs: They eat tasks. It’s a hirer’s decision if technology is used to replace an entire job. (More on this below in “Unbundling Jobs.”)

Processes

• For workers, software will make it easier to perform complex series of tasks. By automating processes, technology supports or enforces a sequence of tasks. That often means that less-trained people can quickly get up to speed. For example, using a cash register used to require training: Today, app-based services walk checkout people through a sequence of steps.
• For hirers, having software manage processes means it’s easier to plug in remote workers — and therefore to enlist workers in other countries who are paid far less. And because software can also perform an increasing number of tasks on its own, having automated processes simply means that technology can more easily take on an increasing number of tasks.

Problems & Results

• For workers, technology can help them to more rapidly understand the problems of customers, to band together, and to dynamically bind around those challenges.
• For hirers, they can simply specify the problems they want solved, or the results they want — without necessarily specifying who or what performs the necessary tasks. Think of this as the “work cloud.” In the same way that computing clouds distribute computing tasks to a range of potential devices, requests to a work cloud can be distributed to a variety of workers — or to software and robots. This kind of “results-driven work” has the potential to be the ultimate unbundler, because it means the hirer has the potential to be agnostic about the source of the work.

In reality, the level of abstraction involved depends on the kind of work, and the level of control the hirer wants to assert. If a hirer defines all the requirements for a simple website design, all that’s typically needed is a set of design options to choose from: Whether it was performed by a crackerjack team of designers around the corner, or a piece of software, probably doesn’t matter to the hirer. But anything that involves iterative design and development, such as creating a complex piece of software, or launching a content product like a magazine, will likely require more “high-touch” involvement where the hirer will want to have a regular collaboration process with the people performing the tasks.

Unbundling Jobs

What does all this mean for jobs?

Just as they have done with entire industries, automation and globalization have turned the components of jobs on their ends, unbundling them, allowing them to be separated into different layers, and fundamentally changing the way work is performed.

Take, for example, geography. Many jobs used to require the work to be conducted in a specific location, such as an office or a factory. But with the combination of automation and globalization, a variety of work can be performed in another place — outsourced halfway around the world, and allowing employers to pay less for the same work.

But automation and globalization have far more seismic implications for work than simple outsourcing: Together, they allow work to become completely unbundled, down to a very granular level. As work becomes unbundled, the likelihood increases that hirers will look for ways to distribute tasks performed by humans wherever it’s cheapest. Rather than simple outsourcing — an entire job goes overseas, where wages can be a tenth or less than in the U.S. — discreet tasks will be more easily distributed by automation. According to Richard Baldwin of the Centre for Economic Policy Research, “What it will do is unbundle our jobs and change the nature of our occupation. Some of the things you do absolutely require your judgement — but parts of your job could be off-shored, just as some stages in a factory can be off-shored.”

Perhaps the clearest examples of the unbundling of work and jobs can be seen in the dynamics of what’s frequently called The Gig Economy.

Sidebar: How Unbundling Evaporates the Middle

As detailed in Unbundling Media, healthy industries look like pyramids, with small, niched companies at the base, and large, multi-national companies at the top — and everything in between. But when automation and globalization unbundle an industry, there are three typical results:

At the top: Power goes to the dominant players at the top of the pyramid — and often to a single player. (There’s only one Amazon, one Facebook, one EBay, one Google, etc.)

At the bottom: There is lower friction to entry at the bottom of the pyramid, allowing small, niched, and highly focused players to emerge overnight. You can start a blog or a small business in the blink of an eye.

In the middle: The middle evaporates. There are fewer mid-sized organizations than before, and maintaining a position in the middle is much harder.

Healthy work markets look like pyramids, too, with low-paid, easy-entry jobs and highly-paid, deep-training jobs — and everything in between. In the middle, as of late 2016, the U.S. median annual income was about $44,000 a year, or $20 an hour.

So what happens when the work market becomes unbundled?

At the top, markets continue to reward workers with much-needed skillsets, paying a premium. As quoted in the Economist, “Tyler Cowen, an economist at George Mason University and a much-read blogger, writes in his most recent book, Average is Over, that rich economies seem to be bifurcating into a small group of workers with skills highly complementary with machine intelligence, for whom he has high hopes, and the rest, for whom not so much.”

At the bottom, becomes far easier to get lower-paying work. Reduced friction means that work will increasingly become available through an app. Today, it’s driving for Uber and fetching for TaskRabbit; tomorrow it will be sweeping a park, or filling a shift. (Note that these are also the kinds of work that may be easily automated.)

In the middle, jobs tend to evaporate, as a Bloomberg article from May 2016 points out. Hirers have greater incentives to automate an increasing number of tasks, especially for people-intensive work roles with repetitive activities — the dynamic that Stephen Hawking worries about the most. Middle-income workers’ tasks are likely to be easier to automate than those who are better paid. And as for those lower-income workers — well, their tasks are the most likely domain for robots and software.

It’s important to note, though, that this trend is not inevitable. Hirers have the ability to decide what work gets automated (or not), how it gets automated, and whether jobs simply change — or disappear.

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Understanding the Gig Economy

To see how work and jobs are unbundled in practice, let’s look at the personal transportation industry.

In the past, we called the transportation hirer “A Cab Company,” and the worker “A Cab Driver.” (In 2012, there were about 233,000 cab drivers in the U.S.) What are the most frequent problems that A Cab Company has? Taking the customer’s order, dispatching a vehicle to pick up the passenger at Point A, depositing the customer at Point B, and charging the customer.

In a traditional taxi business, the tasks needed to solve these problems would have been performed using the skills of the dispatcher, who takes the customer’s order and tells the driver to pick up the passenger, and the driver, who transports the customer and takes the customer’s payment.

Along comes Uber. The tasks needed to solve the problems are now performed by an app, which takes the customer’s order, tells the driver to pick up the customer, and takes the customer’s payment; and an untrained driver with a car, who transports the customer.

As of July 2016, Uber alone was reported to have 160,000 drivers in the U.S. — equal to more than two thirds of the existing cab driver workforce. (And probably overlapping it substantially; a cab driver often can also be an Uber and/or a Lyft driver.) That’s a lot of “gigs,” as these work opportunities are often called. So what it would it look like if an increasing amount of work is performed as gigs?

The main difference in the Gig Economy is that much of the distribution of paid work is happening through labor platforms — software that enables two-sided markets, such as worker and hirer. Other examples of labor (or unbundled work) platforms include TaskRabbit and Taskloop, which connect hirers with workers (“taskers”) willing to perform odd jobs, and Mechanical Turk and Samasource, which distribute online “micro-work” tasks.

Unbundled work platforms benefit the hirer because they provide some kind of increased value over the prior way of doing things (or else they’d fail). These platforms also benefit the worker, by providing easier entry (they often don’t require anything but a web browser), rapid access (you can become a Lyft driver today), flexibility (tasks can be often performed when the worker is available), mobility (workers can often perform tasks from anywhere), and extra income (workers can make money in their “spare time”).

How much of a gig economy is there? That depends on whom you ask.

Although Pricewaterhousecoopers projects this alternate economy to generate about a third of a trillion dollars by 2025, in 2016 it didn’t add up to a significant percentage of the domestic work market. JPMorgan Chase Institute estimated that as of July 2015, adding all of the income from labor platforms barely totaled one percent of the workforce. (A TechCrunch contributor even declared the entire “gig economy” arena DOA in 2015.) The Wall St. Journal went on in March 2016 to speculate that the gig economy was mostly Uber.

From WSJ.com

These are only estimates using government data. The Bureau of Labor Statistics itself won’t commit to specific numbers of gig economy participants, because it hasn’t been tracking the data directly. A recent study suggests that 22% of American adults, or 45 million people, have already offered some kind of good or service in this economy, and that 44% of U.S. adults have participated in such transactions, playing the roles of lenders and borrowers, drivers and riders, hosts and guests. However, a 2015 study by QuickBooks found that only 5 percent of those engaged in on-demand work said it was their sole source of income. And 43 percent said they also had a part-time or full-time job.

Still, there is growing concern that as the traditional characteristics of jobs fade, there will be a rapid rise of automation and globalization that will mean rapidly-growing unemployment. The question is: What’s really happening?

Sidebar: The Erosion of Worker Power

It’s a fascinating dynamic of our time: At a time when the erosion of worker wages is headline news, there’s also a decreasing amount of collective power for workers. Unions are a pale shadow of their former selves, and the rise of gig platforms inevitably will erode that power — and those wages — further.

Independent work has a variety of benefits, including flexibility, variability, and (potentially) control. It also has a number of recurring challenges, including lack of promotion, training, and benefits. But the biggest potential downside for the worker is pay, since unbundled work platforms are designed to encourage a race to the bottom.

Unbundled-work platforms mean broader competition for available work (most people with cars can be Uber drivers), employer control (the hirer usually defines the work to be done and the pay), and the potential for “wage compression” (reduced wages are almost inevitable). It’s even more challenging to get good pay with platforms like TaskRabbit, where workers compete at ever lower pay levels, until someone “wins.”

Unbundled-work platforms are unquestionably useful for people who have minimal or no income, or who need a supplemental income, or who want to develop a new set of skills. They’re also useful in developing economies where wages are already low. But in developed economies, they don’t necessarily represent stable, long-term, full-time work opportunities.

It’s entirely possible that unbundled-work platforms will emerge that have the opposite effect, aggregating workers and increasing their bargaining power. But except for in-demand workers like high-end computer programmers, it’s far more likely that these platforms will continue to compress worker wages.

-gB

Part III: The Problem Domain

The unbundling of work is often distilled down to a single question, embodying a single fear: Will software and robots eat our jobs?

People like Microsoft co-founder Bill Gates say it’s true. Physicist Stephen Hawking believes it as well. Rice University professor Moshe Vardi says in the Financial Times, “We are approaching the time when machines will be able to outperform humans at almost any task. Society needs to confront this question before it is upon us: if machines are capable of doing almost any work humans can do, what will humans do?”

Will Software and Robots Eat Our Jobs?

Many writers have done an excellent job detailing the various ramifications of this issue.

• In The Second Machine Age, Andrew McAfee and Erik Brynjolffson documented the ways in which technology and globalization are affecting today’s job market.
• The Economist has an excellent overview of key issues in The Onrushing Wave.
• In Rise of the Robots: Technology and the Threat of a Jobless Future, Martin Ford asks — and extensively answers — if it’s possible that robots and software are indeed eating our jobs.
• The Aspen Institute’s Future of Work initiative offers a series of insights into how the work arena is changing, including Connecting Young Adults to Employment and The Future of Work for Low-Income Workers & Families.
• The World Economic Forum has weighed in on the topic with The Future of Jobs.
• McKinsey has a foundational report on Connecting Talent with Work in the Digital Age.

We can distill much of the thinking about the coming impact of automation and globalization into two scenarios at the polar ends of our economic future.

Scenario #1: The Job-less Future Scenario

Automation and globalization will rapidly decrease the amount of compensated work available. Less work means lower wages and rampant un- and under-employment. Robots and software will inevitably eat our jobs, so we better start thinking about strategies to help deal with a jobless future. That picture would look like this:

Call this the Job-less Future scenario.

How job-less, and by when? That depends on the study.

• 47% of all jobs by 2025. (Oxford University)
• “50% of occupations today will no longer exist in 2025.” (CBRE Research)
• 51% of all activities in the economy by 2055, accounting for nearly $2.7 trillion in wages. (McKinsey, January 2017)

To show that the U.S. isn’t alone, physicist Stephen Hawking in a December 2016 lecture warned of massive disruption to middle-class jobs, and the Daily Mail reported that Bank of England governor Mark Carney claimed “almost half of Britain’s workforce could be replaced by robots over the coming years” — consistent with Oxford’s projections, albeit on a more vague timeline.

Note that researchers vary in three ways:

• Whether tasks will be automated, or are simply automate-able. These are very different things. Just because, for example, 40% of tasks may be automated, doesn’t mean they will be, or when. Employers make unpredictable decisions, on unpredictable timelines, making specific projections challenging.
• Tasks versus Jobs. Even if 40% of all tasks will be automated, that doesn’t meant that 40% of jobs will go away: Hirers could make different decisions than just to aggregate those lost tasks and do a lot of layoffs.
• The net impact of automation on compensated work. The Job-less Future depends heavily on there being no large countervailing work opportunities, and that may simply be due to a lack of imagination — and planning — on all of our part. In fall 2016, the World Economic Forum suggested a net loss of 5 million jobs in 15 economies around the globe by 2020, and Forrester Research projected that there would be a net loss of 6% of U.S. jobs by 2021. That’s within the range of a mild to a major recession — but not a job-less near future.

Source: World Economic Forum

To reiterate: software and robots don’t necessarily eat jobs. Software and robots eat tasks. It’s the hirer who determines if a job gets eaten — or doesn’t.

Software and robots don’t necessarily eat jobs. They eat tasks. A hirer determines if a job gets eaten.

Scenario #2: The Job-Full Future

History is filled with cycles of automation when jobs were lost. Eventually, new jobs were created. Technology taketh away, and technology giveth. In other words, robots and software won’t eat our jobs, and in fact technology always creates new work opportunities that we can’t envision. That picture would look like this:

Call this the Job-full Future scenario.

Perhaps the most avid proponent of the job-full future is venture capitalist Marc Andreessen, who believes in what Singularity University calls the “abundance” scenario — with tools for production in the hands of everyday workers, things become cheap to make instead of buy, and the overall cost of a standard lifestyle drops precipitously. We make less money, but it costs less to live. As Andreessen says, suppose that… “Robots eat jobs in field X. What follows is that products get cheaper in field X, and the consumer standard of living increases in field X — necessarily. Based on that logic, arguing against robots eating jobs is equivalent to arguing that we punish consumers with unnecessarily higher prices. Indeed, had robots/machines not eaten many jobs in agriculture and industry already, we would have a far lower standard of living today.” (Note that Andreessen isn’t saying there will be no asymmetry in the work market. He’s simply saying that the cost of living will descend, and that in aggregate people will have better lives.)

John Markoff, former New York Times reporter, and author of Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots, says that he’s not worried about robots taking our jobs, because our workforce is aging so rapidly. What this doesn’t seem to take into account is asymmetry — what happens when jobs are lost in one category, and the likely categories that would be taken by humans (such as home health care) are instead occupied by automation.

What Do We Know — Today?

We can’t reliably say which scenario will actually happen — Job-less, Job-full, or something in between. But we can take a look at what we already know.

Certainty #1: We know that automation has the potential to disrupt an increasing number of work categories. It seems there’s a new article every day claiming that a new job role is being automated by some entrepreneurial company. Many of these are labor-intensive, repetitive-task jobs like baristas, bartenders, berry-pickers, box-packers, cashiers, table-waiters — and, of course, factory workers. But white collar, advice-intensive roles like hedge fund managers, lawyers and financial services coaches are also in the crosshairs. And government work isn’t far behind.

Source: Oxford University via Bloomberg News

The Times of London has a searchable version of the Oxford study that lets you determine the percentage of risk that the Oxford researchers have projected for a range of occupations.

McKinsey Global Institute has issued its own risk assessment chart.

Source: US BLS & McKinsey Global Institute

Again, this doesn’t mean these jobs will be automated. For consumer-facing service jobs, we don’t know how rapidly customers will accept the lack of a human touch. But innovative entrepreneurs clearly have virtually every possible work task in their automation headlights.

Certainty #2: We know that automation creates a lot of jobs. There’s no question that technology creates new opportunities. For example, employment of software engineers quadrupled between 1990 and 2010, from 400,000 to 1.6 million. We need more research, though, to point to other arenas where scaled work opportunities can be generated by technology.

However, because technology tends to make people more efficient, large tech companies typically generate about one tenth as many jobs as their earlier counterparts, according to a recent McKinsey study. Nobody knows if this is true for smaller hi-tech firms, but it certainly seems plausible that technology will continue to enable employers to use fewer people.

Certainty #3. We know that automation will change a lot of jobs. How many managers in organizations used a keyboard 50 years ago? Typing was considered menial work, performed by secretaries. Today, it’s hard to find any white collar worker of any occupation who can’t type. Technology has already changed a huge percentage of jobs, and it will transform many others even more quickly. For example, Forrester Research projects that “humans will find themselves working side by side with robots.” CBRE Research suggests that “artificial intelligence will transform businesses and the work that people do.”

Certainty #4: We can be certain that the potential for displacement is dramatic. In early 2017, a variety of employers were already claiming they were finding it increasingly difficult to find trained workers for new job roles. If this trend continues, we’ll have increasing asymmetry in the work market.

Barring some big leaps in education and assistive technology, it will be increasingly difficult for displaced workers to adapt to the requirements of new work. The result is that it will be possible to have high unemployment, high underemployment, and a large amount of unfilled job openings — all at the same time.

For example, in February 2017, these two items were listed in a row in by LinkedIn’s New Economy editor, Caroline Fairchild.

• The end of employees. Top American employers like Walmart and Alphabet continue to grow their share of outsourced employees in order to cut costs. As many as 20 million Americans currently work as contractors. [WSJ]
• Hiring spree. Private companies added 246,000 new employees to their payroll last month, a sign that wages may soon be on the rise. [CNBC]

The chances for this kind of schizophrenic job market increase as the pace of automation and globalization increases.

Certainty #5: We know that the pace of change will continue to grow rapidly.

Ray Kurzweil, author of The Singularity Is Near, has famously shown that technology-fueled change doesn’t happen linearly. It happens exponentially, moving at an increasingly-rapid pace.

Source: The Singularity Is Near

We know that the pace of change will continue to grow exponentially — with no end in sight.

No matter whether or not robots and software will eat our jobs, or gig economy platforms will ultimately win, we have a variety of strong indications that the pace of change in the world of work is accelerating.

We Need New Strategies — Today

If we accept that…

• The pace of change driven by automation and globalization isn’t going to stop.
• There are many workers today who are already having huge challenges with the pace of change.
• There will be even more workers tomorrow who will struggle to adapt to increasing change.
• Our institutions like education and work are not currently capable of preparing us for such rapid change.

…then we need to act. Today.

We don’t need to know if robots and software will eat our jobs. We need new strategies, and concerted action, now. We need to be able to adapt, continuously, no matter what the overall picture for compensated work looks like. And we need to adapt as people; as organizations; and as economies.

Part IV: The Solution Domain — Here’s What We Can Do

I’m often asked, What can we do? What is The Answer to all this disruption? I’d rather that we ask the question this way:

In 20 years, what will we wish we had done — today?

We don’t need to debate whether robots and software will eat our jobs in a few decades. Automation is already having a profound impact on a broad range of workers. While a huge percentage of workers are likely to be impacted in the future, we need to understand the likely effects on specific populations today, and to pro-actively help them to prepare for a world of constant change. These cohorts can be organized into categories such as:

• People in life transition. Returning military, spouses re-entering the workforce, recently handicapped, and the formerly incarcerated all have a similar core set of needs.
• Affected job roles. Predictable jobs to be affected include many white-collar jobs, as automation replaces an increasing number of tasks. But many blue-collar jobs will be affected as well, including truck drivers, fast-food workers, and taxi drivers.
• Rural areas. In 2017, 50 percent of the U.S. lives in cities, and according to the Population Reference Bureau, “it is expected that 70 percent of the world population will be urban by 2050.” Imagine, then, that every small town in the U.S. drops in population by 40% in about 30 years — and will primarily be comprised of older Americans. How can we give them the tools to lay the groundwork today so they can maintain their economic viability?

What happens when a large number of people no longer have access to compensated work? Widespread unemployment leads to a raft of societal ills, from poor health to the conditions for radicalization. We need brilliant minds to commit to helping create solutions for affected populations. People should become involved because they think it’s the right thing to do, or because they fear the onset of revolution. Either should be sufficient motivation.

People should become involved because they think it’s the right thing to do, or because they fear the onset of revolution. Either should be sufficient motivation.

In a world of rapid change, we need to modify our thinking from seeking The Answer — a potential solution that will be applicable long into the future — to developing The Process, a set of ongoing rapid-cycle steps to allow individuals, organizations — and, yes, economies — to continually adapt to constantly-changing conditions.

What we need is a set of processes to help us continually to adapt as exponential changes continue to occur. Each era can have its own unique processes, but every succeeding period from now on will require new processes — far into the future. We need to follow strategies that we can begin using now, today. And we need to develop approaches that allow us to continually iterate the solutions we’re delivering. Ultimately, what we want is the ability for all of us to be able to thrive in uncertain times.

The rapid changes in the world of work have raised a series of challenging questions, such as:

• How can a worker continue to have the skills and knowledge needed to continue generating a living income?
• How can a worker verify what they know and what they can do?
• How can a hirer trust that the worker knows and can do what they say?
• How can workers find new work opportunities — and get rapidly trained to perform them?
• How can we change the massively inefficient process of linking workers to work needs?

The answer to all of these questions, and more: We need new models. We need a set of processes to help us to continually adapt as exponential change continues to occur.

If we continue to depend on industrial-era models for secondary education, higher education, organizations, management, and work, we will be simply unable to maintain even a semblance of inclusive economies. We must reshape our major institutions, intentionally, to ensure that we have functional systems that will meet the needs of a broad range of constituents.

Many brilliant people have made suggestions in recent years for ways to not only mitigate the negative impact of automation and globalization on compensated work, but to offer ideas for ways that people, organizations, and institutions can thrive in disruptive times. Those ideas and more have been organized below into a set of models, listing the complementary strategies with the greatest potential for having a positive impact.

NEW MODEL: LIFELONG LEARNING

Our industrial-era model of education that’s designed to manufacture learners on a mass scale is no longer up to the task of preparing young people for adult life in a time of rapid change. We need a completely new model of learning that lasts throughout our entire lives, and helps us to continually adapt to a rapidly-changing world.

Perhaps the greatest early champion of lifelong learning was Parachute author Dick Bolles. In his influential book from 1978, The Three Boxes of Life, and How to Get Out of Them, he advocated the need to completely change our model of education from a single “box” at the beginning of our lives, to a model of continuous self-education.

What should lifelong learning look like, in an era of exponential change? The goal should be to train proactive creative problem-solvers, at all ages.

When we’re young, we need to break apart the model of mass production on which our public schools are based. Why do we group our kids in schools solely by age? Why do we force kids to learn the same things at the same time? Why do we use testing as the sole determinant of achievement? We need to leverage technology to deliver customized learning opportunities to every student at every age. But technology isn’t the sole answer. We need to provide teachers with the resources they need to become stewards of each learner’s journey.

We need to teach:

• Proactive, student-driven learning, rewarding each student’s creativity.
• Critical thinking. Kids need to learn to be intelligent consumers of the information they receive.
• Collaboration. Learning how to team with others early on will increase their ability to collaborate when they’re older.
• Structured problem-solving. (The common Silicon Valley suggestion is to teach every kid to learn computer programming. But Tom Goodwin, head of innovation at Zenith Media, suggests that this is missing the point.)
• Project-based learning. As adults, they’ll increasingly work in projects; by learning how to approach projects when they’re young, they’ll learn the basics early.
• Digital literacy. (Example: ProjectDQ)
• The importance of values. The more that kids can be encouraged to understand what values are, and how they drive our actions, the more they will want to contribute when they’re older.

Taken together, these can all be thought of as “agency” — the ability to be a creative, proactive problem-solver. People with agency take action to find new opportunities — or to create them.

The goal should be to train proactive creative problem-solvers, at all ages — with the result that people will have “agency.”

When we’re in our late teens, we need to completely re-think the steps that we follow to enter the world of work. Why do we send young adults to institutions of four-year learning? Why is it four years? Why at the age of 18? When we ask these fundamental questions, we realize that we have accepted a world of higher education that’s also built on a post-industrial model.

There’s no question that a two-year, four-year, or even longer college experience is completely appropriate for many young adults. But we have created a pressure-cooker environment for our kids that makes college a requirement for many, rather than a valuable decision for some. There is also no question that a college degree is increasingly necessary to provide young workers with greater job opportunities. But that’s not an immutable law: It’s the result of decisions that employers make. And employers will need to dramatically change the way they hire, if they want to have the workers they need tomorrow. (More on this below.)

We need a completely new way of thinking about the transition to adulthood. We need to learn:

• Self-inventory. Each of us has a unique set of interests, skills, knowledges, and traits. Every youth needs to learn how to do this self-inventory, on an ongoing basis, for the rest of their lives.
• Entrepreneurial thinking. By thinking of themselves as “a startup of one,” youth can learn to become more “agent-full” in their own activities.
• Risk-taking & embracing failure. Only by taking risks, and by accepting our own failures, and the failures of others, will we be able to act entrepreneurially. That doesn’t mean everyone needs to start a company. But it does mean everyone needs to act with agency.
• Being adaptive. The world will constantly change, so youth need to learn how to continually adapt.
• Values-based problem-solving. Solving problems based on the needs of family, friends, community, and the planet.
• Emphasize transferable and self-management skills. We must shift toward learning opportunities that emphasize transferable skills, as well as knowledges. In the digital era, where so much information is available online, our transferable skills are what will allow us to continually adapt. This means that the traditional value of a liberal arts education is significantly amplified. (More on this in Unbundling Higher Education.)

When we’re adults, we must accept a work world that will constantly change. We must think of ourselves as lifelong learners, and become adept at navigating our individual paths to work opportunities. That’s an uncomfortable reality for many, especially for those who grew up working in long-term jobs or fields. But if we’re to thrive in disruptive times, we need to think and act differently. Some strategies include:

• Targeted learning experiences. A four-year software engineering degree at a well-known school can cost up to $300,000, and comes with no guarantees of future work opportunities. But an increasing number of online and in-person code-camps like Code Fellows and Bloc charge fees ranging from free to $24,000 for programs ranging from 4 to 48 weeks, and, if successfully completed, comes with a guarantee to be hired. Which would you choose? Of course, not all students will be directed enough to choose such learning opportunities. A traditional view would point to all that a code-camp graduate loses, such as the chance to grow up on a campus, build lifelong friendships, and gain exposure to a range of classes that could help spawn critical thinking. All of these are tremendous benefits for those who can afford it — but the number of American families that can either pay such fees, or take on that kind of debt, is rapidly shrinking. Online learning company Udacity calls these “nano-degrees,” and in fact such targeted learning experiences are one solution to a rapidly-changing work world. By allowing workers to become quickly trained in new fields of compensated work, targeted learning offers one answer to the needs of workers who might otherwise be unemployed.
• Annual self-inventory. We need to continually understand what makes each of us unique. We have annual health checkups with a doctor; we also need annual “life design checkups,” when we assess how our work matches up with our capabilities and goals. This also allows us to set goals that can guide the choices we make about the work we want to do in the future, and what we need to and want to learn.
• Colleges as Lifelong Learning Platforms. Our institutions need to help us to adapt more effectively. We need to provide workers with the tools and information they need to identify what they want to learn, and give them the opportunity to gain that knowledge and experience as rapidly as possible. For example, colleges need to remake themselves into lifelong learning platforms, providing opportunities for alumni and other adults to repeatedly prepare themselves for their next career step. As I said in Unbundling Higher Education, what other business sees you as a customer for four or eight years — and for the rest of your life as a cash register? Rather than simply asking you for donations, your alma mater should be watching when you update your LinkedIn profile, and send you an invitation to re-invent your career — for a weekend, a week, a month, or a year, online or in-person.

NEW MODEL: A PERSONAL PORTFOLIO OF WORK

A world of rapid change means that our relationship with work is changing. We need a new model that helps workers to continually grow and develop, and to continually find new sources of opportunities for compensated work. When our relationship to work is binary (we either have a job or we don’t), we usually have predictable activities and earnings. But when rapidly-changing times means we have a fuzzier relationship with work — requiring multiple sources of income from a variety of activities — I call this a “Portfolio of Work.”

In the same way that an investor often has a “distributed portfolio” — some safe investments, some riskier investments — an important strategy for dealing with the uncertainty that can come with rapidly-changing times is to have a variety of work opportunities at any one time. Workers will have a range of activities they do to generate income and to perform the activities they enjoy.

In the past we called this “working at (fill in the number) jobs.” But the reduced friction for access to work, from errand-work like TaskRabbit to spot-driving like Uber — means that it’s far easier to add a new component to our work portfolios.

Of course, jobs as we know them will continue to exist for a long time. But for many people, there will be strong incentives to work in a different manner. Alternatives to traditional jobs have existed for years, but the incentives to use those alternatives are increasing. At any one point, you may be working…

• Full-time long-term
• Full-time temporary
• Part-time long-term
• Part-time temporary
• On call
• Project-based or piece work
• App-based (e.g. Uber)
• Asset based, sharing something you own (e.g. AirBnB)
• Selling and buying assets (e.g. eBay)
• Creating and selling wares (e.g. Etsy)
• Participating in a work co-op

… or several of the above, all at the same time.

Think of each of these as potential parts of your Portfolio of Work.

A Portfolio of Work is inevitable, and it’s already in practice by many workers. For those who thrive on variety and change, a Portfolio of Work is ideal: Life is varied, with a constant flow of new challenges. For those who thrive on stability and predictability, though, a Portfolio can mean stress and uncertainty.

The biggest question in the Era of Unbundled Work: Can a given worker continue to maintain or increase their lifestyle? If in aggregate the answer is yes, then we continue to have a growing economy. But if workers’ real wages continue to decline, then the economic impact is likely to be high. We need a concerted effort across a range of stakeholders — education, organizations, and government — to modify their traditional approaches so that work is more easily defined, created, found, and performed.

The same approach is true for learning. As a lifelong learner, you may also be investing your time in:

• Taking in-person courses.
• Taking online courses.
• Training experiences with one or more of the organizations you work with.
• A hobby, which may one day become compensated work for you.
• Leisure activities, such as travel or sports.

Together, these define your Portfolio of Learning, which will go hand-in-hand with your Portfolio of Work.

We need to recognize that Portfolios will be the new normal, and adapt everything from hiring practices to worker benefits in ways that will enable flexible work and learning.

NEW MODEL: TRUSTED REPUTATION

The process of rapidly connecting a worker and work opportunities requires reducing friction at a variety of points. One of the most important is the process of automating trust between worker and hirer. There are three important questions to be answered in the discussion between hirer and worker:

1. How can workers describe their knowledges and skills? Today we call this a Resume, and a LinkedIn profile.
2. How can the knowledges and skills needed for a work opportunity be consistently described? Today, we call this a Job Description.
3. How can the worker’s information be verified? Today, we call this a degree or certificate from a recognized school.

But the process we have today is tremendously inefficient. Job descriptions and resumes are orthogonal: They use different words for the same thing, and the same words for different things. Every time a hirer includes a new keyword in an online job description, workers immediately add those keywords to their resumes. It’s a metadata arms race.

As for verification, many employers treat degrees from recognized schools as verified, trustable credentials. But this can only be effective when the courses included in a particular degree exactly match the training needed for specific work, and where the degree is recent enough to be relevant — a situation that will occur less and less in a rapidly-changing world.

How can we change this process so that it works for everyone?

• A common language. Hirers and workers need to use the same language — explicit descriptions of what’s needed, and of what workers know and can do. The most valuable language is the language of skills and knowledges, nomenclature that’s been used in the career development field for more than haUnlf a century. It can’t be as brittle a language as the taxonomy used in the U.S. Government’s O*NET database, nor as loose a folksonomy as LinkedIn’s “skills” endorsement process. It needs to be a constantly-updated information space that remains continually relevant to workers and to hirers. For example, a startup called Forge has a “common app” that can be used for a range of employers.
• Digital identity and reputation. a trust mechanism whereby a worker’s knowledges, skills and experience can be codified and verified. Much like the Merit Badges that Girl Scouts and Boy Scouts can earn, Digital Badges recognize and reward incremental learning, experience, and accomplishments. They must be certifiable (by their issuer), verifiable (by co-workers and former hirers), and portable (to be used in a range of contexts). There are numerous badging initiatives around the world, including the EDUCAUSE Badging Program, but the most widely used is the Mozilla Foundation’s OpenBadges.org is an open, global badging initiative designed to make badges portable.

Source: CodeAcademy.com

Individual badges are important to recognize specific knowledges, skills, experiences, and accomplishments. But badges must also be “stackable,” organizable into larger groupings that recognize abilities in entire fields. (Think of today’s college degree as a stack of badges — that is, the courses and other experiences and accomplishments required to earn that degree.)

• Verification processes. Some knowledges and skills are eminently testable, such as writing software code, or doing math problems. Some are far more subjective, such as writing or synthesizing information. Badges associated with abilities that are highly testable will often be connected to the actual test results to which they’re linked. But subjectively-analyzed skills will need other methods of verification, including testimonials from former co-workers, hirers, clients, and partners. It’s likely that some form of digital trust will be used, such as credentials embedded in Blockchain technology, so that reputation remains highly portable.
• Rating Processes. Workers and hirers each have a perspective on how well or poorly each has performed in a work experience. eBay has an open rating system, so why shouldn’t workers and hirers? The answer is that it’s an extremely sensitive issue, on both sides of the equation. While services like Glassdoor offer some level of transparency for worker ratings of organizations, designing one that works for both workers and hirers is challenging, but will become an increasingly important function as an increasing amount of work becomes unbundled.

NEW MODEL: RESHAPING EMPLOYMENT

Organizational leaders make a series of choices related to the people the organization compensates for work. When they source, compensate, promote, demote, train, transfer, fire, or retire, one or more decision-makers is choosing a particular process or outcome that has a series of effects. The context for those decisions depends on a set of factors ranging from the specific steps that hiring managers are supposed to follow, to the top-level employment strategies of the organization. In an era of disruptive change, there aren’t just new rules for workers. Employers have a new set of rules, creating a new context for decision-making.

One of the most important decisions that hirers need to make is the way they define and distribute the work they need done.

• What work gets done by humans?
• What gets automated?
• How much will a worker get paid?
• Does the work have to be done in person, or can it be done remotely?
• If a lot of tasks get automated, what happens to existing workers? Do jobs go away, or are workers offered the opportunity to go create new value for the organization?

According to economist Jeff Sachs, “We should prepare for a workforce in which workers will change jobs with much greater frequency than in the past. In an age of disruptive technology, we should plan for disruption. Changing jobs should be regarded as normal; training and skill upgrading should be life long, and health care and other benefits should follow workers, not jobs.”

The result is an end-to-end redefinition of what an organization is. This will be the subject of a subsequent piece, “Unbundling the Organization,” but here are some of the underlying tenets.

• From a process perspective, Human problem-solving can be seen from the standpoint of friction. Bringing a new worker to solve problems on a team has a series of “frictions,” from the challenges of finding qualified workers, to the process of integrating the worker into the team, to the difficulties in moving workers efficiently around within the organization. For a variety of reasons, the old rules of work required a high level of friction. Organizations were typically constructed with “hard walls” — processes that made it difficult to hire, transfer, and promote. But in a rapidly-changing world, those traditional constructs need to be completely re-thought.
• From a values perspective, organizations will need to increasingly articulate and support the values of their workers, to increase their ability to recruit talent, as well as to establish stronger connections to their customers. Anchoring the organization in core values will also allow the organization to embrace constituents beyond their shareholders, such as workers, partners, customers, communities, and the planet. (More on the need for values-driven organizations in Unbundling the Middle Class.)

Here are some of the strategies for Unbundling the Organization:

Reducing the friction to hiring. This includes practices like:

• “Right-skilling” job requirements. An increasing number of job openings require a college degree. According to Wall St. Journal columnist Catherine Rampell in 2014, “Just 25 percent of people employed as insurance clerks have a BA, but twice that percentage of insurance-clerk job ads require one. Among executive secretaries and executive assistants, 19 percent of job-holders have degrees, but 65 percent of job postings mandate them.” While it’s understandable that a hiring manager would look for the best-educated worker for a position, that doesn’t mean the manager will get the most effective candidates. Hiring managers need to be encouraged to define worker requirements appropriately, and to be supported with a useful process for determining the best candidate from the available pool.
• Apprenticeships. Hirers need to provide opportunities for young and “other-skilled” workers to gain critical on-the-job experience. Programs such as the Global Apprenticeship Network encourage hirers to commit to apprenticeships as a way of rapidly increasing the number of trained workers in a profession.
• “Temp week” tryouts. Candidate workers work for one week performing the tasks they’ll be required to do in the long-term role. Weebly, a 300-person startup in San Francisco, does exactly that.

Reducing friction for who can work — embracing diversity. Since research consistently shows that diverse workgroups perform better, organizations will benefit from broadly inclusive practices that bring new perspectives into the organization, across a range of factors — including gender, age, educational background, ethnic background, and experience.

• Incentives for hiring managers. Beyond right-skilling requirements, managers need to be provided with the incentives to hire and promote workers who represent diversity.
• Treating diversity as a problem to be solved. Teams of workers are the ones who most benefit from diversity — so they should be the ones responsible for determining how to increase the diversity of their teams.
• Hiring from non-traditional sources. Employers increasingly need to seek workers with creative problem-solving skills they’ve learned from non-traditional environments. As John Seely Brown of Deloitte’s Center for the Edge has said, “I would rather hire a high-level World of Warcraft player than an MBA from Harvard.”

Reducing the friction for how we work.

• Reward practice over process. Deloitte’s John Hagel suggests that while many businesses prize their well-honed business processes, “as much as 60–70% of employee time in large, established enterprises is being spent on something called “exception handling” — an event that occurs that was not anticipated by the process and that the process policies and procedures cannot handle, so it gets handed off to an employee who has a short time (typically 24–48 hours) to resolve the exception.” It makes little sense to embed these problem-solving processes into software, or into established process. Instead, Hagel suggests that we might “focus instead on the practices that small, front line work groups use to improve their performance over time by learning faster on the job.”
• Design jobs based on the problems to be solved. Since workers are problem-solvers, the work they do needs to be centered around the challenges that need to be overcome.
• Treat teams as groups of problem-solvers. A team is a pool of skills, and their goal is to solve a pool of problems. The more that a team is made responsible for a set of problems to be solved — rather than telling them how to solve the problems — the more adaptive and agile they will each be as individuals.
• Reduce the friction to changing jobs within the organization. When one manager loses a worker, another manager gains. The organization benefits in aggregate. And the more that worker mobility is encouraged, the more that workers can “self-optimize” — finding the work that best contributes to the organization.
• Rethink the role of the manager. The role of a manager needs to transition from requiring a group leader with answers, to someone who can help a team of problem-solvers to continually solve a pool of problems. (If you want to see a radically open approach, check out Valve Software’s Handbook for New Employees — which details what it’s like to work in a manager-less organization.)

Reducing friction for when and where we work.

• Flexible hours. As work becomes increasingly unbundled, why should it matter when work is performed? The more flexible an approach we can take toward worker hours, the more we can include workers with family and other needs — who are typically the least-paid workers with few alternatives.
• Sabbaticals and unpaid leave. Studies show that workers return with renewed engagement — especially if they’ve been given the opportunity to do good works.
• Outsource tasks — to rural areas in the U.S. To help rural areas to remain economically viable, hirers need to do everything possible to distribute work to rural workers. As more and more youth move to urban areas, rural areas will become the province of an older workforce, many of whom will be the least likely to be able to adapt to the new rules of work. Distributing work to rural areas will allow these communities to increase their average wages, yet still provide hirers with lower-wage workers compared to urban pay.
• Outsource tasks — to impacted communities overseas. Part of the organization’s “portfolio of workers” can include communities in developing economies. Companies like Samasource make this process easier by taking on the burden of distributing the tasks, and ensuring that the revenue helps to increase the economic viability of remote communities.

Rethinking who or what does the work, and how.

• Technology can be used to augment worker abilities, rather than simply replacing them. Hirers can make decisions that ensure automation will amplify worker skills, and the resulting capabilities will both encourage adaptive workers, and provide competitive advantage to organizations.

NEW MODEL: RETHINKING “THE PERIOD FORMERLY KNOWN AS RETIREMENT”

We are living and working longer, and many of us will live and work far longer than our parents and grandparents. The “period formerly known as retirement,” as I call it, needs to be completely re-thought. Important elements include:

• A new approach to savings. As of mid 2015, the Government Accounting Office said that workers aged 65–74 had median savings of less than $150,000 — barely enough to pay for a few years of living in a high-cost city. In early 2016, the Center for Retirement Research said that about half of all American workers hadn’t saved enough for retirement. And many of those who believed their housing investment would serve as a nest egg received a wakeup call during the Great Recession, as the value of their homes descended dramatically, and in many cases have not yet returned to pre-recession values — if the owners were able to hold onto their houses at all. We need to educate people of all ages about the value of creating financial resources that allow us to achieve our goals — including reducing the amount of compensated work we’ll need at various points in our lives, not just when we’re older.
• Portfolios of Activity. Rather than thinking of it as the period of our lives where we’re done with the “boxes” of education and work, we will have portfolios of activity, just as we did earlier in our lives. But we’re likely to have more flexibility and extensive experience, so we’re far more likely to be teaching and mentoring younger workers as part of those activities.
• Ways to leverage elder expertise. Older workers will often have greater flexibility for when, how, and where they work, and for how much. Just as the gig economy is enabling younger workers greater access to various kinds of work, we need two-way online markets that increase access to that expertise.

NEW MODEL: RETHINKING THE PURPOSE OF THE ORGANIZATION

In 2008, our group served as co-founders of an initiative known as SoCap, Social Capital Markets, with the goal of helping entrepreneurs and investors to form and transform into businesses with purpose — what today is called social entrepreneurism, impact investing, and benefit corporations. Our premise: Since for-profit business is the single largest source of economic activity in our economy, changing the motivations of corporations will have far greater impact than the combination of non-profits and foundations.

Our group also served as executive producers in late 2016 for a conference called Closing The Gap, in partnership with The Greene Institute. Speakers like Robert Reich, Tony Blair, Tom Friedman, Nouriel Roubini, Niall Ferguson, Dan Ariely, and a range of other thinkers talked about the dynamics of inequality baked into our specific form of capitalism. As many of our catalysts detailed onstage, if the sole purpose of a corporation is to benefit shareholders, there is little that can be done to reverse the tide of inequality, or to increase economic mobility. Only by increasing the stakeholders of corporations to include employees, customers, partners, communities, and/or the planet will there be economic incentives for corporations to change their decision-making for choosing human tasks over automation. Some of these decisions include:

• Make workers stakeholders. Distribute ownership in the organization generously, so that workers benefit from the increased value of the organization.
• Take responsibility for training. Organizations need to become more responsive to the needs of workers — if they want to have a trained, adaptive workforce. According to the Economist, on-the-job-training “…has fallen by roughly half in the past two decades.” Hirers need to see the value of supporting workers dedicated to lifelong learning. Even though highly-mobile workers may move on to other hirers, in aggregate all hirers will benefit from a trained pool of workers.
• Take responsibility for “negative externalities.” While considering taxing robot owners for displaced workers may be an over-reach, it’s important to start linking negative effects (which technologists tend to ignore) with the societal costs that those technologies incur. If the self-driving trucks of companies like Uber are going to impact the work of 3.5 million truck drivers, they need to be part of the solution — if only so they’ll have the trained workers they need for the rollout and maintenance of the new technology.
• Codify the full cost of automation. Cost savings due to automation aren’t isolated to the comparison of tech purchase+operations versus human wages: There are other “externalities” that can be included in the calculus, such as the loss of future workers, economic loss to communities and damage to the corporate brand. Corporate decision-makers need to have the tools that let them see these “all-in” costs, measured over a long timeframe, so they can make decisions that fully benefit all corporate stakeholders, not just shareholders.
• Learn that impact brands draw impact-focused customers and employees. Young workers are continually drawn to vendors and hirers dedicated to specific values. As companies like Companies like Warby Parker and Tom’s Shoes have found, organizations increasingly find that it’s possible to do well and to do good — and to have a competitive advantage by doing so.
• Design new forms of organizations. If the purpose of an organization is to make a happy customer, then radically new organizational forms will arise as technology and globalization enable resources to be rapidly aggregated around new customer needs. Examples today include crowd-funded startups, work clouds, and blockchain-fueled dynamic organizations like Ethereum. Tomorrow, we’ll see approaches like skills banks, global work co-ops, and nano-trained teams.

Sidebar: Jobs & Identity vs. Work & Lifestyle

As we detailed in the conference that Charrette LLC co-produced in December 2016, Closing The Gap,we live in a time when the gap between the better-paid and the less-paid is dramatically widening. As work is becoming unbundled, entire job categories are beginning to evaporate, and the old rules of work no longer apply.

Part of the Big Shift (as John Hagel likes to call it) in moving from a Job Market to a Work Market is a change in identity. Dick Bolles of What Color Is Your Parachute? Is fond of saying that one of the biggest challenges for people undergoing career change is an identity shift. You’re no longer a steelworker or a lawyer; you’re “a person who” — works at a steel mill, or advises legal clients. Locking your identity into a job you can no longer perform is guaranteed to affect your feelings of self-worth, and makes it much more difficult to rebuild your identity around a new form of work. Removing that identity anchor can help to soften the impact of career change.

Of course, entrepreneurs in Silicon Valley will scratch their heads and wonder what the problem is. Logically, if you can perform a series of projects, and maintain a similar lifestyle to the one you’d have if you worked at a full-time job, why wouldn’t you do that?

But to someone who has worked in a steel mill or advised legal clients for decades, that’s easier said than done. As David Nordfors of i4j (Innovation for Jobs) likes to point out, a job has a unique meaning to many workers. What does it matter if your flat-screen TV is cheap, or you can drive a slightly better car than before? For someone with a more traditional trade or college background, if you’re not doing the work you were trained for, it’s completely understandable why you might find yourself in the depths of depression.

Part of the challenge we need to collectively solve is to remove the societal and perceptual stigma around the Big Shift from jobs to work.That’s a tall order. But it’s critical if we’re going to have an adaptive workforce that can more easily shift from one kind of work to the next — because that’s increasingly what we’ll all be doing.

-gB

NEW MODEL: DYNAMIC POLICY FOR AN ADAPTIVE ECONOMY

We have very little policy today designed for an adaptive workforce. We need the combination of support for individual workers, and incentives for hirers to change their policies to support an increasingly-mobile workforce.

• Change the way we report on employment, and the ways that money is connected to reporting. Most of the metrics we use to assess the ongoing health of the work-related portion of our economy is tied to jobs. Since anywhere from half to two thirds of the U.S. economy comes from consumer spending, high employment rates can directly contribute to economic growth. The federal government ties much of its social spending to the prevailing unemployment rate (as inaccurate as it is), using a binary “employed or unemployed” metric. We need more nuanced metrics that reflect the complexities of unbundled work.
• At the state level, revise certificate requirements to allow more workers to enter hot markets faster. As the Economist points out, the state of Tennessee requires 300 hours’ practice to become a hair washer in a hairdressing salon — but becoming an emergency medical technician takes far less. Regulations that inevitably keep workers from entering existing fields need to stop being barriers, and instead to involve rapidly-trained workers.
• Create individual learning accounts.Singapore gives everyone over the age of 25 several hundred dollars to spend on courses from hundreds of approved providers. We can provide even greater support, perhaps through tax benefits to corporations, and by supporting the organizations that provide online and in-person education.
• Don’t just retrain: Prepare adaptive workers. In the past, the federal government has attempted to deal with large-scale shifts in the work market by re-training, with programs like JTPA and CETA. But the government no longer has any reliable way to project future workforce needs. Instead, it needs to provide the training and tools for workers to become more adaptive, such as teaching self-inventory, entrepreneurism, and core skills for the use of technology.
• Portable benefits. As economist Jeff Sachs has said, In the past, benefits followed the job: In the future, they must follow the worker. For example, less than 1 in 5 Americans between age 45 and 65 have saved more than $200,000 for retirement (which probably means, no retirement). We need more ways that workers can save, starting very early in life. Aspen Institute has posted a July 2016 report with a number of recommendations to help start experimentation on mobile benefits.
• Incentives for outsourcing tasks — to rural America. Make hirers less likely to send tasks overseas by providing economic incentives that reduce the delta between local and foreign wages.
• Compensation for beneficial work. There is a huge amount of work to be done that contributes to our economies and our societies. We just haven’t figured out how to pay for it yet. Our communities need to deal with issues like homelessness, inequality, discrimination, lack of early childhood education, food deserts, vanishing parks, traffic overload, waste management, addiction, mental illness, aging infrastructure… The list is functionally endless. The more ways we can think of providing compensation for work that benefits communities, the more we can benefit from the energies of displaced workers.

Sidebar: The Nuclear Option for Policy: A Universal Basic Income

Some who are deeply concerned about the risks of a Job-Less Future believe that the situation will be so dire — with a huge portion of the population unable to find enough work for a basic lifestyle — that we need to consider a guaranteed government stipend for all. This is often called a Universal Basic Income (UBI), and usually includes a plan for a set amount that every citizen receives. Since anyone in a strong economy and society should have access to reliable housing, food, and education, UBI is intended to serve as a baseline safety net that could potentially mitigate some of the risks of a Job-Less Future.

The best overview I’ve seen comes from Gerald Huff, a Silicon Valley engineer; you can see his overview here. Futurist Guy Standing makes an impassioned case for it here. And there’s an entire Reddit thread on UBI.

The idea of a UBI tends to gain interest both by conservative and progressive thinkers. Progressive advocates like it because it provides a universal safety net that fills in many of the gaping holes in today’s social services, while conservate thinkers like the idea of consolidating most existing government-funded safety-net programs into a single amount — and potentially costing little more than the sum total of those programs. Experiments are occurring all over the world, from Canada to Namibia.

UBI is frequently discussed in Silicon Valley, because it looks like an engineering approach to a social problem. And that’s my biggest concern.

There are excellent programs that give money directly to people, like the Family Independence Initiative. But at, say, $10,000 per year, UBI alone would rarely be sufficient to provide all of a family’s basic needs. So, if instituting a UBI mean that we would avoid large-scale solutions to impacted populations, then it’s a bad idea. But if it’s a component of an integrated program that helps people to thrive in disruptive times, then we need plenty of experimentation to determine how it could help the most — while still encouraging workers to learn new skills so they can perform meaningful work.

There is much we need to do, in reshaping our institutions of work and learning, and I’m concerned that adopting a UBI would be seen as sufficient — and could potentially keep us from making some of the big decisions we need to make in adapting our institutions to an era of constant change. It’s a critical piece of the puzzle, but it’s not a complete answer, and shouldn’t be used as an excuse to sweep an entire generation of displaced workers under the rug.

gB

Epilog: There Is Much Work to Be Done

We need to create the kinds of programs and collaboration that will do the following:

• Research & Publishing. We need clear, constantly-updated data that accurately defines the current state of knowledge about the ways in which work and education are being affected by disruption, especially for particular constituent groups. And we need publishing vehicles to continually educate and inform a wide variety of constituents about the best strategies.
• Strategies. Various populations, organizations and economies will be affected by disruptive technologies in different ways. We need to develop and share strategies that can be effective in a variety of different contexts.
• Convenings. Decision-makers, change agents, sources of capital, and affected populations all need to be brought together to collaborate on developing a shared understanding of the risks and opportunities, and to develop and execute strategies designed to meet the needs of the broad range of stakeholders.
• Innovation. We need startups and initiatives that will focus on new disruption-driven opportunities and scaled solutions, as well as ways to amplify existing innovations.

People should become involved because they think it’s the right thing to do, or because they fear the onset of revolution. Either should be sufficient motivation.

• Curriculum. Individual workers, managers, strategists, and other constituents need learning opportunities to help them to become more adaptive.
• Investment. We need to channel capital that can be used to support innovation initiatives focused on lifelong adaptive work & learning.
• Policy. We need policy recommendations and supporting data on an ongoing basis to help policymakers to craft intelligent regulations at the local, state and federal levels.

Work, Re-Bundled

We have a tremendous opportunity to pro-actively anticipate the inevitable impacts of automation and globalization, and to turn their “negative externalities” into new opportunities to help create an adaptive and agile workforce that will be continuously able to adapt to exponential change.

You can stay informed on these issues by:

• Add yourself to Charrette’s Fulcrum Series email mailing list, which provides a weekly digest.
• Subscribe to medium.com/@gbolles for subsequent articles in the Unbundling series.
• Watch for Fulcrum articles published by Techonomy.
• Check out eParachute and JobHuntersBible for posts related to personal career change.
• Follow the Technological Unemployment thread on Google+.
• Joining i4j, a global consortium of individuals focused on innovation for jobs.
• Watch for articles on disruptive change at the Singularity University hub.

But let’s continue to be intelligent consumers of our media. Watch to understand, for example, if a news report is talking about automating tasks versus jobs. (Both are conflated in this report.) And let’s be sure that we don’t just talk about the problem domain: We all need to be part of the solution.

-gB

Gary A. Bolles, Partner, Charrette LLC; Co-founder, eParachute.com; Steering Committee Member, People Centered Internet

The perspective included here comes in part from a 40+-year history with What Color Is Your Parachute?, the enduring manual for job-hunters and career changers. (I was trained as a career counselor at the age of 19 by the author of Parachute, who is one of my business partners in eParachute.com — and, as you may have guessed, my father.) For decades, Parachute has defined the most effective strategies for helping individuals to connect to meaningful work, and that bias toward the needs of the individual is admittedly present in this document, as well.

Thanks to Dick Bolles, John Hagel, Vint Cerf, Peter Sims, David Nordfors, Parag Khanna, and Heidi Kleinmaus for their contributions to the thinking here.