There’s a meme going round Silicon Valley that there are programmers with 10x the productivity and impact of an ordinary programmer. I don’t doubt it. Sports show us the extraordinary impact that a superstar can have on the success of a team. As my friend Bob Poole used to say whenever we watched an NBA Finals series, “The team with the most superstars wins.”
But there’s a key word there, and it’s not “superstar.” It’s “team.” The TEAM with the most superstars wins.
Success in today’s world, whether of sports or business, requires assembling a team of people who can work together to achieve something extraordinary. And yes, to achieve something extraordinary, it helps that some of those people be superstars. But here’s another lesson from sports, the best players “make their teammates better.” Selfish superstars rarely win.
All of this is by way of introducing the role of talent in the Next:Economy.
Superstar vs. team
Here are some of the unfortunate changes in business that have resulted from focusing only on the superstar while ignoring the team:
- Companies have made a deliberate choice to reward their “superstars” incredibly well, while treating ordinary workers as a cost to be minimized or cut. Top US CEOs now earn 373x as much as the average worker, up from 42x in 1980.
- The bonds of loyalty that once tied companies and their workers have frayed or have been deliberately broken. Long gone, for most companies, are the days when individuals spent most of their career working for the same company, ascending the career ladder till they found a comfortable rung on which to work for the rest of their lives.
- Outsourcing is the new corporate norm. That goes way beyond offshoring to low-wage countries. Right here in the United States, tons of companies are getting away with paying workers less and providing fewer benefits. Think your hotel housekeeper works for Hyatt or Westin? Chances are good they work for Hospitality Staffing Solutions. Think those Amazon warehouse workers who pack your holiday gifts work for Amazon? Think again. It’s likely Integrity Staffing Solutions.
- Technology has been harnessed not to empower workers, but to make them cogs in a tightly controlled machine. (This is the subject of Esther Kaplan’s brilliant expose, The Spy Who Fired Me.)
It doesn’t have to be that way.
In his book Work Rules, Laszlo Bock, Google’s SVP of People Operations, starts out by comparing Google to Wegmans Supermarkets. Google is one of the most successful high-tech companies in the world, with an average 30 percent profit margin. Wegmans is a 99-year-old, family-run, supermarket chain of 84 stores in the Northeast United States with a one percent profit margin. Yet Wegmans has been on the Fortune “Best Places to Work” list seventeen times. Google has topped the list 6 times.
Both, says Bock, are “high freedom” environments, where employees are given a great deal of discretion to “do the right thing” for customers, and where the company seeks to do the right thing for employees.
MIT’s Zeynep Ton, author of The Good Jobs Strategy, comes to similar conclusions. She writes:
“Many people in the business world assume that bad jobs are necessary to keep costs down and prices low. But I give this approach a name — the bad jobs strategy — to emphasize that it is not a necessity, it is a choice.
“There are companies in business today that have made a different choice, which I call the good jobs strategy. These companies provide jobs with decent pay, decent benefits, and stable work schedules. But more than that, these companies design jobs so that their employees can perform well and find meaning and dignity in their work. These companies — despite spending much more on labor than their competitors do in order to have a well-paid, well-trained, well-motivated workforce — enjoy great success. Some are even spending all that extra money on labor while competing to offer the lowest prices — and they pull it off with excellent profits and growth.”
Tools to manage a high freedom workplace
In their books, Bock and Ton describe the management style of companies that want to employ high-freedom, good jobs management. I highly recommend both of these books, along with some published by my own company, like Beautiful Teams, by Andrew Stellman and Jennifer Green, andThinking in Promises, by Mark Burgess.
But increasingly, there are also software tools that support high-freedom environments. Collaborative ideation tools like Trello, shared document editing with Google Docs or Microsoft Office 360, and real time conferencing environments like Google Hangouts or Skype have all contributed to the ability of companies to build distributed teams that can come together to solve a problem or work on a time-limited project, and then be reformed to tackle something else.
Slack is the latest (and one of the most promising) of the tools for self-managed ad-hoc teams. It is a real-time communication tool that allows teams to self-organize around any project. Its website proudly claims that “We’re on a mission to make your working life simpler, more pleasant, andmore productive.” And it backs it up with data from a survey of 1,100 teams using Slack: “A 25.1% reduction in meetings. A 48.6% reduction in internal email. 80.4% increase in team transparency. A 32% increase in team productivity.”
Stewart Butterfield, the co-founder and CEO of Slack, says:
“What we are selling is corporate transformation… None of the work we are doing to develop the product is an end in itself; it all must be squarely aimed at the larger purpose. Consider the teams you see in action at great restaurants, and the totality of their effort: the room, the vibe, the timing, the presentation, the attention, the anticipation of your needs (and, of course, the food itself); nothing can be off. There is a great nobility in being of service to others, and well-run restaurants (or hotels, or software companies) serve with a quality that is measured by its attention to detail. This is a perfect model for us to emulate. Ensuring that the pieces all come together is not someone else’s job. It is your job, no matter what your title is and no matter what role you play. The pursuit of that purpose should permeate everything we do.”
That’s a great vision of what it means to be a team!
“The best — maybe the only? — real, direct measure of “innovation” is change in human behaviour. In fact, it is useful to take this way of thinking as definitional: innovation is the sum of change across the whole system, not a thing which causes a change in how people behave. No small innovation ever caused a large shift in how people spend their time and no large one has ever failed to do so.”— Stewart Butterfield, Slack
In addition to understanding the importance of teams, Next:Economy companies understand that they must use technology to augment their workers, not just to replace them. In addition to general purpose tools, like those outlined above, they focus on tools and training that are specific to their industry.
In a conversation this past spring with Buzzfeed founder and CEO Jonah Peretti, I asked him why he chose to use employees rather than the outsourced content model that has increasingly been used by his peers in the media business. Jonah made a compelling case that he can outperform the market by carefully selecting employees, training them, empowering them with data, and building tools that let them work more effectively together.
Andrew Gauthier, executive producer of BuzzFeed Video, notes:
“Data influences every stage of production. In the pre-production stage, we’re very conscious of existing conversations on the Internet, about topics or identities or certain styles that appear to be resonating with people. Everybody that works here lives on the Internet, so it’s this very natural thing to say, “Oh, I’ve noticed that a lot of my friends are posting this type of thing on Facebook.” We’ll talk about why certain things went viral, then we’ll incorporate that into a larger conversation.
“And after a video is released?”
“We pay close attention to how viewers are interacting with our videos. We look at share stats on Facebook, comments on YouTube and BuzzFeed.com, and through those metrics, we will learn about what types of things in the video resonated with viewers, and also how viewers use the video to interact with their friends — whether they share on Facebook or Twitter or elsewhere.”
Jonah told me that the secret to Buzzfeed’s success is taking this learning, and spreading it through the organization, then empowering their producers, and getting out of the way.
I find Buzzfeed fascinating because they have found a way to benefit from Next:Economy media platforms like YouTube and Facebook that are designed for individuals to participate, but that can be used even more effectively by a business. The insights and the experience of the best performers can be deployed at scale by their co-workers, leveling up the entire organization. Buzzfeed had revenues of over $100 million in 2014 by recognizing how to put together high-performing teams empowered with data and 21st century collaboration tools and turning them loose.
Marketplaces and teams
It is worth revisiting the comparison between traditional, tightly-managed and tightly-scheduled low-wage work and the approach of on-demand platform companies like Uber, Lyft, Instacart, and TaskRabbit that I discussed in Workers in a World of Continuous Partial Employment. These firms offer an improvement over the outsourcing trend because they give more autonomy and control over earnings to workers. Workers have the freedom to choose their own schedule, and can work as much or as little as they like. This is an important step towards the “high freedom” environment that Laszlo Bock explains is so important for productivity.
But we’re not at the end point of the evolution of these platforms. The marketplace algorithms that drive these kinds of companies are a real innovation in corporate organization, and need to be understood and improved further. But they often still seem to accept the feudal system that our corporate world has come to resemble, with a privileged class of well-paid aristocrats as employees at the center of the platform, and another class of undervalued serfs acting as subcontractors (what I’ve called “the franchise of one”) providing actual services to end users .
There are glimmers, though, of an understanding that these workers are not all alike, and that companies must make a commitment to them, even if that commitment doesn’t resemble the old pledge of lifetime employment.
In a recent conversation with Leah Busque, co-founder and CEO of Taskrabbit, she noted: “Our job is to build tools that help increase the income of our workers.”
This same renewed focus on the worker can be seen in the way that the competition between Uber and Lyft is increasingly not for passengers, who are flocking to both services, but for workers. Which of these companies wins in the marketplace may end up not being driven by technology but by which company provides the most compelling environment and wages for workers, who are ultimately the ones delivering the service that the technology only enables. And as Zeynep Ton makes clear, it takes happy workers to deliver outstanding service.
Unfortunately, the toxic legal environment in which these firms operate makes it more difficult for them to take the necessary next steps to focus on training or other improvements for their on-demand workers. The distinction between employees and subcontractors doesn’t really make sense in the on-demand model, which requires subcontractor-like freedoms to workers who come and go at their own option, and where employee-based overtime rules would prohibit workers from maximizing their income. (It’s clear that we need a new worker classification, and a portable benefits approach that lets multiple employers contribute to a benefits system that is centered on the employee, not the job. We’ll be talking about both of these topics at the Next:Economy Summit a few weeks from now.)
However, there are some very interesting ways that platforms can embed training and income improvement opportunities into the platform itself.
Upwork, which many might think of simply as an online platform for outsourcing work to the lowest-cost workers, may have the deepest insights into solving this problem. In a conversation with Stephane Kasriel, the CEO of Upwork, a few months ago, he told me how he thinks about solving the different challenges for various classes of workers on the platform. There are three kinds of workers on Upwork:
- Those who already have marketable skills, good reputations on the platform, and are getting all the work they need because they are “in the flow.” The platform doesn’t need to do much to help these people.
- Workers who have marketable skills but have not yet built a reputation and are not getting enough work. A lot of the focus of Upwork’s data science team is to find these people, and point them to the right open jobs. The challenge here is not just helping them find a perfect match with the work they have the skills for; often it is pointing them to new areas where there is not enough supply, where some study or retraining will let them get a foothold in the virtuous circle of reputation and recommendation. For example, he pointed out that a few years ago, there were plenty of Java developers, but not enough Android developers, and the best way for people in this second group to get traction in the system (and better pay, since Android was paying more than Java) was to gain new skills. Today, there aren’t enough workers with data science skills, and there’s a pay premium to be had there.
- Workers who don’t have the right skills for the jobs that they are applying for. Here, the right thing to do is sometimes to discourage people from applying for these jobs that they aren’t going to get. This wastes the time not only of employers but of the workers themselves. “The time they spend applying for the wrong jobs is time they could spend working.”
Upwork has developed its own skills assessment system, and Stephane told me that the company does 100,000 hours of assessment a month! Stephane also makes the point that if you want to understand how to study the dynamics of job marketplaces, there is no better place to do it than on Upwork, because the “velocity of jobs” is so high. What’s so fascinating about Upwork’s assessment system is that it is immediately verifiable, because someone either is able to do a job to the satisfaction of the customer, or they aren’t. This is in stark contrast to many of the assessment tools sold by education companies, which provide paper certifications but little evidence that workers with those certifications can actually do the job.
There’s a lot of talk today about online talent platforms and their role in increasing job market liquidity, and there is still a lot to learn. James Manyika and Michael Spence write:
Much of the impact of online talent platforms stems from the use of technology to bridge information asymmetries that impair labor-market performance. In the past, these gaps were only partly bridged by signals carrying useful information. But online talent platforms aggregate much larger amounts of information efficiently, increasing the “signal density.”
With expanded data, companies can use predictive analytics to identify the best candidate for a given role. Job seekers can augment their educational credentials and employment histories with samples of their work and endorsements from co-workers and customers, thereby conveying their potential value to employers more effectively.
Furthermore, platforms that aggregate anonymous reviews from current and former employees give individuals a better idea of what it is like to work for a given company, as well as the salary they can and should expect. As employee satisfaction becomes more widely reported, companies are facing pressure to ensure good working conditions in order to recruit the talent they need.
So far, the biggest winners from this shift have been educated and skilled professionals in the advanced economies. In fact, the most sought-after engineers and software developers may not need to apply for jobs at all; companies are now increasingly recruiting “passive” candidates, sometimes forcing employers to increase the salaries of workers they want to retain.
But it is not all good news. Now that employers have new tools for recruitment and assessment, they may find low-skilled workers easier to replace, potentially worsening income inequality in the short run. In the longer term, however, a better overall system for skills upgrading could be designed — one that could be integral to facilitating upward mobility.
And there is another benefit in this regard. As the career outcomes associated with specific institutions and degree programs become more transparent, education and training providers will become more accountable for preparing their students for prosperous and productive lives.
All of these points suggest that we may be reaching a tipping point where we escape the shackles of the superstar syndrome, and instead rediscover how to enable teams, finding people’s strengths and matching them with opportunity, building tools that make it easier and more effective to work together, and creating dynamic labor marketplaces in which on-demand, “high freedom,” and the “high velocity” of work go hand in hand.
It all starts, though, with a different mental model of the relationship between company (or platform) and its workers.
“The employer-employee relationship is broken, and managers face a seemingly impossible dilemma: the old model of guaranteed long-term employment no longer works in a business environment defined by continuous change, but neither does a system in which every employee acts like a free agent.
The solution? Stop thinking of employees as either family or as free agents. Think of them instead as allies.”
Esther Kaplan, Laszlo Bock, Zeynep Ton, Stewart Butterfield, Leah Busque, Stephane Kasriel, James Manyika, and Reid Hoffman are all speakers at the Next:Economy Summit, Nov 12–13 in San Francisco. We are learning together how to build companies where great performance and great jobs go together.
Editor’s note: this post was first published on Medium. It is republished here with permission.