The term “gig economy” was coined by former ‘New Yorker’ editor Tina Brown back in 2009. It was used to describe how workers in the knowledge economy were increasingly pursuing “free-floating projects, consultancies, and part-time bits and pieces while they transacted in a digital marketplace.”
The wisdom of the time was that the gig economy would completely change white-collar jobs and call into question the very existence of professional service firms: Why would anyone hire a data analytics firm for a project when you could have unrestricted access to a bunch of experts, connected by a digital platform from all around the globe, who could work together for your company? Given the freshness of the idea, it certainly looked like things were headed that way: the Netflix million-dollar challenge back in 2009 for creating and developing the best recommendation algorithm was won by a team that didn’t belong to a company — or even geography.
In the 1960s, Jack Nilles, a physicist who turned into an engineer, built a long-range communications system at the U.S. Air Force’s Aerial Reconnaissance Laboratory. Later on in his career, at NASA, he helped design space probes that could send messages back to Earth. In the early 1970s, as the director for interdisciplinary research at the University of Southern California, he became fascinated by a more terrestrial problem: traffic congestion. Unrestricted growth in urban areas and cheap gas were creating incredible traffic jams; more and more people were commuting into the same city centres. In October 1973, the OPEC oil embargo began, and gas prices quadrupled. America’s car-based work culture seemed suddenly unsustainable.
That year, Nilles published a book, “The Telecommunications-Transportation Tradeoff,” in which he and his co-authors argued that the congestion problem was actually a communications problem. The PC hadn’t been invented yet, and there was no easy way to relocate work into the home. But Nilles imagined a system that could ease the traffic crisis: if companies built small satellite offices in city peripheries, then employees could commute to many different, closer locations, perhaps on foot or by bicycle. A system of human messengers and mainframe computers could keep these distributed operations synchronised, replicating the communication that goes on within a single, shared office building. Nilles coined the term “telework” to describe this possible arrangement.
However, nowadays remote work is the exception rather than the norm. Flexible work arrangements tend to be seen as a perk; a 2018 survey found that only around three per cent of American employees worked from home more than half of the time. And yet the technological infrastructure designed for telecommuting hasn’t gone away. It’s what enables employees to answer e-mails on the subway or draft pre-dawn memos in their kitchens. Jack Nilles dreamed of remote work replacing office work, but the plan backfired: using advanced telecommunications technologies, we now work from home while also commuting. We work everywhere.
As spring gives way to summer, and we enter the uncertain second phase of the coronavirus pandemic, it’s unclear when, or whether, knowledge workers will return to their offices. Citigroup recently told its employees to expect a slow transition out of lockdown, with many employees staying out of the office until next year. Jack Dorsey, the C.E.O. of Twitter, went even further, announcing in an e-mail that those whose jobs didn’t require a physical presence would be allowed to work from home indefinitely. In a press statement, Twitter’s head of H.R. said that the company would “never probably be the same,” adding, “I do think we won’t go back.”
According to Peter Miscovich, Managing Director, Strategy + Innovation, JLL Consulting in New York, by 2020 gig workers will comprise half the workforce, and as much as 80% by 2030. In the very near future, says Miscovich, enterprise “Liquid Workforce” platforms will be based upon the emerging “Hollywood Model” of working where agile and “liquid” knowledge workers will be intelligently organized via the Internet on a project basis much like Hollywood movies are made today. The future Liquid Workforce will be organized via crowdsourced “uber-like” cloud-based work platforms providing greater workforce and workplace efficiency.
At some point, the pandemic and its aftershocks will fade. It will once again be safe to ride commuter trains to office buildings. What then? Many companies seem amenable to the idea of lasting changes. In April, a survey of chief financial officers conducted by the research firm Gartner found that three-quarters planned to increase the number of employees working remotely on a permanent basis. From an economic perspective, companies have a lot to gain from remote work: office space is expensive, and talent is likely to be cheaper outside of the biggest cities. Many workers will welcome these changes: in a recent Gallup poll, nearly sixty per cent of respondents said that they would like to keep working remotely after restrictions on businesses and schools have been lifted. For them, the long-promised benefits of work-from-home—a flexible, commute-free life, with more family and leisure time—have finally arrived.
And yet remote work is complex, and is no cure-all. Some of the issues that have plagued it for decades are unlikely to be resolved, no matter how many innovations we introduce: there’s probably no way for workplaces to Zoom themselves to the same levels of closeness and cohesion generated in a shared office; mentorship, decision-making, and leadership may simply be harder from a distance. There is also something dystopian about a future in which white-collar workers luxuriate in isolation while everyone else commutes to the crowded places. For others, meanwhile, isolation is the opposite of luxury. There may be many people who will always prefer to work from work.
But Brown turned out to be only half right. There has been tremendous growth in the gig economy, but most of it can be attributed to unskilled work such as driving (Lyft and Uber), delivering (food, parcels, etc. through DoorDash, Postmates), and doing simple errands (TaskRabbit). A vibrant gig economy for knowledge workers — engineers, consultants, management executives — has not really materialised.
Gig workers in the knowledge economy will have to work with and for firms that have pronounced values, incentives, practices, and preferences. But they do not assimilate easily into these organizations (unless they join them) as they often work at arms-length with them and are seen by people in the organizations as outsiders — or even threats —impeding effective cooperation and creating the potential for conflict. In this context, gig workers often struggle to understand, let alone accept, the larger organizational processes, people, and politics of many of the people they have to work with. Performance assessment may also be problematic, especially if the gig worker is hired by a firm to do a job that the traditional metrics of most organizations still cannot properly capture.
When you start listing these problems, it becomes less of a mystery why the firms still prefer to hire knowledge workers as full-time employees or other firms with knowledge workers rather than contract directly with gig workers, despite the ability of tech to reduce many of the more obvious costs.
This may, at last, be about to change. But not from the advent of any new technology — it’s from the global pandemic that is forcing the global economy to its knees. The organizational factors that act as barriers for knowledge-based gig work are the same ones that in the past have inhibited remote work by full-time employees. If these issues can be resolved, whether a remote worker is full-time or gig-based is simply a matter of contractual documentation. Clearly, the experience of working during the pandemic provides useful insights on how to successfully contract knowledge work to external contractors. But we need to approach these lessons carefully.
Tasks Are Vital
Knowledge work is not uniform and, to the extent that you can even talk this way, a given “unit” of knowledge work is itself highly complex. A university, for example, educates students for degrees. A unit, therefore, could be the degree that a student comes out with. But a lot of very different tasks go into creating that unit. So what does “gigification” mean in this context?
Universities could certainly consider using gig workers for graders, teaching assistants, or for pre-recorded online lectures. But it is unlikely that the majority of milestone classes (face-to-face or virtual) that need to be delivered live at specific moments will be delivered by gig workers. Since any degree will inevitably involve both kinds of classes, university teaching will always be hybrid between the two, at least at the course level, possibly even at the class level.
The lesson is that all knowledge-based work can be unpacked into a set of different tasks. To figure out the future of the gig economy for knowledge workers, therefore, we need to analyse things at the task level rather than at the work level. We have found the simple process chart shown below to be extremely useful in figuring out which kinds of tasks are amenable to gigification. It involves asking these three basic questions about each knowledge-intensive task involved in delivering a product or service.
The Covid-19 epidemic could well prove to be a pivotal point in the gigification of knowledge work, and many firms will be attracted by the prospects of the direct and indirect cost savings that the gig economy model seems to offer. But given the complexities of knowledge work there’s also a risk of overreach and wasted investment. The simple task-based categorization we propose will help managers make smarter choices about how just what tasks should be contracted to gig workers.
Given our current situation knowing that your colleagues or employees are best suited for this new scenario we find ourselves in. Finding the right talent, the best fit for the job and your organisation can be a very challenging task. It is now important to find out whether your managers or your team is well-equipped of working together from various locations. It requires deep knowledge of their personalities, strengths, weaknesses, interests, work style and other characteristics. Our technology and solutions will do the work for you, helping you discover if your people are resilient during times of hardship, if they are autonomous, if they are team players, without actual human contact. Given that our platform is cloud-based, everyone can use it from home as well. Humanity finds itself at a crossroad for various reasons now, why not help people discover and develop themselves from the comfort of their own homes?
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