The Future of Work – Part 1: Employee to Free Agent
The Future of Work is a multi-faceted subject. One that’s ripe for multiple books, not just a few short articles. I’d like to tackle the topic here from just a couple of angles. First, the ways in which people are working. Second, the ways in which automation and robotics will augment and sometimes replace people altogether.
The Portfolio Career
People with Portfolio careers either have several concurrent part time jobs or a series of jobs, each for a short and overlapping time. In part this can be attributed to reduced job security, but it’s also an active choice made by people looking to live more diverse work lives.
We should say, there’s a difference between people who have three jobs just to get by and people who have a portfolio of jobs as a career choice. “In 2013, only 20% of those with portfolio careers were doing so because they needed to take more than one job to make a living”, Charlie Ball, Deputy direct research at careers website Prospects.
Portfolio careers aren’t a new idea. The idea was popularised by 90s management guru Charles Handy in his book ‘The Empty Raincoat’. The concept was simple; going portfolio was exchanging job security for independence – being our own boss.
Employee to Free Agent – Rise of the Freelancer
According to the Bureau of Labor Statistics, 15.5 million people in the US were self-employed in May 2015 – a jaw-dropping 1 million increase on the previous year. According to some forecasts (link), over 40% of the US workforce (60 million people) will be independent workers by 2020. That’s a four-fold increase in five years!
Independent workers comprise three types – pure freelancers, contractors and temporary employees.
Mobile and other technologies are creating completely new work ecosystems. Indeed, one of my friends makes his entire livelihood by splitting his time as a gardener (via mobile app TaskRabbit) and taxi driver (via Uber). He’s also been learning web development via online training provider Lynda.com and gaining paid experience by selling his skills on Upwork.com. This may not suit everyone, but for many, digitally facilitated labour exchanges will be the new normal.
Introducing the ‘Gig Economy’
‘Gigs’ were once something musicians sought out. Ideally, they were paid opportunities to play music at different venues. They helped musicians build reputation and (hopefully – although many musicians today would disagree!) generated some cash in the process.
Away from music, the ‘gig economy’ has come to signify much more. Since 2010, we’ve seen the growth of online platforms matching those who require tasks to be completed (employers of a sort) with those looking to complete tasks (freelancers). For the most part, these tasks are completed digitally. Typical tasks include book-keeping, programming, video editing and much more. Two of the biggest players are Upwork and Amazon Mechanical Turk, but there is a wealth of other options and some pure-play platforms for specific skills (e.g. voice overs, cleaning etc.). As someone who ran a creative agency, I was a regular employer on these platforms. We often used them as a place to expand our capacity, either for specific projects (e.g. graphic design, motion graphics) or more routine work such as cleaning databases.
Despite an incredibly fast moving market, Mckinsey estimate that c540 million workers globally will have used an online platform to find short-term work by 2025.
One humourous example of this ‘personal outsourcing’ being taken to its logical conclusion was in 2013. An employee who became known as ‘Programmer Bob’ (working with a critical infrastructure firm) was found to have outsourced his entire job to a firm in China, paying a fifth of his annual salary for the privilege. Prior to his subsequent sacking, he was bestowed a ‘best programmer in the building’ award for his productivity.
The investigation revealed his typical workday included:
- 9:00 a.m. – Arrive and surf Reddit for a couple of hours. Watch cat videos
- 11:30 a.m. – Take lunch
- 1:00 p.m. – EBay time
- 2:00-ish p.m – Facebook updates, LinkedIn
- 4:30 p.m. – End-of-day update e-mail to management
- 5:00 p.m. – Go home
Depending on your perspective, ‘Bob’ was a model intrapreneur or was guilty of facilitating access to proprietary systems and threatening the firms’ information security.
Forward thinking organisations are well placed to take advantage of these online labour exchanges. They facilitate increased capacity without the associated headcount costings. That said, the ‘Bob’ example above highlights the importance of putting in place sensible policies, which take account of the associated business risk when using these services. Not only is proprietary information at risk, but there may be data protection implications as well. Even if your gig economy assistants sign NDAs, if they are in another territory, are you really going to navigate a foreign legal system to seek redress if your sensitive company documents end up in public hands?
According to Deloitte’s 2016 millennial study, 44% of those surveyed plan to leave employers within 2 years. Additionally 56% stated they would refuse to work for employers whose values were not congruent with their own. The competition for skilled graduates and early stage career professionals is intense. Philippe De Ridder, co-founder ‘Board of Innovation’ says corporates can innovate like startups by creating environments more like startups. They work with clients who set up ‘intrapreneurship’ programmes where individuals get full ownership over projects. In addition to greater decision-making, those employees could be free to hire ‘as and when needed’. I've little doubt some of these people will utilise their new skills in setting up their own ventures at a later date.
For example, a manufacturer could prototype an ‘Internet of Things’ concept by co-coordinating circuit and CAD designers, user interface specialists, software programmers through one or several of the online platforms available. Not only would this keep bureaucracy to a minimum, but costs are controllable and the project can quickly be brought to a halt if it shows signs of sure failure.
It’s not all good though. Especially from the freelancers’ perspective. There’s no doubt these Gig Economy platforms will favour one group over another. Those employers seeking the lowest possible price will find their workers where living costs are lowest. Where labour becomes commoditised, those in the Philippines or India are far better placed to win work than people in the US or UK. In addition, we’ll likely see a huge emerging cohort with no job stability, financial security or opportunities to progress their careers.
The intermediate step towards full automation – Algorithmic Management
If you live in a major urban development as I do, chances are you’ll have seen a host of takeaway and other delivery services sprouting up.
One such service is ‘Uber Eats’, the subsidiary of taxi giant Uber, which launched in June 2016. They promise ‘the food you want, from the London restaurants you love, delivered at Uber speed’. What marks it as a trend to watch is that (like Uber drivers), these delivery workers don’t have managers, known colleagues or even a hub from which to work. They are managed exclusively by their mobile apps – ultimately by algorithms.
The early promise was a win-win for everyone. Drivers could work the hours that suited them. Restaurants would not be required to increase headcount to make deliveries.
Things ran smoothly for a few months - until the app updated. The pay formula changed and many found themselves out of pocket - and angry. August 26th 2016 saw the first London strike by gig workers who felt cheated.
And Uber’s not alone. According to an FT article, this algorithmic management goes much further:
"Deliveroo’s [a similar delivery business] algorithm monitors couriers closely and sends them personalised monthly “service level assessments” on their average “time to accept orders”, “travel time to restaurant”, “travel time to customer”, “time at customer”, “late orders” and “unassigned orders”. The algorithm compares each courier’s performance to its own estimate of how fast they should have been. An example from one of Kyaw’s assessments: “Your average time to customer was less than our estimate, which means you are meeting this service-level criterion. Your average difference was -3.1 minutes.” Deliveroo confirmed it performs the assessments but said its “time-related requirements” took into account reasonable delays and riders were “never against the clock for an order”.
There’s little doubt that the growth of those with freelancer status and increased access to online labour exchanges will revolutionise the future of work. As tasks become increasingly commoditised, wealthier countries will struggle to win work and will be forced to differentiate their offerings to do well. Algorithmic management is also here to stay and I’d argue represents the inevitable steps closer towards full automation of many jobs. In short – if a job can be automated – it will be.