Can the sharing economy solve the UK’s productivity puzzle? We need to properly crunch the numbers to see how beneficial it could be
If you want to get better at something, you first need to understand how you are presently performing. Without a starting reference, you can’t plan how best to move forward.
In the UK right now, we face a measurement problem. Digital technology and the rise of the sharing economy has so quickly reshaped how we live and work, the way we collect official statistics hasn’t kept up with the pace of change.
In a recent report for the UK sharing economy trade body SEUK, leading economist Diane Coyle convincingly put forward the case that traditional measures of productivity do not capture the true economic impact of the sharing economy.
With the government rightly trying to boost UK output through its productivity plan, it’s vital we grapple with our measurement problem. Otherwise, we can’t make the informed choices and formulate the right policies to improve how we work.
Counting on the wrong numbers
Make no mistake, Britain is changing. A December 2015 snapshot of LinkedIn users showed a 30 per cent increase year-on-year in self-employment and a 43 per cent rise in those working at SMEs with fewer than 10 staff.
The sharing economy has played a large part in this shift.
Coyle argues that the growth of platforms such as Airbnb, TaskRabbit and Uber have created a "measurement gap". Official statistics don’t account for the economic benefits that arise from the sharing economy, such as time saved, lower costs and increased consumer and business choice.
For many sharing economy workers, the flexibility of choosing when and where they work (as well as the ability to exploit underused assets such as cars or home space) is making them far more efficient than they would have been in traditional jobs.
Standard GDP statistics simply don’t measure these types of ‘win-win’ efficiency gains, but instead illustrate more straight-forward things like market revenues.
Government statistics also fail to capture the growing number of ‘micro-entrepreneurs’ in the sharing economy. For example, an individual renting out a spare room on Airbnb is unlikely to consider this ‘work’ and subsequently wouldn’t class themselves as a freelancer. These kind of little details add up and are key for the government to be able to take an accurate pulse of the UK economy.
The government deserves praise for its ambition to help ensure the UK becomes the global hub of the sharing economy. But to do that it needs to make sure it has the right information to hand to shape policy. Otherwise it won’t be able to identify what needs to be done to help those in the sharing economy further or attract others to it who may not yet realise its plus points.
A new measuring stick
Coyle’s report contains some excellent recommendations on how the Office of National Statistics (ONS) should begin to revamp and modernise its data collection techniques.
One of the most important suggestions is the need to collect data from individuals, not just businesses. The sharing economy is essentially a peer-to-peer model and without directly asking people for information, much of this data will slip out of the loop.
Additional questions on ONS surveys, such as its quarterly Labour Force Survey, can help capture the extent to which people are using sharing platforms and the benefits they get from it.
An updated Time Use Survey – 2005 was the most recent one – that encompassed the sharing economy would also be a step in the right direction, assisting in classifying the types of activities people engage in and the time spent doing so.
One of the most important, but also most challenging needs for the number-crunchers, is getting a better grasp on ‘big data’. Scraping websites for information and collaborating with sharing platforms would help statisticians build a more accurate statistical picture of the UK and reduce the size of that measurement gap.
The measure of success
Among G7 countries, only Japan is thought to have a worse record than the UK in terms of output per hours worked. Such a dismal status makes Coyle’s case for fixing the ‘measurement gap’ even more pressing.
To push on, we need to be sure the decisions we are making are based on the reality on the ground, not on measurements designed for the analogue age.
So let’s find out exactly where we stand. There isn’t a moment to lose.