The gig economy is booming. Uber drivers, Deliveroo bikes, and Airbnb apartments are everywhere you turn. The rise has been rapid, with the FT claiming that between 2012 and 2014 it grew 48% across the 50 largest US cities.
This kind of increase has been due to a number of factors, from relatively stagnant wages forcing people to look for other forms of income through to the spread of technology that has allowed more people to access these services, both from a customer and labor perspective. This kind of growth has slowed, which is unsurprising given the initial impact it had. The longevity may also be an issue, with JP Morgan reporting that 52% of those who download labor apps quit after a year.
However, the numbers within the the gig economy are still huge. Uber alone has 160,000 drivers across the world, who have undertaken over 2 billion trips for the company. And people now rely heavily on these on-demand services to the extent that Uber has become a proper noun, noun, adjective, and verb, linguistically beating even Google, which is only a proper noun and verb. Uber alone is installed on 21% of all Android phones in the US, showing the huge reach that it has.
With numbers this large and the instant changes that these services require, it makes them ripe for real-time analytics, enabling them to respond to constantly changing situations. This could be anything from huge demand for a certain food in the financial district of a city over lunch through to redirecting cars due to congestion.
Technologies like Apache Spark have allowed companies to take advantage of the gig economy in a way that was previously impossible. Without data it would be impossible for companies to react to demand or optimize their service. It even allows for speedier billing once the service has been used.
One of the most important elements is in safety and trust for customers. Uber use GPS data from the driver’s smartphone to include the route taken by the driver in the instant invoice so the customer can be certain they haven’t been ripped off by taking a longer route than necessary. Similarly, real-time tracking of delivery drivers allows customers to know when their item is picked up and delivered, so there is no issue regarding delays or suspect behaviour from the driver.
It also allows companies to take advantage to unexpected situations, and designate resources accordingly. For instance, if there is an issue with public transport in a specific area, Uber can attract more drivers there by implementing a ’surge charge’ which increases the amount paid to a driver. Without access to real time data, these kinds of fleeting opportunities are likely to be missed.
The development of technologies has allowed real-time data to become more widespread, which has in-turn improved gig economy companies and therefore increased their use. Although companies like Uber would certainly be able to operate without real-time data, it is one of the most important differentiators that has seen them become the dominant force and poster child of the gig economy.