We know from looking at the development path of sectors in the economy that many exhibit an ‘S-curve’ pattern. Initial low and volatile volumes make way for a breakthrough company to accelerate growth before a market saturates. At this point, old sectors mature and decline – replaced by the next overlapping innovation.
We believe traditional rental industries are being disrupted by the sharing economy as established industries mature and are displaced by a “Sharing S-curve”.
In PwC research conducted in 2014, we compared the revenue potential in five new ‘sharing economy’ sectors (peer-to-peer finance, online staffing, peer-to-peer accommodation, car sharing and music and video streaming) with the potential in five traditional ‘rental’ sectors (equipment rental, B&B and hostels, car rental, book rental and DVD rental).
We used the resulting S-curve and model as a base for our expectations of the future growth for each sector.
S-curve based on industry reports, company revenue data and subject-matter expertise
PwC research conducted in 2014 estimated that the five main sharing economy sectors generate $15bn in global revenues, making up just 5% of total revenue generated by the ten sectors we looked at.
However, by 2025, these same five sharing economy sectors could generate over half of overall sales in the ten sectors – a potential revenue opportunity worth $335bn. We estimate the UK’s slice of the pie could be worth around $15bn (or £9bn) in 2025.
Between 2013-2025, sharing economy sectors are likely to grow much quicker than the rate of traditional rental sectors. The least developed sectors as measured in 2014, such as P2P finance and online staffing, could grow the quickest of all.
However, for the sharing economy companies to realise their potential, they will need to overcome significant barriers. We think that two hurdles stand out: first, major regulatory and fiscal issues need to be resolved; and second, in scaling up, sharing companies face challenges in maintaining their uniqueness and authenticity.
Due to a lack of long-term historic data, we’ve used a number of assumptions to develop our projections, which are therefore subject to considerable uncertainties. We recommend looking at a range of scenarios and viewing the overall total figures as more reliable than individual industry results. Access our methodology here.