Companies have been using variable pricing for decades. But in the past, approaches to variable pricing were fairly crude.
Companies have been using variable pricing for decades. But in the past, approaches to variable pricing were fairly crude – largely based on time of day availability (peak versus off-peak) and scarcity. Energy is cheaper at night when fewer customers are using it, rail travel is cheaper outside rush hours, and so on.
For infrastructure owners and operators, variable pricing helps manage demand and ration capacity. In the energy sector, this has helped authorities to better manage peaks. In transport, it has encouraged commuters to shift their travel times.
In recent years, we have seen the emergence of dynamic pricing: charges adjusting in real-time to reflect actual capacity, supply and demand. Some of the first adopters were low-cost airlines. They were soon followed by railway companies and app-based taxi companies such as Uber and Grab. Governments are also getting in on the action; some managed lanes in the US require operators to adjust their tolls in real-time to achieve a certain traffic speed.
We believe that the trend to use more dynamic pricing is only going one way. The availability of real-time data, computing power and more sophisticated algorithms now means that companies can calibrate their prices much more carefully, knowing exactly the shape of the demand curve and the true costs associated with delivering a service.
As technology becomes more complex, we expect infrastructure owners to move towards a form of dynamic pricing, allowing them to hone rates to the individual, in real-time, based on a variety of variables including their ability to pay, the value they place on a service and the urgency of their use. And in many cases, this shift will mean much closer alignment between those who pay for infrastructure and those who benefit.
Yet there is also a social dilemma to dynamic pricing; it can reduce access for those unable or unwilling to pay a premium for the infrastructure they need. For example, making roads more expensive during peak hours impacts workers, many of whom have no ability to change their hours in order to reduce their costs. Higher pricing for air travel during holiday periods leaves poorer travelers at home. Raising energy prices at 5pm hurts young parents and the unemployed more than it hurts office workers. Choice and the presence of alternative services is key. Airlines have addressed this issue by charging lower prices for those willing to buy long in advance of consumption.
Over the coming year, we expect infrastructure owners to start placing more emphasis on understanding the need, value and ethics of dynamic pricing. We expect to see regulators think more clearly about how fairness can be achieved in certain dynamic pricing models. And we expect to see new dynamic pricing models being applied across a wider variety of infrastructure services.