The economics of data sharing: unlocking value in regulated industries

For regulated companies, the benefit is better performance in areas where outcomes are rewarded (or punished) by the regulatory framework.

However, for the most part the regulator considers only a company’s or a sector’s own customers when setting the incentives to invest in data. This means that data which delivers benefits to stakeholders outside the boundaries of an organisation or sector, known as externality benefits, will attract less investment than is socially optimal.  This problem is particularly relevant in a world in which the operations of different infrastructure providers (water, energy, transport, etc.) depend on the resilience of other providers’ assets.

Take a water company that is deciding how much to invest in data to diagnose flood risk at its pumping stations. The company will invest up until the point at which the marginal benefit (from avoiding regulatory penalties and reputational damage) equals the incremental cost of further investment. However, if the pumping station in question is located next to an electricity network substation or transport hub, the marginal benefit to society from another pound of investment in related data may be much higher than the private benefit to the water company. This will lead to underinvestment from a societal perspective.
Shifting this external risk back onto the water company may prompt it to invest more, independently, in its own data. But this course of action may not be optimal if it means water customers are paying for the resilience of energy and transport users – and at a cost which may be greater than if those infrastructure providers themselves were better equipped with data to make their own decisions. Instead, in an increasingly interconnected world, sharing data among different infrastructure providers can enable more efficient investments and better outcomes for customers.

Connected ‘digital twins’ present a significant opportunity in this area. A digital twin is a virtual real-time representation of a physical network which allows the operator to understand how different actions may affect the real world by characterising interdependencies between its assets. The Connected Places Catapult (CPC) has demonstrated the value of connected digital twins through  its Climate Resilience Demonstrator (CReDo), bringing together the digital twins of Anglian Water, UK Power Networks (UKPN) and BT.  Frontier Economics supported the CPC in measuring the benefits of improved coordination of operational and investment decisions to increase resilience against flooding events through a simulation. This showed that asset operators can achieve greater resilience (for a given cost) through connected digital twins than via siloed digital twins.

More recently, UKPN has begun developing an artificial intelligence-enabled platform called Climate Resilience Decision Optimiser (‘CReDO+’). This builds on the connected digital twins just described by combining historic and predictive data to simulate how resilient power lines would be during different types of extreme weather. 
While these demonstration projects offer enormous promise, is there more that regulators and policymakers could do to encourage utilities to exploit opportunities from data sharing? Frontier Economics examined how to improve data accessibility for the Department for Digital, Culture, Media and Sport (DCMS). We found that there was a package of interventions which could enhance data sharing – from reducing the cost of sharing through data foundations (e.g. improved findability and interoperability), to easing the regulatory burden and creating better incentives.

To accommodate and encourage data sharing across organisational boundaries, regulators will need to set appropriate incentives and decide how to recover costs from customers in different sectors. These are difficult questions, but the prize is huge.