There was a time when a tyre was a simple ring of rubber. But no longer. Italian brand Pirelli has developed the Cyber Tyre: still a rubber ring, but containing sensors that collect and transmit a mass of data on friction, grip, pressure and other performance factors.
The Cyber Tyre has been tested on heavy-vehicle fleets and Ferraris whizzing round race tracks. But it could become common on ordinary cars.
According to Pirelli, its “Cyber Fleet” tests have brought businesses substantial per-vehicle cost savings. Tyre pressures are continually monitored and kept at optimum levels, resulting in fuel economies because correctly-pressurised tyres reduce rolling resistance.
Cyber tyres also, in principle, offer safety improvements – they transmit information to the vehicle about road conditions, and either the driver or the vehicle itself can make adjustments to ensure safe driving.
More broadly, the mass of data assembled via the sensors can help Pirelli improve the design of its tyres, which should result in less waste and greater efficiency.
The Cyber Tyre is a practical example of a sustainability dividend from the use of data, especially “big data” – the analysis of huge databanks (in Pirelli's case, millions of sensor readings) to reveal patterns and insights.
Big data is set to become increasingly important to corporate sustainability. It can help companies know themselves better and make more sustainable choices, either through more operational or product-related information, or through improved modelling and forecasting.
In company operations, big data could underpin sustainability by, for example, showing where water or energy is used inefficiently at production plants, or even across whole value chains.
Big data could also help companies get closer to their customers and to promote sustainability in the usage phase of their products. Pirelli Cyber Tyres, in principle, will be able to provide data to the driver to help with more fuel-efficient driving, and to provide warnings when tyre pressures drop too low.
In terms of modelling and forecasting, big data can produce increasingly fine-tuned inputs to corporate decision-making. For example, a decision about where to build a new production facility could be informed by ever-more detailed forecasts of water stress at potential sites.
However, big data also has implications that need to be carefully considered. First, there are practical issues – deciding to pay for the hardware and software and the training of a new breed of big-data analysts.
Second, big data analytics will only work if the inputs are of good quality. Any company wanting to collect data from sensors in the way that Pirelli does, for example, must be confident in its systems and processes – which could imply a need to become specialised in a new type of activity that is quite distinct from the core business activity.
Third, the privacy implications must be taken into account. This is perhaps the main issue with big data, which could easily tip over into surveillance.
Analysing the performance of a car’s tyres, for example, could result in the profiling of the driver – by providing data about where, when and how he or she drives. This could have a host of implications in terms of data protection law in an increasingly privacy-conscious world.
Increased production and sharing of data could also put commercial confidentiality at risk. The gains from big data in terms of sustainability measurement, analysis and decision-making could be substantial, but it is new territory, and companies will have to tread carefully.