Sharing brings happiness: data for new digital business models

New data-driven business models are emerging across all sectors: digital citizen assistants in public administration, predictive maintenance in logistics, predictive analytics in the healthcare sector and smart transport solutions are just a few examples.

The underlying data – often referred to as the ‘new gold’ – is not only valuable but, unlike other raw materials, is becoming increasingly abundant. How this data is managed depends largely on the design of the data spaces – the data ecosystem. Four-fifths of data currently lies dormant, unstructured and unused, in the depths of organisations. Extracting, enriching and analysing this data is currently a major challenge, but one that is well worth the effort. With the right data, new products, services and user experiences can be created, sustainability promoted and, ultimately, money earned.

To create a data ecosystem that provides the ideal breeding ground for new business models, a radical rethink is needed in many areas. This is because the value of data can increase when it is used in collaboration with other providers. Seen in this light, data is ‘happiness that doubles when shared’. To achieve this, separate data silos must be interconnected and also opened up to the outside world. Sovereign infrastructures ensure that the parties involved retain control over the data they generate.

An example: big data in the automotive industry

More than 80 per cent of companies in the automotive industry have recognised the potential of customer data – accessible across departments for research and development – for the further development of their products. With the help of built-in IoT sensors, car manufacturers can gather important data that can be used for predictive maintenance and product optimisation, as well as to support fuel-efficient driving behaviour.

Vehicle users can, for example, automatically receive a notification if tyre pressure is too low or an oil change is due. Linked to the mileage, drivers can be reminded of their next service appointment, which can then be arranged directly via an automated call. A predictive efficiency assistance system can significantly reduce fuel consumption. Working in conjunction with the navigation system and camera-based traffic sign recognition, the speed is automatically adjusted to suit the route, speed limits and traffic ahead. A vibration through the accelerator pedal signals an impending obstacle or a speed limit, prompting the driver to ease off the accelerator in good time.

Fully integrated driving experiences can be created when multiple stakeholders link their data together. For example, with a navigation system that suggests alternative routes depending on traffic and weather conditions, and also alerts the driver to free parking spaces and available e-bikes in the destination area. By linking their data, several players ensure an optimal, needs-based customer experience: car manufacturers, e-bike hire companies and even other road users who also use this navigation system and share their location data.