Features
5 Aug 21

5 Insights into optimising vehicle data

Barriers to data sharing lie in the following areas: technology, standardisation, organisation and privacy. The technology behind connected vehicle data is immature and the quality of it varies, so some businesses are using it better than others. But, as increasingly more cars are shipped with embedded connectivity, data management and optimisation important.

The adage that “everything is standardised except standards” applies here. A great deal needs to be harmonised across brands, countries, products and companies for automotive data to be truly optimised. In the meantime, the following insights are helpful.

1. Break down the data Silos

In a paper entitled: Breaking down silos: Driving decisions from fleet data, Geotab advises that this should be the first objective. Trying to make sense of fleet data can be overwhelming due to the sheer quantity of what’s available. in the end, fleet managers need to be specific on what they are trying to understand and achieve. However, for fleet data to make an impact on the entire enterprise, fleet insights need to be shared outside of the silos that currently exist. Driver data will help Human Resources with Human Capital Management. Fleet costing and financial performance data should be integrated into ERP systems for the finance team to benchmark. CSR operatives can use emissions data to find out what impact electric vehicles will have on carbon emissions. The procurement team can use predictive maintenance data to proactively order new components that are about to fail. Expense management will benefit from fraud detection data to enable them to catch expenses fraud.

2. Build trust with end customers and incentivise them to share their data.

End customers are reticent to share personal data. Research by CapGemini found that 63% of customers wouldn’t (or didn’t know if they would) be willing to share the data generated by their vehicles. 67% said they would only share anonymised data but not personal data. Primary concerns are privacy and how the data will be used. To overcome this, businesses must create awareness and transparency about how and why customers’ data is being used and give them full control over it. Explain the consent management process and design the consent flow to be as convenient as possible. Offer discounts (not gamification) as incentives.

3. Enrich vehicles data with other data sources to enable more valuable data services.

In this way, product and service offerings can be made more customer centric. However, such products and services need to be highly personalised because some offerings will appeal to some customers more than others. Segment customers into those who enjoy convenience, for example, and offer time saving initiatives. Other customers will be more interested in welfare benefits such as safety improvements, or fuel savings. Some will want lifestyle products such as mobility miles, car clubs and so on.

4. Prioritise investment carefully

Setting up the vehicle data infrastructure is the OEM’s responsibility, as is developing new components and value added functionality. Services that require data from multiple automotive OEMs (parking or traffic apps) needs to be created, managed and offered by data platform providers or aggregators who can gain full market reach. Service providers (SPs) should focus on service provision. But this will involve OEMs opening up their data ecosystems to service providers. To that end, service providers should not get involved in hardware provision but instead collaborate with OEMs in the early stages of service development. Concurrently, SPs should connect with data platform providers to gain full access to their data through a standardised interface.

5. Build an ecosystem of business and technology partners

This will involve working with a team of external players and organisations. Businesses need to be clear on which aspects of vehicle data monetisation they want to own and which they can outsource or set up long-term collaborations with external partners. The next step is to identify who those partners might be and engage with them. Building a strong internal team of mixed capabilities and strengths is also a priority. This team needs to be agile, open to change and experimentation.

There is no one-size-fits-all approach to optimising vehicle data, the road to get there could be a bumpy one, with a few potholes and blind alleys along the way. That said, it’s a journey worth taking, especially post global pandemic when many businesses have been forced to re-evaluate to stay afloat.

*Image of a futuristic car showing data points, courtesy of Shutterstock.

Authored by: Alison Pittaway