The transport sector stands to be one of the primary beneficiaries from the windfall of data coming its way from the Internet of Things.

81%

of transport respondents believe that IoT will revolutionise their industry

Digital exhaust, the data generated by people’s online actions, can be an important source of crowd-sourced intelligence for transport companies, and as rollout of Wi-Fi on planes, trains and other public places continues, evermore data sets will become available. Furthermore, sensor-derived data, generated by sensors placed on cargo, vehicles, employees and places, has the potential to fuel a revolution in the sector.

The shoots of this revolution are already beginning to show. This data is spawning a host of new business types and models. Courier company Gophr has been using sensors on its bicycle couriers as they speed around London creating a real-time picture of air pollution in the city, while apps like AppyParking collect data from sensors in parking bays to help drivers find parking spaces. Other initiatives are more ambitious in their scope. Daimler, for example, is positioning itself as a gateway to mobility services with its moovel app which uses data to enable passengers to move seamlessly between different mobility services, from car shares and taxis to bike rentals and public transportation.

But while many in the industry have been deft at leveraging passenger data to dynamically manage routing, calculate fuel requirements and find efficiencies, respondents have not yet mastered their approach to the data generated by connected things. An aeroplane engine might be equipped with as many as 250 sensors, yet this data will commonly be used primarily to spot anomalies, rather than for optimisation purposes – which is where the most value sits.

How do you/will you use the data collected through your organisation’s IoT systems? (%)

Monitoring environmental changes
Speeding up time to market
Managing stocks/assets
Identifying efficiency/cost saving opportunities
Greater automation of business processes
Monitoring and improving health and safety
Decreasing problem resolution times
Identifying and developing awareness of trends
Monitoring productivity
Monitoring customer engagement
We have no plans for the data

Encouragingly, respondents broadly recognise that the data generated by the IoT could make them leaner, faster, and more efficient, but there are a number of barriers that will need to be overcome before these benefits are realised. One of the most important of these barriers is related to the sharing of data. Organisations’ abilities to extract maximum value from data is predicated on employees from different departments having access to it, though in over half of cases, this access is restricted to departments directly related to the IoT deployment. This is a missed opportunity and suggests that respondents may be limiting the scope of their transformations.

To what extent does/will your organisation share the data created through IoT deployments? (%)

23% It is only available to the IT department and senior management
32% It is only available to certain departments involved in the IoT deployment
32% It is available to anyone in the organisation but access must be granted
13% It is available to anyone in the organisation to access and use

A lack of available talent threatens to be a further issue and our research indicates that a skills shortage is already starting to bite.

Transport Systems Catapult, and the UK’s technology and innovation centre Intelligent Mobility, estimates that as many as 3,000 data specialists will be needed in the UK alone to support the transport industry’s drive to exploit data. Indeed, four in ten respondents in this research stated that they required additional analytical/data science skills to successfully deliver IoT, indicating that this is an area that requires attention.

Connectivity is similarly critically important for any adoptee of IoT solutions wishing to engage in data analytics. Data-driven decision making relies upon organisations’ ability to collect and analyse all data sets at their disposal to decide on the best course of action, making 100% reliability critical. When tracking moving assets, such as vehicles, location accuracy can be particularly important. Car insurance companies, for example, determine their premiums based on drivers’ habits – including how they drive in different traffic intensities – but would struggle to do so accurately without full and real-time access to this data. But while the importance of reliability has not escaped our respondents, doubts exist about how possible it is to achieve, with almost three in ten (28 per cent) stating that connectivity issues could derail their IoT deployments, making accurate data collection a challenge.

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