The past decade has seen the rapid growth of data. What are the implications in the transport industry?
The information a vehicle or fleet holds has drastically accelerated data-driven decision-making throughout the transport industry. Depreciation modelling, route optimisation and use calculations are now more accurate than ever. All of these areas have a direct effect on a business’s bottom line, sharpening the need to comprehend what data is available and how to use it.
As an example, connected vehicles are becoming somewhat standard practice in the OEM [original equipment manufacturer] space, gathering their own telematics and feeding it back to a data pool. By 2030, 88% of cars sold worldwide will be pre-connected to networks via embedded devices and nearly all vehicles in the EU and US will be connected, according to a study by Ptolemus Consulting.
How has this impacted how fleet managers and operators approach data?
With the increasing focus on sustainability and fleet transition from internal combustion engines (ICE) to electric vehicles (EVs), they’ve come to realise two critical points. First, data is core to a successful EV transition strategy. Fleet managers must first understand how their existing vehicles are used and then what they can transition to. As a pioneer in EV fleet transition, Geotab has supported countless fleets on this journey through the use of our electric vehicle suitability assessment platform.
Second, data is needed to efficiently operate an electric fleet and, in many cases, a mixed fleet of EVs and ICE vehicles. While there may be overlap in many data points, there are also new ones to get to grips with, such as state of charge.
How important is it that large dataset businesses collaborate and share data?
Data democratisation maximises value to businesses and end users, which has implications not just for commercial fleets but also local and national government initiatives such as charging infrastructure planning. It means every individual benefits indirectly from shared data practices.
From an organisation standpoint, this requires looking at data from a product management perspective, not just a data science perspective, to truly understand the solution and benefits that a dataset can provide. Also, you can’t forget that data sharing agreements have privacy implications, which can be a barrier if not defined clearly and transparently from the beginning.
What role is Geotab playing in bringing data points together?
Processing billions of data points every day, our open platform allows fleet businesses of all sizes to automate operations by integrating and aggregating vehicle data with their other data assets. Geotab does the heavy lifting on behalf of businesses to contextualise and present data in a meaningful way and scale in line with growing fleet sizes. MyGeotab is the front-end that delivers all this information in an easy-to-understand format, while our recently added ‘Active Insights’ feature takes the leg work out of analysing tables and charts by identifying areas that may be of concern or require attention, further enhancing overall fleet management efficiency.
What is the ultimate value for fleet organisations that pull in multifaceted data insights?
The ultimate value is in providing diagnosis rather than hypothesis. The ability to generate insights combining both frequency of data and ‘labelled data’, such as engine error codes and OEM part numbers, drives direct bottom-line improvements. For example, historic telematics data, vehicle error codes and SMR records can combine to provide predictive maintenance analytics, flagging when vehicle underperformance might become an issue in the future.
Ingesting data from consumer vehicle providers, as well as other streams such as hyper-local weather data and camera footage, also helps paint a contextual picture of current and future fleet sustainability. When we conducted an EV suitability assessment of Enterprise Fleet Management’s 91,000-strong fleet, we found that 13% could be economically replaced by EVs. This represents a potential saving of $33m and 194,000 tons of CO2 over four years.
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