Telematics data aggregation is one of those “it does what it says on the tin” capabilities.
It is the bringing together of the mass of data that is generated by telematics devices, dashcams, black boxes, apps and, increasingly, wearable devices, into a useable solution.
The solution is normally a software, and one that is cloud based.
It also helps immensely if the telematics data aggregation software is hardware agnostic.
That is, it can take data from any connected hardware, regardless of the data protocols that the hardware is running on.
And if it can do that, it needs to be able to not only aggregate telematics data, but also standardise and normalise the telematics data for consistency and comparison.
Given all this, telematics data aggregation is seen as a part of the Big Data, Machine Learning (ML) and Artificial Intelligence (AI) developments. Which are now taking hold in business, commerce, and society.
While it is a relatively new field, it is one that is only set to grow in importance. As telematics data aggregation services become a key facilitator for transport managers, fleet managers, insurers and risk managers seeking to make the best use of the big data that their telematics systems are generating.
There are two key reasons why we need telematics data aggregation.
Is that most fleet operators and insurers have more than one telematics system in use.
This could be from different hardware vendors, the Telematics Service Providers (TSPs), or they could be upgrading from one model to a newer one. A process that can’t be done overnight on a fleet of several hundred or thousand vehicles.
The point being that they will be collecting telematics data from more than one data source. And many times, these data sources won’t be truly comparable or consistent.
And more pressing need, for telematics data aggregation, is the sheer amount of data that is being generated.
We wrote about the phenomena of “Too Much Telematics Data” recently.
As a synopsis, the amount of data that is being generated is huge and will only get bigger. Because our vehicles are no longer self-contained mobile boxes. Instead they have become very sophisticated data platforms generating, transmitting, and receiving a mass of digital data.
Is a phrase often heard from transport managers and fleet managers, seeking to get on top of the data they are getting. So that they can gain insight to do their job of managing their fleets on a day to day basis (see here for more about fleet management).
It expresses the problem very well, if somewhat graphically.
As a 2018 report by Ptolemus, a specialist consultancy in connected mobility, on telematics data aggregation, put it:
“While the amount of data generated is growing at a phenomenal rate, the quality of data analysis and actionable insights delivered to the fleet operator have not developed at the same pace. More data does not automatically translate into more value.”
Or as Jorge Fernández, from Roche, 2019’s Global Fleet Manager of the Year, said;
“It would be good to develop platforms to simplify and aggregate services in order to help fleet managers”
So, in this case, telematics data aggregation is designed to take the problem of too much data, away from the fleet operators and transport managers. Replacing it with clear and simple insight, management information and alerts. Such as FNOL (First Notification of Loss). Which will enable them to be both more efficient and effective.
In this situation, as the Ptolemus report says, “It no longer matters who generates the data – what matters is who can provide the clearest insight into that data.”
Particularly those insurers providing services to light commercial vehicle (LCV) operators. The need is like the first reason above. Telematics data aggregation for bringing data together from a range of different TSP devices.
With this capability, insurers can use telematics data aggregation as a value-added service to their customers. Using it as a source of information which can help refine, improve, and evolve the insurance business model and the claims process.
Which neatly brings us on to the benefits of telematics data aggregation.
The core benefit of telematics data aggregation, as highlighted above, is the efficient and effective compiling of telematics data to provide simple, easy to use insights for fleet, insurance, and transport management.
The point is worth restating.
Telematics has revolutionised the fleet and transport industries in the last decade. But with it has come a situation of multiple reporting, inconsistent data, and a new management task of staying on top of the data and the reporting.
This point is highlighted and expressed in a recent conversation CMS had with a fleet operator in the UK:
“One of our biggest barriers is the multiple systems we use, with little integration, the duplication of workload, multiple data entry, and no clear insight of trends and drivers of activity”
So, the core benefit of telematics data aggregation is taking away this management task. Replacing it with clear insight for management action. Rather than management being lost in the activity of just being able to understand the data.
But what are the other benefits of telematics data aggregation?
Well, they all stem from this core benefit of being able to manage better. Be that in identifying training needs by driver or depot. Being alerted in real time to FNOL or traffic incidents. Or being in better control of maintenance schedules and plans.
From an insurers point of view, having real time FNOL alerts allows the insurer to proactively take charge of an incident, rather than reacting to a call from their insured party. A call that often happens a good while after the incident.
And as we know, faster action leads to better cost control and management when it comes to incidents
For the fleet and transport manager, real time FNOL alerts help them in their duty of care for their drivers/employees. Alerts them to any logistic or delivery issues they may need to update customers on. And, if working with their insurer, can help bring insurance premiums down as average claim costs become smaller over time.
This management benefit can be extended further within the organisation.
For example, as a tool for enhanced risk-management, telematics data aggregation can be used to help guard brand and company reputation.
By having insight on near misses, problem routes, and problem drivers, management resources can be targeted at these areas. By doing this, things will improve, and the risk of an incident happening will decline. Plus, if one does happen, having proof of processes of risk management can help immensely with official procedures and investigations.
At CMS we summarised these benefits into this staircase, which we feel captures the benefits of telematics data aggregation. It also shows how the benefits go beyond the fleet and transport managers and their offices:
Telematics data aggregation is for any organisation that is facing the management burden of too much telematics data, not enough time to process it, and not getting the best from their investment in telematics.
At CMS, we work with fleet and transport operators and insurers. We also focus on these distinct operational businesses
Middle mile distribution
Utilities & Energy
Our findings are that given their operations of predominately light commercial vehicles. The fact that journeys will rarely be regular repeats for the drivers. Their travelling through the urban, suburban, and rural road networks. Plus, their investment in telematics. They have a real need for telematics data aggregation, as these combination of factors will give them both lots of data and lots of alerts.
Additionally, organisational values, duty of care and wanting to keep their people safe, also provide a need for telematics data aggregation services. Which goes beyond the direct need of the fleet and transport managers.
Telematics data is provided either in real time from a connected system such as a modern dashcam, or via a regular upload when the vehicle is back at depot. Obviously, this second method is of an older variety, is not necessarily automated, and has a delay built in.
Also, we are predominately talking about after market or third-party telematics installations, in the vehicles. While vehicle manufacturers do generate a lot of telematics-based data from the factory fitted devices, this is not normally made available to the fleet operator or insurer. This may change in the future (see below).
So, you have a number of telematics data sources, how do you aggregate them?
Well, the simplest way to explain that is to show what we do at CMS, with this handy graphic of our process:
Effectively there are four stages.
Stage one: the aggregation of the data from the telematics devices, and in our case, a range of other data sources such as training information, employee reviews, and speeding fines.
This is a combination of real time feeds from the telematics devices. Daily uploads from the older systems. And digitised data from the company and employee records.
Stage two: all this data is then standardised through our big data and machine learning processes.
This part is key, as it removes the false alerts, the inconsequential data, and compares the data sets.
Removing all the information that, through big data and machine learning, is irrelevant.
Leaving just the key information that the user needs.
Saving them time and empowering them to act rather than be overwhelmed with a flood of telematics data.
Stage three: with this cleaned and consistent data, the user is alerted to just the incidents that need their attention (FNOL).
Rather than being lost in the mass of alerts.
Stage four: feed valuable data into the user’s risk management process for training and management focus.
Telematics data aggregation IS effectively the future of telematics data.
The capability to bring in data from multiple sources, clean it up and provide actionable insight is, arguably, more important than the tools to create that data in the first place.
That is, the current model of telematics service providers focussing on hardware is going to be secondary to the capabilities of the (software) management system the telematics data is fed into.
Additional features of the future for telematics data aggregation are:
This is a given.
As the number of devices grow, the quality of the images from dashcams moves from SD to HD to 4K, and things like the London Direct Vision Standard, requiring operators to have more devices on their vehicles, come into force, the amount of data is only set to increase.
A related challenge to this will be the bandwidth and processing power needed to gather and work this data.
This is an area which will grow, as traffic and route data, communications, and entertainment data are all fed into the vehicle.
While this may not at first be an area for telematics data aggregation to be concerned with, the data going in will have an impact on the actions of the vehicles and the data coming out.
Being able to match and understand that relationship, speed of response, value, and impact etc will become a valuable metric for telematics data to understand.
Related to both of the above.
Driverless vehicles, creating and processing data from other vehicles (V2V) and their surrounding infrastructure (V2I) is set to make the data oceans we face today seem like puddles.
The process and approaches being used in telematics data aggregation now, will be a useful and powerful place to start from when approaching this new data mass.
Currently most, if not all, vehicle manufacturers don’t make the telematics data they gather available for fleet operators to use.
That is why third party after market telematics devices are so prevalent.
This could be set to change as we move towards autonomous vehicles, with cameras and other sensors being built in, and the need for shared access to V2V/V2I communication becomes a necessity.
As this happens, fleet operators will be spared the cost of having to invest in after market installations, potentially.
However, if they are running a fleet of say Renault, Ford and Mercedes vans, they will still need a telematics data aggregation service to bring the data together for them and provide the management insight they need in one system, rather than across three separate ones.
Data privacy is a mainstream topic, and telematics data aggregators work to meet the needs of things like GDPR and employee concerns. Of course, the regulatory environment can change, meaning that the telematics data aggregators will need to change with them.
Additionally, as big data and machine learning come under more scrutiny, there will be a need to explain and detail what and how the decisions are being made from the aggregated data.
Regulators will become reticent to let machine learning make important decisions, as things become more automated, without some understanding of how and why those decisions are being made.
This will also extend to customers.
There is value in the aggregated telematics data, beyond its use by fleet and transport managers.
For example, local and national government could use the data to prioritise road network improvements and repairs.
Or retailers could use it to plan advertising campaigns from electronic billboards, based on the demographics of the drivers by route.
As the richness of the data increases, and the simplicity of its access grows, because of data aggregation, there will come a time when someone will either offer it as a commercial product, or someone else will enquire about purchasing it.
Regulation aside, at that point the value of aggregated telematics data steps into a whole different realm.
The simple answer is it’s what we do, the technical insight we were founded, and all that we focus on.
We therefore have a depth of experience and expertise that is at the forefront of the telematics data aggregation industry.
But overarching this, our purpose is to address the challenges of connected data and with that, help make the working world a safer place.
As an expression of this, CMS’ business and our solution is grounded on these three guiding principles:
Our approach is to combine telematics data with any other relevant data the organisation has.
Such as training plans, driver reviews, and traffic offences.
To create a fuller picture of the risk factor at driver/employee, depot, division, and organisation levels.
From this, our focus is on providing clear actionable information to enable users to answer four principal questions:
One: Is my organisation’s risk profile going up or down?
Two: What behaviours are causing this change?
Three: Which employees or drivers are the biggest contributors to my risk profile?
Four: What incidents are occurring right now that I need to respond to?
As a result, the platform to do this, our telematics data aggregation, risk analytics and incident detection software, is used by fleet operators, and insurers across the world.
Enabling them to
By utilising their data to automatically identify and intervene with high risk drivers, and reduce incident frequency.
Through receiving real-time, accurate collision alerts without having to review large volumes of false alerts.
By accessing consistent and comparable connected vehicle data from any new or existing installed telematics system.
Many CMS customers use our platform to score all the risk data they have, for targeted training intervention.
All of this gives our customers the power to transform their duty of care, claims and risk management programmes for drivers & remote workers.
Thus, reducing claims frequency, costs and making for a safer world.
If you are a faced with too much data from your telematics systems, or wish to improve your risk management process, then a chat with us would be a great place to start.
We have helped fleets and insurers manage their data in the most efficient ways possible.
By collecting their telematics data, camera footage and HR related data direct from all their sources, then aggregating it and standardising it and displaying it all in one system they have all seen a massive ROI in the first year.