Five key steps for fleets using data to manage road risk
On average, 70 deaths occur every day on European roads – and these alarming statistics are on the rise.
An estimated 19,900 people were killed last year – a six per cent increase on 2020 – and preliminary figures for 2022 indicate a further year-on-year rise of more than 10 per cent.
Delve deeper and estimates suggest that road collisions are responsible for around six out of every ten work-related accidents. Complacency for fleets is, consequently, not an option.
The global economic outlook may be a gloomy one, but averting eyes from the risk management ball can prove a costly mistake. A safe fleet is a productive fleet, and one that is less susceptible to hefty service, maintenance and repair costs, insurance premium rises, corporate prosecutions and reputational damage.
Despite the inherent nature of road risk, it can be mitigated, reduced or even eliminated through careful analysis and implementation of appropriate control measures.
Business intelligence underpins this process and the increased availability of fleet data offers greater opportunities than ever before to tackle the problem.
Information from an insurer, accident management provider or telematics system, for example, can offer insights into the potential root cause of collisions, poor performance or overall inefficiency, highlighting exactly where problems lie and providing benchmarks for improvement.
1. Foster a positive safety culture
Data can only effectively empower a business, and act as an enabler for fleet managers, if it is supported by an over-arching safety culture.
This should be established by championing a set of core principles through inspired leadership at every level, from C-suite and senior management to drivers.
By sharing a fleet safety vision, risk management initiatives are more likely to gain continuous companywide buy-in. Employees will be clearer about what they are being asked to achieve, how to achieve it and how fleet risk factors impact them.
By establishing a culture of on-road safety drivers will have greater motivation to make meaningful behavioural adjustments and, what’s more, can themselves become advocates for change.
Securing engagement for this with senior management, along with buy-in for data-led risk management initiatives, can sometimes pose a challenge for fleet departments. Making a business case can help demonstrate the potential returns on investment. This involves highlighting the current impact of poor performance and identifying the savings that could be made if KPIs are met.
2. Establish a data policy
With a wealth of intelligence now available, a clear, structured policy is vital, outlining who has responsibility for risk data, with provisions for where and how it’s stored to ensure security and privacy.
To ensure vehicles comply with maintenance standards, for example, the employee responsible should ensure all vehicle servicing and roadworthiness test details are logged and reminders set when services are required. Driver checks would need to be enforced to ensure they are happening on a regular basis, with details recorded.
Telematics systems can be useful here, with solutions having the capability to integrate with hardware and software applications to consolidate data from different sources on a single platform for easier analysis.
Clear goals should be set for what might be achieved using data and these should align with key organisation objectives and values.
3. Devise a framework for identifying and addressing risk
To ensure a risk management programme is coordinated, focused and tailored towards business goals, fleets should establish a framework that forms the bedrock of a continuous process for improvement.
This will outline how risk is identified and analysed, how control measures are developed and how safety policies are fashioned over time.
Risks that should be understood will include those born out of company structure and operational need, such as KPIs for mobile worker response times, proven risks such as those highlighted by insurance claims data, dynamic risks such as those identified through driving behaviour insights and theoretical risks such as those signposted by driver risk assessments.
Strategies to control these risks might include systems for improved mobility decisions and journey planning to reduce fleet mileage, or processes and procedures to ensure best practice. Taking driver fatigue as an example, this might mean enforcing regular breaks to ensure drivers do not spend too long behind the wheel.
4. Set KPIs and measure success
Key performance indicators (KPIs) are an important ingredient to tackling risk and benchmarking improvements.
Using the right data here is paramount. Not all data will align with a business’s risk priorities and so it must be filtered to ensure it provides the requisite insights.
A top-level goal might be to reduce the number of road traffic collisions, but delving deeper, data analysis might mean looking at incidences of harsh steering or braking to improve driving style.
Datasets that inform risk programmes may include insurance claims that reveal when and where incidents occur; total incident costs, including the cost of replacement vehicles, uninsured losses and business disruption; vehicle off road time; maintenance cost per driver; mileage travelled per driver; driving licence penalty points; incidents of speeding and working time behind the wheel.
5. Maintain, monitor and review
Continual evaluation and review of risk data will help ensure that programmes remain effective. This not only allows for improvements to be tracked over time and for areas that require urgent attention to be addressed, but also for emerging issues to be identified and priorities refocused.
Communication strategies should also be reviewed to ensure core risks remain front of mind, with relevant guidance provided to drivers and other risk stakeholders.