What is reactive maintenance?

Maintenance is reactive when it's carried out as and when faults or breakdowns occur. Although this is rarely an active strategy for fleets, they can find themselves reverting to reactive maintenance due to operational constraints or unexpected vehicle faults that occur outside of the scheduled services of a preventive maintenance programme.

What is preventive maintenance?

In a preventive maintenance programme, vehicles are assigned a service schedule interval based on a combination of their age, duty cycle and usage (commonly measured by mileage). This helps fleets to comply with DVSA requirements, but can cause fleets to slip back into reactively managing breakdowns when faults go undetected.

What is predictive maintenance?

Predictive maintenance (PdM) uses vehicle data to predict when fleet vehicles need repairs. PdM reduces vehicle downtime and maintenance costs, and improves vehicle health, since minor faults can be identified and resolved before they escalate into larger, more expensive faults.

How is fleet maintenance software used to improve fleet maintenance?

Fleet maintenance software can help you stay on top of maintenance reminders, view diagnostic trouble codes (DTCs) that indicate the need for predictive maintenance, manage workflows and inventories, and balance scheduling to increase vehicle uptime and decrease costs.

What does the best fleet maintenance software do?

The best fleet maintenance software enables fleets to automate DVSA compliance, with digital DVIRs and logs to proactively address issues and prepare for audits. It will connect all your fleet and maintenance data so that fleets get the actionable maintenance insights they need to make faster, smarter decisions. And it will provide rich vehicle data, supported by advanced AI, so that the workshop can identify and resolve minor issues before they escalate into serious faults.

What is the best telematics provider for fleet sustainability?

Geotab's fleet telematics solutions are centred on helping fleets to improve their sustainability performance by driving down their fuel consumption. Driving performance is scored against the common metrics of eco-driving, idling reports allow managers to reduce this wasteful practice, and drivers can receive in-cab feedback to improve their fuel economy in real-time. Geotab's route optimisation tools allow for the most fuel-efficient routes to be taken, and vehicles' fuel efficiency can be optimised with predictive maintenance solutions.

What are the systems that a telematics-based predictive maintenance system should monitor to improve fuel efficiency?

A predictive maintenance programme built around telematics data can provide substantial fuel savings and reduce the fleet's operating costs. By monitoring the health of the following components, fleets can realise substantial fuel savings, as well as improve the long-term condition of the vehicle: Engine oil levels Condition of intake and exhaust systems Engine temperatures Engine cooling system condition Air compressor performance Wheel alignments Tyre inflation levels Fuel filter system condition Condition of the battery, starter motor and alternators Air conditioning system condition

How to reduce fleet downtime with telematics?

A telematics device collects diagnostic trouble code (DTC) and engine data and sends it to the fleet maintenance software, which generates notifications and alerts when faults are detected. The workshop can triage their vehicle servicing schedule based on the severity of the faults, ordering parts in advance and considering vehicle usage schedules. The maintenance work can then be carried out on time using the workflow and inventory management capabilities of the fleet maintenance software. This reduces the amount of time that the vehicle has to be off the road.

Fleet Management

How predictive maintenance reduces downtime and costs for large fleets

Predictive maintenance uses real-time telematics data to prevent costly breakdowns, reduce fleet downtime and lower maintenance costs for large fleets.

By Geotab Team

Jun 23, 2026

Fleet technician using tablet for predictive vehicle maintenance

Key Insights

Predictive maintenance (PdM) uses data to predict when fleet vehicles need repairs.

Using data-driven vehicle insights, PdM can help reduce fleet maintenance costs and improve vehicle uptime.

Fleets using predictive maintenance can save up to £20,000 per engine fault avoided, based on Geotab customer data.

Predictive maintenance reduces fleet downtime and costs by using real-time telematics data to identify potential vehicle faults before they cause breakdowns, allowing fleet managers to schedule repairs at the right time rather than reacting to failures or over-servicing vehicles on fixed schedules.

When it comes to fleet maintenance, there are three categories that fleets follow. These are evolutionary in nature, with each one offering improvements in efficiency, safety and cost savings over the previous form. Large fleets, particularly those with over 100 vehicles, are now shifting away from purely preventive maintenance, implementing predictive maintenance programmes that use real-time vehicle data to predict potential failures before they develop into costly major faults and service-impacting breakdowns.

What are the different fleet maintenance types?

In order of evolution, these maintenance categories are summarised below:

Maintenance type	Reactive maintenance	Preventive maintenance	Predictive maintenance
Description	Vehicle maintenance is carried out as and when faults or breakdowns occur. Fleets sometimes revert to reactive maintenance due to operational constraints or unexpected failures.	Vehicles are assigned a service schedule interval based on a combination of their age, duty cycle and usage (commonly measured by mileage).	Vehicle data and analytics are monitored in real-time to predict potential equipment failures in advance.
Downtime	High — parts must be ordered reactively, often resulting in delays that keep vehicles off the road for longer, and workshop capacity cannot be managed effectively.	Lower — as long as service intervals have been correctly identified and upheld, and breakdowns don't occur outside of scheduled maintenance.	Lowest — PdM flags faults in advance so that the workshop can order parts in advance and manage workflows for timely maintenance.
Maintenance costs	High — since there is no planning, repairs are generally urgent in nature to get the vehicle back on the road as quickly as possible. In some instances, hire vehicles have to be used to cover the downtime, further increasing costs.	Lower — most maintenance can be scheduled in advance, avoiding costly emergency repairs. However, if faults occur between the scheduled maintenance intervals, then it reverts to being reactive in nature, which can cause costs to swell.	Lowest — PdM can reduce maintenance costs compared to preventive maintenance, basing the need on actual vehicle data, as opposed to over-servicing vehicles on pre-defined schedules.
Results	Escalating fleet risk due to unplanned failures.	Fleets have the structured inspection schedule they require for DVSA compliance.	Risk is proactively reduced, and vehicles are kept in optimal health.

How does fleet telematics data enable predictive maintenance?

Telematics devices can extract vehicle health data points from a wide range of sources, presenting the workshop manager with real-time diagnostic trouble code (DTC) data through dashboards or notifications in the fleet management platform, including:

Engine diagnostics
Vehicle fault codes
Usage patterns
Tyre pressure monitors
Wheel alignment monitors

This allows vehicle health to be proactively optimised to reduce the risk of unplanned downtime. The workshop can schedule timely maintenance to rectify these minor issues before they develop into larger problems that risk service disruption and costly repairs.

What are the benefits of predictive maintenance for large fleets?

When large fleets implement predictive maintenance programmes, the benefits are manifold. This table summarises the pros and cons of predictive maintenance.

Advantages of predictive maintenance	Disadvantages of predictive maintenance
Reduces costly downtime by eliminating surprise repairs that may be needed between the regular service intervals of a preventive maintenance schedule.	Takes some time and effort to implement the new system.
Reduces workshop visits and costs, as maintenance is carried out based on its predicted need, rather than an arbitrary schedule.	Fleets will need to prioritise the vehicle health indicators where predictive maintenance will generate the greatest return on investment (ROI).
Improves fleet safety by proactively identifying minor issues before they develop into larger, safety-impacting faults.	The workshop and fleet management team will require additional training to understand and accurately triage the fault codes they receive.
Boosts fuel efficiency by optimising vehicle health, reducing fuel consumption, which is commonly one of the fleet's greatest operating costs.
Increases vehicle service life by optimising health, reducing capital costs across the fleet.
Reduces the likelihood of DVSA violations from vehicles being pulled over with faults that drivers have failed to identify or report.
Improves driver retention by improving their everyday working environment, since vehicles are kept in better, safer condition.

The real-world cost savings of predictive maintenance for a large fleet

The real-world savings of predictive maintenance can be considerable. Go-Ahead Group deployed Geotab telematics in over 6,000 UK buses to access rich real-time Diagnostic Trouble Code (DTC) data. With this solution, the engineering department can now look out for early signals that their vehicles need repair. These maintenance insights help the team to take advanced interventions to keep their buses on the road and ensure that route schedules are adhered to. This mitigates the risk of performance-related fines and saves thousands of pounds by identifying minor problems before they escalate into expensive repairs or catastrophic failures.

With the help of Geotab's data, Go-Ahead London has unlocked substantial maintenance cost savings, including:

Preventing catastrophic engine failures by monitoring low oil pressure; between 8 and 10 vehicles are identified per month at Go-Ahead London, saving up to £20,000 per engine.
Avoiding over 10 breakdowns in the first month alone by monitoring coolant temperature and detecting faulty sensors. When considering the maintenance costs and the need to provide a replacement vehicle, the cost savings are significant.

How to start integrating fleet telematics data for predictive maintenance

The transition from preventive to predictive maintenance begins by integrating telematics data into existing maintenance processes, allowing the workshop to gradually build a more proactive approach to vehicle health management.

Fleets should start by identifying their most common faults and considering which vehicle systems create the greatest operational and financial risk when they fail. This can include engine faults, cooling system issues, tyre pressures and battery health. By configuring telematics dashboards and notifications around these high-priority indicators, workshop teams can focus their attention where it will have the greatest impact.

Once real-time vehicle health data is available, maintenance teams should establish clear workflows for reviewing and triaging diagnostic trouble codes (DTCs). Not every fault requires immediate intervention, and understanding which alerts require urgent action and which can be scheduled into upcoming maintenance windows helps to maximise vehicle uptime while avoiding unnecessary workshop visits. By combining telematics data, maintenance expertise and structured workflows in this way, fleets can proactively optimise vehicle health.

How Geotab's predictive maintenance insights improve vehicle condition

Geotab's predictive fleet maintenance software makes real-time diagnostic trouble code (DTC) and rich engine data available through dashboards or notifications that the workshop manager can use to act in the moment. The highly granular and customisable data is then analysed by advanced AI to predict potential problems in advance, comparing it against hundreds of thousands of data points from Geotab-connected vehicles to pick out patterns that have led to distinct failures in the past, potentially weeks before the failure occurs.

The workshop manager then has the data they need to triage minor issues in the necessary order to maximise fleet health and reduce the likelihood of major faults that carry the risk of breakdowns and the expense of vehicles off the road (VOR), and could otherwise impact service delivery.

Contact our team of experts today to learn how your fleet could benefit from implementing a predictive maintenance programme.