Predictive maintenance that drives revenue and builds loyalty

From eliminating costly breakdowns to optimising spare parts inventory, AI-driven insights will streamline your operations and improve customer loyalty. Welcome to a smarter, more profitable way to manage your automotive business. 

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Predictive maintenance

From reactive to predictive: revolutionising maintenance in automotive industry

For decades, the automotive aftersales sector has relied on reactive or preventive maintenance models – addressing issues after they occur or attempting to guess when they might. The result? Unexpected breakdowns, unnecessary costs, and missed opportunities for building brand loyalty. 

Predictive maintenance changes the landscape. By combining real-time sensor data, AI, ML, and true cross-functional collaboration, OEMs and aftermarket leaders can predict failures, personalise services, and optimise operations. 

Turn data into business impact

Predictive maintenance can play a crucial role in your business strategy. The numbers speak for themselves: 

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40%

reduction in unplanned repairs
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20-35%

decrease in inventory costs
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Over 95%

parts availability across service levels
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60%

of customers cite reduced service expenses as a key loyalty factor

Your 5-step roadmap to predictive success

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1

Assessment and planning

Audit current workflows – Identify inefficiencies in reactive and preventive maintenance.

Set measurable goals – Aim to reduce unplanned downtime, improve reliability, and cut costs.

Create synergy – Build a task force across Maintenance, IT, Procurement, and Logistics.

2

Data collection and analysis

Utilise existing telematics data – Integrate sensors and data loggers to capture vehicle performance metrics, such as engine vibration and temperature.

Review historical data – Identify recurring issues, patterns, and trends from past records.

Integrate AI/ML – Use AI and machine learning tools to analyse real-time and historical data for predictive insights.

3

Predictive maintenance

Develop a predictive model – Create a model to forecast potential vehicle failures based on data patterns, before issues arise.

Set up an alert system – Notify maintenance teams of impending issues.

Schedule maintenance – Implement a proactive maintenance schedule.

4

Integration and optimisation

Establish cross-functional collaboration – Ensure seamless communication between Maintenance, Procurement, and Logistics to align operations.

Optimise costs – Eliminate unnecessary repairs and optimise resource allocation.

Continuously refine – Enhance the accuracy of predictive models.

5

Monitoring and evaluation

Track what matters – Establish KPIs to measure downtime reduction, service cost savings, part availability, and client satisfaction.

Implement a feedback loop – Update predictive models based on real-world outcomes.

Drive strategic expansion – Apply predictive maintenance strategies to other areas within the organisation or fleet.

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Assessment and planning
Data collection and analysis
Predictive maintenance
Integration and optimisation
Monitoring and evaluation

What predictive maintenance looks like in action

01

Forecast failures before they happen

HOW

How it works

  • Onboard sensors and historical data are utilised to monitor key vehicle performance metrics like engine temperature, oil quality, and tyre pressure. 
  • ML algorithms analyse these metrics to identify patterns that may indicate potential issues. 
  • Unusual patterns trigger real-time alerts to car owners via a mobile app or email, allowing them to schedule maintenance before the problems escalate. 

BENEFITS

Benefits

  • Reduced unexpected breakdowns 
  • Increased safety by addressing issues before they lead to accidents 
  • Stronger brand trust thanks to proactive care 
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Personalised maintenance scheduling

HOW

How it works

  • Driving habits, climate conditions, and vehicle usage patterns (such as mileage, speed, and acceleration) are analysed. 
  • Predictive models adjust based on the collected data. 
  • Customers receive proactive alerts and personalised maintenance schedules, ensuring that checks and repairs are performed at optimal times. 

BENEFITS

Benefits

  • Better vehicle performance and fuel efficiency  
  • Reduced service friction 
  • Increased customer satisfaction and retention 
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Spare parts inventory optimisation

HOW

How it works

  • Integrate historical sales data, vehicle usage patterns, economic indicators, and weather data. 
  • Deploy a Support Vector Regressor (SVR) for parts with stable demand, and hybrid models for those with erratic demand, as supported by recent research. 
  • Categorise Stock Keeping Units (SKUs) into tiers (e.g., Platinum, Diamond, Gold) based on demand frequency and criticality to prioritise stocking strategies. 

BENEFITS

Benefits

  • 30% reduction in overstocking 
  • Stockouts reduced by 50% 
  • Optimal inventory levels ensured 

Why you should take the leap

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Break down silos with unified data

Fragmented data across departments leads to inefficiencies and miscommunication. A unified data platform solves this by consolidating historical and real-time information from sources like CRM, ERP, and IoT systems into one cohesive ecosystem. 

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Collaborate across departments

With shared, up-to-date data, teams can work together more effectively. For instance, Claims Management provides insights to Spare Parts Planning, leading to smarter forecasting, while GCC directors seamlessly align with technical teams. 

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Integrate without disruption

A modern data platform connects with your existing tools, eliminating the need for a steep learning curve. It streamlines workflows and uses artificial intelligence to automate data processing, reducing manual effort and minimising disruptions. 

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Make decisions with real-time insights

Tailored dashboards provide predictive alerts and demand forecasts to decision-makers at all levels. This leads to faster, smarter decision-making and less dependence on third-party analytics. 

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Unlock the power of predictive maintenance for your automotive business

Paweł Grygiel

Pawel Grygiel

Director of Automotive

+48 504 758 786