EES Solutions | Engineering, Data, Recruitment

EES Data Solutions’ 18+ years of engineering knowledge within the automotive sector provides you with confidence that you’re working with people with immense domain expertise. They’ll quickly understand your business allowing for more time to develop the solution.

Our work adds value to functions across the various tiers of the supply chain within the automotive sector. From Product Research and Development, Aftermarket, Technical Service Operations, and Warranties within OEMs to the Operations Manager at the customer-facing retailers. While these are the primary functions with whom we liaise, we include all available data so that the final analysis and visualisation is comprehensive.

The benefits

Reduced costs, production downtime, and in-field failures | Increased predictive maintenance

You’ll be able to realise these benefits too.

A recent case study

We were working with an automotive OEM that wanted to understand the details behind a specific issue. Specifically, warranty analysis within the aftermarket: were the warranty claims genuine and which models were showing consistent problems?

For this project, it was decided that the most appropriate approach combined applied data analytics with Natural Language Processing (NLP). Given the nature of the OEM’s issue, NLP was especially important as it applied automatic computational processing of the qualitative data. That is, it efficiently reads the technician and customer comments recorded in warranty claims to identify the root cause of a failure of a particular model or part of the vehicle.

Taking this data that would have otherwise been inaccessible, we were able to, successfully and clearly, display the root causes of issues, faulty components, trends and patterns in production, technician comments, and warranty costs for the company.

This information was clearly communicated to the OEM through a bespoke worldwide warranty tracker dashboard that allowed for top-level trend analysis as well as drilling down into the detail.

A recent case study

We were working with an automotive OEM that wanted to understand the details behind a specific issue. Specifically, warranty analysis within the aftermarket: were the warranty claims genuine and which models were showing consistent problems?

For this project, it was decided that the most appropriate approach combined applied data analytics with Natural Language Processing (NLP). Given the nature of the OEM’s issue, NLP was especially important as it applied automatic computational processing of the qualitative data. That is, it efficiently reads the technician and customer comments recorded in warranty claims to identify the root cause of a failure of a particular model or part of the vehicle.

Taking this data that would have otherwise been inaccessible, we were able to, successfully and clearly, display the root causes of issues, faulty components, trends and patterns in production, technician comments, and warranty costs for the company.

This information was clearly communicated to the OEM through a bespoke worldwide warranty tracker dashboard that allowed for top-level trend analysis as well as drilling down into the detail.