Software-Defined Aftersales: The OEM’s Next $150 Million Opportunity

The vehicle already knows what is wrong with it. The real question is whether the service network is listening.

Our value assessments with automakers (OEMs) show that a large OEM's aftersales network can hold more than $150 million in untapped annual value. With over 20 years of experience in vehicle software and diagnostics, from engineering to the workshop floor, we have seen how value is lost in the gap between how vehicles are engineered and how they are serviced.

Closing this gap is important not just for OEMs, but also for the customers they serve. Aftersales delivers three to five times the operating margin of new vehicle sales, while nearly one in two drivers could potentially switch brands after a frustrating service experience. The quality of the service experience, therefore, has a direct bearing on both customer retention and business performance.

Customer expectations make this even more significant. Across the services they use every day, be it e-commerce, food delivery or digital banking, customers have come to expect speed, convenience and transparency. They are coming to expect the same from vehicle servicing, whether it is quicker diagnosis, clear communication about repairs, visibility into service timelines or fewer unexpected costs. Traditional aftersales processes often struggle to meet these expectations.

The challenge is not a lack of information. Modern vehicles generate extensive data about their condition through dozens of electronic control units, but much of it never reaches technicians in a usable form when they need it. Software can bridge this gap by connecting diagnostics, vehicle data and AI-enabled workflows, helping service teams make better decisions, anticipate maintenance needs and deliver a more seamless service experience.

Rethinking the service journey

A closer look at day-to-day aftersales operations reveals where established processes fall short and how better use of vehicle data can make a difference. Three key lessons emerge from different stages.

The first lesson is that the service visit begins well before the vehicle arrives. When connected data flags an emerging fault early, the right part and the right technician can be ready in advance, and some issues can be resolved remotely altogether. Even for unplanned visits, capturing the vehicle's data and the customer's symptoms accurately at intake shapes everything that follows, from bay allocation to parts planning. In our experience, predictive maintenance can reduce unplanned downtime by 15-20%. For commercial vehicle and off-highway operators, where every idle day means lost revenue or a stalled site, that is the difference that matters the most.

The second lesson is that many repeat repairs trace back to the first diagnosis. Today's faults often sit at the intersection of hardware, software and connectivity, and conventional troubleshooting is not built for that. AI-guided diagnostics, drawing on field data, repair history and engineering knowledge, can reduce repeat repairs by up to 30%. As fewer vehicles return for the same issue, technician productivity improves by 25-30%. For passenger car owners, getting it right the first time is often what decides whether they return to the authorised network once the warranty ends.

The third lesson is that warranty is, in large part, a diagnostic question. When parts are replaced on suspicion rather than evidence, costs rise, parts come back with no fault found and the real root cause stays hidden. Precise diagnosis improves claim accuracy, and the data flowing back helps engineering and quality teams spot emerging patterns earlier, improving the next generation of vehicles as well.

Why the value compounds

None of these improvements sits in isolation. Better intake leads to more accurate diagnosis. Accurate diagnosis leads to the right part, a cleaner warranty claim and a vehicle back on the road sooner. That is why the opportunity adds up to more than $150 million a year for a single large OEM. The gains come from improving the connections between stages of the service process, rather than treating each problem in isolation.

These improvements also have practical implications across the automotive value chain. Dealerships gain more productive bays. Fleet operators gain predictable uptime. Parts suppliers gain better demand visibility. OEMs gain relationships that continue well beyond the warranty period.

But capturing these gains requires OEMs to measure performance across the service journey, rather than assess each function independently. Tracking indicators such as first-time fix rates, repair turnaround times and warranty costs can help identify where improvements are holding and where inefficiencies persist. This gives service leaders a clearer basis for deciding where technology and process changes can deliver the greatest benefit.

Building a smarter aftersales ecosystem for India

India offers a unique chance to apply these capabilities on a large scale. With a rapidly growing number of vehicles on the road and the rising use of connected cars, there is a much bigger opportunity for data-driven servicing. However, access to diagnostic expertise is inconsistent across service networks, which range from city dealerships to highway workshops.

Software can help by making vehicle information and diagnostic guidance available exactly where they are needed. The goal is to help technicians fix issues accurately, no matter where a vehicle is serviced. Achieving this depends on how well automakers blend software into everyday workshop routines, ensuring the benefits turn into practical, on-the-ground improvements. 

The vehicle has always been talking. The opportunity now belongs to those who listen.

Amit Shah is VP and Business Head, Vehicle Diagnostics and Aftersales, KPIT Technologies. Views expressed are the author's own.