From Firefighting to Foresight: How OEMs Navigate Software Quality Challenges

But not all approaches to software quality are created equal.

Some OEMs still rely on reactive strategies: launching task forces only after quality issues surface, often reported by end-users or during late-stage validation. These ad-hoc responses, while sometimes necessary, tend to be expensive, disruptive, and reputationally damaging. In extreme cases, they may lead to recalls, eroded customer trust, and strained supplier relationships.

Others have shifted to a proactive approach: investing early in advanced analytics, automated testing, and AI-powered root cause detection. By catching defects early in the product development lifecycle, these OEMs can iterate faster, reduce costs, and ensure long-term software stability. Instead of firefighting, their teams focus on continuous improvement and robust validation.

This article explores these two mindsets in depth, analyzing the trade-offs, industry examples, and how proactive strategies can become a competitive advantage in the era of software-centric vehicles.

The red curve in the diagram below illustrates a typical reactive approach. Issues are gradually discovered during development, but the real surge happens in the late development phases, just before the Start of Production (SOP). At this stage, the pressure is on, resources are stretched, and task forces are hastily assembled to triage defects. Given the lack of time to fix defects and the inability to postpone production start, vehicles are released to markets at suboptimal software quality levels (point #1 in the diagram). Another way to "solve" this problem is keeping manufactured vehicles in OEM's storage facilities, until software problems have been resolved and vehicles can finally be sold to customers.

Because of inadequate quality analysis, some issues slip through and emerge post-SOP, now impacting real users and requiring costly patches or even recalls (point #2). This case is more severe than the previous one, because it automatically leads to customer dissatisfaction and OEM brand erosion. Unfortunately, this is often still the case today, and many OEMs have been in the news for wrong reasons.

By contrast, the green curve represents a proactive strategy, where advanced analytics, automated testing, and continuous monitoring are used during development. While the number of known issues spikes early, that’s a good thing — because they’re found when there’s still time to fix them efficiently (point #3). As the project progresses toward SOP, the issue count steadily decreases, reducing downstream risk and cost (point #4).

This approach doesn't just improve quality. It shifts the mindset from firefighting to foresight, allowing OEMs to avoid expensive escalations, improve software stability, and protect their brand reputation.

Shifting to a proactive quality strategy isn’t just about peace of mind. It directly improves business outcomes.

OEMs that have adopted early-stage issue discovery and AI-driven analysis have seen measurable gains:

These gains translate to faster time-to-market, fewer last-minute escalations, and reduced reliance on post-SOP patches and costly task forces. Ultimately, it means less disruption for engineering teams and better experiences for end-users.