Chinese electric vehicle manufacturers are bringing products to market faster than their Western OEM counterparts and people are starting to ask why.
Facing intense competition in their local market, Chinese OEMs like BYD are expanding globally. And as new entrants gain market share, Western OEMs face pressures on price and innovation speed.
Several Chinese OEMs have achieved profitability with their EV offerings, while Western automakers are still losing money on their EV plays. McKinsey & Company reported that Chinese EV OEMs are bringing products to market in about 24 months, compared with 40-50 months for traditional OEMs.
Can Western OEMs catch up? Does it even make sense to try?
What often gets lost in these conversations is what speed actually represents. It’s easy to treat it as a standalone capability—something you either have or don’t—but that’s not how it shows up inside an organization.
Western automakers aren’t slow in a vacuum. They are operating within systems built for a different set of constraints, such as diverse product portfolios and supply chain complexities, which behave differently under pressure.
The issue is not that they need to match speed everywhere; it is that, in certain parts of the design and manufacturing process, automakers lose time grappling with these system limitations, which slows development. Eliminating these bottlenecks—not just replicating the Chinese development model—is where Western OEMs have the greatest opportunity to compete.
Rewriting the U.S. design playbook
For Western OEMs, the design challenge is one of decision quality under complexity. Every design decision carries downstream risk. Managing diverse product portfolios across legacy and next-generation platforms multiplies complexity and the number of design tradeoffs to be made. The critical question is how to make better decisions faster, which requires getting the right knowledge to the right engineers at the right time.
Most Western automakers already have the knowledge and data to understand the downstream impacts of design decisions. The challenge is that it’s scattered: in the heads of experienced engineers, in old files and slide decks, in standards that are intended to be referenced but rarely are in practice.
When speed becomes a priority, engineers don’t have time to go digging through old programs to reconstruct design rationale. So, they rely on memory to make decisions. When memory is unreliable, those decisions resurface as late-stage errors, tooling failures, warranty claims, lost margin and increased business risk.
The real competitive advantage for Western OEMs is building the systems that ensure their engineers can make high-quality decisions without slowing down to find the information they need.
Western vs. Chinese models for supply chain and supplier collaboration
Chinese EV manufacturers are operating from a different starting point, often building on EV-native platforms with tighter hardware-software integration and more vertically integrated supply chains. Western automakers, by contrast, coordinate across large supplier networks spanning dozens of Tier 1 and Tier 2 partners. That complexity is not going away and it has a direct cost on design velocity.
When design, manufacturing and supplier teams work across disconnected tools—slide decks, email threads, issue tracking spreadsheets—design context gets lost at every handoff. Issues that a supplier flagged in a review meeting go undocumented. Feedback captured in one email thread contradicts feedback captured in another. Engineers spend days trying to determine whether a concern raised three months ago was ever resolved.
McKinsey estimates that Chinese OEMs bring products to market 3-4 months faster because they’ve simplified supplier collaboration. Western OEMs that bring suppliers onto shared engineering platforms, where design feedback is documented in context, assigned, tracked and resolved against the actual CAD, are the ones closing that gap.
AI can help, but only if it starts with the right data
When an organization is simultaneously developing multiple platforms—each with its own set of design standards, supplier relationships and engineering constraints—the risk of knowledge fragmentation compounds. Engineers on a new program are often making decisions that mirror mistakes already made and documented on a previous program. Now, AI-enabled design tools are beginning to make institutional knowledge accessible at the moment it is needed.
The root cause is a design review problem as much as it is a knowledge management problem. Most automotive engineering teams run design reviews through a combination of meetings, PowerPoints with CAD screenshots and spreadsheet issue trackers.
Subject matter experts who could have flagged a DFM issue or a long-lead-time part are never consulted because scheduling a meeting took too long. Issues that were raised verbally are not captured and issues that were captured are tracked in a spreadsheet that nobody follows up on.
Leading automotive OEMs are beginning to address this directly by moving design reviews onto shared engineering platforms that make it easy to review CAD, capture feedback against a saved view state, assign issues to owners and track resolution across internal teams and supplier partners alike. This becomes the knowledge backbone for AI agents that anticipate and flag mistakes before they happen on new programs.
This has ripple effects beyond engineering. When issues surface earlier and get resolved in design, the late-stage surprises that complicate production become preventable, not inevitable. McKinsey has pointed to optimized tooling and supplier integration as key differentiators in development speed and the underlying mechanism is design coordination.
Leading automotive manufacturers are already bringing suppliers onto shared engineering platforms as a direct response to the complexity of managing multi-tier supply chains.
Where we go from here
Western automakers are not going to out-iterate Chinese EV startups. Their path to competitiveness runs through doing what they have always done well: engineering reliable, high-quality vehicles at scale across complex supply chains and eliminating the coordination failures that currently slow that work down.
That means ensuring SMEs can participate in design reviews without a calendar invite, capturing design feedback against the actual model, not a screenshot in a deck and knowing at any moment which issues are open, who owns them and whether they have been resolved. This requires building systems that ensure engineering knowledge is captured, surfaced and acted on before a design decision turns into a late-stage problem that no one can afford to fix.
Taylor Young is the chief strategy officer at CoLab.
