How Automakers Are Rethinking Retailer Network Management

Automaker retail networks are getting harder to run. Shifting market demands, new retail formats and mounting competitive pressure are forcing OEMs to rethink how they plan, manage and optimize their dealer footprints — and tracking sales or service figures alone no longer cuts it.

According to analysis from Urban Science, effective network management rests on a repeatable, data-driven process rather than one-off reporting. The framework starts with a simple question: what is actually happening across the network? Answering it requires a consistent set of key performance indicators, supported by four core datasets — vehicle sales, service performance, market coverage and demand forecasting. Together, these reveal which retailers and regions are beating expectations, where market share is slipping, whether service demand is being met, and how the network as a whole is tracking against strategic goals.

Once a weak spot is flagged, the harder work begins: understanding why it exists. An underperforming store might be losing ground to local rivals, missing sales targets or running half-empty service bays — but the numbers alone don’t explain the cause. That requires market studies that distinguish between a retailer problem, an underserved market, constrained capacity or a misaligned territory. From there, OEMs can weigh concrete options such as opening new points, relocating or consolidating stores, redrawing territories and preparing for electric vehicle service readiness.

The execution stage is where many network strategies stall. Adding, moving or selling a retail point, reworking a contract or realigning a market involves multiple stakeholders, approval chains, legal records and audit obligations. Without a centralized system to coordinate and document these steps, changes become difficult to monitor and defend. Standardized workflows for approvals, communication and accountability help OEMs move quickly while keeping confidence in the process.

Urban Science frames this as a continuous loop: measure network health, identify targeted interventions, execute through structured governance, then feed the results back into the next round of decisions. As an illustration, the firm says it worked with a multi-brand automaker whose market studies were spread across teams, tools and decades of records — unifying those workflows cut study timelines from several years to under six months and removed roughly 1,600 to 1,800 hours of administrative work annually. The broader point is that network planning, management and optimization now need to operate as one connected system rather than separate exercises.

This article was produced in collaboration with Urban Science.