Auto-parts Chain System
Auto-parts Chain System · Scenario
Challenge
Guangzhou Howard is an auto-parts chain with multi-tier stores and regional agents — high procurement and support costs, with stocking and pricing decisions long lacking data support.
stores, regional agents and HQ couldn't share data; procurement and inventory fragmented.
stores and agents relied on manual ordering and phone support — slow and costly.
lacking sales and inventory data, stocking and pricing relied on gut feel, causing overstock or stockouts.
scattered operational data couldn't support management decisions.
Solution
We built a digital auto-parts chain platform where stores and regional agents self-procure online, end customers self-order, and operational data drives stocking and pricing.
stores and agents order online with tiered permissions and pricing.
end customers self-order, lowering support cost and speeding response.
coordinated store / regional / HQ inventory with multi-tier visibility.
unified sales, inventory and procurement data as a data asset.
stocking suggestions, pricing analysis and fast / slow-mover insights for management.
Results
Procurement moved from support-dependent to online self-service, and operational data moved from scattered to unified, giving decisions a real basis.
, with stores and agents self-ordering and markedly lower support cost.
, with healthier turnover and less overstock.
, providing a basis for management decisions.
, with stores, regions and HQ sharing information.