Jiangsu Wenfeng Auto Chain Development Company, established in 2003, has seen the ups and downs of automobile retailing in China. It sells brands that include Mercedes-Benz, Cadillac, Lexus, and Volvo through dealerships in several major Chinese cities.
Over the past few years, the once red-hot auto market in China has cooled due to lower-than-expected sales, overproduction, increased competition, and changing consumer tastes.
Wenfeng Auto leadership sees tougher times as a chance to gain market share through better operations—overhauling processes for data management, marketing, supply chain, financial controls, and executive decision-making. At the same time that it was getting a better handle on its data, Wenfeng Auto also moved to a more customer-oriented approach to its operations.
Due to complex management processes, the domestic auto retail service industry is backward in digital operation management.Yingzhen Gu, Vice President, Wenfeng Auto
The rapid cooling of China’s domestic vehicle sales in 2018 drove Wenfeng Auto to look for ways to improve how it collects and uses its business data. Doing this required tearing down information silos, because data was often held at dealerships.
Wenfeng Auto chose Oracle Autonomous Database running on Oracle Cloud Infrastructure as the centerpiece of its digital transformation. Autonomous Data Warehouse’s cloud-based architecture and self-patching capabilities freed the company from expensive IT operations and maintenance. Using pay-for-use models for compute, storage, and networking resources also lowered costs.
With all its data residing in a single platform, Wenfeng Auto now has real-time access to front-end sales data and other financials, which provide quick insights via reports that previously took days to run. With multidimensional deep analytics enabled by Oracle Autonomous Data Warehouse, the company can target its marketing more precisely, resulting in an 8% increase in sales revenue.
Oracle Autonomous Database
The Wenfeng Auto financial department can now create statistical analysis reports in hours instead of days, improving the value of financial reporting and accelerating executive decision-making.