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As a leading QSR company in China, The client owns a number of well-known catering chain brands under its affiliation, and currently runs over 10,000 restaurants across the country.
The huge multi-level supply network, rapid store growth plan, and complex data system require the supply chain team to upgrade the supply chain through digital systems and management processes to achieve refined operations and help enterprises reduce costs and increase efficiency continuously.
The store coverage is to be optimized. The current network coverage of customers is affected by market-oriented administrative divisions, and it is often the case that the distribution center in the province only meets the needs of stores in the province. With the expansion of business and the increase in the number of stores, the phenomenon of "seeking far and wide for what lies close at hand" will be prominent, resulting in high store delivery costs./p>
The existing network is extremely complex. With the continuous growth of the number of stores and warehouse density, manual estimation and past experience can no longer meet customers' needs for more refined management, and the resilience of the supply chain are also facing challenges.
Data scale and quality poses a problem for us. The scale of data has reached a 0.1 billion milestone, and since the data are collected from multiple systems, there are many inconsistencies in the statistical methods of system data.
The project team, with a comprehensive consideration of factors such as distance, transportation rate, warehouse cost, and operation capacity, establishes an optimization model, re-examines the rationality of the network coverage relationship, selects the area with the greatest opportunity for optimization and adjustments, and assists customers in promoting the implementation of the scheme.
By using the "Hetu" product, the project team models the fine granularity and compares the differences between multiple versions through what-if analysis. Moreover, through knowledge transfer, it improves the solution capabilities of the customers' supply chain team to meet the needs of customers for refined operation and continuous optimization of the supply chain.
The project team uses Python and SQL to clean, verify and analyze data. It communicates with customers promptly to confirm key assumptions for missing or poor-quality data. Furthermore, the project team cleans defined data quality issues and improvement actions during the implementation period to support the optimization of customers' business and IT team's data governance.
Through digital solutions, we can optimize the customers' supply chain network relationship with finer granularity, which is expected to help customers save millions of yuan in terminal distribution costs. Meanwhile, the customer team can continue to use the digital model to tackle the dynamic changes of the future business, which truly helps customers reduce costs constantly and increase efficiency, and achieve high-quality business growth.