During the 2023 Global Smart Logistics Summit, Cainiao Logistics Technology officially released its new digital supply chain product "Supply Chain Plan". The product has attracted industry attention since its launch, and many customers and merchants have inquired about its related features. To this end, we have specially communicated with Fang Zeling, a product expert in Cainiao Logistics Technology (nickname: Huizhen), to deeply introduce the “supply chain plan” in a Q&A format.

Q: What scenarios is the “Supply Chain Plan” product from Cainiao Logistics Technology suitable for?

A: The Cainiao Supply Chain Plan has implemented demand planning based on sales forecasts, inventory planning based on global optimization, replenishment planning based on intelligent distribution, and production planning scheduling based on operations optimization. It provides the planning team with operational tools to make good plans, helps them achieve simulation optimization under multiple business goals, provides a unified collaborative portal for planning coordination parties, and provides supply chain managers with tools for visual analysis of the entire chain.

Q: How does Cainiao Logistics Technology's “Supply Chain Plan” balance inventory planning with different customer demands?

A: When it comes to inventory planning, different companies have different approaches. Some companies prioritize safety stock because they don't want to run out of products. On the other hand, some companies focus on inventory turnover because they want to minimize the cost of capital tied up in inventory. Some companies even prioritize sales rate and avoiding stock shortages.

For different inventory targets, Cainiao “Supply Chain Plan” can achieve overall optimization. By combining specific business indicators and optimization goals, we can choose different inventory models and then set goals for overall cost savings, thereby generating the system's recommended best solution.

While producing this plan, the system will quantitatively display the impact of the plan on overall costs and inventory levels, and project the impact on inventory turnover in the future. It will then explain to the user why the system recommends this particular plan.

A: What are the advantages of Cainiao Logistics Technology in production planning and scheduling?

A: Cainiao “Supply Chain Plan” can simulate production weekly plans and daily plans based on its ability to optimize operations, specifically for cases such as rush orders or shortages. In this process, taking into account the material constraints of the existing procurement plan, the actual available saturation of the existing production capacity, and the manpower allocation of the existing workshop, a production week plan and daily plan with the shortest overall production time and the lowest overall cost are generated.

Previously, people needed to deal with many complex process logic and resource situations, but now they can help people solve the standardization of the data layer and the implementation of the logic at the algorithm layer, helping users deal with the optimal solution for shipping under complex production logic.

A: Which industries is Cainiao “Supply Chain Plan” suitable for?

A: Up to now, this product has been implemented in three industries, namely fast-moving consumer goods retail, industrial manufacturing, and automotive industry.

In the case of fast-moving consumer goods industry clients, the main focus is on inventory optimization, transforming pull-based replenishment into push-based replenishment, and optimizing finished product inventory by 10%.

In industrial manufacturing cases, production planning and scheduling optimization are mainly aimed at the scenarios of inserting orders and material shortages. In this scenario, we have effectively shortened the delivery cycle by 10%.

In collaboration with a client in the automotive industry, we have implemented a demand forecasting solution for automotive spare parts, focusing on product labeling and demand prediction. This has resulted in a 20% increase in forecasting accuracy.