Analysis of SF Instant's Fresh Food Category Spoilage Rate Control Strategies
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Based on the collected data, I will systematically analyze the strategies and practices of SF Instant (HK09699) in controlling the spoilage rate of fresh food categories.
According to data from the Cold Chain Logistics Professional Committee of the China Federation of Logistics & Purchasing, the spoilage rate of fresh agricultural products in China’s circulation links is much higher than that in developed countries [1]:
| Category | China’s Circulation Spoilage Rate | Developed Countries’ Level | Gap Multiple |
|---|---|---|---|
| Fruits & Vegetables | 25% | 5% | 5x |
| Meat | 12% | 3% | 4x |
| Aquatic Products | 15% | 5% | 3x |
- Full-Link Temperature Control System Not Yet Connected: Approximately 65% of primary agricultural products are not pre-cooled within 24 hours after harvesting [2]
- Cold Chain Breakage Crisis: 62% of B2B deliveries use open-air loading and unloading, and a temperature difference of over 15°C increases the rot rate of fruits and vegetables to 40% within 24 hours [2]
- “Pseudo Cold Chain” Dilemma: 75% of C2C deliveries use the “foam box + ice pack” model, with insulation validity of only 6-8 hours [2]
- The industry average spoilage rate is about 25-30%, much higher than the 20% in the United States and Japan [3]
As the
- Cooperate with full-platform partners including Douyin, WeChat, Meituan, Ele.me, and JD Flash Delivery [4]
- Provide customized fresh food delivery solutions for chain supermarkets and catering enterprises
- Respond to order fluctuations through an elastic capacity network to ensure delivery timeliness
SF Instant’s self-developed CLS Urban Logistics System covers three core functions [4]:
| Functional Module | Technical Connotation | Spoilage Control Effect |
|---|---|---|
| Intelligent Business Planning and Marketing Management | Predicts order fluctuations and comprehensively coordinates front-end marketing strategies | Reduces waiting time for fresh food |
| Integrated Rider Dispatching and Intelligent Order Distribution | Optimal matching of orders and riders to reduce rider pressure | Improves fulfillment stability |
| Intelligent Operation Optimization | Optimizes route planning, acceptance willingness, and in-store waiting time | Shortens delivery duration |
SF Instant has reached cooperation with multiple domestic large model manufacturers, achieving [4]:
- User Demand Preference Analysis: Accurately predicts fresh food demand to reduce inventory backlog
- Merchant Operation Strategy Optimization: Intelligent restocking suggestions to reduce unsalable spoilage
- Intelligent Customer Service Q&A: Rapid response to abnormal situations
- Delivery Process and Capacity Dispatching Management: Real-time dynamic adjustment to ensure fresh food quality
SF Instant is accelerating the layout of its “AI + Unmanned” strategy [4]:
- Unmanned Vehicle Delivery: As of H1 2025, unmanned vehicles have been deployed in more than 60 cities across the country, with the operation scale increased to300 units, and the monthly average active trips are about 20,000
- Single-day delivery volume can reach 3,000 orders, reducing labor costs by 50% directly
- Complete “Sky, Ground, Human” Delivery Ecosystem: Unmanned delivery + two-wheeled/four-wheeled vehicles + riders, forming multiple human-machine collaboration modes
- White Rhino R5 Unmanned Vehicle: Equipped with high-precision lidar, perception cameras, intelligent path planning, and second-level response
SF Instant, through ecological collaboration with SF Group, has built an integrated supply chain solution of
| Link | Technical/Service Features | Spoilage Control Function |
|---|---|---|
| Origin End | Based on cold transport trunk network and warehouse network | Pre-cooling treatment to reduce “first kilometer” spoilage |
| Trunk Transport | Cold Transport Express, Cold Transport Full Truck | Full-process cold chain controllable with real-time temperature control |
| Last-Mile Delivery | Cold Transport Store Delivery, Same-City Instant Delivery, C-End Home Delivery | Quality assurance for the last kilometer |
| Temperature Zone Management | Multiple temperature zones for refrigeration, freezing, and room temperature | Classified storage with precise temperature control |
- Transport temperature range: Refrigeration, freezing, room temperature
- Applicable consignments: Primary agricultural products (vegetables, fruits, livestock and poultry meat, eggs, aquatic products), processed foods (frozen foods, dairy products, catering raw materials) [5]
| Delivery Distance | Committed Time Limit | Actual Performance |
|---|---|---|
| Within 3 km | 30 minutes | Average 22-23 minutes |
| Within 5 km | 60 minutes | Average 50-55 minutes |
High timeliness directly reduces the in-transit time of fresh food and lowers the risk of spoilage.
- Diversified Capacity Integration: Meets diverse order needs, enabling immediate pickup and delivery without transshipment [5]
- Peak Elastic Dispatching: Ensures fulfillment capacity under special circumstances such as severe weather and peak hours
- Last-Mile Delivery: In-depth collaboration with SF Group to obtain more “last mile” orders, making the delivery network more stable [4]
- Damage/Loss Compensation: Compensates according to the agreement, with a maximum limit not exceeding the actual sales value of the commodity [5]
- Full Amount Guarantee Service: Under the condition of full amount insurance, compensation can be received as fast as12 hoursafter application
- Full-Process Traceability: Intelligent information system empowers full-process management of cold chain logistics
According to industry research data, Ocado’s spoilage rate is only
- Robot automatic picking: “Goods to person” mode improves efficiency
- Backend logistics capacity utilization rate reaches as high as 81.25%
- Refined management of over 50,000 SKUs
| Improvement Direction | Current Measures | Future Development Focus |
|---|---|---|
| Intelligentization | CLS System + Large AI Models | Deep learning model optimization |
| Unmannedization | 300 unmanned vehicles in operation | Expand coverage |
| Refinement | Multi-temperature zone management | SKU-level spoilage tracking |
| Collaboration | Group ecological integration | Tighter supply chain collaboration |
- Instant Retail Track Dividend: The scale of the instant delivery industry is expected to achieve a CAGR of 18.9% from 2023 to 2028 [4]
- Deepened Cooperation with Head Customers: In 2024, it cooperated with head brands such as Sam’s Club, Kenjoy Coffee, and A’Ma House, adding more than 7,500 cooperative stores [4]
- Beneficiary of Traffic Polarization: As an independent third-party platform, it undertakes overflow orders from various platforms
- Intensified Subsidy Competition: The food delivery war may lead to fluctuations in profitability
- Cold Chain Infrastructure Investment: Requires continuous capital expenditure
- Rising Labor Costs: Pressure on rider cost management
[1] China Federation of Logistics & Purchasing Cold Chain Logistics Professional Committee, Research Report on Agricultural Product Origin Cold Chain
[2] Research on the Current Situation and Optimization Strategies of China’s Fresh Food Cold Chain Logistics, 2025
[3] Logistics Zhixin, “Dry Goods: Disassembling Density Model and Loss Reduction Model, the Only Two Profitable Ways for Fresh Food E-commerce?”
[4] Shanxi Securities, SF Instant (09699.HK) Overweight - A (Initiation) Research Report, October 21, 2025
[5] SF Express Official Website, “Introduction to Cold Transport Store Delivery Service”
Insights are generated using AI models and historical data for informational purposes only. They do not constitute investment advice or recommendations. Past performance is not indicative of future results.
About us: Ginlix AI is the AI Investment Copilot powered by real data, bridging advanced AI with professional financial databases to provide verifiable, truth-based answers. Please use the chat box below to ask any financial question.
