At Alibaba Digital Agriculture, I was responsible for the counting agriculture supply chain planning project.Through data model and algorithm optimization, this project realizes digital decision-making in the supply chain, reduces operating costs, and improves turnover efficiency.

# Project Background

Traditional supply chain management relies on manual experience and lacks data support, resulting in inaccurate procurement plans, inventory backlogs, and low turnover efficiency.We hope to achieve intelligent decision-making in the supply chain through data models and algorithms.

# Data Model Design

We have designed a data model for the integration of supply and marketing:

# # 1. Procurement Model

Forecast future demand and develop purchase plans based on historical sales data, market trends, seasonal factors, etc.The model considers several factors:

• Historical sales data: analysis of historical sales trends and patterns
• Market Forecast: Forecast changes in market demand
• Seasonality: take into account the seasonal characteristics of agricultural products
• Price Factor: Consider the effect of price on demand

# # 2. Production planning model

Develop a production plan based on the procurement plan and capacity.The model optimizes the production schedule and improves production efficiency.

# # 3. Sales Forecasting Model

Predict sales in different channels and regions to optimize sales strategies and inventory allocation.

# Algorithm Optimization

We use a variety of calculations