Effective Inventory Forecasting & Demand Planning for eBay Business Expansion

Enhanced Prompt: Comprehensive Strategy for Effective Inventory Forecasting and Demand Planning on eBay for Business Expansion

Objective:
To implement a scalable and data-driven approach to inventory forecasting and demand planning, enabling sustainable business growth and expansion on eBay. The strategy should ensure accurate predictions, optimized inventory levels, and alignment with market demands.

Deliverables:

1. Inventory Forecasting Model: Develop a machine learning-based model using historical sales data, seasonality, and external factors (e.g., Google Trends, economic indicators) to predict inventory needs with 90% accuracy.
2. Demand Planning Framework: Create a demand forecasting system that integrates with eBay's API to monitor competitive pricing and market trends, ensuring 85% accuracy in demand predictions.
3. Tools and Technologies: Utilize Python, R, and Tableau for data analysis; employ machine learning libraries like scikit-learn and TensorFlow; integrate with SAP and Excel for data management and reporting.
4. Reports and Dashboards: Generate weekly, monthly, and quarterly reports with KPIs such as forecast accuracy, inventory turnover rate, and fill rate. Create dashboards for real-time monitoring.
5. Collaboration Framework: Establish a cross-functional team including sales, marketing, and operations to ensure alignment and continuous improvement.

Industry Best Practices:

• Prioritize data accuracy and integrity.
• Validate models using out-of-sample testing and A/B testing.
• Continuously monitor and update models to adapt to market c