Inventory Analytics

A Comparative Study Of the Retail and Manufacturing Industries in China and the U.S.

Yang Zihan

Student of Supply Chain Management

Northeast Normal Universuty

Industry Comparison and Trend Analysis of Inventory Management Importance

ratail and manufacturing industry between China and U.S.

Inventory is not evenly distributed among countries

Key Discoveries

• 1. Inventory management is more critical for the retail industry than manufacturing in both countries, as retail faces faster demand fluctuations and higher holding costs.
  1. China’s advantage lies in high-volume, efficiency-driven inventory turnover, while the U.S. excels in demand predictability and resilience.
  1. GCPS tools (e.g., Supply Chain Mapping, Region Comparison) have directly contributed to turnover improvements by enhancing data visibility and cross-regional optimization.

Value Driver Analysis – Inventory Turnover and Financial Performance

ratail and manufacturing industry between China and U.S.

Inventory is not evenly distributed among countries

Analysis Metrics

• • Inventory turnover ratio (2024): Amazon (12.8x), Alibaba (9.8x), Walmart (8.3x)
  • Stockout rate (2024): Amazon (2.1%), Alibaba (3.5%), Walmart (2.8%)
  • Obsolescence rate (2024): Amazon (1.8%), Alibaba (2.7%), Walmart (2.3%)
  • Inventory as % of total assets (2024): Amazon (15.2%), Alibaba (18.7%), Walmart (21.5%)

Company-Level Inventory Problem Diagnosis 

ratail and manufacturing industry between China and U.S.

Inventory is not evenly distributed among countries

Diagnosis of Inventory Problems

• 1. Walmart (U.S.):
     • Issue: Highest inventory as % of total assets (21.5%) and moderate stockout rate (2.8%) due to inefficient omnichannel inventory sync. GCPS Supply Chain Mapping shows discrepancies between in-store and online stock levels, with 15% of online orders requiring fulfillment from distant warehouses.
     • Root cause: Legacy inventory management systems in physical stores, which are slower to integrate with online platforms compared to Amazon’s purpose-built logistics network.
• 1. Alibaba (China):
     • Issue: Lower turnover (9.8x vs. Amazon’s 12.8x) and higher obsolescence rate (2.7%) due to overstocking of seasonal products (e.g., fashion, home goods) in its Taobao marketplace. GCPS scatter plot analysis highlights that 30% of its inventory consists of SKUs with <5x turnover.
     • Root cause: Fragmented seller management in the C2C segment, leading to poor demand forecasting alignment. The platform’s open model makes it difficult to enforce uniform inventory standards.
• 1. Amazon (U.S.):
     • Issue: Minimal inventory problems, but the 2.1% stockout rate (concentrated in niche electronics) indicates gaps in demand forecasting for low-volume, high-growth products. GCPS annotations on scatter plots reveal that stockouts correlate with sudden spikes in social media-driven demand.
     • Root cause: Over-reliance on historical data in forecasting algorithms, with limited integration of real-time social and trend data.

Key Discoveries

• 1. Amazon’s superior inventory management stems from its closed-loop supply chain and AI-driven forecasting, while Alibaba and Walmart face structural challenges (platform model, legacy systems).
  2. Inventory problems are not just about turnover speed but also about alignment with demand volatility and channel integration.
  3. GCPS tools (data point highlighting, supply chain mapping, annotation) are critical for identifying root causes, as they enable visualization of inventory inefficiencies across SKUs and channels.