通过商品级超参数优化，提升床垫电商销售预测精度。
DemandLens: Enhancing Forecast Accuracy Through Product-Specific Hyperparameter Optimization
- 基于Prophet模型，针对不同商品定制超参数以提高预测准确率。
- 在真实业务场景中，显著降低预测误差，助力供应链提前备料。
- 适合依赖第三方代工的床垫品牌及制造商使用。
DemandLens 提出一种基于 Prophet 的创新预测模型，专为床垫盒装行业设计，融合新冠疫情指标与商品级（SKU）超参数优化。该行业近年来快速增长，主要依赖外包制造与物流，聚焦于直销渠道的营销与转化。美国境内床垫代工厂数量有限，因此需智能管理原材料、供应链和库存，以服务更多品牌。本研究针对依赖外部代工的行业痛点，提出精准销售预测方案，帮助代工厂提前准备，避免瓶颈，并实现原材料最优采购。模型通过商品级超参数优化展现强大预测能力，为代工厂与品牌提供可靠工具，有效优化供应链运营。
原文摘要 · Abstract (English)
DemandLens demonstrates an innovative Prophet based forecasting model for the mattress-in-a-box industry, incorporating COVID-19 metrics and SKU-specific hyperparameter optimization. This industry has seen significant growth of E-commerce players in the recent years, wherein the business model majorly relies on outsourcing Mattress manufacturing and related logistics and supply chain operations, focusing on marketing the product and driving conversions through Direct-to-Consumer sales channels. Now, within the United States, there are a limited number of Mattress contract manufacturers available, and hence, it is important that they manage their raw materials, supply chain, and, inventory intelligently, to be able to cater maximum Mattress brands. Our approach addresses the critical need for accurate Sales Forecasting in an industry that is heavily dependent on third-party Contract Manufacturing. This, in turn, helps the contract manufacturers to be prepared, hence, avoiding bottleneck scenarios, and aiding them to source raw materials at optimal rates. The model demonstrates strong predictive capabilities through SKU-specific Hyperparameter optimization, offering the Contract Manufacturers and Mattress brands a reliable tool to streamline supply chain operations.
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