KappAhl 利用分配精度实现盈利
公司规模
1,000+
地区
- Europe
国家
- Finland
- Norway
- Poland
- Sweden
产品
- Luminate Retail
技术栈
- Artificial Intelligence
- Machine Learning
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
技术
- 分析与建模 - 机器学习
适用行业
- 零售
适用功能
- 销售与市场营销
用例
- 需求计划与预测
- 库存管理
服务
- 软件设计与工程服务
- 系统集成
关于客户
KappAhl 是一家领先的北欧零售商，在瑞典、挪威、芬兰和波兰拥有 400 家门店。该公司每季提供 12,000 种独特的款式/颜色组合。KappAhl 之前使用两个自主研发的系统，每晚执行约 3,800 次分配。然而，这些系统无法提供实现公司目标所需的详细程度和灵活性。KappAhl 需要一种解决方案，既可以提高其分配精度和符合当地需求的尺寸，又可以提高销售额并保持利润。
挑战
KappAhl 是一家领先的北欧零售商，其分配系统面临挑战。该公司每晚在两个自主研发的系统上执行大约 3,800 次分配，但这些系统已无法满足需求。以前的系统是自动化的，但不允许公司在实现目标所需的较低细节水平上工作。KappAhl 在瑞典、挪威、芬兰和波兰的 400 家门店每季有 12,000 种独特的款式/颜色组合，因此需要更大的灵活性和扩展功能来提高销售额并保持利润。
解决方案
KappAhl 实施了 Luminate Retail，这是一种由人工智能 (AI) 和机器学习 (ML) 技术驱动的解决方案。实施过程耗时约 12 个月，其中包括两个月的测试。Luminate Retail 现在管理着 KappAhl 所有分配的 95%，占交叉转运流量的 80% 和补货的 100%。该解决方案为 KappAhl 提供了所需的灵活性和能力，以提高其分配精度和符合当地需求的尺寸。
运营影响
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