联想利用 DataRobot 计算供应链和零售成功
公司规模
1,000+
地区
- America
国家
- Brazil
产品
- DataRobot
技术栈
- R
- Machine Learning
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Revenue Growth
技术
- 分析与建模 - 机器学习
适用功能
- 商业运营
- 销售与市场营销
用例
- 预测性维护
- 供应链可见性(SCV)
服务
- 数据科学服务
关于客户
联想是全球最大的科技公司之一，每年在全球销售的电脑、笔记本电脑和配件价值超过 450 亿美元。这家中国跨国公司将巴西视为其主要新兴市场之一，为在客户和零售商中确立南美市场领导者地位提供了绝佳机会。联想巴西技术有限公司负责该地区的销售和制造业务。该公司早就知道，准确预测销售量将改善业务的许多方面，从发现供应链中的问题到做出更好的营销投资。
挑战
联想是一家跨国科技公司，在平衡巴西零售商的产品供需方面面临挑战。该公司的目标是预测销售量，即零售商向客户销售的产品单位数量，但受到资源的限制。该团队已开始开发 R 代码来预测销售量，目标是每周为其十大零售客户更新。然而，由于只有 2 个人每周为一位客户编写 1,500 行 R 代码，因此每周为十位客户进行预测的目标是不可能的。该团队需要投资更多数据科学家，或者找到一种可以自动执行所有建模和预测步骤的工具。
解决方案
联想巴西采用了自动化机器学习平台 DataRobot，以加速并提高其销售量预测的准确性。该团队确定了 59 个可能影响零售商销售量的变量，并使用 DataRobot 自动化了模型构建过程。DataRobot 使用不同的算法快速创建了数十个模型，将它们排列在排行榜上，并快速总结它们的准确性和预测性。该工具还使团队能够轻松解释哪些变量最具预测性，并透明地将这些模型的结果传达给业务利益相关者。使用 DataRobot 显著提高了速度和效率，并显著提高了预测的准确性。
运营影响
数量效益
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