GE Motors by Wolong · 2025
Finding the signals in pricing.发现定价中的异常信号。
Used regression and segmented visualizations to investigate OEM versus distributor pricing across states, product divisions, and volume tiers.用回归模型与分组可视化,分析不同州、产品部门和销量区间中 OEM 与经销商的价格差异。 The goal was to make unusual orders easier to spot and explain, then connect those findings with clearer pricing information and review workflows.目标是让异常订单更容易被识别和解释,并将分析发现与更清晰的定价资料和审核流程衔接起来。
Explore the case查看项目详情
The question业务问题
Which orders deviate from expected pricing after accounting for customer channel, geography, product, and volume?在考虑客户渠道、地区、产品及采购量之后,哪些订单的价格仍显著偏离预期?
My contribution我的工作
Built a regression model in R, used faceted boxplots to compare segments, and presented three underpriced orders with a combined $130K gap to leadership. Also restructured pricing files containing 40+ technical fields and developed a multi-level sales approval workflow in Power Apps.在 R 中建立回归模型,以分面箱线图比较各业务分组,向管理层汇报 3 笔合计约 13 万美元定价差额的低价订单。同时整理包含 40 多个技术字段的价格文件,并通过 Power Apps 搭建多级销售审批流程。
The pricing gap identifies an opportunity for review; it is not a claim of realized savings.该差额代表识别出的定价问题,不等同于已实现的节省或追回收入。












