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Analytics Driving Supply Chain Segmentation for Lenovo
| Content Provider | Semantic Scholar |
|---|---|
| Author | Sáenz, María Jesús |
| Copyright Year | 2019 |
| Abstract | This research provided an approach for a Machine Learning application for customer-oriented supply chain segmentation at Lenovo. A k-Means model on Importance and Complexity dimensions identified four major segments among their Hyperscale Business Unit. A supply chain policy analysis suggested the design of three distinct policies and strategies for the identified clusters. Lenovo will expand the model for further business units, and integrate more segment characteristics and performance metrics, particularly capturing Customer Experience and Cost Efficiency. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://digitalsc.mit.edu/wp-content/uploads/2019/06/Executive-Summary_v17.pdf |
| Alternate Webpage(s) | https://ctl.mit.edu/sites/ctl.mit.edu/files/theses/43820885-Executive%20Summary_Gosling&Urrutia.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
