Xiaoyue Shan

Publication Date


Document Type


First Advisor

Aase, Gerald

Degree Name

B.S. (Bachelor of Science)

Legacy Department

Department of Operations Management and Information Systems


This research explores how items are grouped into product families in a manner that reduces travel time (or distance) for operators picking orders in a warehouse. By identifying items commonly ordered together and locating those items together in the warehouse, operators can pick multiple items using a single trip rather than separate trips to different warehouse locations. Using secondary data source provided by our business sponsor, this research uses K-means clustering analysis and Market basket analysis as the primary analytic methodologies to generate SKU families. Other technical tools are MS Excel, MS Access and SAS University Edition. This final report gathers the various deliverables pertaining to the four analytic steps: 1) Getting & Exploring Data, 2) Cleaning Data, 3) Analyzing Data, and 4) Presenting Results. Final results reveal fifty items grouped into 6 families can reduce warehouse picking expenses of $420,000 by $40,134.85. This reflects a 9.6% reduction in total warehouse labor expenses.

Appendix A_Front50Skus.xlsx (20 kB)
 Appendix A_Front50Skus

Appendix B_K-Means Clustering-results_6.rtf (719 kB)
 Appendix B_K-Means Clustering-results_6

Appendix C_K-Means ClusteringCl2-results.rtf (276 kB)
 Appendix C_K-Means ClusteringCl2-results

Appendix D_Highlighted Summary.xlsx (21 kB)
 Appendix D_Highlighted Summary

analysis.xlsx (68 kB)
 Analysis process excel file

financial.xlsx (28 kB)
 Financial excel file

HonorCapstoneData_XiaoyueShan.accdb (138008 kB)
 MS Access file


37 pages




Northern Illinois University

Rights Statement

In Copyright

Rights Statement 2

NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.

Media Type