RFID for Better Supply‐Chain Management through Enhanced Information Visibility

Dursun Delen, Bill C. Hardgrave, Ramesh Sharda

Production and Operations Management · 2007 · 357 citations · 12 references

Concepts

TL;DR

RFID adoption is rapidly expanding in retail, yet the business case for its use remains unclear. The study investigates RFID’s business value by analyzing real data from a major retailer’s supply chain. The authors mapped RFID reader placement across a partial supply chain, defined performance metrics from the readings, computed these metrics, and examined how they could improve micro‑level logistics between distribution centers and stores. The metrics revealed average movement times, demonstrated usefulness for retailers and suppliers, and highlighted data quality challenges.

Abstract

Mostly fueled by mandates, adoption, and implementation of the RFID, technology in the retail industry is growing rapidly. At these early stages of adoption, one puzzling issue for retailers and suppliers is the compelling business case for RFID. In order to explore the potential business case for RFID, we conducted a case study using actual RFID data collected by a major retailer for the cases shipped by one of its major suppliers. We show the physical layout of the RFID readers on a partial supply‐chain covering product movement from distribution centers to retail stores. First, in the analysis phase, we identify several performance metrics that can be computed from the RFID readings. Next, using this RFID data, we compute the values of those performance metrics. These values represent mean time between movements at different locations. Then, we discuss how these measures can assist in improving logistical performance at a micro supply chain level of operations between a distribution center and a retail store. We present how such information can be valuable to both the retail store operator and the supplier. We also discuss the initial lessons learned from actual RFID data collected in the field, in terms of data quality issues.

References

12