CHain Integration Project (CHIP) Proof-of-Concept Whitepaper

The CHIP (CHain Integration Project) Initiative at the Auburn University RFID Lab recently concluded its Proof-of-Concept phase, which sought to prove the viability of a blockchain solution for serialized data exchange. Nike, PVH Corp., HermanKay, Kohl’s, and Macy’s participated in the first phase of the project by contributing item-level data streams from various supply chain nodes from January to December 2019. The project was able to successfully integrate serialized data streams from source to store, connecting the dots between isolated touchpoints and forging a history for each product that passed through the supply chain.

The solution was constructed on a Hyperledger Fabric foundation and additional details regarding the business case, solution architecture, and next steps are available in the official CHIP Whitepaper.

Click here to complete a brief form and download the paper.

Why Retail is Ready for Blockchain | An Exclusive Position Paper from the RFID Lab at Auburn University

In today’s retail and apparel industry, there are many factors that prevent organizations from achieving end-to-end product visibility. One of the most critical examples of this is poor communication of data between organizations. The data associated with products is often substituted or discarded as goods are transferred from one stakeholder to the next, with each organization redefining and replacing the previous product data with information relevant to their own operations.

Enter blockchain, a transformative technology that holds the promise of alleviating today’s supply chain pain points. In our latest white paper, the Auburn RFID Lab research team reviews the problems facing the retail and apparel industry in regards to how they share their data, as well as the business value of blockchain for the supply chain stakeholders, brand owners, retails, logistic providers, and solution providers.

Download the full position paper

Project Zipper: EPC-Enabled Item-level RFID Supply Chain Brand/Retailer Exchange Study

The goal of Project Zipper was to evaluate and analyze the benefits of Radio Frequency Identification (RFID) technology to retailers and brands through their supply chain shipping and receiving processes. This report outlines the parameters of the study, the conclusive results for Phase 1 of the project, learning opportunities drawn from findings, and return on investment (ROI) implications.

Download the full research paper

2016 State of RFID Adoption Among U.S. Apparel Retailers

Each June for the past six years, the Auburn University RFID Lab has analyzed RFID adoption by U.S. apparel retailers. The analysis is based on publicly available information and the lab’s work with various retailers.  As such, the analysis provides a reliable snapshot of both new and existing adopters. Following an initial three years of slow adoption due primarily to the great recession and issues with patent enforcement agencies, the past three years have witnessed growth in both the number of adopters and movement up the adoption curve.  The adoption is occurring across all types of retailers —from large department store chains to smaller specialty shops, though mostly in the apparel sector.

In this paper, we look at the 2016 adoption including where retailers are in the adoption cycle and the changes since 2015.  We also provide insight into the reasons behind the changes and the factors that may impact 2017 adoption.

Download the full research paper

Annual Audit Report


Auburn University’s RFID Lab conducted audits at eight major retailers across ten product categories in 2013-14. The goal of an audit was to capture the status of the RFID deployment by collecting accuracy and compliance data. The process also analyzed tagged items that did not work in the field, and determined the cause of failure.

The average accuracy from RFID system was 93.8% across all the retailers and product categories. 5% of the issues observed were related to compliance and execution in the supply chain and store. 1.2% of the issues observed were relate to technology failure. Non-tagging of items and double tagging of items were the major issues observed, 3.5% of the items on average had tagging issues with the best store having only 1% of the items with tagging issues but the worst store having issues occurring in 23.3% of the items.

It was also observed that these compliance issues affected the store employee’s confidence on the technology because it generated more work and undermined the trust they had in the technology. In some cases, low employee confidence lead to execution issues in the long term. The key lesson learned from the audits was that retailers should design and implement compliance verification methods relating to tagging execution and data collection for the long term success of the technology.

Key Considerations for RFID Pilots and Deployments


Over the past several years, we have worked with many retailers (large and small) on their RFID pilots and early-stage deployments. Every pilot and deployment is different and presents its own opportunities and challenges. However, across all of these projects, we have recognized some common errors and pitfalls that retailers face. Accordingly, we have distilled these errors and pitfalls into a list of 10 deployment rules. While following these rules will not guarantee pilot or deployment success, they can hopefully make one aware of the issues and, thus, make a decision to either make a correction or intentionally accept the potential consequences of ignoring the pitfall. Although this is not an exhaustive list, the 10 rules represent the most severe and most common pitfalls.

RFID Item-level Quantity Auditing for Apparel Supplier Distribution Centers.


The study is a continuation of the Phase I study into Supplier ROI, and was performed through 2011 with funding by GS1 US and the American Apparel and Footwear Association AAFA. The goal of the research was to focus on a few key use cases as identified in Phase I, analyze RFID data collected from Retail Suppliers who are implementing these use cases, and determine to what extent RFID can be used to generate ROI within a Supplier’s own operations. Much of the research focused on the Supplier’s Distribution Centers, and how RFID can help with inventory accuracy, shipping accuracy, and the costs to achieve high levels of accuracy. Also the effects of inventory accuracy on Retailer claims and DC operations are discussed. Some tools are included to allow suppliers to calculate potential ROI within their own operations.

An Empirical Study of Potential Uses of RFID In The Apparel Retail Supply Chain


Phase I of an empirical study of potential uses of radio frequency identification (RFID) in the apparel supply chain was conducted in the fall of 2010. This Phase of the research was designed to identify potential use cases for the use of RFID in an apparel supply chain and was funded by GS1 US and the American Apparel and Footwear Association (AAFA). The three-phase Supplier ROI study is commonly referred to as the Many-to-Many study. Phase II will involve the measurement of ROI for select use cases identified in Phase I. Phase III will study the effect of RFID on multiple suppliers simultaneously through an experiment. The use cases were solicited from a wide range of companies, in several different countries, in many different types of facilities, and thus reveal where the industry collectively believes the greatest RFID benefits reside. Over a period of several months, we collected more than 60 use cases. The findings of Phase I show that the potential benefits of item-level RFID in the apparel supply chain reach beyond the retailer and include apparel manufacturers.

RFID-Enabled Visibility and Retail Inventory Record Inaccuracy: Experiments in the Field


Accurate inventory records are key to effective store execution, affecting forecasting, ordering, and replenishment. Prior empirical research, however, shows that retailer inventory records are inherently inaccurate. Radio Frequency Identification RFID enables visibility into the movement of inventories in the supply chain. Using two different field experiments, the current research investigates the effectiveness of this visibility in reducing retail store inventory record inaccuracy IRI. Study 1 used an interrupted time series design and involved daily physical counts of all products in one category in 13 stores 8 treatment and 5 control of a major global retailer over 23 weeks. Study 2, which used an untreated control group design with pre-test and post-test, the number of categories was expanded to five and the number of stores to 62 31 treatment and 31 control stores. The results from both studies provide guidance for researchers and practitioners for the deployment of RFID in the retail store by 1 demonstrating that case-level tagging can be effective in reducing IRI with the ecological validity provided by a field experiment, and 2 providing the key insight that the technology is most effective for product categories characterized by known determinants of IRI.

Item-Level RFID for Apparel/Footwear: The JC Penney RFID Initiative


It has been proven that item-level RFID can improve many in-store processes for retailers. In particular, the business case for RFID for retailers looks promising. Previous studies have shown the benefits of RFID at the pallet and case level, such as reducing out of stocks and improving inventory count accuracy. Therefore, it seems logical that item-level RFID would provide even more benefits. In this study, we examine the use of item-level RFID at a major apparel and home retailer, JCPenney. Specifically, the use cases of inventory accuracy and inventory management using RFID replenishment reports are investigated, with incidental attention to cycle counting. This pilot’s results support previous research, demonstrating the tendency for inventory accuracy to diminish over time, as well as the potential for improvement in inventory accuracy due to RFID. Improved inventory accuracy leads to fewer out of stocks, less safety stock, and better ordering and forecasting, among others.