Slide 1: Beyond Data Capture: Solving the Real Traceability Problem – Bad Data
Today’s Webinar: Beyond Data Capture: Solving the Real Traceability Problem – Bad Data Presenter: Derek Hannum Chief Customer Officer ReposiTrak March 11, 2026
Slide 2: Thanks For Attending
Thanks For Attending A few guidelines for today ▪ Everyone who registered will get the recording ▪ There will be time at the end for questions, which you can submit by typing in the question pane ▪ There is a brief survey that follows the webinar • Your feedback helps us make future webinars even be
Slide 3: ReposiTrak and the Traceability Network
ReposiTrak and the Traceability Network Connecting the supply chain to deliver real traceability ▪ More than two decades of experience tracking product shipments ▪ Over three years of in-depth work on FSMA 204 compliance with suppliers, wholesalers/distributors and retailers ▪ Nearly 2 million lot c
Slide 4: Quick FSMA 204 Review
Quick FSMA 204 Review FDA FOOD SAFETY MODERNIZATION ACT —=—==
Slide 5: Critical Tracking Events and Key Data Elements
Every Critical Tracking Event (CTE) has a set of Key Data Elements (KDEs) that must be collected and saved as an easily retrievable record. The CTEs that impact wholesalers/ distributors and retailers are Shipping, Receiving, and in some cases Transformation. 5 https://www.fda.gov/media/163132/downl
Slide 6: Which traceability records are required at each step?
Which traceability records are required at each step? …From the supplier when product is shipped – a KDE Shipment Record …At the DC/warehouse when product is received – a KDE DC Receiving Record …From the DC/warehouse when product is shipped – a KDE DC Shipping Record …At stores when product is rece
Slide 7: Receiving and Shipping KDE Records
Receiving and Shipping KDE Records These are the FDA required data elements Product 1. The traceability lot code for the food data that 2. The product description for the food stays the same 3. The location description for the traceability lot code source, or the traceability lot code source referen
Slide 8: Retailers are Looking for Much More Data
Retailers are Looking for Much More Data If you are required to share more data elements, does the chance for errors increase? If you need to share different data with different customers, does the chance for errors increase? How will customers react if you share bad data? Fines? Rejected shipments?
Slide 9: The FDA is No Longer Driving the Timing
The FDA is No Longer Driving the Timing ▪ Over 70 retail and distribution companies have announced their requirements or plans to do traceability, many with deadlines well in advance of the FDA deadline. ▪ Suppliers, you may already have customers telling you to get started…this will soon turn into
Slide 10: How Dirty Data Can Wreck Your Traceability Program
How Dirty Data Can Wreck Your Traceability Program 10
Slide 11: Poll Question
Poll Question Kk 11
Slide 12: Why Aren't More People Talking About Data Errors?
Why Aren’t More People Talking About Data Errors? Let’s ask ChatGPT about data errors and EDI… 12
Slide 13: Why Aren't More People Talking About Data Errors?
Why Aren’t More People Talking About Data Errors? What ChatGPT says about data errors and EDI… 13
Slide 14: How is what ReposiTrak Does Different from EDI?
How is what ReposiTrak Does Different from EDI? When data accuracy counts ▪ ReposiTrak data sharing is not a commercial service, like with an EDI company ▪ Simply “moving the data” is not something we sell ▪ Data sharing in ReposiTrak is a means to an end ▪ Data must be transmitted, shared and track
Slide 15: The REAL Data Error Rate in Traceability
The REAL Data Error Rate in Traceability ▪ Based on experience with millions of records and hundreds of suppliers, we know the REAL Data error rate is close to 40% of all records ▪ At that error rate, traceability is totally compromised ▪ When suppliers push dirty data to wholesalers and retailers,
Slide 16: Manual Corrections Don't Work at this Scale
Manual Corrections Don’t Work at this Scale ▪ ReposiTrak sends notifications to suppliers when errors are found ▪ At the scale of shipments and high percentage of errors, it won’t be possible to turn around all the corrected files before shipments arrive at the wholesale and retailer customer sites
Slide 17: Example 1 Error Detected: Invalid Product ID
Page 1 of 2 Example 1 Error Detected: Invalid Product ID EDI 856 Error Detection & Correction Enabling ReposiTrak to Create KDE Records at Supplier Shipping CTE ▪ See the highlighted area. A product number that does not exist in the sender’s catalog was sent in the EDI 856. ▪ Because ReposiTrak stor
Slide 18: Example 1 Error Corrected: Product ID Matched/Added
Page 2 of 2 Example 1 Error Corrected: Product ID Matched/Added EDI 856 Error Detection & Correction Enabling ReposiTrak to Create KDE Records at Supplier Shipping CTE • If found using expert systems AI, the Product ID sent in the file will be corrected, and the record will process and post. • If no
Slide 19: Example 2 Error Detected: Invalid Product ID
Page 1 of 2 Example 2 Error Detected: Invalid Product ID EDI 856 Error Detection & Correction Enabling ReposiTrak to Create KDE Records at Supplier Shipping CTE ▪ See the highlighted area. A product number that does not exist in their catalog was sent. ▪ Because ReposiTrak stores the sender’s produc
Slide 20: Example 2 Error Corrected: Product ID Matched/Added
Page 2 of 2 Example 2 Error Corrected: Product ID Matched/Added EDI 856 Error Detection & Correction Enabling ReposiTrak to Create KDE Records at Supplier Shipping CTE • If found using expert systems AI, the Product ID sent in the file will be corrected, and the record will process and post. • If no
Slide 21: Example 3 Error Detected: Invalid Customer ID
Page 1 of 2 Example 3 Error Detected: Invalid Customer ID EDI 856 Error Detection & Correction Enabling ReposiTrak to Create KDE Records at Supplier Shipping CTE ▪ See the highlighted area. A customer ID was sent that is invalid (not recorded as this sender’s customer ID.) ▪ Because in the N1 segmen
Slide 22: Example 3 Error Corrected: Customer ID Matched/Added
Page 2 of 2 Example 3 Error Corrected: Customer ID Matched/Added EDI 856 Error Detection & Correction Enabling ReposiTrak to Create KDE Records at Supplier Shipping CTE • If found, the Customer ID sent in the file will be added as an additional Customer ID, and the record will process and post. • If
Slide 23: Example 4 Error Detected: Missing Shipped Product
Page 1 of 2 Example 4 Error Detected: Missing Shipped Product EDI 856 Error Detection & Correction Enabling ReposiTrak to Create KDE Records at Supplier Shipping CTE ▪ See the highlighted area. There was no Product Number sent in the file for this product (between the VN indicators **). ▪ Because Re
Slide 24: Example 4 Error Corrected: Product Identified
Page 2 of 2 Example 4 Error Corrected: Product Identified EDI 856 Error Detection & Correction Enabling ReposiTrak to Create KDE Records at Supplier Shipping CTE • When found, the Product ID for the Product sent in the file will be added using expert systems AI and the record will process and post.
Slide 25: Example 5 Error Detected: Missing TLC Source
Page 1 of 2 Example 5 Error Detected: Missing TLC Source EDI 856 Error Detection & Correction Enabling ReposiTrak to Create KDE Records at Supplier Shipping CTE ▪ See the highlighted area. There was no TLC Source sent in the file for this product ▪ The N1*MP,N3, and N4 fields are missing at the item
Slide 26: Example 5 Error Corrected: TLC Source Added
Page 2 of 2 Example 5 Error Corrected: TLC Source Added EDI 856 Error Detection & Correction Enabling ReposiTrak to Create KDE Records at Supplier Shipping CTE • When found using expert systems AI, the TLC Source for the Product sent in the file will be added and the record will process and post. •
Slide 27: Steps to Avoid Dirty Data: Suppliers
Steps to Avoid Dirty Data Suppliers ▪ Don’t trust EDI to do this for you…it doesn’t work ▪ Send test files before you send any data to customers ▪ Ensure you have a robust process that is repeatable and reliable ▪ Find a technology partner who can help 27
Slide 28: Steps to Avoid Dirty Data: Wholesalers/Retailers
Steps to Avoid Dirty Data Wholesalers/Retailers ▪ Communicate the bad data problem to your IT teams so they understand the garbage in-garbage out problem ▪ Don’t trust EDI to do this for you…it doesn’t work ▪ Deploy technology that validates the accuracy of data 28
Slide 29: Q&A
Q&A siTrak. 29
Slide 30: Thank You!
Thank You! Derek Hannum, Chief Customer Officer ReposiTrak 407-558-9829 dhannum@repositrak.com