Lot and Serial Tracking: Traceability and Expiry Date Management Guide

What is Traceability?

Traceability records the entire journey of a product from raw material to the end consumer

Traceability is the ability to record all movements and transformations of a product within the supply chain and to query this history when necessary. It has two fundamental directions:

Forward Traceability

Tracking from raw material to the finished product and the customer. It answers the question: “Which products were made from this batch of raw materials, and who were they sold to?”

• From supplier lot number to production batch
• From production batch to finished goods inventory
• From inventory to shipments made to customers

Backward Traceability

Tracking from the customer back to the raw material. It answers the question: “Which raw materials were used to produce this item, when, and in which process?”

• From customer complaint to sales invoice
• From sales invoice to shipment batch
• From shipment batch to production work order
• From production work order to raw material lots

Traceability Levels

The depth of traceability is determined by industry requirements and risk tolerance:

• Level 1 – Batch-Based: Products are tracked by lot/batch number. Common in food and chemical industries.
• Level 2 – Unit-Based: Each unit is tracked with a unique serial number. Mandatory in pharmaceutical, medical device, and electronics industries.
• Level 3 – Component-Based: Tracking down to critical components within the product. Applied for critical parts in aerospace and automotive industries.

As we see in our industry-specific solutions, traceability requirements for every sector can vary in depth and breadth.

Lot and Serial Number Concepts

Lot and serial numbers form the fundamental components of product identity

The concepts of lot and serial numbers are often confused. Understanding them correctly forms the foundation of a traceability strategy.

Lot (Batch) Number

A lot number identifies a group of products produced under the same conditions at the same time. Characteristics:

• Products with the same lot number are considered homogeneous
• Quality control tests are performed on a lot basis
• Recalls usually occur on a lot basis
• FEFO (First Expired First Out) management is lot-based

Lot Number Design

An effective lot number should carry information within its coding:

• Production date: Julian date or YYMMDD format
• Production line/shift: Which equipment and team
• Product group code: Product family identifier
• Sequence number: Batch order within the day

Example: 26032A01 – Year 2026, 32nd day (February), Line A, 01st batch

Serial Number

A serial number uniquely identifies each individual unit. Characteristics:

• Must be globally unique
• Provides unit-based traceability
• Used for anti-counterfeiting
• Critical for warranty and service tracking

Serial Number Management Models

• Sequential: Assigning numbers in increasing order. Simple but predictable.
• Random: Random number generation. Unpredictable, makes counterfeiting difficult.
• Hybrid: Combination of lot number + sequence number.

Lot vs. Serial: Decision Matrix

GS1 Standards and Implementation

GS1 standards create a common language in the global supply chain

GS1 is a non-profit international organization that sets global supply chain standards. Critical GS1 identifiers for traceability include:

Core GS1 Identifiers

GTIN (Global Trade Item Number)

Defines product identity. Formerly known as the EAN/UPC barcode number.

• GTIN-8: For small packages
• GTIN-13: For retail products (EAN-13)
• GTIN-14: For trade units and cartons

SSCC (Serial Shipping Container Code)

Uniquely identifies logistics units (pallets, cartons). 18-digit numeric code.

GLN (Global Location Number)

Defines physical locations (factory, warehouse, store) and legal entities (company). 13-digit numeric code.

GS1 Barcode Types

GS1-128 (Formerly: EAN-128)

Linear barcode format. Carries additional information such as lot number, expiration date, and serial number.

• AI (01): GTIN
• AI (10): Lot/Batch number
• AI (17): Expiration date (YYMMDD)
• AI (21): Serial number
• AI (37): Quantity

GS1 DataMatrix

2D barcode format. Fits more data into a small area. Standard in pharmaceutical and medical device industries.

• High data capacity
• Error correction feature
• Suitable for small-sized prints
• Direct Part Marking (DPM) possible

EPCIS (Electronic Product Code Information Services)

EPCIS records supply chain events in a standard format. Each event answers four basic questions:

• What: Which product (GTIN + lot/serial)
• Where: Which location (GLN)
• When: Event time
• Why: Event type (production, shipment, receipt, etc.)

Expiration Date (SKT) Management

The FEFO principle is the foundation of expiration date management

Expiration date management is critically important, especially in the food, pharmaceutical, and cosmetics industries. Inadequate management leads to product waste, customer complaints, and legal issues.

FIFO vs. FEFO

FIFO (First In First Out)

First in, first out. Management based on warehouse entry date. May be insufficient for lots with different expiration dates.

FEFO (First Expired First Out)

First expired, first out. Management based on expiration date. Products with the nearest expiration dates are shipped first.

Expiration Date Warning Mechanisms

• Yellow zone (warning): X days before expiration (e.g., 90 days)
• Red zone (critical): Y days before expiration (e.g., 30 days)
• Blockage: Products that have fallen below minimum shelf life cannot be shipped

Shelf Life Policy

Customers are provided with a minimum remaining shelf life guarantee. For example:

• “Minimum 75% shelf life at the date of delivery”
• “Minimum 6 months remaining expiration date at the date of delivery”

This policy is integrated into sales and logistics systems, ensuring that non-compliant lots are automatically excluded.

Management of Products Near Expiration

• Discounted sales: “Last X days” campaigns
• Alternative channel: Outlet, B2B, donation
• Disposal: Disposal in accordance with legal procedures
• Production input: Reprocessing in some industries

Recall Management

Product recall is the “stress test” of a traceability system. An effective recall process demonstrates the quality of the traceability infrastructure.

Recall Types

Class I – Serious (Critical)

Products that could cause serious health damage or death. Example: Contaminated food, incorrect medication dosage.

• Emergency public announcement
• Initiation within 24 hours
• Mandatory notification to official authorities

Class II – Moderate

Products that could cause temporary or treatable health problems. Example: Labeling error, missing allergen information.

Class III – Minor

Products with low health risk but non-compliance with regulations. Example: Incorrect weight information, cosmetic defect.

Recall Process

1. Detection and Assessment

• Determine the scope of the issue
• Perform risk classification
• Identify affected lots/serials
• Make the recall decision

2. Traceability Query

• Identify locations of affected products
• Inventory in the warehouse
• Inventory in distribution channels (dealers, warehouses)
• Products sold to customers

3. Notification

• Official authorities (if required)
• Distribution channels and dealers
• End consumers (if required)
• Public (for Class I)

4. Collection and Disposal

• Physical collection logistics
• Quarantine storage
• Inspection and analysis
• Disposal or correction

5. Closure and Reporting

• Calculate collection rates
• Root cause analysis
• Preventive actions
• Closure report to authorities

Mock Recall (Drill)

A recall drill should be conducted at least once a year. By simulating a real scenario:

• Test whether traceability data can be accessed 100%
• Aim to identify 95% of affected products within 4 hours
• Verify the communication chain and decision-making mechanisms
• Document deficiencies and create an improvement plan

Field Example: Food Manufacturer Case

Real Case (Unbranded)

Situation

A mid-sized food production facility. 15+ different products, 50+ lots produced daily. Current situation: Excel-based lot tracking, paper forms, manual barcode entry. When a quality warning arrives from a raw material supplier, it takes 3 days to identify the affected products.

Steps Implemented (representative duration: 4 months)

1. Month 1: Current situation analysis. All production lines, raw material entry points, and shipment areas were mapped. Critical Control Points (CCP) were determined.
2. Month 2: GS1-128 barcode structure was designed. Barcode scanning points were established for raw material entry, production, and shipment. Lot number coding standard was defined.
3. Month 3: System integration. The lot tracking module was activated in the system. FEFO logic was implemented. Team training was completed.
4. Month 4: Mock recall drill. A full traceability test was performed for a randomly selected raw material lot. Improvements were applied.

Result (observed)

• Traceability query time: Reduced from 3 days to 2 hours
• Waste rate due to expiration: Representative 35% reduction
• Mock recall success rate: 92% in the first attempt, 98% in the second
• Customer complaint resolution time: Representative 60% reduction

7 Most Common Mistakes in Lot and Serial Tracking

1. Assigning Lot Numbers Only in Production

Not tracking lots at raw material entry breaks backward traceability. It becomes impossible to determine which products were made using raw materials with quality issues.

2. Manual Data Entry

Manual entry of lot and serial numbers dramatically increases the error rate. Traceability data cannot be trusted without barcode scanning.

3. Keeping Lot Size Too Large

A large lot size affects too many products in the event of a recall. Optimum lot size requires a balance between production efficiency and recall risk.

4. Implementing FIFO Instead of FEFO

Shipping based on warehouse entry date (FIFO) increases the risk of waste for lots with different expiration dates. Management based on expiration date (FEFO) is safer.

5. Not Conducting Mock Recalls

Leaving the traceability system to be tested during a real crisis is the riskiest approach. An annual drill reveals the true performance of your system.

6. Neglecting Data Integration

If lot information does not flow between production, warehouse, and sales systems, traceability is broken. End-to-end integration is mandatory.

7. Not Defining Standards

Starting without defining standards for lot number format, barcode structure, and data fields requires major revisions later. Adopt global standards like GS1 from the start.

A systematic approach prevents errors

Success Metrics

Measure the performance of your lot/serial tracking and traceability system with the following metrics (representative values):

By regularly monitoring these metrics, you can continuously improve the effectiveness of your traceability system.

Traceability Checklist

This checklist can also be adapted and used in your industry-specific projects. Special requirements can be added for each sector.

Frequently Asked Questions (FAQ)