How Poor Print Quality Disrupts Production, Compliance and Brand Trust
A Technical White Paper for Pacific Labeling
Abstract
Poor print quality in coding and labeling is often treated as a nuisance, a scanner issue or an operator problem. In reality, unreadable or marginal codes trigger a chain reaction across production, warehousing, logistics, retail receiving and regulated compliance workflows. These failures create measurable costs through downtime, rework, scrap, rejected shipments, chargebacks and delayed recalls. They also create harder to measure damage through customer frustration, audit findings and erosion of brand trust. This paper explains how code quality breaks down, why it happens, how it is measured using recognized verification standards and how manufacturers can build a prevention system that lowers total cost while improving compliance readiness.
1. Introduction
A product code is a tiny-printed object that carries outsized responsibility. It is used to identify product and packaging levels, connect a physical item to production data, enable track and trace, support recalls, validate expiration dating and provide proof of compliance. In many operations, the code is also the entry ticket into customer systems. If it cannot be scanned reliably, the product may not move.
As industries adopt more automation and data driven supply chains, the tolerance for weak codes shrinks. Warehouse automation, high-speed sortation and retail point of sale scanning reduce opportunities for manual correction. Regulators also require specific forms of identification in markets like medical devices and pharmaceuticals. The FDA UDI system, for example, requires device labelers to provide the UDI in both plain text and a machine readable AIDC form on labels and packages. In pharmaceuticals, DSCSA guidance and industry guidelines describe use of a 2D Data Matrix barcode for product identifiers.
The result is simple: bad codes are no longer a small print defect. They are an operational risk.
2. What counts as a bad code
A bad code is not only a code that fails to scan. Many costly failures start as codes that scan sometimes.
2.1 Failure types seen in real operations
- Non-decode: scanners cannot decode the symbol at all
- Marginal decode: scans only at certain angles, distances or scanner models
- Data mismatch: encoded data is wrong even if the symbol scans
- Inconsistent quality: some shifts or lanes produce readable codes and others do not
- Degrades over time: code scans at pack out but fails at receiving due to abrasion, condensation, rub or low contrast
2.2 Why simple scanning is not enough
A handheld scanner can say a code is readable, but it cannot quantify margin. That is why formal verification standards exist. Barcode verification evaluates print quality against defined parameters and produces a grade that predicts scan performance across environments and scanner types.
3. How code quality is measured
Most quality programs fail because they do not measure what matters. Verification standards provide a shared language between manufacturers, suppliers and customers.
3.1 Linear barcodes, ISO IEC 15416
ISO IEC 15416 specifies how to test print quality for linear symbols. It uses multiple scan lines across the height of the code and assigns grades based on defined parameters, then averages results to determine overall grade.
3.2 2D symbols, ISO IEC 15415
ISO IEC 15415 covers print quality test methods for 2D symbols and grades against multiple parameters related to symbol structure and reflectance.
3.3 GS1 guidance and the real world of trading partners
GS1 publishes general specifications and implementation guidelines tied to barcode quality, placement and verification processes. These documents matter because many customer compliance programs reference GS1 and ISO based requirements.
4. The operational cost stack of bad codes
Bad codes create costs in layers. The earliest cost is the cheapest to fix. The latest cost is the most expensive.
Many logistics and compliance practitioners warn that unreadable shipping labels can cause returns, non-compliance fines and quality audits. These impacts are consistent with how vendor compliance programs operate, where barcode quality is frequently cited as a common reason for chargebacks.
5. Compliance risk, not just inconvenience
The compliance angle is often the most persuasive to executives because it converts a print issue into a governance issue.
5.1 Medical devices, FDA UDI
The FDA states that device labelers must provide the UDI in both plain text and an AIDC machine readable form on labels and packages and submit device information to GUDID. When UDI marking is required, FDA guidance clarifies acceptable forms and content expectations. A low-quality code increases the chance of downstream scan failures in clinical receiving, inventory control and adverse event workflows.
5.2 Pharmaceuticals, DSCSA serialization
FDA materials and industry guidelines discuss DSCSA compliant product identifiers and the use of 2D Data Matrix barcodes for certain packaging scenarios. If the code does not scan reliably, the operational burden shifts to manual processes and exception handling, undermining the efficiency and integrity serialization is meant to provide.
5.3 Retail and the shift toward 2D
GS1 guidance for 2D barcodes at retail point of sale emphasizes criteria including size, quality, placement, syntax and human readable text. As retail scanning evolves, quality requirements become less forgiving, not more.
6. Root causes of poor code quality
Most bad code incidents trace back to a short list of causes. The key is to treat them as a system, not isolated events.
6.1 Process causes
- Line speed variation not reflected in print settings
- Print distance changes due to product handling drift
- Inadequate substrate testing before launch
- Poor changeover discipline between SKUs
- Lack of verification feedback loop to production
6.2 Materials causes
- Substrate reflectance differences, gloss, texture
- Condensation, cold chain moisture, abrasion
- Wrong label stock, ribbon, ink chemistry selection
- Contamination or dust affecting adhesion or printhead
6.3 Equipment causes
- Misalignment, vibration, worn rollers or tamp pads
- Printhead wear, clogged nozzles, inconsistent jetting
- Inadequate lighting or sensor timing in integrated systems
- Dirty optics or lens issues in laser marking systems
7. What the data should look like
A strong program uses simple visuals to make quality trends obvious.
Standards based grading and multi-scan methodologies are described in resources discussing ISO IEC 15416 and ISO IEC 15415 verification approaches.
Graph 1: Cost per incident by where it is caught
Graph 2: Verification grade trend over time after installing a verifier
Graph 3: Pareto chart of defect causes
8. Building a prevention system that actually works
A prevention system is a closed loop: specify, test, verify, correct and document.
8.1 Start with a shared specification
- Define required symbology and data content using customer and regulatory requirements
- Define minimum verification grade at the point of manufacture
- Define acceptable print placement and quiet zone rules using GS1 guidance where relevant
8.2 Validate materials and environment, not just the printer
- Test on real substrates, at real speeds, under real conditions
- Include cold chain, dust, abrasion, moisture as applicable
8.3 Verify on the line
Verification devices grade codes against standards like ISO IEC 15416 for linear and ISO IEC 15415 for 2D. The goal is to detect drift early, not to create paperwork after failures.
8.4 Use verification results to drive action
- Create an escalation rule: if grade drops below threshold, trigger maintenance, cleaning, material check and re-test
- Track grade by lane, head, shift and operator to isolate systemic issues
8.5 Document for audits and customer programs
When compliance is questioned, documentation showing defined requirements, test evidence and ongoing monitoring reduces exposure and speeds resolution.
9. Brand trust, the hidden multiplier
A single shipment rejected for unreadable codes is a hard cost. The deeper damage is relationship based.
Bad codes cause customers to add friction. They may increase incoming inspection, require more documentation or push for alternate suppliers. Over time, your organization becomes perceived as risky, even if the product itself is excellent. This is why quality leaders treat code quality as part of brand quality.
Articles and industry commentary increasingly frame unreadable barcodes as a meaningful cost driver across modern operations.
10. Conclusion
Bad codes are a systems problem that shows up as a print defect. Poor print quality disrupts production through downtime and rework, disrupts logistics through rejects and chargebacks and increases compliance risk in regulated environments. The most effective approach is to treat code quality as a measurable, verified process using recognized standards, then use that data to control drift. When manufacturers build a closed loop program of specification, validation, verification and corrective action, they reduce total cost, improve customer performance and protect brand trust.
References
- GS1, GS1 General Specifications (PDF).
- GS1, 2D Barcode Verification Process Implementation Guideline (PDF).
- GS1, 2D Barcodes at Retail Point-of-Sale Implementation (guideline page).
- ISO, ISO IEC 15415:2011 Information technology (standard page).
- FDA, UDI Basics (web page).
- FDA, Unique Device Identification System UDI System (web page).
- FDA, Form and Content of the Unique Device Identifier UDI (guidance PDF).
- FDA, Product Identifiers Under the Drug Supply Chain Security Act (PDF).
- Healthcare Distribution Alliance, Guidelines for Bar Coding in the Pharmaceutical Supply Chain (PDF).
- Omron, Layman’s Guide to ANSI, CEN and ISO IEC Linear Bar Code Print Quality Documents (PDF).
- Cognex, Explanation of ISO 15416 1D barcode grading process (blog).
- ISO IEC 15416:2016 preview PDF, Bar code print quality test specification Linear symbols (PDF preview).
Frequently Asked Questions
If a barcode scans, why should we worry about print quality grades?
A code that scans once is not necessarily reliable across scanners, distances, angles and environments. Verification grades measure margin, not just readability. Low margin codes often fail later in the supply chain, especially in high-speed automation, cold chain environments or customer receiving systems that use fixed scanners.
Are barcode verification standards required by regulation?
Verification standards such as ISO IEC 15416 and ISO IEC 15415 are not laws themselves. However, many regulatory and customer programs reference them directly or indirectly. In regulated industries like medical devices and pharmaceuticals, verification provides documented evidence that identification requirements are being met, which reduces audit risk and remediation effort.
How often should verification be performed on a production line?
Best practice is to verify during initial setup, after changeovers, after maintenance and periodically during production. The frequency depends on line speed, environment and risk tolerance. High-speed or harsh environments benefit from more frequent checks to catch drift before it becomes a shipment problem.
Does verification slow down production?
Verification does not need to slow production when implemented correctly. Many operations verify samples at defined intervals rather than every unit. The small amount of time spent verifying is typically far less than the time lost to rework, downtime or rejected shipments caused by bad codes.
Can operators reliably judge code quality without verification tools?
Visual inspection and handheld scanners are useful but limited. They cannot quantify margin or predict scan performance across different systems. Verification tools provide objective, repeatable measurements that remove subjectivity and help operators make consistent decisions.
Is poor code quality usually a printer problem?
Not usually. Poor code quality is often caused by a combination of process conditions, materials and equipment setup. Line speed variation, print distance changes, substrate reflectance and environmental factors like moisture or dust frequently play a larger role than the printer itself.
How does code quality affect brand trust?
Customers associate unreadable or inconsistent codes with poor process control. Over time, this can lead to increased inspections, additional documentation requirements or reduced confidence in a supplier. Even when products are safe and compliant, recurring code issues can quietly damage long-term relationships.
What is the minimum acceptable verification grade?
The minimum acceptable grade depends on customer requirements and application conditions. Many organizations target a C or 2.0 as a minimum, with higher targets such as B or 3.0 for high-speed, automated or regulated environments. The key is consistency and sufficient margin for real-world conditions.
Does this apply to non-regulated industries?
Yes. Food, beverage, logistics, building materials and general manufacturing all experience real costs from bad codes. Retail chargebacks, warehouse rejects and shipping delays affect profitability regardless of regulatory oversight.
What is the first step to improving code quality?
The first step is defining clear requirements. This includes symbology, data content, placement and a minimum verification grade. From there, testing on real substrates under real conditions and implementing routine verification creates a closed loop that prevents issues instead of reacting to them.
