How to Solve Common Barcode Scanning Challenges

Over 10 billion barcodes are scanned every day — twice as many as a decade ago. With this volume and increasingly complex workflows, it's harder to isolate and fix barcode scanning issues.

These problems could be poor barcode print quality affecting scanning accuracy, incompatibilities between scanning software and devices, an inability to scan new barcode types, environmental conditions degrading scan performance, or ergonomic gaps that frustrate users.

This guide explains how to address these common barcode scanning challenges and walks through real-world case studies that demonstrate how the right barcode scanning library can improve business outcomes.

The barcode is the backbone of data capture around the globe. Its widespread and varied use means there is no "one size fits all" solution to handle every real-world scenario.

In retail, barcode scanners are used at checkouts and throughout the back-of-house and supply chain operations. In healthcare, barcode scanning tracks patient information, medication administration, specimens, and devices. Logistics and supply chain management use barcode scanning to monitor inventory, manage shipments, and streamline warehouse operations. Airlines scan boarding passes and luggage tags. Last-mile delivery companies scan parcels at every stage of the process.

Most barcode scanning challenges stem from barcode scanning solutions that don't hold up in the real world.

It could be a configuration issue, testing that didn't reflect what users actually do, or the actual features of the barcode scanning hardware or software. Individual symptoms, such as slow performance or inaccurate scans, grow into larger process inefficiencies and data quality issues, resulting in poor employee and customer experiences.

Consider this scenario: your users complain that it takes too long and too much physical effort to scan tiny electronic shelf labels (ESLs) on the bottoms of shelves. How would you solve this problem?

Every barcode scanning solution has three components that you can play with:

1. A barcode: Either printed or shown on an electronic screen.
2. A scanning device: A smartphone, tablet, handheld computer, or a dedicated handheld barcode scanner.
3. Barcode scanning software: A runtime library that detects and decodes barcodes and passes data to a calling application.

In this example, it might seem obvious that you should increase the physical size of the barcodes. But that may not be possible, or have downstream impacts.

A more scalable alternative with minimal physical impact is to upgrade your barcode scanning software to one that can decode small barcodes from farther away.

For example, advanced software libraries include features that improve barcode scanning speed and accuracy. These include:

• Handling difficult codes, e.g. low light, small or damaged.
• Multiple barcode scanning (batch scanning).
• Augmented reality (AR) overlays.
• Context-aware AI that analyzes multiple signals beyond just detecting and decoding barcodes, to reduce unwanted or accidental scans.

Our comprehensive guide on how barcode scanners work takes a deep dive into types of barcode, standards, software, hardware, UX, and common issues.

The following sections explain seven common barcode scanning issues and their solutions.

If you have issues integrating a barcode scanner library into your app, consider whether it provides native support for your target device, operating system, and development stack. If it's not compatible with the existing technology infrastructure, you will spend more time porting it to your environment and potentially delaying the project.

While open-source barcode scanning software is appealing from a cost perspective, consider whether you have the in-house expertise and resources to manage its integration. Open-source software is often poorly documented and lacks official support, so developers have to rely on community help and timelines.

Many commercial solutions offer broad support, documentation, and code samples for different technology stacks — always review their system requirements before purchasing a license.

Scandit's advanced solutions reduce integration effort by offering pre-built components and turnkey apps, alongside fully customizable APIs. These reduce development effort and risk.

Working with vendors who provide comprehensive support and work closely with in-house IT teams reduces integration and schedule risks. A good vendor will also advise you to conduct thorough testing and validation in real-world scenarios to identify any issues and enable timely resolution.

Even the clearest, best-lit label won't scan properly if your barcode scanning software doesn't support its symbology.

There are many different types of barcodes, or symbologies, used globally. Different industries and applications have varying data encoding needs, resulting in symbologies such as UPC, EAN, Code39, Code 128, and Data Matrix. Each one has unique characteristics and encoding patterns.

To ensure your users aren't frustrated by failed scans, confirm that the barcode scanning software you deploy supports the symbologies your industry uses. Scandit’s industry-leading software supports all major 1D, 2D, 3D (engraved, etched, or embroidered), and composite barcode types, but other libraries may offer more limited coverage.

To improve performance, your software should also let you configure which symbologies are read, as the app won't require as many resources to process a smaller set of types.

If your scanner has trouble reading or capturing barcodes, it could indicate issues with the label's condition or the environment.

How to fix barcode quality problems

Common challenges with barcode quality include insufficient contrast between the black and white elements, incorrect size or dimensions, printing errors, and smudging or fading. Barcode scanners may also struggle to read codes that are torn, crinkled, or otherwise obscured.

There are two approaches to address these challenges.

• Improve the quality of your printed barcodes: Ensure that barcodes have high contrast against the background and meet size and resolution requirements. Use high-quality printing equipment and materials; reduce print speed to ensure accuracy; regularly maintain and calibrate equipment; and avoid printing on uneven or textured surfaces. The ISO/IEC 15416 standard defines methodologies for verifying the print quality of barcodes such as Code 128 and EAN-13.
• Upgrade your barcode scanning software: Industry-leading barcode scanning software, such as Scandit, is designed to capture barcodes under difficult conditions. You may find that a software upgrade solves many of your barcode quality challenges without the need to change printing workflows.

How to compensate for environmental factors affecting barcode scanning

These environmental factors can significantly affect barcode scanning performance, leading to errors and inefficiencies:

• Insufficient or uneven lighting.
• Dirt, dust, and smudges on the barcode or the scanner’s lens.
• Reflective surfaces that create glare, such as a package wrapped in plastic.

One way to improve barcode scanning performance is to change the environmental conditions. For example, moving packages to areas with bright, stable lighting and cleaning barcode labels and scanner lenses.

For situations where you have less control over environmental conditions, consider upgrading your scanning hardware or software — this is often a more cost-effective and scalable solution.

• Hardware: Some barcode scanning hardware provides its own light source, so you can tell users to manually trigger it as part of their workflows. Software such as Scandit SparkScan can be configured to automatically turn on the device’s torch for low-light scans.
• Software: Advanced barcode scanning software can compensate for degraded conditions by employing sophisticated image processing algorithms to extract label information in low-light and "noisy" situations.

Barcode duplication occurs when two or more items have the same barcode, leading to confusion, incorrect tracking, and errors in stock management. Cross-contamination occurs when barcodes from different products or batches mix in an inventory system, leading to misidentification and incorrect tracking.

When addressing barcode duplication and cross-contamination problems, it's more effective to rely on software rather than forcing users to perform additional manual steps. By implementing data deduplication techniques in your app, you can automate duplicate removal and avoid user errors.

Some barcode scanning software includes built-in algorithms to prevent duplicate barcodes and cross-contamination in back-end systems. They can also automatically verify that a newly scanned code matches an expected code, and alert users if it does not.

For example, Scandit's MatrixScan Count for inventory counting and receiving automatically counts the number of scans, filters out unnecessary barcodes, tracks progress using an augmented reality (AR) overlay, and counts non-unique items (for example, multiple packages of the same product).

Advances in smart devices and barcode scanning software have led to enterprises shifting away from traditional dedicated scanners to smartphones, tablets, and handheld computers. Teams are even deploying rugged smartphones for barcode scanning in challenging environments.

However, scanning barcodes on mobile devices presents unique challenges. Operating a barcode scanner is very different from using an e-commerce app or WhatsApp — if you apply the same UX techniques and UI components from those applications to barcode scanning, you run the risk of frustrating users and incomplete data capture.

On-screen workflows and device ergonomics must account for how often users scan barcodes, where barcodes are located, environmental conditions, and how the scanner fits into the existing application. For example, a full-screen scanning interface may obscure critical information located in the app underneath.

The easiest way to avoid poor UX and user frustration is to use pre-built barcode scanning software that includes user interface components. For example, Scandit's SparkScan offers a highly optimized, customizable user experience built on a powerful AI scanning engine. For even faster deployment, Scandit Express provides a turnkey app and UX optimized for workflows ranging from single barcode scanning to multiple barcode inventory counting.

Human error in barcode scanning can occur for various reasons, such as poor scanning techniques, distractions, lack of training, and fatigue.

You can reduce these errors by training users in proper barcode scanning techniques, such as how to position their device so that the label is within range and fully visible in the viewfinder.

However, while manual workarounds can help, any process that requires someone to aim carefully at thousands of individual codes and repeatedly press a button every day will inevitably lead to human error, not to mention being extremely tedious for users.

Technology offers alternative solutions to reduce human error:

• Smart barcode scanning software can implement error reduction and efficiency-boosting features such as built-in validation, auto-correct capabilities, and AR overlays that guide users on scanning success or failure.
• Context-based scanning that uses AI to automatically detect barcodes that users want to scan based on signals such as barcode position, device movement, and barcode characteristics.
• Automatic and simultaneous capture of barcode and printed text from labels, eliminating the need for humans to enter either type of data. Scandit's Smart Label Capture is an advanced form of this, using AI to extract the exact information an app needs up to seven times faster than entering elements one by one.

These techniques address the root causes of human error and inefficiency by shifting the burden of accurate, repetitive barcode scanning from people to technology.

Most barcode scanning challenges can be avoided earlier in the development lifecycle by conducting systematic testing under real-world conditions.

The best practices for real-world testing are:

• Use-case-based testing: Actual users use pre-release software to run test cases in environments that mimic the real world.
• Test with real user devices: Run tests with the actual hardware and operating systems deployed in the field, minimizing the risk of configuration issues skewing results.
• Use the latest version of scanning software: Install the latest versions, patches, and security fixes to ensure your software has the latest capabilities.
• Perform systematic testing: Break test cases down into atomic steps that validate a single feature. This helps isolate and remediate issues faster than having to debug multiple features at once.
• Choose the right test methodology: Different test methodologies, such as timed process runs and A/B testing, yield different results, so it’s important to use the best one that matches your use cases and chosen metrics.

Find out more about these best practices and examples of how to implement them in our How to Measure Barcode Scanning Performance guide.

Here are three businesses that solved many of the barcode scanning challenges listed above by deploying Scandit software:

• VF Corporation: One of the world’s largest apparel, footwear, and accessories companies achieved 100% inventory accuracy for omnichannel orders and over 50% time saving for store associates by upgrading from legacy, single-purpose scanners to smartphones running Scandit software.
• OK Corporation: This Japanese discount supermarket chain reduced in-store picking time from 5 seconds to 2 seconds and its picking error rate to almost zero by upgrading its barcode scanning engine.
• Stockholm Public Transport: This public transport organization improved service efficiency and ticket validation accuracy by switching from legacy handheld scanners to smartphones using Scandit software capable of scanning smartphone screens through reflected sunlight and glare.

As frontline workflows increase in volume and complexity, addressing root causes of barcode scanning issues instead of just symptoms results in more efficient operations, fewer frustrations, and an improved customer experience.

The solutions described here will help reduce or eliminate many common issues that affect barcode scanning performance and accuracy. It’s up to you to find the right balance between development effort and existing features in your software to implement these fixes.

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What are the most common challenges in barcode scanning?

The most common challenges in barcode scanning are software configuration issues, unsupported barcode symbologies, low-quality or damaged barcodes, and environmental conditions such as poor lighting or reflective surfaces. Human error and poor mobile UX also contribute to slow and inaccurate barcode scanning, particularly in high-volume enterprise workflows.

Each of these issues impacts speed, accuracy, and user satisfaction. Replacing hardware to fix these problems is often not feasible; that's why having reliable barcode scanning software designed to handle real-world complexity and support modern enterprise needs is essential.

Why do barcodes fail to scan even when printed correctly?

Even correctly printed barcodes can fail to scan due to improper configuration of the scanning software or environmental conditions that make them difficult to read. If the software doesn’t support the specific symbology used, such as EAN, UPC, or Data Matrix, the barcode may appear fine, but it won’t register.

Additionally, if multiple barcodes are in the device sensor's field of view, the software may struggle to identify the correct one. Barcode scanning software that isn't optimized for variable-distance scanning may also struggle, particularly if the barcode is very small or placed at an awkward angle.

How do environmental factors like lighting or glare affect barcode scanning?

Environmental factors such as low lighting, reflections, dirt, and glare can distort barcode visibility and significantly reduce scan success rates. Barcode scanners may fail to distinguish between the dark and light elements of the barcode or misread data due to visual interference from reflective packaging or protective film.

Advanced barcode scanning software compensates for these conditions by employing image processing algorithms and adaptive adjustments to image capture. Some barcode scanning SDKs can automatically activate the device torch in low-light environments and filter out background noise to extract clean barcode data.

Do smartphones scan barcodes as well as dedicated scanners?

Yes, modern smartphones equipped with advanced barcode scanning software can match or exceed the performance of dedicated scanners in many use cases. With the right software, smartphones can scan a wide range of barcode types, at different distances and angles, in varying environmental conditions.

Smartphone-based barcode scanning also provides greater app flexibility, lower total cost of ownership, and simpler deployment across distributed teams — especially where bring-your-own-device (BYOD) programs are used. Paired with optimized UX workflows, smartphones are a viable alternative to legacy scanning hardware in every industry.

Why do scanners struggle with barcodes on screens or digital boarding passes?

Barcode scanners often struggle with digital barcodes due to glare, low screen brightness, or pixel distortion. Barcode images displayed on smartphone screens may have insufficient contrast or may be curved, dimmed, or obstructed by smudges or cracks, making them difficult for traditional laser and low-end imaging scanners to interpret.

Advanced, enterprise-grade barcode scanning software is designed to handle digital screen scans by employing sophisticated image processing techniques and decoding that's resilient to glare, low-light, and distortion.

Solutions like the Scandit Barcode Scanner SDK can scan digital boarding passes, coupons, and digital IDs directly from screens — even in bright environments like airports and outdoor checkpoints.