Traceability with a System: Turning Auto-ID into a Success Factor in Logistics

Auto-ID and Traceability: Basics and Key Differences

At the core of every intelligent logistics process lies the ability to automatically identify, locate, and digitally track objects. The digitalization of intralogistics starts with Auto-ID, which is a prerequisite for reliable traceability throughout the entire logistics chain.

Auto-ID stands for "automatic identification" and includes technologies that enable machines to recognize physical objects. There are two types of methods:

• Passive methods: Barcodes, QR codes, and passive RFID tags store information that can be read by external devices. Since they either do not require their own energy source or draw power from the reader, they can be used almost indefinitely.
• Active methods include: BLE (Bluetooth Low Energy), UWB (Ultra-Wideband), and LPWAN-based technologies (e.g., NB-IoT) actively transmit data and are therefore also suitable for real-time location tracking.

In industrial contexts, particularly intralogistics, these technologies enable traceability by capturing and transmitting information throughout the entire supply chain – from goods receipt through warehousing and transport to final delivery or assembly lines.

To better understand traceability, it’s important to distinguish between three related concepts.

• Identification: The ability to recognize an object via a globally unique ID. For example, a specific component identified by a barcode or RFID tag.
• Tracking: This goes a step further by enabling the determination of an object’s position at a specific point in time – typically enabled by active Auto-ID technologies.
• Traceability: The capability to reconstruct the complete journey of a product or container, including every process step, transport movement, and handling. The ultimate goal: full real-time transparency. 

Pilot Project or Breakthrough? The Maturity of Auto-ID Technologies Put to the Test

The history of Auto-ID technology is impressive. As early as 1973, the first RFID patent was granted. By the mid-1980s, initial industrial applications had begun, such as at Union Pacific in the U.S., where railcars were identified via RFID. The launch of Norway's first nationwide toll collection system in 1987 made it clear that the technology was ready for large-scale use.

Since then, Auto-ID technology has continued to evolve. Pioneers in the automotive industry, such as Audi and Ford, began using RFID early on to track car bodies and vehicle parts. Use cases range from tracking components at the prototype level to monitoring transport movements end-to-end in serial production.

A major milestone in this evolution was the integration of newer technologies, such as Bluetooth Low Energy (BLE) and Ultra-Wideband (UWB). These technologies enable not only precise identification but also reliable localization. The combination of these technologies can close existing gaps in the use of Auto-ID along the supply chain, significantly boosting efficiency, transparency, and traceability in smart logistics.

Despite this history and the clear benefits, many companies still struggle to implement Auto-ID consistently and strategically. Most initiatives remain stuck at the pilot project stage.

At first glance, the Auto-ID market seems ideally positioned: hardware costs are low, the technology is mature, and there is no shortage of providers. Yet this abundance of options is part of the challenge. Rather than offering holistic, end-to-end solutions, companies face a fragmented market consisting of niche providers, startups, and industry-specific, isolated solutions. Consequently, businesses find it difficult to establish a sustainable, unified digitalization strategy for logistics. 

Unified Rules for Traceability: How VDA, ISO, and PPWR Are Setting the Standards

To counteract fragmentation, industry associations like the German Association of the Automotive Industry (VDA) are actively promoting the harmonization of Auto-ID standards. Through initiatives like the “Key Technology” working group, the VDA collaborates with original equipment manufacturers (OEMs) and suppliers to develop practical, end-to-end reference models and interface guidelines. The goal is to ensure that components and containers can be identified and tracked seamlessly across manufacturers and systems. Meanwhile, ISO standards are being established at the European level to anchor these rules internationally. 

MHP as an Active Shaper of End-to-End Standards 
MHP plays an active role in defining these industry-wide standards. The aim is to overcome technological fragmentation and establish future-proof, interoperable system landscapes that enable true end-to-end traceability. Through the MHPLab, MHP demonstrates its practical problem-solving expertise: challenges are analyzed conceptually and transformed into usable technical solutions in close collaboration with partners.

Meanwhile, expectations for transparency and compliance are increasing. Customers, regulators, and ESG guidelines demand seamless traceability of material flows, packaging, and environmental impacts. This pressure will become especially visible with the upcoming EU Packaging and Packaging Waste Regulation (PPWR), which will be phased in starting Q2 2026. 

What Does PPWR Mean in Practice?
The regulation requires that all packaging be fully recyclable by 2030 and obligates companies to: 
use recycled plastics, ensure digital traceability of materials, meet minimum reuse quotas and provide transparent reporting on sustainability and environmental, social, and governance (ESG) disclosures.
For companies, this means one thing: without digital traceability, compliance will be nearly impossible. Those who fail to invest today risk facing not only regulatory penalties but also falling behind the competition. Future audits, sustainability reports, and product certifications will rely on data that can only be generated through integrated Auto-ID solutions in smart logistics and intralogistics. 

Economic Pressure: Why You Need to Act Now

Beyond new regulatory requirements, the economic environment for industrial logistics in Europe is becoming increasingly challenging. The automotive sector is grappling with growth rates of just around 1%, while grappling with unpredictable market developments, persistently high energy costs, and intensified competition. Manufacturers and suppliers are under immense pressure due to supply chain disruptions, raw material shortages, geopolitical uncertainties, and volatile sales markets. It is essential for processes to become more efficient and resilient.

In this climate, a company’s ability to drive digital transformation is a prerequisite for survival and growth. However, the MHP Industry 4.0 Barometer 2025 study revealed that digitalization is progressing slowly in the DACH region. According to a recent Bitkom study, 53% of companies report facing challenges with digitalization, and only 32% consider themselves pioneers.  

This makes one thing clear: even if budgets are currently tight, now is precisely the right time to invest in the digitalization of logistics. Only by doing so can companies remain competitive in an increasingly data-driven market. Those that push forward with digital traceability gain measurable advantages – from reduced process costs and improved service levels to greater steering capabilities.

Treating traceability as a strategic priority secures compliance while building the foundation for efficiency, transparency, and digital value creation. It also enables companies to uncover and leverage cost-saving opportunities not only within their own operations but across the entire value chain.

Yet, many companies still struggle to transition from the pilot phase to full-scale implementation. This is exactly where the next chapter begins. 

Between Isolated Projects and System Gaps: Why Many Companies Struggle to Implement Auto-ID

In most cases, Auto-ID projects do not fail because of the hardware itself, but because of the system landscape and project structure. Many solutions cannot be seamlessly integrated into existing IT systems, warehouse management, or production processes. Another major barrier is the lack of standardization. Companies often need to develop their own interfaces to integrate new technologies, which is costly, error-prone, and difficult to scale. This is especially true in the automotive industry, where a wide range of partners and suppliers are involved, making networked, interoperable systems essential.

Many Auto-ID initiatives begin as pilot projects without a strategic foundation. These projects are often driven by individual departments – typically out of technical curiosity or interest in innovation – without a clear business case or defined long-term goals. As a result, these projects cannot be scaled because they lack management commitment and integration into core operational processes.

Additionally, companies often underestimate the complexity of integration. An Auto-ID solution can only deliver its full value when seamlessly embedded into existing systems. Without this integration, companies end up with data silos, manual handovers, and operational friction. Captured data often remains unused or is not systematically evaluated, which prevents the benefits of digitalization in logistics and traceability from materializing. 

Business Value: Why Auto-ID Really Pays Off

Complex supply chains, countless load carriers, and high-frequency goods movements present a daily challenge for many companies. It is often difficult to know exactly where a shipment is at a given moment or who last handled it.

One of the most costly issues is container loss. Industry experience shows that between 5% and 15% of load carriers are lost or returned late every year, causing damages worth millions. At the same time, up to 20% of required containers are often missing from circulation due to a lack of transparency. The result: companies are forced to increase pool sizes, order costly replacements, schedule special trips, and absorb unnecessary waiting times in production.

Even in day-to-day operations, significant potential is wasted. Logistics teams spend hours manually searching for containers, recording transport movements, and reconstructing container histories. These activities are error-prone, drain valuable resources, and slow down response times.

Another key challenge is the unclear expectation of ROI. Many companies struggle to quantify the economic effects they can achieve through Auto-ID implementation. Business cases often rely on assumptions such as “time saved on searches,” which rarely translate into measurable staff cost reductions. Without reliable KPIs for savings, process improvements, or transparency gains, Auto-ID projects risk being perceived as cost centers – and can quickly stall when budgets are tight.

Auto-ID technologies address these pain points and deliver clear, measurable advantages: 

• Reduced transport costs: Accurate localization and real-time data enable precise scheduling and eliminate empty runs.
• Optimized container usage: End-to-end tracking reduces the number of containers that need to be purchased, freeing up storage space and cutting costs significantly.
• Reduced shrinkage and replacement costs: Automatic traceability minimizes loss rates and reduces the need for expensive replacements.
• Higher process efficiency: Automated booking replaces manual entries, saving time and reducing errors.
• Improved material availability: Continuous tracking helps prevent shortages of critical container types.
• Proven compliance: Every movement is automatically documented, providing a reliable basis for audits and ESG requirements.
• Foundation for data-driven optimization: Auto-ID generates the granular data required for advanced analytics, AI-supported planning, and real-time process improvements. 

Therefore, Auto-ID technology is the strategic enabler of transparent, resilient, and future-proof logistics processes. Companies that leverage their potential today will secure a competitive advantage tomorrow. Traceability is the key to optimizing intralogistics in the era of smart logistics. 

The MHP Approach: From Strategy to Scaling

To prevent Auto-ID initiatives from getting stuck in pilot projects, companies need a structured, multi-phase approach. MHP supports this journey with a holistic model that connects strategy, use-case development, and technical architecture. 

Phase 1: Strategy – setting the right course

The first step toward achieving scalable traceability is to establish a clear strategic framework that balances technological openness with defined decision-making boundaries. The objective is to implement technologies and achieve tangible business outcomes, such as reducing costs, increasing transparency, and promoting sustainability.

The Auto-ID and tracking market is broad, dynamic, and highly fragmented. Startups and established providers often use different protocols and standards. Therefore, a comprehensive market overview is crucial to setting the right course.

Another key success factor is managing technological dependency consciously. While choosing a specific solution can make sense, it should be based on a well-founded evaluation. Companies that explore multiple approaches during the evaluation phase and focus on modular, scalable architectures can ensure that later adaptations or expansions will be possible with minimal effort.

Critical questions to address during this phase include: 

• What are the primary objectives: cost optimization, efficiency gains, greater resilience, or meeting sustainability requirements?
• Which competencies should be developed in-house, and which tasks should be outsourced to partners or service providers? 

The outcome of this strategic alignment is a robust concept that integrates technical, organizational, and economic factors, setting the framework for all subsequent steps. 

Phase 2: Use cases – start small, think big

A successful entry begins with a clearly defined use case. Together, we will identify an area that reflects typical challenges, yet is small enough to deliver quick results. Often, we choose a specific product type or container type, especially if it experiences high loss rates or requires significant manual effort.

It is crucial that the pilot is economically viable from the start. Internal confidence to take further steps grows only if the benefits can be demonstrated quickly. Typical starting points include goods receipt, order picking, and the export area.

Based on the pilot, we develop a prioritized roadmap that can be gradually extended to additional processes, such as internal warehouse movements, external transportation, and last-mile delivery. 

Excursus: SCALING Arena – embedding organizational structures

To ensure that traceability remains scalable, a central control unit is required—the SCALING Arena. The SCALING Arena serves as the organizational backbone for company-wide implementation. It ensures that synergies across sites are leveraged, standards are defined, and new technologies are systematically monitored. 
The SCALING Arena has four core responsibilities: 

1. Technology governance: The SCALING Arena ensures that solutions align with strategy, are scalable in the long term, interoperable, and maintainable.
2. Use-case management: A structured use-case portfolio is systematically developed and continuously expanded. Use cases are prioritized based on their economic potential and the feasibility of integrating them into existing architectures to ensure an optimal implementation sequence.
3. Capability management: The SCALING Arena tracks and manages existing and required company competencies. The SCALING Arena strategically decides how to realize these competencies, whether through internal development or external partners, and guides the ongoing development of skills through targeted training and upskilling measures.
4. Market monitoring: This organizational unit detects technological trends, new providers, and regulatory changes early, ensuring that relevant developments are incorporated into strategy and implementation in a timely manner. 

Phase 3: Architecture – modular and future-proof

A scalable traceability system requires a well-thought-out technical architecture that can adapt flexibly to changing requirements without having to start from scratch each time. At its core, this involves creating a system landscape that unites different technologies for diverse potential use cases. To achieve this, the architecture must be modular, interoperable, and future-proof. The focus is on a holistic approach that continuously processes data from capture to utilization within enterprise systems.

The following principles are central: 

• Modularity: New sensors and tracking technologies, such as RFID, NFC, or BLE, can be integrated at any time without major adjustments.
• Scalability: The architecture is designed to reliably handle large volumes of objects, data points, and devices, making the technology usable across different processes. A successful pilot at one site serves as a blueprint for others.
• Interoperability: Open interfaces ensure that solutions from external providers integrate seamlessly into existing systems, allowing processes to be automated in-house.
• Flexibility: The architecture enables providers to be switched and individual technology components to be replaced quickly without compromising the overall structure. 

This approach directly supports the company’s strategic goals. A flexible and expandable architecture is essential for establishing traceability as a cornerstone of a data-driven organization from the outset, enabling smart logistics and optimized intralogistics processes. 

Mastering Traceability: The Right Time Is Now

Auto-ID technologies are widely available, proven, and affordable. However, they only reach their full potential when companies implement them strategically, structurally, and organizationally. Technological maturity alone is not enough; how companies shape the transformation matters most.

Rising economic pressure and new regulatory requirements leave little room for hesitation. Acting now allows companies to measurably optimize processes, reduce costs, and meet compliance requirements on time.

A successful start does not require the biggest solution but rather a focused use case that delivers real value. A clear target vision and a structured approach are essential. We support you in setting the right course with solutions like our cloud-based, open infrastructure, such as MHP's AUTOID INFRASTRUCTURE AI2. Start now. Create transparency. Make your smart logistics ready for the future. 

MHP's AutoID Infrastructure AI2 in Detail
AI2 acts as a cloud-based orchestration layer between Auto-ID technologies and enterprise systems. The platform addresses typical scaling challenges by offering:
Technology independence: The solution consolidates various Auto-ID technologies, such as RFID, Bluetooth, UWB, and LIDAR, into a unified, vendor-independent platform. 
Modular architecture: New technologies and use cases can be flexibly integrated without disrupting existing system structures or requiring complex reimplementations. 
Central data harmonization: Different data sources are standardized and validated to enable cross-use case data connectivity. 
Open integration: Standardized interfaces allow for the seamless connection of enterprise applications, such as ERP, MES, and Power BI, eliminating the need for costly custom solutions. 
Cost efficiency: Standardization and low-code programming significantly reduce licensing and implementation costs compared to custom solutions.
The result is end-to-end traceability from individual pilot projects to company-wide solutions that are free from vendor lock-in and have fast implementation times enabled by low-code programming. 

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