Shipment Tracking: Tracking and Tracing

Tracking and tracing are the technological cornerstones of modern supply chain visibility (SCV). While the terms are often used interchangeably in everyday language, they describe two distinct functions of logistics data management. In an era of just-in-time deliveries and lean management, the ability to locate goods in real time and reconstruct their history without gaps is no longer merely a competitive advantage, but an operational necessity.

To gain a precise understanding of the topic, it is essential to distinguish between the two processes technically:

• Tracking (The “Now”): The process of monitoring the current location and status of a shipment in real time. It answers the question: “Where is my freight right now?”
• Tracing (The “Past”): The process of reconstructing the historical path of a shipment. The focus is on audit trails and documentation. It answers the question: “What route did the goods take, and where were there delays?”

Synergy: Only the combination of both functions creates a transparent “digital twin” of the physical flow of goods.

A tracking system is only as valuable as its ability to exchange data across company boundaries. This is where global standards come into play, preventing the creation of data silos:

• GS1 (Global Standard 1): The world’s most important standard for identifying products and locations. The use of GTINs (Global Trade Item Numbers) and GLNs (Global Location Numbers) ensures that a package in Shanghai speaks the same “language” as one in a logistics center in Germany.
• EPCIS (Electronic Product Code Information Services): A GS1 standard developed specifically for tracing. EPCIS defines what, when, where, and why an event took place. It is the “grammar” behind tracing, enabling events to be synchronized across various partners in a supply chain.
• ISO/IEC Standards: Standards for hardware communication (e.g., RFID frequencies) that ensure a sensor from Manufacturer A is compatible with a reader from Manufacturer B.

Depending on the value of the goods and the required precision, different technological levels are used:

A. Passive Identification (Event-Based)

• Barcode / QR codes: Most cost-effective solution; requires manual scanning at predefined checkpoints. Highly dependent on human discipline.
• RFID (Radio Frequency Identification): Enables contactless reading of multiple items simultaneously. Ideal for warehouse exits and gate monitoring.

B. Active Monitoring (Real-Time)

• GPS / GNSS: Satellite-based positioning for vehicles and containers. Provides absolute coordinates but is energy-intensive.
• BLE (Bluetooth Low Energy): High precision within a limited radius; ideal for the “last mile” or internal tracking within the warehouse.
• IoT & Sensors: Integration of environmental data (temperature, vibration, humidity). Indispensable for cold chain logistics (pharmaceuticals/food).

When data flows across different organizational boundaries (shipper $\to$ Freight Forwarder $\to$ Customs $\to$ Recipient), a “trust gap” arises . It must be ensured that the data has not been tampered with and that all parties have the same level of information. There are three technological approaches here:

1. Decentralized Ledgers (Blockchain)

• Concept: A distributed ledger in which each participant holds a copy of the data. Changes are only possible by consensus and cannot be deleted retroactively.
• Use Case: Ideal for extremely complex supply chains involving many parties who distrust one another, or for highly regulated goods (e.g., diamonds, luxury goods).
• Criticism: High energy consumption, slow transaction times, and often overkill for standard logistics processes.

2. Centralized Trusted Third Parties (TTP) & Platforms – the pragmatic alternative

• Concept: Instead of building a decentralized system, all partners trust a neutral “data hub” or a leading platform (e.g., a 4PL provider or industry-specific networks such as Catena-X in the automotive industry).
• Advantage: Significant speed advantages and easier integration via standardized APIs. Trust here is based on legal frameworks (SLAs) and the platform operator’s reputation.
• Use Case: The current industry standard for most enterprise logistics solutions.

3. Cryptographic Integrity & Digital Signatures — the technical alternative

• Concept: Here, the entire database is not distributed; instead, individual data records are assigned hashes (digital fingerprints) and digital signatures. If any information is altered, the signature breaks, and the fraud becomes immediately apparent.
• Advantage: Offers nearly the same level of security as a blockchain in terms of tamper detection, but is technically trivial to implement and requires very little computing power.
• Use case: Electronic consignment notes (eCMR) and digital customs clearance.

4. Federated Data Spaces (e.g., IDS – International Data Spaces) – the sovereign alternative

• Concept: Instead of sending data to a central location or storing it in a chain, the data remains with the owner. Only authorized partners may access it temporarily via defined interfaces (“Data Sovereignty”).
• Advantage: Maximum control over one’s own trade secrets while maintaining transparency for the partner.
• Use Case: Strategic partnerships where data sovereignty is more important than a single source of truth.

A strategic decision for logistics managers is choosing the level of tracking detail:

• Unit Level (Individual Items): Every item is tracked. Highest costs, maximum transparency (ideal for high-value electronics/luxury goods).
• Pallet/Container Level: The transport unit is tracked. Balanced cost-benefit ratio; requires that all contents of the unit move together.
• Shipment Level: Tracking via the shipment number. Lowest precision, focus on milestones (e.g., “In transit”).

5. Integration into the IT Ecosystem (WMS & TMS)

Tracking and tracing only realize their full value through deep integration into the software architecture:

1. TMS (Transport Management System): T&T data enables dynamic ETA (Estimated Time of Arrival) calculations and proactive route optimization.
2. WMS (Warehouse Management System):</ strong> Incoming T&T data triggers “pre-arrival” processes, allowing the warehouse to optimize staffing based on the actual arrival time.
3. Customer Interface: Automated push notifications reduce the workload on customer service by providing customers with self-service transparency.

Tracking and tracing only realize their full value through deep integration into the software architecture:

1. TMS (Transport Management System): T&T data enables dynamic ETA calculations (Estimated Time of Arrival) and proactive route optimization.
2. WMS (Warehouse Management System): Incoming T&T data triggers “pre-arrival” processes, allowing the warehouse to optimize staffing based on the actual arrival time.
3. Customer Interface: Automated push notifications reduce the workload on customer service by providing customers with self-service transparency.

Implementing a comprehensive T&T system has a direct impact on key performance indicators:

• Reduction in lead time variability: Greater predictability of arrivals.
• Reduction in safety stock: Less buffer inventory required due to increased visibility.
• Increase in NPS (Net Promoter Score): Transparency reduces the perceived risk for the buyer.
• Loss prevention: Quick identification of the point in the chain where a shipment went missing.

Despite technological maturity, operational hurdles remain:

• Data silos: Different service providers use various proprietary systems, leading to “blind spots” during handoffs.
• Cost-benefit ratio: The cost of an active IoT sensor can exceed the value of the goods being transported.
• Hardware Lifecycle: Managing thousands of active trackers (battery replacement, maintenance) requires significant operational effort.

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