I need for this one as well: The “same address, different identity” problem across systems

A company can have the same physical location stored in several systems and still have no reliable way to know that those records represent the same place. The address may look identical, or almost identical, but each system can assign its own identifier, structure, naming convention, or internal reference to it. What is one warehouse, customer site, or supplier location in the physical world can therefore become several different locations in the digital supply chain.

This is one of the less visible challenges of location data management. Businesses often focus on whether an address is correct, complete, or properly formatted. But even a perfectly correct address can create problems if different systems do not recognize that they are referring to the same physical location. The issue is not only about the quality of the address itself. It is about the identity attached to that address.

One Physical Location Can Have Multiple Digital Identities

Consider a warehouse at a single physical address. In the ERP, it may have one customer or site ID. The WMS may assign it a warehouse code. The TMS may store it as a transport location with its own identifier. A carrier may have another reference for the same place, while a mapping or geocoding service may identify it using coordinates or a separate location ID.

There is nothing inherently wrong with systems having their own identifiers. Different applications have different purposes, and their internal structures are designed around specific business processes. The problem appears when those identifiers are treated as if they represent different physical locations simply because they are different system records.

The physical warehouse has not changed. Only its digital identity has multiplied.

Why Identifiers Matter More Than Addresses Alone

An address is an important part of identifying a location, but it is not always enough to establish a reliable relationship between records. The same address can be written in different formats, translated into another language, abbreviated, separated into different fields, or enriched with additional information.

For example, one system might store “Industriestrasse 15, 8005 Zürich,” while another stores the street, number, postal code, and city in separate fields. A third might include coordinates, a site code, or a delivery entrance. All three may refer to exactly the same physical location.

If systems compare records only through exact text matching, these differences can make identical locations appear unrelated. As a result, the organization may create duplicate records, lose relationships between systems, or fail to recognize that an update in one database affects the same location elsewhere.

The Problem Starts When Data Moves Between Systems

Location identity becomes especially important when data moves from one system to another. During an integration, a location may be copied from the ERP into the TMS, from the TMS to a carrier, or from a customer database into a delivery platform.

The receiving system may not understand the source system's identifier. It may create a new record instead of connecting the incoming information to an existing location. Even when the address itself is identical, the receiving platform may have no way of knowing that it already has a record for that physical place.

Over time, this process can create multiple records for the same location. Each one may be technically valid within its own system, but the relationship between them is lost.

Small Differences Can Hide the Same Location

In practice, identical locations rarely remain perfectly identical across every system. Formatting differences are common, but they are only one part of the problem. Company names can change, abbreviations can differ, postal information can be structured differently, and additional operational details may be added in one system but not another.

A warehouse might appear as “Logistics Center West” in one database and “LC West” in another. A supplier may be recorded under its legal company name in the ERP but under a site-specific name in the TMS. The street address may be the strongest common element, but even that can contain variations.

These differences do not necessarily mean that the records refer to different places. They simply mean that the systems are describing the same place in different ways.

The Opposite Problem: Different Locations Can Look the Same

There is another reason why address matching cannot be based on one field alone. Two records can look very similar while representing different physical locations.

A large company may have several facilities on the same street, different buildings within one industrial complex, or multiple entrances and operational points associated with a single postal address. A shared address does not automatically mean that two records should be merged.

This creates an important balance. Businesses need to identify records that represent the same physical location, while avoiding the accidental consolidation of genuinely different locations. Reliable location identity therefore requires context and matching logic, not simply an exact text comparison.

Different Identities Create Operational Blind Spots

When the same location has multiple identities, the consequences can extend well beyond the database. A planner may see two separate delivery points where there is actually one. A reporting system may count the same customer site multiple times. A routing platform may maintain separate histories for what is physically the same destination.

This fragmentation can affect planning, reporting, forecasting, and optimization. Historical delivery performance may be split across multiple records. Transport volumes may be attributed to different locations. Changes made to one record may not be reflected in another. And teams may spend time investigating discrepancies that exist only because different systems have different representations of the same place.

The problem is particularly difficult to detect because each individual record can look perfectly reasonable.

Integration Does Not Automatically Solve Identity

It is easy to assume that if systems are integrated, their location records must also be connected. But integration primarily enables information to move. It does not automatically establish whether the information represents an existing location or a new one.

When a new address enters a system, the receiving platform needs to determine whether it is a new physical location or another representation of a location that already exists. Without a reliable matching process, the safest technical choice is often simply to create another record.

That may work for an individual transaction, but repeated across thousands or millions of locations, it creates a fragmented network of records that become increasingly difficult to manage.

Location Identity Needs to Survive Across Systems

A more reliable approach is to establish a consistent identity for the physical location and maintain the relationships between its different system representations.

This does not mean replacing every ERP, WMS, TMS, or carrier identifier with one universal ID. Each system can continue using the identifier it needs. What matters is knowing that those identifiers belong to the same underlying location.

Once that relationship exists, businesses can connect records across systems even when their formatting, attributes, or identifiers differ. An update made in one environment can be associated with the correct location elsewhere. Historical information can be consolidated. Duplicate records can be identified more reliably, and downstream processes can work from a much clearer picture of the network.

From Address Matching to Location Matching

This is where the concept of location matching becomes more important than simple address comparison. The question is not just whether two strings are identical. The real question is whether two records represent the same physical place.

A reliable matching process can consider multiple elements of a location record, including address components, postal information, geographic coordinates, names, identifiers, and other contextual attributes. The goal is to determine relationships between records with enough confidence to distinguish genuine duplicates from legitimate differences.

This creates a much stronger foundation for cleaning and consolidating location data. Instead of treating every variation as a new location, businesses can begin to understand the network behind the records.

Why This Matters for Logistics Continuity

Logistics Continuity depends on more than moving information between connected systems. It depends on maintaining the identity of the things that information describes.

If the same warehouse is recognized as one physical location across the ERP, WMS, TMS, carrier, and other systems, information can remain connected as it moves through the supply chain. If every system treats that warehouse as a completely separate location, continuity becomes much harder to maintain.

The “same address, different identity” problem is therefore not simply a master data issue. It is a continuity issue. When a physical location loses its consistent identity across the digital network, changes, decisions, and operational events can become disconnected from one another.

Conclusion

A location does not become a different place simply because a different system gives it a different identifier. Yet without a way to connect those identities, businesses can end up managing multiple digital versions of the same physical reality.

The challenge is not to force every system to use the same structure or identifier. It is to establish the relationships between records so that one physical location can be recognized across different applications, databases, and organizations.

Once businesses can reliably answer the question “Which records represent the same place?”, they have a much stronger foundation for cleaning, consolidating, enriching, and continuously managing location data. That is an essential step toward maintaining Logistics Continuity — and a natural starting point for understanding why matching and cleaning location records is so important.

Disclaimer: Image created with AI