Successful Data Integration in Transportation Management

Key Takeaways What you need to know

Automated data interfaces in a transportation management system (TMS) enhance efficiency and accuracy by eliminating manual data entry errors and reducing costs and time.
Use cases for data interfaces include handling large data transfers for transportation orders and frequent smaller data transfers for real-time ETAs.
Businesses can choose between standard interfaces for standardized data formats and individual connectors for customized data integration, depending on their specific needs.

How data interfaces enable automated, efficient and transparent supply chain processes.

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Reliable data integration is a necessary part of an efficient transportation network. But transferring data manually costs time and money, and the process is prone to errors. Especially in transportation management, mistakes can have significant consequences – for example, one extra zero can lead to a delivery with ten times more material than required. Interfaces for automated data transfer within a transportation management system (TMS) are a common solution. Interfaces support automatic transfer and processing of large amounts of data from an ERP system or other internal or supplier data sources to the TMS in just seconds. Once the data is transferred to the TMS, the data can be used in other systems as well. This method saves cost and time, in addition to reducing the risk of error.

Key takeaways at a glance

Data interfaces enable efficient data transfer from company data sources to software solutions for transportation management

Uses cases with the greatest potential include large data transfers and frequent smaller data transfers

Explore related questions

Businesses must decide between a standard interface and individual connectors

Collaboration with a service provider helps identify the optimal implementation approach

Use cases for data interfaces using a TMS as an example

An automated data interface is a good solution to transfer very large amounts of data. Typical use cases include using demand data to create transportation orders or using master data to calculate routes. The scalability of an interface plays an important role. Once implemented, an interface can process amounts of data thousands of times greater than what humans could manage.

Smaller amounts of data that need to be transferred more frequently are another use case for integrating a data interface – for instance, if estimated times of arrival (ETAs) need to be provided in real time. The amount of effort required to do this manually is often simply too high.

Standard interfaces vs. individual connectors

Generally, data interfaces can be sorted into two categories. Standard interfaces are standardized solutions offered by service providers to be used by diverse businesses. They require a certain format for data to be transferred. Standard interfaces are appropriate when working with master data, demand data or transaction data that exist primarily in a standard form.

As an alternative to standard interfaces, connectors can be created and customized to individual businesses. They accept data in the existing format and automatically adapt it to the standard format. With this solution, businesses do not need to carry out data mapping to ensure successful data transfer – which saves significant amounts of time when working with heterogeneous data. In addition, connectors can support businesses to meet individual requirements for transmission protocols, data security and authentication, or error management.

With both kinds of interfaces, data from the ERP system and any other data sources within the organization can be transferred automatically to the TMS or other systems. From there, the data has a variety of use cases, including the analysis, planning or execution of transportation, supporting freight cost management or enabling more efficient and transparent supply chain processes.

The path to a more efficient data interface

To successfully implement a data interface within an organization, checking data quality is an important first step. Upstream process steps and appropriate tools are often required to identify and correct errors in the data sets. Once the data quality is assured, the TMS interface can be integrated in several steps. Businesses should evaluate existing interfaces in an as-is analysis and build on them by defining additional necessary interfaces. These additional interfaces are detailed in a design phase, set up in an implementation phase and reviewed in a test phase. The more thorough the tests, the lower the risk of problems is after the go-live.

The go-live should be followed by a hypercare phase, in which optimization potential is identified using data and processes during normal business operations. Operational monitoring is often necessary to react to further demands for the interface in later phases of implementation. A thorough documentation of the technical implementation makes updating the interface easier, should new requirements arise.

Establishing data integration requires various approaches, depending on the organization and industry. In general, it is not sufficient to simply purchase a software solution. A software service provider can help define key specifications and implement the solution according to organizational requirements. Error analysis and management are two additional areas where collaboration with a service provider often makes sense. 4flow provides expertise in implementation of various data interfaces in the 4flow iTMS, the integrated transportation management system from 4flow, and creates end-to-end, industry-specific solutions together with its customers.

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