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Home » Blogs » Think Tank » Five Ways Data Moves Through a Logistics Network

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Data Management (Big Data/IoT/Blockchain) / Technology

Five Ways Data Moves Through a Logistics Network

data
Network cables in a data center. Photo: Getty Images.
January 20, 2022
Bernard Brode, SCB Contributor

Data is the most important currency in any effective logistics network. Today's supply chains, more complex than ever, are built on the rapid exchange of immense amounts of data that's used to track goods, optimize operations, mitigate risks and more.

The variety of data applications in contemporary logistics networks has also given rise to a number of networking technologies. Data moves through supply chains in many different ways, each with their own advantages and disadvantages. 

If you're looking to improve and develop your logistic network — whether in response to the supply chain crisis or simply to avoid common logistics mistakes — you'll need to understand these data exchange technologies.

1. Email

It might seem strange to start this list with email. Surely contemporary supply chains and logistic networks are built on far more sophisticated forms of data exchange than email?

Well, yes and no. It’s true that there are faster, more “modern” forms of data exchange in use today. But that doesn’t necessarily make them “better” forms of data network than the humble email. This is because logistics networks rely on a wide variety of data being exchanged — not just data collected by internet-of-things (IoT) networks or those related to the operation of mainframes, but also those that can only be collected, analyzed and shared by humans.

When it comes to this kind of data, email has a lot of advantages. It is easy to use, and everyone can send data in this way without having to undertake specialized training. When it comes to sharing a quick link to a dataset, or even a spreadsheet that contains the KPIs for your logistics network, it’s really quite difficult to beat email. That’s why email would find a place even in the perfect logistics network.

2. IoT Devices

IoT devices are also an important part of contemporary logistics networks. In fact, when building such a network from scratch today, the cost of IoT devices is likely to be the single largest expense. This means that when you estimate working capital requirements for your logistics network, you will need to calculate the level of IoT functionality needed.

Though implementing large-scale IoT networks can be costly, this is an expense that most companies recoup quickly via improved efficiency in their logistics networks. IoT devices can now be used to track the location and condition of goods in real time and can automatically share this information not only with each other but with centralized data processing software. This allows you to constantly optimize your logistics network to ensure it is as reliable as possible.

Today, most IoT solutions are offered as all-in-one packages. IoT devices are designed to be modular and adaptable to a wide variety of circumstances and types of networks. They achieve this by relying predominantly on Wi-Fi connectivity to exchange data. While this makes working with Wi-Fi devices simple and inexpensive, it also means that you must ensure good Wi-Fi coverage throughout your network in order for it to function correctly.

3. Transportation Management System (TMS)

TMS platforms are a more focused approach to data collection and analysis than IoT networks. A TMS is normally used to plan, manage and assess the physical movement of goods. TMS solutions are generally integrated into larger systems and can be used in conjunction with both IoT devices and even more specialized EDIs and APIs.

The primary advantage of a TMS is that it provides small- and medium-sized businesses (SMBs) with an inexpensive way to access the kind of advanced logistics functionality that was previously reserved for national firms. At a time when logistics costs are rising, a TMS system can allow smaller firms to cut costs. These cost savings can then be passed on to consumers.

TMS platforms typically work from a centralized, common data and application framework. This can make them easier to manage than distributed, heterogeneous IoT networks. Equally, they are more general systems than the dedicated APIs described below. Because of this, they provide an easy way for inexperienced businesses to start to gain truly valuable insights into the operation of their supply chains.

With all this said, SMBs should be aware that TMS platforms have disadvantages. TMS solutions require that all staff are able to access — and work within — a single, central platform. While this simplifies access and user management, it can also limit the flexibility of technical and software development staff.

4. Application Program Interface (API)

At the sophisticated end of data exchange in contemporary logistics networks are APIs. This is a customized way for a logistics application to send, receive and transfer information with other supply chain applications, with little or no human involvement. 

APIs have a long history — they have been the standard way for applications and other supply chain entities to communicate for decades. A few decades ago, custom-designed APIs were pretty much the only way that these entities could communicate. TMS and EDI platforms, in fact, can be thought of as more generalized versions of APIs. 

APIs have several key advantages over more generalized TMS and EDI systems. Because they are custom-made for your software and hardware, in most cases they are a much faster way to exchange data than the competition. Data transmission is also more reliable, because APIs use automated data collection and analysis tools to minimize human input, and therefore minimize human error.

On the other hand, APIs have some disadvantages. These are complex, custom systems that can be equally complex to develop and manage. This, in turn, means that they can be expensive to develop. You may need to employ highly specialized staff to manage them. The risks of not doing so were seen recently in an incident where an Amazon Web Services outage brought a warehouse to a halt — due in part to a lack of AWS experts on site.

Nevertheless, for companies looking to scale, beginning to build an API system can provide benefits long into the future. By putting in place dedicated, fast, reliable ways to work with your key logistics systems, you are providing yourself with a great foundation for a highly effective logistics network.

5. Electronic Data Interchange (EDI)

EDI can be thought of as a half-way point between an API and a TMS. Like an API, EDI provides you with a way of controlling entities that are part of your logistics network. But whereas APIs normally rely on customized ways of exchanging data between them, EDI uses an agreed-upon standard to transfer information between supply chain businesses and logistics applications. Like APIs, EDI is used for many different types of logistics data and use cases.

This means that EDI comes with some of the key advantages of API — speed, reliability and control. At the same time, EDI is easier to work with than a completely custom API, and so does not require highly trained and specialized staff. Many supply chain systems now offer integration with EDI as standard. This can be an effective way for companies to start building an effective logistics technology stack.

On the other hand, EDIs have some disadvantages compared to both dedicated APIs and TMS. They are more expensive than the latter and less secure than the former. Also, at a time when companies are investing in blockchain to lower costs, EDI has begun to lag behind when it comes to compatibility with the newest technologies.

The speed, reliability and efficiency of data exchange is one of the most important factors contributing to an effective logistics network. Because of this, leaders and technicians alike need to make sure that they understand the ways in which data can be exchanged across contemporary logistics networks in order to maximize their efficiency and efficacy.

Bernard Brode is a product researcher at Microscopic Machines.

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