Middleware was a term coined back in the 1990’s to describe software that bridged the gap between the numerous application ‘islands’ that existed within large organisations. It was seen as a solution to enable the operation of so called ‘distributed systems’. As the demand for information systems grew across the organisation, along with the requirement to share more information with partners, the core applications could not cope. So as users grew impatient with internal IT delays, they started buying solutions from a variety of vendors. This resulted in lots of different systems, generating large amounts of valuable operational data, but only within the function where the solution was deployed.
To try and regain control of this disjointed landscape, corporate IT departments looked at so called ‘Middleware’ platforms as the solution. They were designed to manage the flows of data between the various applications so that the data and information flows matched those of the operational process flows.
While the intent of today’s middleware of linking various systems may be similar, the challenges are more complex. This is due to the huge variety of different data sources and the need to understand the context of that data. As more companies have outsourced their systems infrastructure and applications to the Cloud, standardised API’s should make the exchange of data easier.
The rapid transfer of data across the network is a necessity as it enables real-time decision making because any unexpected events should show up faster. However, the ‘controlling mind’ described above, is often augmented by machine learning algorithms providing decision support to the supply chain managers. This is why the precision and context of any data a necessity. The role of a middleware component is vital in this context, as it must enforce conformance to the requirements designed into the operational systems.
Decision support ‘tools’ like this are commonly known as logistics ‘Control Towers’ and they collect data and information from across the entire operational landscape. Therefore, these systems are dependent on all of the other systems across the operations to provide the appropriate data. This is where middleware applications can add tremendous value. Not only by enabling the exchanges between the various systems, but by doing so in a consistent and coherent manner. These exchanges also have to be bidirectional because if the ‘Control Tower’ needs to respond to information about an event, it must be able to send the appropriate command back to the relevant system if something needs to happen.
This also illustrates why supply chain visibility is also critical. Visibility is the means to collect and qualify information flows from across the supply chain. Indeed, if middleware enables the various systems to share the data, the visibility system provides the context necessary for the Control Tower applications to make sense of it. They must all work in harmony for the best outcome.
Middleware will become even more significant with the ‘Internet of Things’ revolution. The collapsing cost of sensor technology means that it is becoming economical to embed sensors for identification, location, environment and status in almost any item. But this data only has value if it can be captured by systems and then shared appropriately. It is the raw material for the intelligent supply chain.
Middleware is just one element in the mix of ingredients to deliver a successful transition from asset to information-intensive enterprise. As the size of a logistics network grows, the ability to quickly incorporate the systems and services of the new entrants will be critical. Making these connections in a manner that also adapts to frequent change, along with maintaining the context of any data, will also be essential.
The conundrum is that the best way to establish this kind of organisation requires systems expertise and operational experience. Attributes that often reside with large established and asset intensive organisations – the very structures this approach will challenge. Well capitalised start-ups may have the systems expertise and financial resources to compete, but they need to accumulate the expertise and then learn how to operate at scale, in a very complex ‘real-world’ industrial landscape. This is not dissimilar to the growing competition between Amazon Logistics (Excellent IT and scale) and Walmart, UPS, FedEx etc. (Massive scale, very large asset base and deep operational expertise).
Source: Transport Intelligence, April 15, 2021
Author: Transport Intelligence
This brief has been taken from a larger paper, ‘Middleware, the key ingredient in the quest to transition from an asset intensive to an information intensive enterprise’ by Ti Advisory Board member Ken Lyon. This paper is available exclusively to GSCi subscribers. Each week, Ti’s team of senior analysts and industry experts deliver analysis covering the latest logistics and supply chain trends exclusively to users of GSCi.