Supply chains are the delicate backbone of worldwide commerce. While many consumers take them for granted, the truth is a lot goes into ensuring a supply chain works smoothly. Everything from manufacturing inventory, storage, logistics, and last-mile delivery faces unique challenges that change daily.
Visibility plays a huge role in making sure operations work smoothly. Alarmingly, visibility is also a major issue for most companies. Research conducted by Zippia in 2021 found that only 6% of respondents claimed to have full supply chain visibility. Some 69% of respondents admitted to lacking total visibility.
Technology is assisting in increasing visibility into supply chain logistics. Here are a few technological advances that are producing an especially significant impact on the industry.
IIoT Finally Going Mainstream
Industrial IoT, or IIoT, devices first appeared in manufacturing lines and have since spread all over the supply chain. Typically, manufacturers use data from their IIoT devices to measure production efficiency and input those data into production models.
IIoT also plays an important role in facility management, with devices equipped with sensors transmitting condition-related data to teams over the cloud. Such devices are especially useful in manufacturing lines serving sensitive equipment such as precision electronics. Every component has to be assembled under specific conditions to ensure product integrity. IIoT devices ensure teams can set thresholds and monitor any deviations from them.
Similar devices are also used by inventory management teams to track the state of goods stored in their warehouses. Typically, these sensors track conditions like humidity, temperature, shock, and even light. Using these data, teams can figure out whether goods are stored in optimal conditions and whether packages were opened before intended.
IoT has extended all across the transportation chain as well, with entire containers fitted with cloud-enabled sensors. These smart containers transmit location and condition-related data to centers worldwide and eliminate the possibility of goods being stolen or compromised in transit.
Local supply chains use these sensors to monitor the integrity of goods inside cold chain-enabled vehicles and alert transporters of any deviation from ideal conditions. Thus, losses can be mitigated, and even more importantly, the damage claims process is simplified.
In an industry with low margins, insurance premiums can wreck business models. This makes it imperative to locate the source of damage quickly and compensate affected parties. For instance, a transportation company might have identified the damage, but the fault might lie with the manufacturer improperly storing goods. Thanks to data gathered by IoT devices along the chain, settling insurance claims investigations becomes far easier.
Centralized Data Storage Solutions
In the initial days of electronification, supply chain participants tried setting up their own data centers and invested in IT infrastructure. However, as technology improved exponentially, they quickly discovered they lacked the ability and resources to keep pace with the rest of the industry.
Cloud-based solutions providers offered a great solution to this problem. By democratizing data storage, companies can now access sophisticated infrastructure without incurring heavy ancillary costs. For instance, they don’t need to invest in hiring qualified personnel or upgrading server architecture. All they need to do is pay their cloud provider a fixed fee every month, and automatically, all of their IT issues are outsourced to a qualified provider.
For their part, cloud providers help supply chain firms bring all of their data onto a single platform. Supply chain stakeholders can now connect disparate systems, such as procurement and logistics transportation systems, via application programming interfaces or APIs.
Many logistics providers now offer system integration as standard via secure APIs, and this removes many traditional blind spots in the chain for manufacturers. What’s more, the data gathered by logistics providers can be used to run analytics on manufacturers’ platforms to inform demand projection and procurement models.
For instance, a manufacturer can model delivery efficiency and timelines and use them as inputs to their demand planning models. Thus, they’ll receive an end-to-end view of their supply chain, from raw material procurement to doorstep delivery to consumers. The result is an accurate demand model that reduces costs and increases efficiency.
Another effect of bringing disparate data onto a single platform is that running analytics becomes simple. Traditionally, supply chain stakeholders had to account for blind spots in their data and adjust their models accordingly. The result was haphazard analytics outputs. Thanks to the integration that APIs now offer, the supply chain has come to resemble an ecosystem, with every stakeholder offering inputs into creating the most robust delivery system.
As a result, not only do manufacturers and other stakeholders reduce their costs by mitigating waste, consumers are virtually guaranteed to receive goods in optimal condition.
Increasing Ubiquity of Artificial Intelligence
AI is increasingly becoming a standard part of all analytics packages, and supply chains are no different. AI’s ability to quickly process vast amounts of data is being put to good use in supply chains. For starters, AI helps stakeholders adopt a proactive stance in their operations and respond to market conditions better.
For instance, AI is used to analyze data on cloud platforms to predict consumer trends. Thanks to integration with delivery data, manufacturers can model various demand scenarios and plan production accordingly. This has a knock-on effect on procurement, and manufacturers can select the best vendors to work with, given the different scenarios.
Some vendors might work better with smaller supply requirements, while others might be geared towards mass rollouts. No matter the demand situation a manufacturer faces, their AI-powered platforms have them ready. AI can also spot productivity holes in the supply chain and help stakeholders resolve them.
A good example of this is the use of AI to combat identity fraud and make informed decisions in real-time. AI can also crunch a wide range of variables to produce the best result. This functionality is especially relevant in route planning.
International logistics firms have to take variables such as geopolitical stability, weather patterns, customers regulations, and vendor ability into account when planning routes. The task is tougher than plotting the shortest route between two points. AI can combat the complexity of this task and suggest optimal routes no matter the conditions it encounters.
The result is fast delivery with goods in optimal conditions. For instance, a human might design a route that is shorter than an AI-suggested one. However, a lack of cold chain facilities at a transit point’s customs shed or complicated goods declaration rules might ruin the product and cause losses to the shipper.
Thus, AI saves money and ensures the safety of all goods delivered for consumer use. AI is also leaving a mark in customer-facing good tracking apps. DHL, for example, offers an Alexa-based AI tracking service where consumers can simply ask their devices where their goods are, and the voice interface responds with the location.
As AI sophistication grows, there’s no doubt that the supply chain will witness deeper involvement that will cut costs and increase value-added manual work.
End-to-End TMS Platforms
Transportation management systems, or TMS platforms, have come a long way from their previous iterations. While some stakeholders prefer connecting disparate systems via APIs, an end-to-end TMS platform removes the need for sophisticated coding knowledge.
Companies can purchase a single solution that scales across their whole organization and onboard their vendors. Some TMS platforms also incorporate warehouse management systems that help companies track everything from storage to logistics. More sophisticated platforms integrate with ERP platforms to create a seamless supplier management experience.
Advanced analytics are a part of these platforms, and thanks to natural language querying, employees don’t need sophisticated technical knowledge to slice and dice data. Needless to say, all of these platforms host data in the cloud, thereby bringing easy scalability to supply chain stakeholders.
Evaluating vendor performance also becomes a breeze thanks to integration with IIoT devices that track goods’ condition-related data. The result is full visibility into the supply chain in a single package.
Sophisticated Solutions for Complex Issues
Supply chain stakeholders have to contend with a wide range of variables when dealing with everyday tasks. Technology is helping them combat these issues while reducing costs and increasing efficiency. As technology evolves, there’s no doubt that supply chain solutions will become more sophisticated and serve a wider range of needs within the supply chain.