There are some latest supply chain technologies and trends that are getting much buzz. How mature are these developments, however? Do they have an ROI that is proven? Will they be worth piloting? Or can businesses neglect them safely?
There are also successful innovations that we anticipate can have great value. However, at this stage, we cannot log the ROI or other advantages. Eventually, some inventions create value that few individuals have heard of.
The leading, exciting, and related reliable solutions, but commonly adopted supply chain management technologies, are covered in this article.
Latest Supply Chain Technology Trends
Hyped technologies are receiving much attention but have no demonstrated value. In pursuit of a solution, these seem like technologies.
5G is the 5th wireless technology generation. With 5G, you will see the download and upload speeds exponentially faster. It would also significantly reduce latency, or the time it takes for devices to connect with each other’s wireless networks. The advantages are apparent for customers who want to download films on their mobile phones and watch them. However, will supply chains have advantages?
The idea is that as more gadgets become part of the ‘Internet of Things‘ in the supply chain and production phase, they will create a vibrant data stream that will send signals to cause a wide range of events in real-time. For example, a component tote might communicate that the tote is 80% exhausted for this SKU using a 5G network, which would cause a re-order of the required components. This would be a catalyst in the supply chain management that would eventually lead to warehouse movements, possibly LTL, restructuring, and re-supply production and delivery.
5G does not get as much coverage as last year, but here we are already at the hype stage. Despite TV advertisements indicating that 5G is here already, 5G wireless networks are still being installed throughout the United States. ARC does not listen to supply chain technology providers using this network to provide its customers with the new value.
In the supply chain domain, we continue to see businesses pitching their blockchain solutions. Sometimes, these start-ups are here now, gone tomorrow. After their portion of a chain of linked activities has been completed, Blockchain is a robust solution for traceability or payment to linked supply chain management partners. As part of their increasingly entrenched way of doing business, we have continued to ask blockchain providers for the names of clients who use their technology every day. Blockchain providers cannot support these references. That is a strong indicator that the program is still in the hype process.
It seems that promising technologies will deliver durable ROI or other tangible advantages. It is exceptionally reasonable that the advantages expected will appear. However, these innovations are so young that ARC has not communicated with references and check that the benefits offered are genuine.
Artificial Intelligence/Machine Learning Platforms
These Artificial Intelligence and Machine Learning platforms allow companies to consume, clean, and prepare vast quantities of historical and real-time streaming data and see if it can make useful predictions for their company by applying machine learning or AI technology algorithms and techniques to that data.
Leading supply chain technology and software companies actively combine current AI and machine learning applications in the supply chain realm. This is a less disruptive and more cost-effective way for most enterprises to access AI capabilities.
However, substantial multinational companies have digital centers of excellence, corporations with over $10 billion in sales. Such businesses claim that it is possible to create custom AI/ML applications that provide value in black spaces not currently protected by existing supply chain apps. Besides, for logistics service providers, excellence is how they distinguish themselves in supply chain management.
It would make much sense to create a custom AI/ML application that their competitors do not have. Indeed, some of the biggest 3PLs working here and saying that they are getting a good value. However, it is not easy to understand how valid these statements are, such as self-serving marketing campaigns.
We are now switching to blended approaches that are partly an AI/ML platform and partly an application system. PlanIQ was launched by Anaplan, a vendor offering supply chain management and planning (SCP), and other business applications. PlanIQ extracts Anaplan data and automatically tests multiple AI/ML algorithms before choosing the optimized model to produce the best forecast for a particular use case. Amazon Forecast is used in PlanIQ. Amazon Forecast depends on the same ML technology that Amazon.com uses.
Startups have been pumping money into experiments, but we are still a few years away from having autonomous truck fleets on the track. Moreover, in some situations, investment dollars for this technology are starting to dry up. Starsky Robotics was one of the biggest names for autonomous truck technology. It was at the forefront of autonomous trucks being placed on the track.
The achievement list is staggering. In 2016, without a driver behind the wheel, it became the first road-legal vehicle to be charged to do real work. It became the first street-legal truck to perform a fully unmanned run in 2018. It was the first utterly uncrewed truck to ride on a live highway in 2019. Moreover, even with these successes, the company closed this year due to a lack of funds. The best guess is that if anything goes wrong in 2024, we might see autonomous trucks carrying loads without drivers in the truck to take over.
This is what the people at TuSimple are planning, and they sound to us like straight shooters. Nevertheless, these trucks will not be driving through all lanes nationwide, even in 2024. Instead, there will be an emphasis on delivering to select customers through targeted lanes. However, what seems evident is that the ROI of autonomous trucks could be excellent.
Digital Twin Technology
River Logic utilizes an AI expert system that drives a graph database to simplify creating the value chain’s digital twin. The model needs to be designed step by step in conventional supply chain planning (SCP) solutions. This is the bill of material of a product; this is the routine; this is the startup time of a production machine. However, River Logic promotes its approach as one where the AI system designs and constructs the graph database and relationships and selects and applies appropriate business rules and logic based on a visual drag and drop diagram that enables users to draw their value chain – significantly accelerating model creation and SCP implementation, including complete financial representation as incurred by the value chain.
Besides, the AI expert system assembles and produces a complete mathematical model of the client’s value chain behind the scenes, enabling advanced scenario optimizations to be easily formulated and operationalized.
Infor also employs a graph database for their multi-enterprise Supply Chain management Network known as Infor Nexus. The Nexus network links companies from suppliers and distributors to traders, 3PLs, and banks to their entire supply chain, paving the way for improved visibility, coordination, and orchestration. Infor claims that a graph database’s capacity to infer relationships helps keep the model up to date.
A business may presume that the part of a supplier constructed in Wuhan China moves via Shenzhen Port and takes an average of 22 days to reach California’s Long Beach Port. However, it may be that the components often flow through a port in Xiamen and take 25 days to reach California. The graph database will, in short, help keep the model of the supply chain accurate. For efficient success, this is important.
High-Value supply chain technologies that are widely adopted
Next Generation Control Towers
A stable supply chain control tower is installed on a cross-functional end-to-end digital twin of the supply chain management. Visibility is used in how incidents around the extended supply chain can influence the ability to meet customer orders. The digital twin models the transportation, storage, and manufacturing constraints and can then create customized plans to deal with the unavoidable exceptions.
In the past, a supply chain control tower focused more on managing exemptions from transportation or focusing more on orchestrating exceptions rather than using real optimization to optimize service at the lowest cost. Most of these new control towers are being constructed using data lakes to get the data, clean it, and normalize it.
Robotic Automated Storage and Exchange
A type of goods-to-person automation has come to market in the past few years. A combination of conventional shuttle systems and free-roaming robots, these “robotic shuttle systems” are. There are currently a handful of supply chain management providers that sell solutions that fall into this categorization. Moreover, they each address the issue differently. However, due to the dynamic movement of bots, they all have the advantage of high storage density and a high degree of versatility. This versatility of the bot reduces limits on throughput and sequencing, creating increased capacity for efficiency. These technologies are compatible with many industries’ organizational needs.
Nevertheless, they are coming to market just as demand for same-day delivery of online orders is accelerating. In e-grocery satisfaction, this demand spike is particularly prevalent. These solutions could be meeting your next online purchase.
Robotic Process Automation (RPA)
Technology that is used to automate high volume, repeatable processes is robotic process automation. Enterprise systems build improved automation over time, and users can do their work more efficiently. However, businesses using legacy systems may have opportunities to automate the legacy system’s work using an external RPA solution. By executing the same machine keystrokes and opening the same modules that humans do, RPA’s do this. We know of a 3PL that earned a strong return on investment by using RPA in their legacy transportation management system to automate the highly manual tasks associated with planning optimization (TMS). For appointment scheduling, it is often used to examine carrier websites.
In its routing approach, Descartes embeds RPA. Descartes points out that designing the best plan is not as easy as loading data and hitting the “optimize” button for all but the most comfortable route planning issues. Instead, to achieve optimum results, the best planners go through several steps. In essence, the RPA will model the steps taken by the best planners to achieve superior performance.