Today, when most people think of logistics automation, they think of equipment. Robots, drones, and autonomous trucking dominate the conversation. Videos of fully automated warehouses circulated online, with news anchors wrestling with employment issues. This hype is incomplete and misses opportunities for supply chain and logistics companies.
Physical automation, transportation and warehouse technology are an important part of the supply chain story. But it doesn't stop there. The flow of information and data is almost as important as the flow of goods and containers. The flow of information is in the opposite direction of the flow of goods/materials. Real-time end-to-end SCV (supply chain visibility) is at the heart of any successful logistics operation.
For example, warehousing can be considered a data job. The only way to know where an item is among hundreds of racks and shelves is through data points. Technology forms the core arterial system that determines cargo to continue to move on time, regardless of disruption. The movement of goods and materials in one direction drives the flow of information in the opposite direction. In other words, information flows backwards as materials move from boxes and racks to warehouses, ports, containers and delivery shipments.
Advances in some technology categories, such as cloud-based services, integration and automation, have significant implications for the future of transportation and logistics. The importance of these developments will only grow as enterprises move toward real-time visibility and advanced track and trace programs. Meanwhile, pressure is growing on supply chain and logistics technology experts as new scrutiny comes over the role of supply chains in the new global economy.
The logistics industry has experienced a century of steady development, from railroads in the 19th century to modern planes, trains and cranes. However, in the short period from 2020 to 2022, the global COVID-19 epidemic has accelerated its evolution.
Before the pandemic, paper was at the heart of logistics information flow. From packing slips to shipping labels, bills of lading and beyond, paper changes hands regularly. The eventual transition to digital is considered inevitable, but progress has been slow due to the lack of an urgent driver. Companies tend to say "it's just working," especially when faced with fierce competition and low profit margins that put customer relationships at risk.
When the epidemic hit, logistics took a turn that no one expected. Paper suddenly became unfashionable. At the same time, the rise of e-commerce and pandemic-related supply squeezes have pushed supply chains and just-in-time manufacturing methods to the brink of collapse. In addition, traditional technologies that are the backbone of the logistics industry are also facing the future - for example, EDI has been its hallmark for a long time, and although it is still important even now, the future trend is the APIization of various services.
Before the pandemic, logistics efficiency dictated priorities, but today, resiliency and the drive for real-time tracking are added to the mix. This new reality is a paradox: an efficient process and a resilient process are difficult to balance. The remaining paper tracking processes or CSV-based processes are no longer sufficient.
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Change is underway
Because of the forces driving these changes, HFS research points to logistics as one of the top industries to expand investment in process automation. This is a step towards cloudification for the industry, in line with the adoption of solutions such as cloud-based logistics platforms, terminal interfaces and digital bill of lading (BOL)/documentation tools.
Other related trends are the Internet of Things (IoT) and blockchain technology. Many expect the proliferation of connected devices to push logistics to the very edge, from shipping containers and beyond. Solutions like Hapag-Lloyd’s 2022 announcement of major investments in GPS tracking of its container fleet, or Maersk’s TradeLens product, showcase this exciting new frontier.
New innovators are finding ways to connect transportation to modern manufacturing in very exciting ways. Many companies, such as automakers, are looking to bring the manufacturing of basic components such as batteries or injection molding in-house, creating new challenges and opportunities for modernizing the logistics industry and engaging those who have historically been indirect consumers of supply chain services. customer cooperation.
For logistics companies looking to implement their own transformation using these technologies, where to start can be a daunting task. To understand this better, let’s take a look at these challenges.
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An unstable end-to-end process
Supply chain and logistics are what IT leaders call "end-to-end processes." In the world of business processes, supply chain is one of the largest end-to-end processes, consisting of many small processes and spanning multiple countries and international waters. In some cases, it can be the most complex and unstable one.
The illustration below gives us an idea of the different elements involved in the second half of the process once the container has been unloaded from the ship and delivered to the consignee:
These processes span multiple companies, from offshore to rail to cranes to trucks. Ports, stations, warehouses, containers and transport providers all have to coordinate harmoniously. Every player in the process is at a different stage of digital transformation—which means we must be prepared to work with any and all levels of automation maturity, from green screens to APIs. Partners and customers are very important because this process is deeply intertwined between partners and suppliers. As a result, the process can change rapidly. A new supplier, a new customer, a new partner will all have a significant impact on the entire process.
A recent New Yorker article detailed a container leak in 1997 that saw more than 5 million Lego bricks disappear into the ocean, only to turn up on European beaches over the next 30 years. This is just one example of the many process disruptions plaguing logistics. Lost containers, weather challenges, accidents and breakdowns mean supply chains are subject to constant disruption and rework. Sometimes, it makes global headlines. In 2021, the Suez Canal was completely blocked by the container ship "Ever Given", which was stranded for more than 2 weeks.
IT departments in this area are often overwhelmed and understaffed. Many follow the pattern of traditional era design, where requests and demands from around the organization get backed up in long queues. It's common to use custom interfaces and have less than ideal situations.
For technology leaders in the logistics industry, this disruption can be seen as both a headache and an opportunity. Dealing with chaos is just part of the job, but new technologies are enabling exciting new approaches. Amid the supply chain chaos of the past two years, a new approach is necessary. The business case must be compelling, fast, cost-effective, and better than past approaches.
Opportunity: Enterprise Automation
A recent research note from Morgan Stanley states that "once siled collections of technologies are coming together with new categories of infrastructure software to create end-to-end enterprise automation platforms." The study observes that enterprise automation is one of the fastest-growing segments of enterprise software, going on to say: "Now, the drive for organizational resilience and real-time decision-making is further fueling automation initiatives. Next steps: Standardize automation and Moving toward enterprise-wide projects".
Enterprise automation is a huge opportunity for those working in supply chain and logistics. While past automation solutions required expensive technical expertise and a collection of tools to automate tasks, enterprise automation offers benefits that are differentiated for our industry:
1. Flexibility and scale to adapt to changing circumstances
2. A unified approach to orchestrate various interfaces: API, web portal, on-premises or in the cloud
3. The basis of integration
4. A low-code approach that fits the existing technical skills in the organization
5. Support the necessary governance models to securely automate end-to-end processes
At TFG, we undergo a rigorous review and POC process to vet out new approaches to automation within our own transformation process. We have found that enterprise automation has unique value to the logistics supply chain. It overcomes many of the barriers we’ve discussed in this article and offers tremendous upside to organizations that fully embrace it.
Once these hurdles are put behind them, it becomes clear that supply chain and logistics are a first-class citizen when it comes to enterprise automation. A quick look at the average project list for organizations in our space reveals that many processes are actually ripe for automation that was previously thought impossible.
If we look at our previous illustration and point out some of the integration and automation points along the way, we can see that there are substantial opportunities for transportation logistics providers to participate in enterprise automation:
Although each of these prominent areas has represented a challenge in the past. With enterprise automation, they represent opportunities for continuous improvement. These parts of the journey are integrated into a coordinated whole and provide opportunities to improve them and make the process smarter. If done right, you can balance the need for improvement with the constant fluctuations and consequent reworking and rebuilding of processes.
All this speed and flexibility comes from a no-code/low-code approach. At this point, continuous improvement is the goal, not static transformation. It’s important to remember that digital transformation shouldn’t be viewed as a high point to be reached or some end state. Rather, it is a state of transformation. This concept is a better corollary to the rapid pace of change we face in supply chain work. In this new era of global unpredictability, the ability to evolve and react quickly in the face of change is paramount. Giving customers the service they expect while taking into account volatility is where the winners have their edge.
Finally, some of the most exciting areas of continued improvement involve incorporating artificial intelligence and machine learning (ML) into processes. Enterprise automation—with its integration-led approach—makes it easy to introduce artificial intelligence and machine learning models into processes. With that in mind, let's look at the ideal approach.
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Enterprise automation in logistics
When we approach technology decisions in this way, our goal is to create a virtuous cycle in which we capture valuable data, turn it into insights, and continually improve. To achieve this, we bring together tools that are common in today's enterprises, including low-code application development, data warehousing, and artificial intelligence. Let's look at each step in more detail:
Step 1: We collect data from various SaaS systems;
Step 2: We need to integrate these data;
Step 3: We need to surface this data for monitoring and real-time tracking;
Step 4: We need to store this data for a long time for analysis;
Step 5: We need to make decisions based on data and benchmarked against our key performance indicators;
Step 6: We need to leverage AI/ML to identify ways we can improve that humans might not see or realize.
At the heart of this approach is enterprise automation – it is the central nervous system that connects all these systems, from RPA robots to AI/ML models that analyze content in data warehouses. In order to establish this, we need to define a series of steps to achieve this. This won't happen overnight. Additionally, several tools are necessary to put it in place:
1. SaaS platforms we already use
2. If our traditional system has no API or website interface, then we need RPA robots to scrape the screen
3. We need an iPaaS
4. We need a low-code application development platform that allows us to create web interfaces or surface information on collaborative platforms in the form of chatbots
5. We need a data warehouse
6. We need some form of AI or ML platform
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start working
We’ve talked at length about the value of low-code, no-code solutions. Understandably, some may express reservations. We also had our reservations at the beginning, but we were able to overcome them in two ways.
First, we assessed our internal capabilities. Most logistics companies are probably in a similar situation: many people have extensive process knowledge but little to no understanding of code. Second, we conducted a rigorous proof-of-concept process to determine whether these solutions actually met vendor requirements in each category.
For this assessment, we've compiled some early priority areas that IT leaders in the field can use to guide their decisions:
Define success early: Defining your key use cases for success will help determine where to focus your limited resources early on. It should limit the time invested in low-yield projects that will pay off in the form of significant results once they are successfully automated.
Conduct a proof-of-concept: Conducting a hands-on test of a new mission-critical platform may seem like a no-brainer, but it’s surprising how many people skip this step. Taking the time to put the platform through their paces is time well spent.
Assess your internal capabilities: Most logistics companies don’t have enough technical expertise in-house to build a top-notch solution out of code. Additionally, many people in our company have extensive process knowledge gained from years (sometimes decades) of experience, but limited coding knowledge. To capture their process knowledge, making the path from idea to automation as short as possible is a best practice.
Consider the operating model: The implementation we choose determines the stack we implement. Will we be pure cloud? On-premises deployment? Hybrid?
Take the time to listen: Capturing functional requirements is 70% of the work, and it's worth getting it right. If functional requirements are not captured effectively, you will run into some unexpected troubles. Just like a few small course corrections in the early days of a rocket launch can have a big impact later on, doing the hard work early in an IT transformation will pay off years later.
Set your timeline: Once all the key considerations are in place, set some goals around how long it will take to complete the work.
These few steps are just the beginning. As the project takes shape, key values become clear, such as short development phases (we recommend 14-day sprints), collaboration with stakeholders, and early and frequent testing. A transparent, agile approach focused on building early acceptance of the work being done is crucial. The success or failure of a project rests on the shoulders of colleagues, so training and development, user stories and other elements are almost as important as the technology itself.
Modernizing and improving the technology posture of key players in the supply chain is an important journey. It's probably an underrated job. The progress that occurs in supply chain modernization is not only valuable within the industry, but has serious implications for millions of people. Supply chains support economic growth, goods, services and the careers of millions of people. The hard work, challenges and unexpected surprises are all worth it.
Now more than ever, people rely on supply chain improvements. This requires us and enterprise automation to implement them.