GenAI/ChatGPT: New Era of Supply Chain & Logistics Process Automation
The supply chain and logistics domain is experiencing a dynamic transformation, bringing forth an array of complex challenges for both corporate entities and Third-Party Logistics (3PL) providers. This sector is characterized by an intricate global network that must adapt to ever-changing market demands and a relentless pursuit of heightened operational efficiency. In response to these evolving demands, organizations have been compelled to explore and adopt innovative solutions. Despite this, the relief provided by traditional automation technologies, especially Robotic Process Automation (RPA), has been notably limited, failing to fully address the intricate and multifaceted nature of modern supply chain complexities.
The Limitations of Traditional RPA in Supply Chain & Logistics
Traditional RPA has been a beacon of hope in automating standard processes within supply chain and logistics operations. However, its capabilities are significantly hampered when dealing with the complexities and variances in essential documents like Bills of Lading (BoL), contracts, certificates, and customs documents. The rigid framework of traditional RPA means that only about 20-30% of supply chain processes are currently automatable, leaving a vast portion of operations reliant on manual intervention. This limitation not only affects efficiency but also increases the risk of errors and delays.
GenAI: A Transformational Leap in Automation
Enter GenAI (aka ChatGPT), the next generation of automation technology that transcends the limitations of traditional RPA. What sets GenAI apart is its remarkable ability to understand and interpret natural language. This breakthrough is particularly transformative in two key areas of supply chain and logistics:
(1) Exceptional Document Processing with GenAI (GenAI Intelligent Document Processing IDP): GenAI stands out in its ability to read and process intricate documents effortlessly, bypassing the need for the extensive training that traditional document processors demand. Traditional systems, which rely on template-based training, involve a laborious and time-consuming process known as 'labelling', where samples are meticulously annotated for machine learning. This method not only prolongs the implementation time but also incurs substantial costs. GenAI, however, circumvents this tedious process through its advanced 'prompt engineering' approach. This innovation allows for rapid deployment and remarkable adaptability in document handling. Such efficiency ensures a high level of accuracy in processing vital documents, markedly diminishing the risk of expensive errors and streamlining what was once a complex and costly process.
(2) Personal Productivity Transformation through No-Code RPA: The idea of empowering everyday users to automate processes, known as the 'Citizen Developer' concept, has previously been explored through Low-Code development platforms. However, this approach often stumbled as it still required a basic understanding of programming, limiting its accessibility. GenAI-enabled RPA marks a significant evolution, ushering in an era of true 'No-Code' automation. This advancement allows users to simply describe their desired automation in plain English. The GenAI RPA technology then interprets these instructions and converts them into executable code, requiring the user to merely initiate the process with a click. Remarkably, about 90% of processes are personal or used by small groups, which traditionally didn’t justify the investment in professional automation development due to low ROI. These processes have long remained untapped, representing a vast potential for automation. The advent of No-Code RPA empowers the workforce to reach peak productivity by enabling them to automate their routine, personal processes effortlessly.
Use Cases for Supply Chain & Logistics
Let's explore a few real-world use cases that demonstrate the end-to-end automation capabilities of GenAI IDP and RPA in the supply chain and logistics sector.
1. International Shipping Documentation Management
End-to-End Process: The process begins with GenAI IDP technology extracting data from various shipping documents such as Bills of Lading, commercial invoices, packing lists, and certificates of origin etc. This data is then validated and cross-referenced against existing records for accuracy. Subsequently, GenAI-driven RPA bots input this data into shipping and customs systems, schedule shipments, and update tracking systems.
Impact: This automation significantly reduces the manual effort and time required in managing international shipping documents. It minimizes errors in data entry, ensures compliance with international trade regulations, and speeds up the entire shipping process.
2. Supplier Onboarding and Management
End-to-End Process: When a new supplier is onboarded, GenAI IDP tools first extract relevant information from various unstructured documents like contracts, tax forms, and certifications. The extracted data is then processed by RPA bots to create supplier profiles in the procurement system, set up payment processes, and initiate compliance checks.
Impact: This seamless integration of IDP and RPA automates the laborious and error-prone process of supplier onboarding. It ensures consistency in supplier data, accelerates the onboarding process, and maintains compliance standards.
3. Inventory Reconciliation in Warehousing
End-to-End Process: GenAI IDP are used to extract data from inventory receipts, delivery notes, and warehouse transfer documents. RPA bots then reconcile this information with the inventory management system, update stock levels, and flag discrepancies for review.
Impact: This process ensures real-time, accurate inventory tracking, reduces the chances of stock discrepancies, and aids in efficient warehouse management.
4. Purchase Order Processing
End-to-End Process: GenAI IDP is used to extract data from incoming purchase orders, regardless of their format. The extracted data includes details like supplier information, product quantities, and prices. RPA bots then validate this information against existing contracts and inventory levels, update the order management system, and initiate the procurement process.
Impact: This automation streamlines the purchase order process, ensuring accuracy in order fulfilment and inventory management, and reducing the time between order placement and procurement.
5. Automated Claims Processing in Freight Logistics
End-to-End Process: In the event of a freight claim, GenAI IDP systems efficiently extract information from claim forms, supporting documents like delivery receipts, and photographs of damaged goods. RPA bots then use this information to validate the claim, update the logistics management system, communicate with involved parties, and process the claim payouts.
Impact: This automation speeds up the claims processing, reduces the workload on staff, and improves accuracy in claims handling. It leads to faster resolution of claims, enhancing customer satisfaction and trust.
In each of these use cases, the combination of GenAI IDP and RPA technologies provides a comprehensive, automated solution that covers every step of the process, from initial data extraction to final execution of tasks. This not only increases efficiency and accuracy but also allows human employees to focus on more strategic, less routine aspects of supply chain and logistics management.
The Evolving Software Landscape for Supply Chain Automation
The software landscape for automation in supply chain and logistics is witnessing a significant shift. Traditional players like UiPath and Automation Anywhere have laid the groundwork for RPA. However, the emergence of GenAI-enabled platforms, such as Laiye, marks a new era of innovation and efficiency. These GenAI-driven solutions are not just ahead in the race; they are redefining the track itself.
Embracing the Future of Supply Chain Automation
The integration of GenAI into supply chain and logistics is not just an upgrade; it's a necessary step to stay competitive in a rapidly changing world. Businesses that embrace this technology will find themselves at the forefront of efficiency, accuracy, and innovation. The hesitance to adopt GenAI could mean being left behind in a new competitive landscape where agility, speed, and accuracy are paramount.
The call to action for supply chain and logistics providers is clear: it's time to take the next step. Embrace GenAI-enabled automation and unlock the full potential of your operations. The future of supply chain efficiency is here, and it's powered by the transformative capabilities of GenAI.
(BioQuest Advisory has a regional team with Supply Chain & Logistics Industry knowledge and deep GenAI Automation expertise to effectively partner our Supply Chain & Logistics clients. Drop us an email at email@example.com)