Next-gen supply chain: from automation to full autonomy

In the world of supply chain operations, the terms “automation” and “autonomy” are often used interchangeably. This can lead to confusion about what each term means and can hinder strategic decision-making and investment. As supply chain leaders look to optimize their operations, it’s important to understand the differences between the two and how each will impact the future of supply chain networks.

The confusion between automation and autonomy stems from their shared technologies landscape and processes. Both aim to streamline operations, reduce manual labor, and increase productivity. However, automation focuses on executing predefined tasks, while autonomy involves systems making real-time decisions based on evolving data and conditions, without human intervention.

In this article, we will explore the evolution and differences between automation and autonomy in supply chain operations. We will discuss the critical role of technology in transitioning from automated to fully autonomous operations. Understanding these distinctions helps supply chain leaders make informed decisions for future supply chain networks. Our recent study shows that many companies still need to implement the next-gen capabilities that will make autonomous supply chains a reality.

What automation means in supply chains

The history of automation in supply chains dates back to the first Industrial Revolution, introducing mechanized systems that reduced human labor in manufacturing and transportation. By the late 20th century, computer-based systems like Material Requirements Planning (MRP) and Enterprise Resource Planning (ERP) revolutionized inventory management, order processing, and production scheduling. These technologies streamlined operations, minimized waste, and improved efficiency, leading to supply chains that could quickly adapt to changing market conditions.

Today, automation has advanced further with technologies like Robotic Process Automation (RPA) and Automated Storage and Retrieval Systems (AS/RS), which automate functions such as picking, packing, and material handling. RPA can automate repetitive tasks, freeing up human resources for more strategic activities. AS/RS can automate the storage and retrieval of goods in a warehouse, improving speed and accuracy. These advancements are creating more resilient supply chains that can better withstand disruptions and maintain operational continuity.

What autonomy means in supply chains

The idea of self-regulating systems and decision-making algorithms was the foundation for autonomous solutions, with early experiments in the 2000s. These early tests reduced human intervention and increased efficiency, paving the way for advanced autonomous systems.

The recent pandemic has accelerated the push for supply chain resilience and agility by highlighting the fragility of traditional supply chains. This has accelerated investments in autonomous technologies, leading to the rise of fully autonomous systems such as autonomous mobile robots (AMRs), self-driving trucks, and AI-powered decision-making platforms.

Today, fully autonomous systems navigate data from stock levels to road conditions to make informed, split-second choices. These solutions optimize operations, mitigate disruptions, and enhance supply chain resilience and adaptability. Although a real possibility, recent Accenture study shows that only 10% of companies are applying the most advanced, technology powered capabilities, with the vision to achieve fully autonomous supply chains.

Industry leaders have been instrumental in this progress, with their pioneering use of autonomous technologies, like drone delivery initiatives have the potential to transform last-mile logistics. Such advancements set the stage for a future where autonomous supply chain networks become the standard.

The core differences between automation and autonomy

To fully appreciate the potential and strategic implications of technological advancements in supply chain operations, it is essential to understand the distinctions between automation and autonomy.

In supply chains, automation refers to systems that follow pre-set instructions and require human oversight. These systems perform predefined tasks based on known answers, executing prescriptive actions that do not vary unless a human intervenes. Automation augments routine tasks like data entry, scheduling, and inventory management, thereby enhancing efficiency and reducing human error without achieving full autonomy. While automation is good at executing fixed tasks efficiently, it lacks the flexibility to respond to unforeseen circumstances.

In contrast, autonomous supply chains represent a significant leap forward in technological sophistication. These systems are capable of independently managing and optimizing  without human intervention, making learning the singularly most important feature of AI.

This advanced decision-making and continuous learning capability is what sets autonomy apart from automation. Autonomous systems can analyze vast amounts of data, identify patterns, and respond to supply chain disruptions in real-time, ensuring that the flow of goods remains uninterrupted and optimized.

Companies today are reinventing different parts of their organizations using AI. 48% of organizations are planning to integrate AI agents into their digital systems to upgrade and modernize their functions within the next 3 years.

The role of technology: driving the shift from automation to autonomy

Technology such as generative AI has been a driving force in the transformation of supply chain operations, particularly in the shift from traditional automation to advanced autonomy. In today's fast-paced market, marked by fluctuating demand, frequent disruptions, and ever-increasing customer expectations, a more agile and adaptive approach is crucial. The move to an autonomous supply chain is not just a next step in evolution, but a necessity to create a more resilient supply chain that can weather disruptions.

To achieve autonomy, an intelligent supply chain needs these key building blocks:

• Strong digital core, that allows data to move seamlessly and decisions to be made in real time
  
  
• Agentic architecture, that incorporates advanced technologies like artificial intelligence and machine learning; enabling systems to learn, adapt, and make decisions on their own, moving from static to dynamic responses
  
  
• Process reinvention, rethinking and redesigning existing procedures to support self-sustaining and adaptive operations
  
  
• Data unification, ensuring that data-driven insights are being used across the entire supply chain network
  
  
• Modern operating model for workforce optimization, shifting the focus of human roles from manual tasks to strategic oversight, data analytics, and system integration.

The current reality: supply chains are evolving along a spectrum, where many companies operate with a mix of automation and early-stage autonomy, and full autonomy is the next stage of development.

To navigate current challenges, companies often adopt a hybrid approach, merging traditional automation with emerging autonomous capabilities. This serves as a bridge to fully autonomous operations. Key technologies like generative AI, machine learning, and real-time data architecture are essential for this transition, enabling systems to self-adapt, optimize, and make independent decisions. The shift to full autonomy fundamentally transforms supply chain management, enhancing agility, reducing costs, and promoting sustainability.

Why understanding the difference matters

Understanding the differences between automation and autonomy is critical for making informed investment decisions and future-proofing operations. As technology advances, the path towards fully autonomous systems is becoming increasingly clear, promising to revolutionize supply chains. It is essential for business leaders to keep up with emerging technologies and their influence on supply chain strategies. This forward-thinking approach will not only preserve a company's competitive edge but also empower them to flourish in the age of autonomous supply chain networks.

To find out more about the key capabilities that will help you build secure next generation autonomous supply chain networks stay tuned for our upcoming report on the topic. Additionally, we will explore the level of implementation of autonomous capabilities in various supply chain activities and their impact on business and customer value.

If you have any questions about your company’s own journey to an autonomous supply chain feel free to reach out.