Digital transformation in global supply chains has attracted a lot of attention, and although the topic has been widely discussed over the past decade, many companies remain confused about how to achieve this unclear goal. The importance of this transformation is widely recognized, and the COVID-19 pandemic and its massive impact have provided a powerful boost to the industry’s push towards digital transformation.
UK CEOs are increasingly concerned about risks to traditional supply chains, with the issue listed as one of their top five concerns, according to a KPMG report. More than 50% of CEOs believe their supply chains are under increasing pressure. Likewise, 50% of CEOs recognize that they need to increase the resilience of their supply chains to avoid more disruptions over the next three years.
However, digitizing the global supply chain will not be easy. Key to this shift is the adoption of solutions that integrate artificial intelligence (AI), machine learning, and automation, which will provide businesses with the detailed visibility, faster response times, and enhanced productivity they need to truly realize Digitizing.
Where to start with automation and AI?
The origins of automation and artificial intelligence can be traced back 120 years to the first conveyor belts, or to the first use of automated storage and retrieval systems in the 1950s.
And now Robotic Process Automation (RPA) is a good place to start. Forward-looking enterprises are exploring the combination of RPA and artificial intelligence strategies to remain competitive in an increasingly digital world. This combination of technologies is called Intelligent Process Automation (IPA), and it can also be used with other technologies such as machine learning, dynamic load balancing, sentiment analysis, and other advanced applications. RPA can increase operational efficiency, reduce costs, and improve cash flow. At the same time, it enables the synchronization of automated operations across multiple systems.
AI and automation provide companies with a deep understanding and clear view of the entire supply chain. McKinsey's report pointed out that supply chain risk is closely related to the opacity of information. Specifically, supply chain risk is mainly reflected in its vulnerability and unpredictable events. To mitigate risk, you first need to have a clear understanding of possible weaknesses in your company's supply chain. For example, which suppliers, processes or facilities might be risk points in the supply chain? Which critical processes may be at risk of supply shortages or price volatility?
In the critical stage of digital transformation, artificial intelligence and robotic process automation (RPA) solutions can monitor multiple systems and integrate information to provide managers with information for decision-making and help organizations find potential problem points.
With clear visibility and transparency, supply chain operations become more flexible and faster. With the real-time insights provided by artificial intelligence, companies can quickly adjust existing problems, or move resources to better meet customer needs. Smart supply chain and business solutions based on artificial intelligence also make it possible for companies to implement more environmentally friendly ways in their products and manufacturing processes. From the beginning of design until the products reach customers, sustainable product design can help companies control costs and reduce costs. waste.
In the implementation of artificial intelligence and automation, the most attractive part is the innovative use of robots that have the ability to think and learn for themselves. The recent development of large language model (LLM) and generative artificial intelligence is showing this trend. The main goal of this type of AI is to provide company employees with the additional knowledge, support and insights brought about by robotic system integration and automation. By automating repetitive, manual labor-intensive and other mundane tasks, organizations can maximize the human resources of their operations personnel and bring their individual talents to bear where they are most critical—especially when a professional with a human touch is required. In the interactive business model, such as the scene of interaction with end customers.
Here's how artificial intelligence (AI) and robotic process automation (RPA) can help in unlocking supply chain resilience:
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Predictive analysis: AI can perform predictive analysis through big data and machine learning algorithms to help organizations predict and manage potential problems and risks in the supply chain. This enables early decision-making and increases the resilience of the supply chain.
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Real-time decision support: AI and RPA can provide real-time decision support to help managers make quick and accurate decisions in complex and dynamic environments. This increases the responsiveness and flexibility of the supply chain.
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Process automation: RPA can automate many repetitive and routine tasks in the supply chain, such as order processing, inventory management, invoice processing, and more. This increases the efficiency and accuracy of the supply chain while freeing up human resources for more complex and human-intensive tasks.
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Demand Forecasting: AI can help organizations more accurately predict customer demand and market trends so that supply chain strategies and plans can be adjusted in a timely manner. This can reduce inventory costs, improve customer satisfaction, and increase the competitiveness of the supply chain.
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Risk management: AI and RPA can help organizations identify and manage risks in the supply chain, such as supply disruptions, price fluctuations, quality issues, and more. This increases the stability and reliability of the supply chain.
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Supply chain transparency: AI and RPA can improve supply chain transparency and help organizations better understand the status and performance of supply chains. This improves supply chain visibility and control, further enhancing supply chain resilience.
In general, AI and RPA can help organizations optimize supply chain management, improve supply chain efficiency and resilience, and thus better respond to changes in the market and environment.
Over the past four years, RPA has demonstrated its power in automating business processes and reducing operating costs. However, in the process of advancing digital transformation, many organizations also face some serious challenges, such as how to choose and manage the process of change, how to fill the skills gap needed to build robots, how to use IT infrastructure to support RPA challenges, And how to deal with the deeper issues of robot implementation and maintenance costs that exceed expectations.
In an increasingly competitive environment, especially in the current environment of high focus on supply chain resilience, artificial intelligence and RPA provide a significant competitive advantage for the development of supply chains. But these functions are just a starting point in the modern supply chain. Supply chain CIOs need to evaluate these technologies and continue to promote their digitalization process.
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