Artificial intelligence (AI) has been gaining a lot of space, especially due to the popularization of AI based on generative machine learning, such as ChatGPT. Its use can bring us significant benefits, automating and streamlining various tasks. In the supply chain, where planning is essential for success and cost reduction, the ability of AIs to assist in the analysis of large amounts of data can be crucial in helping decision-making, increasing its speed and assertiveness and reducing the need for human participation in an area full of complexities and challenges.
The supply chain is made up of several links that require the monitoring of numerous indicators and variables to ensure its optimal functioning. Managing and monitoring this data, identifying trends or signs of possible problems is essential for optimizing the supply chain, a major challenge for companies. However, the recent transformation of artificial intelligence has the potential to make this work easier, training an AI system allows it to identify these signals, improving its accuracy and speed by learning from each new set of data.
In logistics where the speed of decision-making is crucial so that you can react without compromising the level of service, the use of AI becomes a huge competitive advantage. Research already indicates that introducing AI into supply chains can reduce costs and increase revenue.
The following are some examples that illustrate the many applications and benefits of using AI across stages and areas of the supply chain:
Capacity and demand forecast
Forecasting allows for proper planning, efficient allocation of resources and minimization of costs, today there are several computational tools to assist in this process, the use of artificial intelligence can facilitate data cleaning, select the best basis for its training, identify patterns, among other tasks, thus creating more accurate predictive models without the need for deep manual analysis of each of the models. The executive partner of ILOS, Leonardo Julianelli, wrote an article that approaches the potential benefits of AI and ML in planning activities. Given that most companies already use programming languages or tools to carry out their planning process, inserting machine learning and AI into this process is feasible and can generate great gains.
Inventory and warehousing management
With companies working with more and more varieties of products, reaching tens of thousands, inventory and storage management is one of the steps that has the most data associated with it, and ensuring that the product can pass through the warehouse efficiently and prevent shortages or excess stock, can in some cases be the most important aspect of the entire supply chain. AI systems can help manage this huge amount of data, allocating each SKUs (Stock Keeping Units) in the most appropriate places in the warehouse, generating alerts for products with little turnover and/or close to expiry, managing the FIFO (First In First Out) or FEFO (First Expire First Out) of your stock and even taking inventory automatically using drones.
Increased efficiency and reduced operating costs
Due to the interconnection between the supply chain links, a delay generated in one part of the network can affect the entire logistical flow. The use of AI can bring a much broader view of the chain, helping to identify gaps and opportunities for improvement and integration, such as, for example, the consolidation of multiple suppliers, better delivery routing, among others. AI also reduces manual dependency, freeing up human resources for more strategic activities.
Service level improvement
AI systems help reduce manual tasks, reduce errors and make the process faster and more efficient, all these advantages directly affect the final link in the chain, the consumer, ensuring that he receives the product faster by removing possible bottlenecks and inefficiencies that exist in the chain.
The Challenges of AI Implementation
The use of artificial intelligence can clearly be very beneficial to the supply chain operation, but its use and implementation does not come without associated challenges, the large amount of data that an AI processes requires powerful hardware, with high storage and processing power, the cost of training these systems is also a major entry barrier, it is necessary to allocate resources to train the system and prepare the data so that it gives good outputs, in addition to the fact that the benefits arising from its use may take some time to be perceived and generate gains in the operation.
Consultation Adhara Ginaid recently made a post about the importance of process mapping before venturing into the implementation of solutions such as AI, which highlights one of these challenges.
The imminent artificial intelligence revolution in the business landscape brings with it significant advantages for companies. While its implementation presents challenges, adapting and harnessing the potential of AIs to drive progress seems inevitable to stay competitive and thrive.
- https://decrypt.co/resources/how-artificial-intelligence-can-revolutionize-supply-chain-optimization
- https://medium.com/@blinx/an-expert-guide-to-ai-in-supply-chain-and-logistics-e45fdc26b5f8
- https://throughput.world/blog/ai-in-supply-chain-and-logistics/#Challenges_of_AI_in_Supply_Chain
- https://www.tecnologistica.com.br/artigos/geral/17087/inteligencia-artificial-e-machine-learning-no-planejamento-da-demanda/
- https://www.dhl.com/global-en/delivered/digitalization/ai-in-logistics.html
