Ever since its inception, supply chain logistics has been evolving. The segment has seen enormous growth and disruption, thanks to technologies like AI, robotics process automation, augmented reality, cloud computing, and more.
In fact, firms that have survived the hostility of the past few years did it by adopting these technologies and getting efficient in the process. Supply chain efficiency largely focuses on optimizing resources and offering quality products faster. To achieve this, firms must prioritize other aspects of supply chain management, sales, and account management.
For instance, besides investing in technology, they must be able to effectively respond to the inevitable changes in the order-and-fulfillment cycle and establish a strong connection between quote-to-cash and procure-to-pay processes.
Today, AI has taken over much of the challenging aspects of supply chain management and optimization. It manages large amounts of data, thus identifying trends and making accurate predictions. No wonder, the AI market in supply chains is expected to reach $20 billion at a CAGR of 20.5%.
In this post, we will shed some light on how AI has streamlined supply chain processes.
1. Supply Chain Data Management
One of the most challenging aspects of the supply chain is accurately categorizing and managing data. Since the process generates volumes of data, it can be tough to spot trends or signs of potential issues.
AI-powered solutions are built with tech stacks that can handle this data, capture, store, process, analyze, and visualize it within minutes. These platforms are designed for quick integration.
Thus, rather than depending on legacy systems, supply chain firms must leverage AI systems that learn and get more refined and faster at processing data. AI systems can be easily trained in managing supply chain data, thus allowing supply chain teams to quickly spot inconsistencies, identify trends and patterns, and spot potential problems.
2. Demand Forecasting and Inventory Management
The supply chain realm often experiences delays, backups, and the breakdown of a specific part of the chain, leading to inaccurate demand forecasting. Further, proper inventory management is challenging as it involves too many factors, namely order processing, packing, picking, and more.
AI can help with both – demand forecasting and inventory management.
AI-enabled platforms serve as accurate forecasting tools for customer demand and supply chain capacity. A survey from Secondmind reveals AI will transform the supply chain for the better by 2025 by bringing about accurate predictions on future demands.
For instance, AI allows accurate prediction of the decline and end of a product’s life on the sales channel. Deep learning algorithms decipher linear and non-linear dependencies to make demand forecasting easy and quick.
Similarly, AI and machine learning frameworks help supply chain teams maintain the level of inventory while creating a revenue generation path for the business.
3. Warehouse Automation
AI can easily integrate with a variety of technologies to optimize supply chain processes and improve warehouse performance.
For instance, computer vision (CV) can load and unload automation to reduce handling costs and the damage caused by human handling. These systems use historical data and spot opportunities to improve warehouse efficiency. Further, AI allows accurate demand forecasting and automates operations and workflows.
Though human intervention will still be needed at the warehouse, AI can help with handling tons of data using a high-performing algorithm. Thus, with AI, supply chain firms can be assured of higher cost savings and efficiency at their warehouses.
4. Supplier Risk Assessment
Today, businesses have multiple partners with services and sourcing being managed by several organizations across the globe. In most cases, this outsourcing is getting complex and sophisticated.
Thus, firms need to improve their supplier risk management framework to avoid unexpected risks. Failing to manage supplier risk can cause businesses reputational, regulatory, and commercial harm.
However, assessing supplier performance is a mundane and unproductive process that can be automated with integrated intelligent solutions.
AI-powered supplier risk management frees up time and resources for supply chain professionals by offering a 360-degree view of the vendors and detailed insights into the top vendor performance factors.
With AI, supply chain firms can build AI and ML-enabled models based on their risk assessment infrastructure. The model then fetches real-time data from various sources to calculate a risk score/index for suppliers. These risk scores alert supply chain teams of a potential supplier failure, thus reducing the chances of these suppliers hurting a firm’s productivity.
5. Conversational AI for Customer Service
Conversational AI can improve all aspects of SCM operations, allowing businesses to make better decisions with greater speed and scale. The technology can support the customer service team in offering an improved customer experience.
The AI-enabled solution can effortlessly manage a huge part of high-touch execution tasks usually taken care of by the customer support executive. Several virtual AI assistants operating together can improve customer engagement and streamline operational efficiency.
An integrated customer support system is capable of leveraging AI, ML, voice recognition, and natural language processing (NLP) to accurately understand customer concerns and respond to them most effectively.
Artificial intelligence is hogging all the limelight in the supply chain segment. From effectively managing supply chain data to managing deliveries, AI is powering supply chain processes by reducing uncertainties, thereby maximizing productivity and lowering costs.
By investing in AI solutions, supply chain businesses can surpass the cumbersome standard processes and improve their profitability.
Author Bio: Hazel Raoult is a freelance tech writer and works with PRmention. She has more than six years of experience writing about ecommerce, technology, entrepreneurship, and all things SaaS. Hazel loves to split her time between writing, editing and hanging out with her family.