{"id":49497,"date":"2022-04-27T00:00:00","date_gmt":"2022-04-27T00:00:00","guid":{"rendered":"https:\/\/www.techopedia.com\/how-machine-learning-can-improve-supply-chain-efficiency\/"},"modified":"2022-07-27T16:22:38","modified_gmt":"2022-07-27T16:22:38","slug":"how-machine-learning-can-improve-supply-chain-efficiency","status":"publish","type":"post","link":"https:\/\/www.techopedia.com\/2\/31846\/trends\/big-data\/how-machine-learning-can-improve-supply-chain-efficiency","title":{"rendered":"How Machine Learning Can Improve Supply Chain Efficiency"},"content":{"rendered":"

In the current global economy, competition is fierce across different business domains. Each and every organization is striving to improve business efficiency and reduce expenditures. Supply chain management<\/a> is one of the critical tasks for business owners. Knowing how to implement an efficient supply chain management system is key. Innovative, disruptive technologies like Artificial Intelligence (AI)<\/a> and Machine Learning (ML)<\/a> can offer some excellent solutions. These AI and ML solutions can help business to predict a reliable demand forecasting<\/a> model (also called demand sensing.) The old predictive forecasting techniques are becoming obsolete as those models are not built to learn continuously and make decisions the way the new AI-driven demand sensing models are.<\/p>\n

In this article, we will explore how AI and ML can improve modern supply chain management.<\/p>\n

What is AI and ML?<\/span><\/h2>\n

Artificial intelligence is a combination of different processes and algorithms<\/a>. AI can simulate some aspects of human intelligence like self-learning, problem solving and responding to given input. Machine learning and deep learning (DL)<\/a> are subsets of AI solutions.<\/p>\n

Machine learning comes under the “limited memory” category of AI, where the AI solution can learn over the time and develop itself. Different ML algorithms are used in the AI solutions to improve the efficiency.<\/p>\n

These powerful AI\/ML solutions, like those created by AltaML<\/a> are used to solve some of the challenges faced in the supply chain industry.<\/p>\n

Supply Chain & Supply Chain Management<\/span><\/h2>\n

The supply chain is a combination of all the activities required to move a product\/service from inception to the end users. The supply chain includes people, resources, information, channels and modes of transportation. All these entities are linked together to complete the cycle from procurement to fulfilment. Reverse logistics also come into play; consider waste management for fast fashion, or recycling. In this regard it is not just a supply chain, but a circular process.<\/p>\n

Supply chain management can be defined as a process to integrate all the activities required to fulfill the demand and supply life cycle. The Covid-19 pandemic has had a very negative impact on the global supply chain. Organizations that have always been focussed on lean supply chain management to optimize the cost and meet end-user demand are now needing to consider risk management and mitigation. With the help of technologies like AI\/ML, a high level of efficiency and visibility in supply chain management can be achieved.<\/p>\n

Pain Points in Logistics and Supply Chain Management<\/span><\/h2>\n

Supply chain management is a very complex process. The pandemic has created a lot of uncertainties in the global supply chain. The set of challenges include logistics and transportation issues, increased customer expectations, unexpected demand, lack of visibility and operational complexities.<\/p>\n

Let us try to summarize these pain points:<\/p>\n