Machine Learning in SCM
Supply Chain Management is an information system flow to take control of supplier. It also translates as a worldwide network used by individuals, organizations, companies to deliver products and services from raw materials to their customers. The term of SCM has been known for approximately 40 years since it was first coined by Keith Oliver long before the 20th century. Before the era of high technology, people used it based on invoice costs. Leaving the criteria on quality, delivery, flexibility, and other costs.
The development of technology today has been transforming the business outcomes as we want. The quality of products, the best services, all are delivered at its lowest cost to achieve optimal results. The presence of Enterprise Resource Planning as the core system of a company, which controls all of its internal aspects, brings the SCM system into a whole more efficient way with faster progression using the highly advanced and integrated technology. Modern SCM use logistic management to plan, implement, and control the forward (or reverse) flow of goods. It also improves how companies could build partnership, alliances, and collaborations.
In industry 4.0, people are now generating a more sophisticated, smart technology, so they build a machine that could simulate human intelligence that programmed to think like humans named “Artificial Intelligence”. What is more interesting is they now combine it to make the SCM system do better with their tasks. One of the applications is to make an autonomous decision-making. With the decisions are now driven by desired outcomes automatically, managers are now also could turn their focus more on higher-level jobs.
Machine learning as a branch of artificial intelligence is surely has made a revolution of how the retailers and suppliers work in this century. It regenerates the system of a business with the accuracy of the algorithm. Machine learning’s value in supply chain management other than to make an autonomous decision-making are to track packages in real-time, reducing manual work, streamlined inventory management, fraud prevention, cost optimization, and enhanced customer service.
When a company implement a machine learning to its SCM system, they could possibly identify quality issues at the very early stages. It prevents a defect product to be delivered to customers because all of the process are based on a real-time. This is genuinely making the production stages at a higher level, really effective, and the process could be directly monitored by the staffs.
Using a machine learning technology in supply chain management processes is multi-purpose or versatile. It helps companies to deliver the best products or services to the customers at all stages. With a correct algorithm, it supports to get a system design that could automatically give you an end-to-end vision to your supply chain management, it also gives you the right decision, get rid of bad quality products, reducing paper-works, and prevent from many other disruptions.