The growing place of Artificial Intelligence tools in the management of the activity of your business implies access to large amounts of data and the implementation of adequate measures. Among the optimization points of its production, the Supply Chain is based on what is called “ machine learning ”. This machine learning aims to update usable data and models in order to significantly improve its daily logistics. In this search for perfecting its logistics, machine learning therefore plays a non-negligible role and requires a substantial database in order to transform itself into useful indicators for making the right decisions.
What does the Supply Chain correspond to?
When we talk about Supply Chain , we are referring in particular to a company's supply chain and the logistics associated with it. However, this term can also include other points when we speak in particular of Supply Chain Management . Indeed, this notion will take into account other factors: resources, means, methods, tools and techniques for managing the activity. In this conception, the Supply Chain envisages logistics in its entirety in order to determine the possible points of improvement at the various stages of supply and manufacturing up to sale. The interest in this aspect of its activity is all the more important for large companies which involve several subcontractors in the manufacturing process.
What place for “machine learning”?
In order to optimize the stages of the Supply Chain, it is important to take into account and evaluate a certain number of indicators. Thanks to machine learning (or automatic learning) , it will be possible to distinguish patterns that are repeated in the supply chain: patterns. Based on algorithms , machine learning will make it possible to clearly and quickly identify relevant supply chain data in order to develop models so as to better understand how production works and discover areas for improvement. In this new approach to logistics and the search for optimization, machine learning will allow to constantly learn about areas for improvement .
The main advantages of machine learning
The era of Big Data and the rise of Artificial Intelligence represent an exceptional challenge for companies. Indeed, they now have an extraordinary resource to perfect their activity and thus offer a service of optimal quality . In this quest for quality of service, machine learning tools will be real assets for anticipating needs and adapting as best as possible to everyday constraints .
Anticipation of volumes and resources required
The implementation of machine learning tools based on Artificial Intelligence will make it possible to process a particularly large number of data and of different natures. Thus, it will be possible to take into account all the information relating to the state of stocks, the planned deliveries, the orders in preparation, the number of employees in service. The collection and linking of these different data will make it possible to plan the necessary resources in order to best respond to the activity to come. These forecasts are part of a desire to significantly improve the performance of the entire Supply Chain .
Demand forecast
The patterns highlighted by machine learning tools are real assets for predicting and precisely estimating future activity. Linked to stock and order data, this demand prediction will allow the company to adapt and efficiently manage its logistics : stocks, flow of goods, marketing of certain products, choice of distribution channels, etc. The accuracy of these predictions is a particularly important element in optimizing the supply chain .
Implementation of predictive maintenance
Optimizing the supply chain also involves quality maintenance . On this point, the data accessible thanks to machine learning and IoT (Internet of Things) will make it possible to identify the elements that will influence the longevity of transport machines and vehicles. Machine learning will also make it possible to measure the overall efficiency of equipment (OEE: Overall Equipment Effectiveness) which is an essential performance indicator in the supply chain.
Permanent activity management
Machine learning tools and available data become assets in the daily management of its activity. Indeed, this technology offers permanent visibility across the entire supply chain and thus allows it to adapt to future developments and needs. In the direction of its activity, machine learning thus appears as a decision-making aid tool to minimize the time and costs of the Supply Chain.
Machine learning: optimization of the Supply Chain
The Supply Chain is therefore a point on which companies can improve. Composed of several stages, this logistics chain can be improved at different levels: inventory management, means of transport, order preparation, etc. In order to know the points for improvement, machine learning is interested in the masses of data allowing to put in highlight the elements on which it is possible to perfect the logistics. Based on algorithms of Artificial Intelligence , it is necessary that machine learning has a sufficient amount of data to analyze in order to translate them into indicators useful for decision-making. In the Supply Chain, the place of machine learning is therefore central and significantly improves its logistics and thereby its profitability.
