How is AI revolutionizing the supply chain today?

No over-stocking or under-stocking. This is the major challenge that logistics procurement has to face on a permanent basis. Over-stocking increases the cost of storing products and also ties up capital. Conversely, too little inventory increases the number of replenishment orders. This can lead to stock-outs and loss of customers. Therefore, in addition to avoiding the problems associated with over- and under-stocking, optimizing the logistics procurement process also means avoiding the risk of stock-outs.

Out-of-stock forecasting and sales forecasting, when leveraging the power of artificial intelligence and machine learning, are among the most effective strategies to achieve supply chain optimization in general, and logistics procurement in particular.

In the following lines, we present you the basics about logistics procurement, and how to use artificial intelligence to optimize the procurement process.

What you need to know about logistics procurement

Procurement: definition

Logistics procurement refers to the purchase, storage and inventory of goods necessary for the proper functioning of the company. It intervenes at the beginning of the processes of production and marketing of the products.

Thus, for a manufacturing company, its logistical supply will focus on the acquisition and storage of raw materials for the production of goods.

In the case of a service company, the role of the procurement department will be to ensure the successful delivery of goods and finished products from the supplier to the warehouse.

Differences between logistics procurement and supply chain

It should be noted that "logistics procurement" and "supply chain" are not the same thing. Logistics procurement is an essential function of the supply chain. More precisely, the supply chain encompasses a whole range of logistics, from procurement to distribution, including the production of goods. It involves a network of internal (employees) and external (suppliers, subcontractors, distributors, consumers) players, which the company must manage as well as possible.

The main functions of procurement

The functions performed within the framework of supply logistics are as follows:

• the acquisition function - this involves the process of purchasing the products necessary for the production department to function properly (among other things), including the selection of suppliers and negotiating prices with them;
• the storage function - this involves setting up a space to store products that will either be used later by the production department or stored until they are shipped and distributed to the final customers;
• the inventory function - this consists of managing the inventory of stocks, i.e. managing the references of the stored products, determining the quantity of stocks to be used (according to the periodicity of the orders from the production department and the final customers), and monitoring the deliveries of the orders.

The objectives of logistics procurement

Supply chain logistics has several types of objectives:

• cost objectives - to reduce purchasing costs as much as possible (by putting pressure on suppliers to obtain the best prices and long payment terms) and storage costs (thanks to very precise inventory management);
• quality objectives - to reduce product failures (defects, waste) and improve the final quality of products purchased from suppliers or delivered to end customers;
• continuity objectives - to ensure continuity of supply by creating and maintaining stable and trusting relationships with suppliers;
• security objectives - in order to secure stock levels and limit possible stock-outs due to unforeseen events, in particular through the creation of a security stock;
• flexibility objectives - on the one hand, to choose suppliers who can adapt quickly to changing needs, and on the other hand, for the company, to demonstrate adaptability in order to improve customer relations;
• lead time objectives - to ensure regular deliveries, to ensure the reliability of the supplier and the carrier, and to reduce lead times.

In summary, the objective of procurement logistics is to buy the necessary quantities of quality products at the right time and at the best price from suppliers who will respect deadlines and who will be flexible.

The benefits of a good procurement process optimization

Effective logistics procurement management enables a company to buy economically from suppliers, remain competitive in its industry and be able to make a profit.

To achieve these results, planning and implementing efficient logistics procurement strategies are essential for purchasing and storing goods.

Effective logistics procurement management enables several kinds of cost reductions:

• Lower storage costs - no need to buy more product than is needed, or risk it becoming dormant stock, resulting in unnecessary storage costs;
• Reduced production costs - since the company has the right amount of goods available at all times to maintain the mentioned productivity levels, there is no risk of stock-outs;
• Reduced transportation costs - by choosing the right suppliers, the company benefits from a regular and inexpensive supply of quality goods.

In short, by optimizing its procurement process, the company benefits from a competitive and sustainable supply chain. This can only have a positive impact on the service provided to customers, as well as on the brand image of the company.

Using artificial intelligence to optimize the procurement process

According to a recent IBM study entitled "Digitally Perfecting the Supply Chain," 85% of supply chain managers say they lack visibility into their supply chain, and that they would like to have clear visibility across the entire supply chain so they can react quickly to unexpected events.

Artificial intelligence, machine learning and data analytics provide a solution to this problem, thanks to the ability of tools using these technologies to make sales forecasts and inventory forecasts.

Thanks to AI, it is possible to optimize the supply chain and to anticipate the impact of internal and external events on the company, in order to prevent crisis situations and to react quickly to an incident. This ultimately improves the overall performance of the company.

Better understanding of supplier risks thanks to artificial intelligence

Thanks to artificial intelligence, data analysis and machine learning, it is possible to correlate all relevant information about all suppliers.

Thanks to its analytical power, artificial intelligence allows the Purchasing Manager to receive answers to all the questions he has about his supplier, for example:

• Will they be able to fulfill their order?
• Does it offer the best deal?
• Is there any concern about the quality of the products supplied?
• Have the invoices been falsified?
• etc.

As the first point of contact for the purchasing department is the supplier, it is essential to maintain a relationship of trust with them over the long term.

Another major advantage of artificial intelligence is that because machine learning algorithms can perform a detailed analysis of expenses and the supplier panel, it is possible for the purchasing manager to make informed decisions in order to rationalize and secure expenses. It should be noted that such a refined analysis allows the company to achieve between 5% and 40% additional savings on raw material purchases.

Automate inventory with artificial intelligence

When it comes to inventory, the use of artificial intelligence, data analytics and machine learning makes it possible to:

• better manage the countless items stored in the warehouse;
• to know precisely the location of each item (as well as the empty ones), thanks to the assistance of a drone equipped with an on-board camera;
• schedule automated daily (or weekly) inventories of goods, in order to benefit from an updated vision of stocks, on a daily basis.

These advantages allow teams to be faster and more efficient, and to work in a safer manner, as they no longer have to operate at height.

Better inventory management thanks to artificial intelligence

And finally, in the area of inventory management, artificial intelligence, machine learning and data analytics make it possible to, among other things:

• Identify trends in the raw data, which are used to develop inventory forecasts;
• Identify products that may sell faster or slower than expected;
• Reduce out-of-stocks, shortages, and overstocks;
• Assist in decision making to optimize resources.