4 proofs that AI streamlines and enhances the supply chain

The supply chain is a hot topic for many reasons, be it pandemics, the environment, changes to demographics, or increasing pressure to digitize. Companies feel the pressure and the connected opportunity to optimize this field, and many perceive translating the need and its challenges into solutions as hard. It is challenging, but addressing the use cases with the right technology is not as painful as many think. Moreover, many cases or challenges can be handled by only one technology. Including those in the supply chain. 

The supply chain has undergone a significant change. Instead of people using crayons, printed maps, and Excel sheets, technologies now easily take into account thousands of rules and restrictions and process everything in seconds or minutes. Still, when implementing AI, many factors have to be considered. Does the company has control of the entire chain or only a part of it? What is the core competence of the company's business? How big is the territory the company operates in? Technological background, open-minded approach, and knowledge of own business are essential for discussions and searching for the right technology to take over a specific process or task as efficiently as possible. It is the starting point of implementing AI into a company. And all of these factors are variable from company to company. On the other side, one more factor will always affect not only the supply chain and be the same for all these companies – the customer.

Every customer prefers a different commodity, one is picky, second likes to experiment. The number of SKUs is constantly growing, as are customers' demands, expectations, and individuality. They expect seamless interaction, new fulfillment options like “buy online, pick up in-store,” drop-shipping, and more. However, sellers can greatly benefit from responses to customer needs in terms of the supply chain.

Whether a retail or e-commerce company, implementing AI into at least part of their supply chain processes brings many benefits and opportunities. And not just because it has a high-value potential for many use cases – from forecasting to delivery optimization. It also opens the door to readiness for the future. We picked four key benefits that AI brings and use cases with which we help most often.

Efficient goods and supplies handling

Efficient goods and items handling are key benefits that AI and other technologies bring. For example, many companies are stocking up significantly more inventory than they need to prevent volatility in the marketplace. Algorithms can estimate demand for the coming days across all inventory, regarding the season, the data about customers' behavior, shopping routine, weather, etc., that can shape the demand. The technology ensures that the seller has everything but in the best possible amount. Moreover, considering the dimensions of the inventory and items and the need of their expedition, AI generates a plan for the best possible space utilization and placement for the smoothest handling possible and within seconds. E.g., for one of our clients, we developer tailored application that optimizes space utilization in sea containers. Thus, the client was able to save 840 000 EUR during the first year.

By better forecasting and analyzing many factors in higher granularity, AI enables to find the balance in all areas of the supply chain, including logistics and warehousing, fulfillment or returns.

Suppose a company manages the supply chain itself, for example, a food retailer. In that case, the company can bring the deep knowledge of its goods into logistics and delivery processes optimization. Then, algorithms can generate optimal routes in accordance with the freshness of the food, rules, needs, etc. Such technologies should reflect all the company's requirements and challenges during transport, delivery or storing, from freshness to the stackability of goods.

Last but not least, efficient work with stocks and goods also concerns the goods management at branches and having all important data in real-time. But not just across individual departments. We are talking about a holistic view. In this case, AI can manage and display everything in one place, whether the seller has 20 or 200 branches. Still, it is not about giving up control from the locals.

Improved customer experience

Whether the customer is shopping online or in-store, customer experience is always important. The customer is looking for a good quality of various products and services. As a result, especially e-commerce companies have had to deal with a higher number of orders. Therefore with changes and queries from customers who expected to easily and quickly change the delivery date or place.

In this case, AI ensures fast internal processing and transmission of information to other departments and the best possible plans for delivery. Thus, all delivery-related processes run smoothly and can be easily rescheduled. Talking about the best possible customer experience, customer service is also related. Whether requests for changes income through different channels and for various changes, fast processing and responding should be a sure thing. We know from our own experience that AI can process a basic query within 10 seconds and completely automatically.

The customer has an answer quickly, knows that the order will be delivered to the required place and at the required time. AI takes over the next part of this process, as it manages to schedule changes quickly and easily at the last minute. Algorithms recalculate the loading of orders into the vehicle, delivery routes, and time in seconds, so the seller can meet customers' needs as much as possible. Customers will be satisfied, so it is easier for the seller to become a loved brand, and customers will happily return. 

Flexibility

For retail and e-commerce, it is essential to respond quickly to changes and requirements, which is not easy using off-the-shelf solutions or Excel sheets. Implementing AI opens up the possibility of dynamic planning. For example, the final destination of trucks with food is often specified much alter after the shipment. It is impossible to predict which branch or shop will be out of the stocks first, so everything is replanned dynamically. Thanks to AI, planners see in real-time where goods and items are already sold out or will be and plan everything easily, quickly, and in one system.

Another case is storing flexibility. AI also helps with the return of goods and prediction of their possible attractivity to customers. Based on the season, the weather, etc., the algorithms can predict which goods are well left nearby and can be taken to the warehouse and where they should be sent.

And in the bigger picture, sellers often have many suppliers. Sometimes it can be hard to handle all of them and consider all the necessary info in planning. Intelligent algorithms can handle supply chain management according to reliability. For example, they consider the reliability of the recall of deliveries of their suppliers, contractual conditions. Moreover, AI also considers the traffic at entrance gates and warehouses.

Sustainability and environmental protection

Thanks to better work with goods, routes, and loading, the companies significantly alleviate the environment. But let's start with some numbers. For example, a rise in volumes in the fashion industry could push CO2 emissions to around 2.7 billion metric tons a year by 2030. An increase like this will have a huge impact on the planet. A major part of global greenhouse gas emissions comes from freight transportation. And transportation can also drain a company's financial resources, such as inefficient shipping routes or vehicles driving half-empty.

It is really advantageous to let AI optimize these processes. By tailoring algorithms, companies can get tools for automated and more efficient planning of delivery and transport routes, milk runs, inter-warehouse transport, truck and container loading, parcel filling and other cases. Every non-shipped truck, better truck route, or efficiently loaded pallet saves in total tens or hundreds of tons of CO2 emissions. In our experience, it can be up to 170 tons of emissions per year.

AI and other technologies bring great opportunities to the supply chain. Therefore, no matter in what business area a company starts deploying technology helpers, it is a good investment in its future. The range of the use cases where AI to deploy in the supply chain is vast. But the good news is that it is possible to grasp many of them with only one robust technology. By tailoring its algorithms for specific needs and business areas, it is possible to increase the efficiency of processes by tens of percent. Thus, companies can not just keep up with the competition, but outperform it, scale up the business and satisfy their customers.

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About the author

Petr Zelenka, Head of Delivery
As a CTU graduate, Petr started his career as an SW engineer, working on products in the healthcare and automotive industry. During his career, he assumed senior engineering roles and worked as a solution architect and tech lead. At Blindspot, Petr has been focusing on delivering AI-driven solutions into multiple domains, specializing in optimization projects.