Supply chain management uses AI to aid exports

September 4, 2023

Artificial Intelligence helps companies predict how many products customers will need in the future, allowing them to prepare adequately to avoid waste.

supply chain, artificial intelligence, industrial production, Más Colombia

Artificial Intelligence (AI) has been, for some time now, an ally in supply chain management and has emerged as a key tool in the business world. Its impact on various sectors is undeniable due to the boost it provides to exports.

In this sense, AI is revolutionizing the way companies approach and improve their shipping and picking strategies.

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As technology grows, AI promises to further revolutionize the export process, optimizing supply chain management and logistics, and providing greater growth potential for companies.

Those organizations that properly leverage AI will be in a prime position to compete in an increasingly globalized and competitive business world.

However, when asked if AI is the future of the supply chain, Felipe Hernández Anzola, co-founder of Datup.ai -a company that transforms data into time and money savings in the supply chain with Artificial Intelligence- assures that “AI is not the future, because for many companies it is already the present and they are using it in strategic areas such as the supply chain to predict what products customers will need, how to manage inventories efficiently and know when is the ideal time to buy their raw materials”.

Additionally, AI provides information that facilitates data-driven decision making by including internal and external data from the organization, which allows business owners to have a global view of what may happen in the company.

Although the use of AI varies by sector and region, many leading export companies are already implementing it to increase the efficiency of their operations.

This is corroborated by Carlos Diaz, Vice President of Data Nola at Keyrus – a global consultancy specializing in developing innovative digital and data technology solutions to improve performance management – when he says, “AI is revolutionizing the logistics industry by offering a wide range of capabilities that improve efficiency, accuracy and profitability. Today it has become a vital necessity if the industry is to survive in the market and stay ahead of the competition”.

These new technologies, which also include data science, make it possible to improve predictive capabilities to optimize order planning, preventive maintenance of machinery, reduce costs, efficiently track exports and imports, and speed up all logistics processes in the industry. In other words, optimal supply chain management.

Carlos Diaz of Keyrus comments that “AI plays a very important role in automating various export-related tasks, such as documentation, customs clearance and order tracking, which can improve efficiency and reduce processing times”.

“It also predicts how many products customers will need in the future, allowing them to prepare adequately and avoid waste. It helps us anticipate and reduce logistical problems by including external data such as a container crisis, a war or different weather problems to be more efficient, accurate and cost-effective”, says Felipe Hernandez of Datup.ai.

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Benefits in supply chain management

By optimizing transportation routes, AI saves time and shipping costs. For exporting companies, AI helps in the early detection of supply chain problems, such as disruptions due to natural disasters or trade disputes, ensuring more reliable deliveries.

In addition, warehouse automation streamlines the picking and packing of products for international shipments.

An example of a company that uses AI in supply chain management is Casalimpia, which has been in the domestic market for more than 6 decades and began its internationalization to Ecuador, the United States, Guatemala and the Central American market, to become a multilatina.

Its president, Pedro Felipe Estrada, assured that for the good management of the supply chain they had to venture into the subject of Artificial Intelligence.

“What we needed was a tool that would allow us to reduce inventories, be more agile in deliveries and more productive in logistics processes, providing a better service to customers”, says the Casalimpia executive.

He also assures that “AI is a fabulous tool for optimizing processes and the profitability of operations, because we detected that we needed to process information faster for decision making, more agile according to what is happening in the market”.

By implementing this technology, Casalimpia increased the quality of its deliveries by 10% and also boosted new business.

How to generate a real balance with AI between service, costs and liquidity?

For Felipe Hernández, the first step is to “collect and analyze relevant data. These tools help to predict product demand, which allows adjusting the level of service to meet customer needs without exceeding inventory”.

For his part, Carlos Díaz says that achieving this balance between service, cost and liquidity with the implementation of AI requires careful planning, data analysis and interactive adjustments.

For example, Diaz points out, in this process it helps to define clear objectives, collect and analyze data, select appropriate technologies, and seek advice from experts who can show you where to start.

However, beyond these business experiences, it is important to remember that achieving the perfect balance requires a continuous process, as business conditions and customer preferences evolve.

It is also important to periodically assess what your company’s strategies are, with the purpose of adjusting your AI models to maintain alignment with your objectives and the actual circumstances in which the business finds itself.

According to Keyrus, these examples can serve to show how to streamline processes in the logistics and supply chain sector:

Route optimization: AI can analyze real-time and historical data to optimize delivery routes, taking into account factors such as routes, traffic, weather and delivery windows. This helps reduce fuel consumption, transportation costs and delivery times.
Demand forecasting: AI algorithms can process and analyze data from past sales, market trends and external factors to predict future product demand. This enables logistics companies to optimize inventory levels, reduce stock-outs and minimize overstocking.
Warehouse management: AI can also optimize warehouse layout and inventory placement to minimize travel distances.
Supply chain visibility: technologies that enable visualization and processing of large volumes of data, including AI, provide real-time visibility of the entire supply chain, allowing stakeholders to track shipments, monitor inventory levels and identify potential disruptions.
By doing so, Keyrus notes, it improves decision making and proactive problem resolution.
“Last-mile delivery”: AI-powered delivery robots and drones can handle last-mile deliveries, especially in congested areas. These technologies can reduce costs, increase delivery speed and improve customer satisfaction.
Predictive maintenance: AI can analyze data from vehicle and equipment sensors to predict when maintenance is needed. This minimizes downtime, reduces maintenance costs and ensures the reliability of logistics operations.
Customer service: chatbots and virtual assistants, powered by AI, can handle customer queries, track shipments and provide real-time updates. These actions tend to improve customer satisfaction and reduce the workload of human agents.
Data analytics: large volumes of data can be analyzed to identify trends, inefficiencies and opportunities for improvement in the export logistics process, enabling data-driven decisions.
Customs and compliance: helps ensure compliance with various customs regulations and requirements in order to automate document verification and ensure that shipments are legally compliant.