Artificial Intelligence (AI) has been, for quite some time, a valuable 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.
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 cost savings in the supply chain using Artificial Intelligence – asserts 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 when is the ideal time to purchase raw materials".
While the use of AI varies by sector and region, many leading export companies are already implementing it to enhance the effectiveness of their operations.
Carlos Díaz, Vice President of Data Nola at Keyrus – a global consulting company specialized in developing innovative technological solutions in the digital and data field to improve performance management – affirms that "AI is revolutionizing the logistics sector by offering a wide range of capabilities that enhance efficiency, accuracy, and profitability. Today, it has become a vital necessity if this sector wishes to survive in the market and stay ahead of the competition. "These new technologies, which also include data science, allow for improved predictive capabilities to optimize order planning, preventive maintenance of machinery, cost reduction, efficient tracking of exports or imports, and acceleration of all logistical processes in the industry. In other words, it leads to optimal supply chain management.
Carlos Díaz from Keyrus comments that "AI plays a very important role in automating various tasks related to export, 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 properly and avoid waste. It helps us anticipate and reduce logistical issues by incorporating external data, such as container crises, wars, or various weather-related problems, to be more efficient, accurate, and profitable," says Felipe Hernández of Datup.ai.
By optimizing transport routes, Artificial Intelligence saves time and shipping costs. For export companies, AI helps in the early detection of supply chain issues, such as disruptions due to natural disasters or trade conflicts, ensuring more reliable deliveries. Furthermore, warehouse automation streamlines product selection and packaging for international shipments.
An example of a company using AI in supply chain management is Casalimpia, which has been in the national market for over six decades and expanded internationally to Ecuador, the United States, Guatemala, and the Central American market to become a multinational. Its president, Pedro Felipe Estrada, stated that for effective supply chain management, they had to delve into the field of Artificial Intelligence."What we needed was a tool that allowed us to reduce inventories, be more agile in deliveries, and more productive in logistics processes, providing better service to customers," commented Casalimpia's executive. He further asserts that "AI is a fabulous tool for optimizing processes and the profitability of operations because we realized that we needed to process information faster for decision-making, becoming more agile in response to market changes."By implementing this technology, Casalimpia increased the quality of its deliveries by 10% and also stimulated new business opportunities.
According to Felipe Hernández, the first step is to "collect and analyze relevant data. These tools help predict product demand, allowing adjustments in service levels to meet customer needs without excessive inventory."On the other hand, Carlos Díaz states that to achieve this balance between service, cost, and liquidity with AI implementation, careful planning, data analysis, and interactive adjustments are required.For instance, Díaz points out that this process involves defining clear objectives, collecting and analyzing data, selecting appropriate technologies, and seeking guidance from experts who can show the way forward.However, it's important to remember that achieving the perfect balance requires an ongoing process, adapting to evolving business conditions and customer preferences.It's also crucial to periodically evaluate your company's strategies to align your AI models with your goals and the real circumstances of the business, as Keyrus emphasizes.According to Keyrus, these examples can illustrate how processes in the logistics and supply chain sector can be streamlined:
Route Optimization: AI can analyze historical and real-time data to optimize delivery routes, taking into account factors such as routes, traffic, weather, and delivery windows. This helps reduce fuel consumption, transport costs, and delivery times.
Demand Forecasting: AI algorithms can process and analyze past sales data, market trends, and external factors to predict future product demand. This allows logistics companies to optimize inventory levels, reduce stockouts, and minimize excess inventory.
Warehouse Management: AI can optimize warehouse layout and inventory placement to minimize travel distances.
Supply Chain Visibility: Technologies, including AI, provide real-time visibility of the entire supply chain, enabling stakeholders to track shipments, monitor inventory levels, and identify potential disruptions. This enhances 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, speed up delivery, 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 operational reliability.
Customer Service: AI-powered chatbots and virtual assistants can manage customer inquiries, track shipments, and provide real-time updates. These actions tend to enhance customer satisfaction and reduce the workload of human agents.
Data Analysis: Large volumes of data can be analyzed to identify trends, inefficiencies, and improvement opportunities in the export logistics process, enabling data-driven decision-making.
Customs and Compliance: AI helps ensure compliance with various customs regulations and requirements by automating document verification and ensuring that shipments meet legal standards.
If your company is considering how to harness the potential of data, contact us at Keyrus. We are data intelligence consultants specializing in digital platforms, e-commerce, marketing, and customer experience.