Future of logistics: Strengthening the global supply chain

One major reason for the rapidly progressing digitalisation in the manufacturing and transport industries is their structure, which lends itself perfectly to automation. Standardised systems, repeated processes and well-established networks are prevalent in these fields. As AI technology becomes more affordable, it will be increasingly applied to further streamline and automate the supply chain.
Though finding real value from AI remains a challenge, global consulting firm Gartner identified AI as one of the top supply chain technology trends for 2018. Here are a few of the practical ways AI can be applied in the supply chain:
Data utilisation
A big problem with Big Data is that it can be hard for companies to effectively use all the data they collect. AI software can help make sense of data, allowing companies to sift through what they already have, and identify what data to prioritise in the future.
Inventory management
Keeping products on the shelves while avoiding costly overstock is a top priority for distributors. By assessing a wide range of factors, from seasonal trends to currency fluctuation to the price of parts and raw materials, AI can help predict consumer demand for particular products.
Manufacturing on demand
Using AI, manufacturers are not only able to predict when there will be a demand for a product, but also where that demand will come from. By utilising data from consumers and resellers, a global manufacturer can begin production closer to where the demand is located. AI can also help assure orders are filled on time if the manufacturer integrates data on parts availability.
Resource management
AI can help supply chain businesses to forecast when more staff will be required, and what skills those people need to bring with them. By incorporating data from connected assets such as factory equipment and vehicles, a business can also use AI to streamline maintenance and avoid downtime.
Customs processes
When goods pass through customs, they are assessed for tariffs using a global classification standard called Harmonized System (HS) codes. AI can help importers both avoid fines and overpayment of tariffs by helping assure that goods are classified and processed correctly.
Delivery routes
Another highly promising AI use case is the prediction of the quickest routes for delivery vehicles. This can be accomplished by combining massive amounts of information, including real-time data on traffic, weather reports, the location of barriers such as narrow streets or low overpasses, and satellite map data covering detours and road conditions.
Risk mitigation
Supply chain risk analysis is a complex task for both industrial and insurance companies. AI can incorporate predictive algorithms for scenarios such as fire, floods or cyberattacks, while also taking into account supplier levels and consumer demand. This approach helps to mitigate risk and avoid business interruption.
For many years, HDI Risk Consulting has been a partner to the industry. While new technologies such as AI are certainly helpful in the acquisition and analysis of data, it is our risk experts who still play the crucial role in supporting our customers use that data to keep the supply chain running smoothly. To learn more about our risk consulting services, please contact your local HDI representative.