AI plays an increasingly important role in logistics. As the logistics requirements at organizations continue to become more complex, big data applications have started to streamline global logistics. Technology logistics startups have started using data-driven technologies such as big data, AI, IOT, sensor technologies, and other machine learning algorithms to manage real-time analytics of large unstructured data.
Recent technological advances and increased demands from shippers have prompted companies to explore AI and the solutions that they can offer to logistics teams. Some of the most common solutions that technology can offer in the supply chain are those that can lead to cost reduction by reducing redundancies and mitigating risks, strengthening traditional forecasting techniques, speeding up deliveries by optimizing routes, and improving customer service. With the right intelligent automation, companies can update their IT systems continuously and improve their data analysis processes in order to support their logistics processes.
Data is generated in a number of places–vehicles, trucking, maintenance systems, accounting, and human resources. Most areas of a company can contribute data points, and data from outside the company can also be used in analytics. Data generated by vehicles is increasing as more and more vehicle-centered data is generated by an increasing number of sensors added to trucks to support improved performance, safety, diagnosis, and maintenance.
Machine learning is a good tool for the early identification and correction of data quality errors. In this application, machine learning predicts and improves the current data values by combining experience with large historical data sets and human feedback.
In addition, robotics is already a part of the supply chain. Tractica Research estimates that global sales of warehousing and logistics robots will reach $22.4 billion by 2021.
Transport organizations rely heavily on their staff’s experience, agility, and abilities in dealing with complex issues. Supply chain leaders must move ahead of the growth curve to avoid being left behind and immediately initiate necessary changes.
