Predictive Analytics in Logistics with AI

There are many reasons to believe that now is the best time for the logistics industry to embrace Artificial Intelligence (AI). In logistics, the network-based nature of the industry provides a natural framework for implementing and scaling AI, amplifying the human components of highly organised global supply chains.

Furthermore, companies deciding not to adopt AI run the risk of obsolescence in the long run, as competitors seize and effectively use AI in their business today. AI offers logistics companies the ability to optimise network orchestration to degrees of efficiency that cannot be achieved with human thinking alone.

AI can help the logistics industry to redefine today's behaviours and practices, taking operations from reactive to proactive, planning from forecast to prediction, processes from manual to autonomous as well as services from standardised to personalised.

Sign up for this one-day course and kickstart your journey with our industry expert on how AI can provide valuable insights and analytics to help logistics companies make data-driven decisions and improve their operations.

What is Machine Learning?

ML is the use and development of computer systems that are able to learn and adapt without following explicit instructions, by using algorithms and statistical models to analyse and draw inferences from patterns in data. Machine learning helps the logistics service providers to analyse large sets of data and make the logistics management system smarter and better. At the time of delivery and management, predicting future results and needs, is a difficult and important task. covering all of the coordination between partners that have a role in this network, including sourcing, manufacturing, transporting, storing and selling.

Predictive Modelling for Logistics

Logistics companies are using advanced predictive analytics to determine the likelihood of a shipment's status changing from on time to arriving late. They do this by using simulation models. By examining the probability of a status change, they can determine the date and time for shipments in specific locations. Predictive analytics allows organizations to determine optimal inventory levels to satisfy demand while minimizing stock. Using sophisticated models, predictive analytics allows supply chain managers to determine detailed inventory requirements by region, location and usage.

Sorting Items for Logistics

Computer vision applications have a major role in product and component assembly in the manufacturing space. As a part of industry 4.0 automation, most of the logistics industry has been implementing computer vision to conduct fully automated product assembly and management processes Computer vision for warehouse management is especially valuable during the critical moments of loading and unloading trucks. Applications include 1) Traceability and tracking of objects. 2) Volumetric properties of goods. 3)Inspection and quality control of goods. 4) Equipment condition monitoring. 5)Occupancy of storage and traffic areas.

Businessmen, marketers or investors who seek to understand how AI can be used to streamline logistics processes to generate useable and trustworthy data to generate value are welcome. This course is meant for beginners, no coding/programming or computer science background required and those without any knowledge of data are also welcome.

Dwight Fonseka is the Head Data Analyst at Plano, the world’s first science-based parental control application and an Adjunct Lecturer at the London School of Business and Finance. His interest in the area of data developed sometime in 2014 when he ventured into data analytics and database management. 7 years later, he has achieved an impressive skill set in data. This includes advanced statistics, big data analytics, cloud computing, neural networks, R programming, python programming, business analytics, data storytelling, and more. Dwight has a Masters in Education (Curriculum & Teaching), a Microsoft Certificate of Achievement (SQL), and an Advanced Certificate in Learning and Performance (ACLP).