How machine learning can improve decisions and automate manual processes in freight forwarding
Abstract
Machine learning (ML) is becoming ubiquitous, yet it is still heavily underutilised in the logistics industry. This paper showcases the role of ML in modernising decision making in freight forwarding. After introducing the concept of ML at its simplest application in freight forwarding, a few examples from a time-critical tech-enabled logistics company, Airspace, are showcased to support the idea. The benefits and costs of ML are highlighted with a focus on what business metrics are improved by implementing ML. In the current world, any logistics company not investing in ML development is abdicating strategic advantage to their competition and losing the ability to compete with the more technologically forward-facing companies.
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Author's Biography
Ksenia Palke is the Director of the AI team at Airspace, where she joined in 2019. Prior to that, she had implemented various machine learning (ML) models and strategies at multiple companies in San Diego. Her main focus is to make ML and applied mathematics relevant and impactful for business. She had her start in the data science world while getting her PhD in geophysics from Stanford University. In 2021 she was recognised as a Woman of Influence in Technology by San Diego Business Journal.
Spence Lunderman is a Senior Applied Scientist on the AI team at Airspace. His work focuses on developing and governing machine learning (ML) and mathematical models to solve internal and customer-facing problems at Airspace. Prior to joining Airspace, Spence developed ML models at the U.S. Department of Energy’s National Renewable Energy Laboratory to aid in the development of new automotive biofuels. He also worked as a visiting researcher at NASA’s Jet Propulsion Lab developing numerical optimisation methods for Bayesian inverse problems (a common class of problem in weather forecasting).
Citation
Palke, Ksenia and Lunderman, Spence (2023, March 1). How machine learning can improve decisions and automate manual processes in freight forwarding. In the Journal of Supply Chain Management, Logistics and Procurement, Volume 5, Issue 3. https://doi.org/10.69554/XNTD5864.
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