Machine learning is a hot topic, and for a good reason. Right at the top, I’d say, machine learning has evolved to the point where it can – and should – be used to help virtually all businesses increase efficiency while reducing costs.
If the company is Airspace Technologies, nothing.
For years the status quo of the logistics industry has been compiled of many large Freight Forwarders who excel at one specific sector or another. Through tribal knowledge of knowing popular flight options, reliable service partners, and knowing what routing worked on the previous shipment, they have built the playbook of logistics world. However, in today’s world, the status quo is not enough.
The vast majority of Internet surveys surrounding supply chain and logistics report that visibility is an essential aspect for stakeholders. However, we continue to accept the industry’s antiquated response to our most crucial need. Even in the most time critical logistics situations (next flight out and on-demand), shippers endure the fact the vast majority of forwarders only provide two data points: when the shipment is picked up and when it has been delivered. This might be acceptable if the delivery is on time (and if it’s the 90s). But, what happens during transport? And, what about the stakeholders who need visibility into their shipment during transit?