Week 4 - Machine Learning and Artificial Intelligence
Welcome to week 4 of our 8 week series on modern technology, specifically in the downstream fuel space. This week we're discussing Machine Learning and Artificial Intelligence and how that's useful for our customers.
ML and AI are super buzzy words that get thrown around a lot, especially as it relates to tech and software. Many people, much smarter than us, have written about the potential and danger of these technologies on the whole.
We, however, are only going to focus on what it means for fuel supply management and logistics, skipping the whole AI takes over the world debate.
When we say we're using ML and AI all we're really saying is we're developing programs that look at the different inputs (data points) + the history and then make adjustments and recommendations to the user on what the system thinks the best option is for that particular action.
As an example - you have 3 different supply contracts at 3 different terminals all within the same distance of the end location. You also have the historical sales data at that location. What is the best option for a load to be scheduled, picked up, and delivered based on those variables?
In today's environment, the supply team + the dispatch team needs to manually determine what the best option is. By leveraging our software, the system will tell you (recommend) what your best option is based on what the system sees from a price and a site run-out perspective.
In its simplest form, across the entire workflow, that's what we're doing. There is a tremendous amount of bottom-line improvement in the business.
When you think about your workflow, from supply and contract management to forecasting and dispatching, to reconciling and invoicing, how many decisions are made by people. We typically find it's almost all. There is a tremendous amount of value in driving that number down by having the "machine" give you the best option.
If you would like to learn more, just send us a note and we'll get something on the books.