A Bit Nerdy! Transportation Costs

I've spent a lifetime helping customers find the lowest possible cost to service their customers. This is NOT AN EASY TASK!

Warning this is going to get a bit nerdy, but its important for you to know. Especially on the transportation side of the supply chain. As the inventor and founder of 4SYTE ™ technologies, I've spent years trying to solve this problem. What most if not everyone doesn't understand is that there is no one magic algorithm that can solve for the lowest possible transportation cost. It doesn't exist! If some one tells you it does, RUN!

There are countless weighting and moving factors that can affect transportation costs. There is an algorithm that solves for shortest distances called geometric median. But if you have multiple locations then you you need to solve distances in "K" groups, called K median clustering (unsupervised machine learning). So that's two algorithms... But that only solves for shortest distances within a group of locations.

What about rate differences between lanes and states? Supply and demand is perpetual and so are rates. Shortest distance DOES NOT MEAN LOWEST COSTS! So, you need another method or algorithm to test these costs. And yes the location with the lowest cost could be a very long ways from the shortest distance location. REALLY!

Be aware of this in your analyses. Make sure you ask your advisor how they are computing lowest costs. Especially for LTL and truckload movements!! Total cost minimization cannot be solved by a single or even two algorithms. It requires a combination of methods with the last step requiring a very special optimization algorithm called Grandient Descent. This is a very complex method for finding a minimum of a differentiable multivariate function.

I told you it was going to get nerdy! And that's just transportation, what about inventory, taxation, labor, utilities, real estate and more? ITS NOT EASY. Or, is it?

I'm happy to report The Beacon Group now has a way to do this very efficiently and quickly! Anyone out there curious how we do it?