Have you seen the movie Looper? It stars Bruce “Won’t Retire” Willis, that Angels in the Outfield kid, and Emily Blunt. The movie involves low-life assassins who are contracted to kill victims sent to them from the future using illegal time travel. The killer will blow the target away, then collect the gold bars that were strapped to their bodies as payment.
Where are we going with this? Let us explain.
The killers are told the precise date and time to show up at an exact set of coordinates so that moments later their blindfolded victims appear out of thin air in front of them. They fire their “blunderbuss” hand cannon and it is all over.
This is how those of us at Quantified Freight think that pairing up trucks with loads should operate in the very near future.
Load boards of some form will always be needed for shipment level details and tracking of transactions — but by nature, they are reactive. For the supply chain networks of the world to hit the next level and get more efficient, they need to better use data to forecast and become proactive. There’s currently no forecasting and predicting to where the next load will pop in on the map so that a driver could have already been moving into position. This would result in the shipper having less down time so their product gets moving more rapidly.
Think about it. Yes the economy ebbs and flows. Consumer buying goes up and down. There are plenty of variables to consider. However — for the most part — in relation to the geography of manufacturing regions, population distribution and trade routes — these factors do not really change.
There are millions of data points going back decades and decades, within the trucking industry.
What if supply chains could leverage the power of this data to make things more efficient and reduce wait times. Many truckers will already be doing this in their head as they all experience successes and failures with filling their trailers in various parts of the country. It is only human nature to store that information and use it to influence your decision next time. Let’s consolidate and harness all of that knowledge and make it accessible to everyone.
Say you drop a load and want to get a good idea of where you’ll be headed next. You pull up an app on your phone that shows in real time the probability of load counts by zip code including what they’ll weigh, where they will be going, and even what type of freight is involved. The sooner you check before wanting to make pick-up, the higher the percentage will be and more accurate the forecasting will become.
Wouldn’t that be great? If we can effectively predict weather, financial markets, business cycles and so much more — we can definitely predict the flow of goods around the country. Those factories, warehouses and retailers ain’t moving around. The next step is doing this on a micro level, as macro is much easier as there’s less to be accountable for when you are wrong.