It has long been possible to build a geofence and detect when an inbound carrier was 20 miles out from a warehouse. But warehouse managers, and transportation planners are busy. What good would those notifications do? These managers and planners don’t have time to look at every carrier notification and examine whether that truck will hit their dock on schedule.
But technology is continuing to advance. I think this kind of event data will become increasingly actionable, because the ability to use it will become increasingly automated.
Supply chain planning applications have long been in-memory applications. This is a fancy way of saying that these applications were based on technologies that allowed them to solve very big problems very quickly. But now there is a new generation of in-memory computing. That means the problems we can solve quickly are getting bigger and bigger.
JDA is an example of one supply chain software firm looking to utilize the new generation of in-memory computing to build larger supply chain models spanning planning and execution. Today a company with advanced logistics capabilities would have a warehouse management system (WMS), a dock scheduling and yard management solution, and a transportation management system (TMS) in order to improve their logistics capabilities. Both WMS and TMS have good business cases associated with them. But these applications are laser focused on their own domains. WMS allows for more accurate and better fulfillment throughput; TMS allows a company to reduce their freight spend. The WMS does not understand the constraints associated with transportation, and the TMS does not understand the warehouse’s constraints. This means cross application optimization opportunities are lost.
JDA is beginning to build JDA Intelligent Fulfillment, a set of logistics planning and execution solutions that understand constraints that cross warehousing, the yard, and transportation. In early versions of this solution, improved supply chain visibility will allow for better iterative planning. But in a longer time frame, JDA wants to build broader, dynamic applications that understand constraints across warehousing, transportation, inventory management, and order promising to solve problems more holistically and dynamically.
I believe that telematics event management will need to become integral to these more holistic in-memory solutions. Also necessary will be more granular, real time cost analytics embedded into the supply chain applications.
Let me give you an example. Today a TMS will take orders and consolidate those orders so lower cost shipments can be built. Imagine that an outbound truck is only 60 percent full because an inbound shipment has not arrived on time. The shipper really does not like underutilizing the truck, it is costly. The shipper also does not want to disappoint the customer.
Now imagine the inbound shipment with the inventory they need is just 20 miles away from the warehouse and the shipper knows that. Capitalizing on this knowledge would not be easy.
The transportation planner needs to look and see if this is a multi-stop shipment. Will waiting a few hours mean other legs are not delivered on time? How do the cost savings of a fuller truck stack up against hitting a customer’s dock a few hours later than planned? How will the customer feel about a truck that misses the delivery window by two hours? Will there be demurrage or customer penalties?
If the transportation planner decides waiting for the inbound shipment makes sense, the warehouse manager has to scramble. He needs to find an empty dock and reassign workers to unload the inbound shipment. Those workers need to pull just the inventory they need, move it to the outbound dock, and load the outbound truck. There are also costs associated with reassigning work in the warehouse when the warehouse becomes less productive. What are those costs? How do those added warehouse costs compare to the transportation savings?
And whatever decision is made, the customer needs to be notified.
In short, even if a shipper knows an inbound truck with hot inventory is 20 miles out, being able to make the optimal decision and execute to that decision is probably not practical.
With more holistic, location aware, supply chain applications, it may not be too many years before capitalizing on these kinds of dynamic opportunities is not just practical, it is the way business is conducted day in and day out.