Why Learned Behavior Models Trump Supply Chain Visibility on the Value Scale
[vc_row][vc_column width=”2/3″][vc_custom_heading text=”Supply chain professionals readily recognize the value of real-time visibility, but most do not understand the implications—or value—of behavior models.” font_container=”tag:h3|text_align:left” use_theme_fonts=”yes”][vc_column_text]Pings from IoT devices such as sensors, satellites, radar, smartphones, meters, control devices, etc., provide organizations with a near real-time picture of conveyances in motion, WIP in manufacturing, inventory in warehouses and finished goods heading to customers, but those pings are still just snapshots in time.
While it’s helpful to know exactly where on the Pacific Ocean inbound parts are from Asia, it’s far more valuable to know when they will arrive at the port of destination, or better yet, when the container will be offloaded from the vessel, clear customs and be available for pick up. Armed with that knowledge, days in advance, a supply chain professional can schedule a dray carrier to pick up the container right on time, rather than having it sit at the port for days, racking up demurrage charges, unaware that it has arrived.[/vc_column_text][vc_row_inner][vc_column_inner width=”1/3″][vc_single_image image=”2083″ img_size=”full”][/vc_column_inner][vc_column_inner width=”2/3″][vc_custom_heading text=”Download this education series now to understand how learned behavior models drive predictive insights within a digital supply chain” font_container=”tag:h3|text_align:left” use_theme_fonts=”yes”][vc_column_text]
What is a learned behavior model and how is it created?
What are examples of learned behavior models and what kinds of supply chain predictions do they inform?
Why are learned behavior models more powerful than real-time visibility?