Improving Logistics Using Data Analytics
The movement of goods to and from company assembly plants, warehouses,
distribution points and retail outlets was historically treated as a
cost center and, in the more general sense, one of the 'costs of doing
business.' The Japanese changed this perception with the exportation to the
U.S. of the concept of Just-in-Time (JIT) manufacturing. With the success of
Japan's electronics industry, JIT methodologies were widely accepted in
North America in the 1980's, and to achieve the goals of JIT consigners of
parts shipments began assigning and measuring gate-in and gate-out times for
shippers.
Using the Data You Already Have
Today, an increasing number of shipping and freight
companies rely on the use of on-board GPS systems for managing their fleets
in real time. The ability of freight to be re-routed after leaving the
terminal and the practice of capturing variances in delivery quantities
against orders at the time of delivery has streamlined the logistics process
and shortened the receivables cycle. Companies that are improving logistics
using data analytics are continuously analyzing collected information on
gate-in/out times, route optimization and exception reports to eliminate
inefficiencies in their shipping operations. Because of the spatial component in all
logistics transactions, data mapping and visualization tools can assist decision makers
in further refining this essential business area, leading to improved
operational control, cost containment and service quality.
 P
|
|
