techwatch
The next big trend:
dynamic optimization
FOR ALL THEIR MANY ADVANTAGES, TRANSPORTATION
management systems (TMS) may be too brittle for today’s flexible
supply chains. This type of software is terrific at determining the low-est-cost carrier to move a shipment between a fixed set of origin and
destination points. But in today’s volatile world, too often those points
are anything but fixed. Because of changing transportation market
conditions—for instance, carrier price increases or capacity issues—a
company might suddenly want to ship product from another factory
in its supply chain network in order to make a timely delivery at the
lowest price.
The solution for companies is to embrace
“dynamic optimization,” according to Brett Cayot,
a global lead for logistics and distribution in the
advisory practice of consulting firm
PricewaterhouseCoopers (PwC). “Take a company
having 10 manufacturing sites in the United
States,” he says. “The decision on what to produce
where is dependent on logistics costs. There’s no
change-over cost for manufacturing.”
Cayot contends that companies need a software
tool that can “view” all the plants in the supply
chain network, take orders in real time, and then
determine the best location to ship from based on
logistics costs. The challenge is that this approach
requires “deck shuffling” on the part of the manu-
facturer. As Cayot notes, if a company decided that it made more
sense from a transportation cost perspective to service Customer A
from Plant 2 instead of Plant 1, then it faces the issue of bumping
Customer B from Plant 2. “That’s a challenging optimization prob-
lem,” he says.
Although TMS solutions are not designed to perform this type of
supply chain optimization, network modeling applications are well
suited to the task. Cayot says at least half a dozen vendors currently
offer applications that can tackle this complex problem.
Up to now, though, network modeling software has used historical
data to make projections on future demand flows. In fact, companies
have often used modeling for strategic assessments of their supply
chain nodes—plants and distribution centers—to determine the
optimal location from a shipping cost perspective. But Cayot says
that if real-time order requests are fed into a network solution, the
software can optimize outbound shipments
to customers by determining plant origins,
or even optimize inbound movements by
choosing the optimal supplier to serve a
plant. “This approach can solve transporta-
tion capacity and throughput issues,” he
asserts.
