Over the last few years there has been a great
deal of interest and development in the area of artificial intelligence (AI)
and the potential to improve the supply chain and logistics. There is an immense amount of data available
across the supply chain from a combination of Internet of Things (IoT) devices
connected directly to supply chain partners and the partners across the supply
chain network. In addition to the data
produced internally in the organization supply chain actions, there is now an
immense amount of data available from external customers to the supply chain network
partners via direct interaction within the supply chain network through partner
portals and direct interactions integration points with supply chain external
customers. The Internet and online
interactions from eCommerce (B2B and B2C) provide this data. Supply chain partners would be foolish not to
use this data to improve their logistics capabilities.
The challenge for the supply chain network has
been two fold;
-
How to utilize the data
-
What data to collect for both
analysis and use
Artificial intelligence starts with the
collection of data for analysis and this is an important starting point. There is no way early on in the collection of
data to determine what will be important.
This is because the analysis must be performed first to understand the
potential use and value of the collected data.
The intelligence part of the analysis also requires a great deal of
information in order to validate the hypothesis and then to determine direction
based on this intelligence. Starting
with the data you can see why it is so important to collect everything because
the intelligence part of the equation will generally require additional data
from the same periods to confirm and validate direction.
It is important to collect all data then
because you cannot tell what may be important for the analysis when determining
direction. The good news here though is
that storage is cheap and the technology to analyze vast amounts of data has
been improved through game-changing improvements in technology. These two points have probably done more for
the growth and development of artificial intelligence than any other
developments over the last few years.
These improvements in technology allow the supply chain to refine and
redirect logistics activities and practices based on facts and data rather than
hunches and hopes. Combine these two
technologies with the growth of the Internet of Things capabilities and
technologies and the potential for improvements is almost overwhelming.
These capabilities bring improvements and
opportunities in automation including warehouse location and slotting, drones
and robotics to improve efficiencies and reduce costs. These are not the only
areas of improvement to the achieved through artificial intelligence. There will be improvements in volumes,
inbound and outbound forecasts for instance, that will bring dramatic change to
the supply chain as manufacturers and transportation providers revise their
processes to incorporate the analytics into their plans and procedures. The warehouse operation though will also be
dramatically impacted as artificial intelligence brings analytics to the
equation that allows the operation to understand and immediately adjust labor
forecasts to changes in the operation during the date based on near real time
events. Artificial intelligence is just
another force bringing transformation to the supply chain and the supply chain
must start with a baseline of continuous improvements in the flexibility and
continuous change practices in order to meet the transformations.
Tom Brouillette
Contact: tom.brouillette.@gmail.com
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Tom Brouillette discusses supply chain
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