Big Data Analytics and
Supply Chain Logistics Coming Together
With the help of data analytics, the data generated
from Supply chain can be used to generate real insights. Applying data analytics
techniques such as Artificial Intelligence, could shape the way Supply Chains
are identified and handled.
Now, what restrains us from fully utilising data
analytics in Supply chain ?
· Shortage
of capabilities: The Supply chain managers lack experience with the data
analysis tools and hence miss out on the opportunities that Supply chain
analytics holds.
· There
is a deficiency of structured processes that could discover, comprehend and
grasping opportunities in their respective supply chain.
Why is Supply Chain Analytics gaining importance?
· Better
understanding of risks: With the available data, Supply chain analytics is able
to predict the future and any potential risks by spotting patterns or trends in
the Supply chain field.
· Improving
precision in planning: By analysing the
customer data, Supply chain analytics will help in forecasting the future
demand by evaluating the customer needs.
· Prepared
for the future: It can help to improve
the decision making skills of the organisation by developing patterns from the
data of different data sources and thus minimising the risks associated with
it.
For
eg: , IBM became one of the first to join a Cognitive Supply Chain
How Supply chain analytics can be used in different areas
of Supply chain?
· Sales
Inventory and Operations Planning
Planning being one of the major process
under Supply chain can be made to
consider the various data sources making it more aligned with the real time
demand and supply. By using the data from Point of sale , Inventory data, production
volume etc, a company could identify the mismatch in supply and demand, based
on which there is a realignment of activities.
Example: IBM had developed links between production planning and weather forecasting for bakeries. By
integrating temperature and Sunshine data , baking companies can forecast the
demand for various products and well as customer preferences.
· Manufacturing
Analytics plays a major role in
improving manufacturing by evaluating the various manufacturing parameters to
identify the root cause of defects. The Internet of Things along with its wide
set of sensors and cameras opens door to many manufacturing opportunities that
can be used in the future.
Example: From the information of
machine’s condition could trigger 3D- printed spare part which is taken by a drone
to engineer who may be using augmented reality
glasses for guidance in replacing the part.
As more and more technologies are being developed in
Supply chain analytics , companies may be looking ahead at an explosion of
benefits. With more advancements in Supply chain analytics , it is leading to
an era of Supply chain optimisation.
Future of Supply chain: https://youtu.be/W-zdoZf57vI
The introduction of analytics has really helped in the bringing the vastness of supply chains right in front of their eyes using data. A lot of developments are being made by many companies to make the supply chain as seamless as possible with automation to reduce inefficiencies in the supply chain
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