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How To Optimize The Supply Chain with AI
Just a few years back, artificial intelligence meant adaptions like Jarvis. Who
would have thought that AI would soon become an application of our daily lives?
Artificial intelligence has the potential to streamline several business processes,
analyze data for insights, and help in building fruitful business strategies. Hence,
globally, it is being used to remediate old processes, invent new methods, and
improve productivity.
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Fortunately, the supply chain is no different than other business departments. This
section of your business can benefit immensely with AI.
Let’s see how.
But, before that, let’s understand what is artificial intelligence.
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Artificial intelligence is a method of imparting intelligence to machines, due to
which machines perform repetitive and action-based tasks just like humans,
sometimes better than humans.
The simplest method to understand artificial intelligence is through Gartner’s AI
categories:
· AI has the power to work in practically any field without human intervention.
This process is called automation of activities, which are effectively performed by
machines without human guidance.
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·AI can augment tasks by performing daily activities, which are augmented or
controlled by humans. These are commonly known as virtual assistants that have
the ability to conclude a set of tasks in a certain manner.
Various businesses across the globe spend 55 hours in manual tasks, 39 hours on
tracking invoices, and 23 hours on responding to inquiries of the supplier. All this
on a weekly basis. AI can streamline and optimize all these tasks, ultimately
reducing the time spent on management.
Here’s how AI can optimize supply chain:
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Operational Procurement
· It can detect and send compliance and regulatory actions to the suppliers.
· It can alert when a new purchase is required.
· It can offer research for internally solving procurement issues.
· It can document and analyze invoices, order requests, and payments.
.
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Supply Chain Planning
Machine learning can analyze demand, supply, and inventory. By synchronizing all
these factors, you can optimize your supply chain decisions. Often a human
analysis of demand can be faulty. However, ML analysis of demand and need for
supply according to inventory is based on data, which reduces errors.
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Warehouse Management
Supply chain planning is intertwined to warehouse management. Under-stocking
and overstocking are both disastrous steps which can severely impact the
organization. Overstocking can waste a lot of your money and under-stocking can
lose you, several customers.
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ML’s data forecasting abilities can allow you to predict the right warehouse
demand. Depending upon the previous years’ trends, market trends, and current
status of the warehouse, ML can predict future demands.
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Shipping and Logistics
Slow and faulty shipping and logistics can plague the whole supply chain. Not
knowing the movement of your goods and losing track of the delivery time can
hamper your reputation.
To avoid that, you can use AI-based tracking of your logistics. It will tell you the
exact position of your goods, which would help you in accelerating the shipment.
You can reduce operational costs, resource utilization, and decrease time to
destination.
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Supplier Relationship Management
AI and ML can together be used to conduct a risk analysis for supplier
management. Using the available data and sources, you can know the risk
involved in collaborating with the supplier. This would help you select a supplier
who can prove most useful to the organization in various circumstances.
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Conclusion
Artificial intelligence can improve a lot of activities related to supply chain
management. Using AI and its related technologies such as ML and NLP would
only help you streamline your day-to-day tasks, reduce operational time, and
decrease cost overheads to a great extent.
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