ARTIFICIAL
INTELLIGENCE
&
SUPPLY CHAIN MANAGEMENT
Group 8
Siddharth Nanda
Srishti Arya
Shubham Kumar
Shubham Raj
Tanuj chaudhry
01
Introduction
What is artificial Intelligence ?
What is Artificial Intelligence ?
Artificial Intelligence is a method of making a computer, a
computer-controlled robot, or a software think intelligently
like the human mind. AI is accomplished by studying the
patterns of the human brain and by analyzing the cognitive
process. The outcome of these studies develops intelligent
software and systems.
Maximizing productivity by lowering uncertainty is the top
priority across sectors in today's connected digital world. In
addition, rising operational efficiency and supersonic speed
demands highlight the necessity to take advantage of
artificial intelligence's (AI) strength in supply chains and
logistics.
02
Role of AI in supply
chain
Business Advantage
Accurate Inventory Management
The proper flow of goods into and out of a warehouse can be ensured
by accurate inventory management.
It can aid in preventing excessive stocking, insufficient stocking, and
unanticipated stock-outs.
The process of inventory management involves numerous inventoryrelated factors (order processing, picking, and packing), which can
make it time-consuming and highly error-prone.
Tools for supply chain planning that are AI-driven and can manage
large amounts of data can be quite useful in this situation.
Large datasets may be promptly analysed and interpreted by these
intelligent systems, providing prompt advice on supply and demand
predictions.
Warehouse Efficiency
A productive warehouse is crucial
to the supply chain. AI-based
automation can help with the
prompt warehouse retrieval of an
item and guarantee a smooth
delivery
to
the
consumer.
Additionally, AI systems can
expeditiously
and
accurately
resolve a number of warehouserelated problems, as well as
streamline complex processes
and speed up labour.
Enhanced Safety
Intelligent planning and effective
warehouse management can be
made
possible
by
AI-based
automated technologies, which can
improve worker and material safety.
Data on workplace safety can be
analysed by AI, which can then
alert producers to any potential
concerns.This enables businesses
to respond quickly and forcefully to
maintain the safety and security
standards in warehouses..
Reduced Operation Cost
Intelligent planning and effective
warehouse management can be
made
possible
by
AI-based
automated technologies, which can
improve worker and material safety.
Data on workplace safety can be
analysed by AI, which can then alert
producers
to
any
potential
concerns.This enables businesses to
respond quickly and forcefully to
maintain the safety and security
standards in warehouses.
On-Time Delivery
As we previously noted, AI systems
assist in reducing reliance on manual
efforts, resulting in a faster, safer, and
smarter overall process. This makes it
easier to fulfil the promise of prompt
delivery to the consumer. Traditional
warehouse processes are accelerated
by automated technologies, which also
reduce the work required to remove
operational bottlenecks in the value
chain and meet delivery targets.
03
Challenges Faced
by AI
4 key Challenges
Challenges of AI in Supply Chain
System complexities
Usually cloud-based, AI systems demand a lot of bandwidth.
The cost of this AI-specific hardware can end up being a
significant initial expenditure for many supply chain partners
because operators occasionally need specialised hardware to
access these AI capabilities.
Lack of trust in technologies
Artificial intelligence is still a relatively young technology, it
continues to attract investment from industry innovators.When
implementing new systems, such as in warehouses, real
people with years of experience may be replaced by computer
systems that don't appear to have the same skill set.
Data Restrictions
I needs a significant amount of accurate data to function properly,
but both the quality and quantity of information are lacking in many
firms. Machine learning requires high-quality data in order to train
algorithms and prediction models.
Before implementing AI in the supply chain, data limitations should
be eliminated to make it more available and incorporate as much
'real-time' data as possible into systems and processes.
Operations Cost
Most firms may encounter difficulty in implementing AI into supply
chain due to the associated costs. Although the operating costs can
be high, so can the initial upfront expenditures of investing in and
integrating the technology. AI is intended to facilitate human
employment by automating repetitive processes or facilitating
improved decision-making.
03
Tools of AI
Popular in Supply chain
Tools of AI
Predictive Analytics:
Predictive analytics can be used to analyze historical data and
forecast future demand patterns, inventory levels, and supply chain
disruptions.
Machine Learning:
Machine learning algorithms can be trained on large datasets to
make accurate predictions and optimize supply chain operations.
Natural Language Processing (NLP):
NLP can be used to analyze unstructured data such as customer
reviews, social media posts, and emails to identify emerging trends
and customer preferences.
.
Tools of AI
Blockchain:
Blockchain technology can be used to improve supply chain
transparency and traceability by providing a secure and
decentralized ledger of transactions.
Robotics Process Automation (RPA):
RPA can be used to automate repetitive and time-consuming tasks
such as order processing, invoicing, and inventory management.
Autonomous Vehicles:
Autonomous vehicles such as drones and self-driving trucks can
be used to improve delivery times, reduce transportation costs,
and increase efficiency.
04
Case Study
NYKAA
NYKAA
Objective
Nykaa, a fashion and beauty retail brand, is a
popular online beauty and health destination. With
over 32,000 staff hours spent each month
addressing and responding to support concerns,
the organisation always provides a great customer
and purchasing experience.
It faced a hurdle because customers increasingly
preferred self-service over communicating with
representatives.
As a result, Nykaa chose to automate its customer
service in order to devote more time to other parts
of the customer experience.
Approach
Nykaa teamed with Verloop.io to boost
consumer engagement through chat support. It
built a solution that allowed Nykaa to manage
recurring requests such as cancellations,
returns, shipping enquiries, replacements,
refunds, and payment issues using bot-qualified
questions.
Nykaa was able to swap software systems
smoothly because of the AI's wide range of
integration options.
The purpose of using AI and machine learning
tools was to comprehend user intent and reply
to queries in a tailored manner.
Impact
Nykaa has been able to respond to client
inquiries with greater context after integrating
Verloop.io, which has increased postpurchase customer happiness and
strengthened customer loyalty.
Nykaa managed almost 1.6 million different
talks in the first 30 days. ‘
The necessity to manually assign
conversations was removed when a client
clicked to send the conversation to one of
Nykaa's own specialists, who would then
handpick products depending on the
customer's needs.
Bibliography
https://dataconomy.com/blog/2023/01/23/artificialintelligence-supply-chain/#google_vignette
https://indiaai.gov.in/article/indian-retail-brands-using-ai-5case-studies
https://throughput.world/blog/ai-in-supply-chain-and-logistics/
https://www.logisticsit.com/articles/2022/09/28/four-aichallenges-businesses-face-in-the-supply-chain
Thank You