What are the use cases of artificial intelligence in supply chain?
With Artificial Intelligence (AI) being the future of the supply chain, businesses have commenced to apply AI for automating tasks and creating value. This is the primary reason why AI has a wide range of use cases in the supply chain and logistics industry. Thus, with its powerful technology, AI in supply chain can help companies make better decisions, reduce cost, and streamline their operations.
Therefore, let us take a look at some of the top use cases of AI in the supply chain.
What is AI in Supply Chain?
AI in supply chain is a wide-ranging term representing several distinct technologies and algorithms that are utilized to enhance operations and boost efficiency. Considering the ongoing global supply chain challenges, AI is set to be an important part of the future of supply chain management.
From automation to predicting demand and supply trends to preparing the product supply and improving customer experience- AI is revolutionising the supply chain and logistics sector.
Why do businesses are focusing on implementing AI in the supply chain?
Supply chain businesses are going through traditional and emerging challenges. AI is capable of resolving many of them. Here are the top challenges of current supply chain network-
- Reduce transportation cost: Post Covid-19, the transportation cost is extremely high which has pushed many supply chain network to rethink their strategy and optimise the end to end network
- Keeping up with customer/industry demands: Ever growing competition in the market, new industry regulations and customer expectations have put the supply chain network on the backfoot. Businesses are looking for a reliable solution which can help them to overcome the hurdle.
- On-time pickup and hassle-free delivery: Speed is an integral metric for any supply chain network success. Incompetent couriers, unorganised system and poor planning often cripple a supply chain network. Supreme technology like Ai can provide a handful of data to help minimise the mistake and improve the planning for the entire supply chain network.
- Quick and effective decision making: One of the biggest challenges in logistics is that it’s a highly data-driven industry and requires supreme technology to make the right and quick decisions. Over the years, logistics businesses have been looking for a solution that can obtain, and analyse this large volume of data, to make better decisions.
- Accurate forecasting to minimise mistakes: Understanding the product demands earlier and keeping everything streamlined is a great edge for logistics businesses. With AI’s supreme technology, businesses can assess the historical data and predict better.
What are the best use cases of AI in the Supply Chain?
From healthcare to retail, AI is changing the way businesses operate. AI has offered a gamut of revolutionary use-cases in the supply chain network. Here are the top 7 use cases in the supply chain.
1.Understanding the future demand and providing better forecasting:
A supply chain network functions better when they are able to forecast the future demand of the product. There are a lot of factors which determine and disrupt the product demand. A surge in customer expectation, customer expectations, price, suppliers and other miscellaneous reasons. With AI, the supply chain network can carefully assess the past data and ongoing trends to predict future demand and keep things in place.
2.Better planning of inventories:
Managing inventories is a huge task for large scale businesses and supply chain networks. Both under-stocking and overstocking can hurt the business and overall flow of product.
With the power of AI, businesses finally tackle this massive challenge. They can build smart warehouses to manage the inventories and leverage the fully automated facilities which will minimise the human error, and take care of tedious jobs like collecting data, sorting and processing goods.
With the introduction of AI in the supply chain, businesses can not only manage their inventories and thereby strike the right balance in warehouse management and shorten lead time.
3.Real-time tracking:
Supply chain networks can make the best use of AI’s real time data to track their products and understand how much product is left in transit. They can also use this information to inform customers when their orders are about to be shipped out or delivered on time so they can plan accordingly with their vendors or retailers.
4.Data mining:
Most of the businesses are moving towards a data drive approach to reduce error and plan better. Supply chain networks too can use AI to mine large amounts of data from across their entire network and stakeholders in order to make predictions about future steps and plan everything better.
5.Optimize routing:
AI can automatically detect and optimise the best route for a shipment based on the destination location, temperature, humidity, rain or snow and other factors. AI can also identify bottlenecks and ensure that each shipment arrives at its destination within an optimal time frame.
6.Planning production:
AI can help manufacturers plan their production processes by identifying potential issues before they occur so that they can be fixed before they cause delays. This allows companies to increase efficiency while decreasing costs by preventing issues from arising during production, which would otherwise require corrective action such as overtime pay or decreased efficiency, which would lead to higher costs down the line.
7.Effortlessly automating back-office operations:
Running a supply chain and logistics company is a big responsibility. Businesses have to hire a large pool of individuals to manage a variety of manual jobs. From order fulfilment. product cataloguing to defect inspection and quality control.
With the power of AI, businesses can automate all the above tasks, replace manual labour with supreme technology, minimise human error possibilities and make the end-to-end operation faster and better.
What are the benefits of using AI in the supply chain?
The above use-cases highlight the supremacy of AI and the future trends in supply chain networks. Using the diverse offerings of AI, businesses can mitigate risks, prepare better and create an excellent customer experience. Here are the top advantages of using AI in supply chain business-
Take better decisions to improve logistics: AI can help optimise the supply chain by identifying and eliminating inefficiencies. It can also help identify areas where there may be more demand for a product, which could lead to increased sales.
Improve customer service and offer excellent customer experience: AI can improve customer service by identifying customers with similar profiles and offering them similar products or services at a discount if they choose to buy from your company. It can also forecast the trends, customer preferences to help companies showcase the right product to the right customer group.
Take better marketing and sales decisions: AI can provide valuable insights into how customers interact with your business allowing you to create more effective marketing campaigns and sales initiatives that meet their needs better than before. This will result in higher conversion rates and better engagement levels with current customers as well as new ones that you may attract through these efforts.
What is the future scope of AI in the supply chain?
AI has certainly brought some major disruptions in the supply chain network. Businesses have to be careful and strategic in their implementations. There is no dearth of potential when it comes to AI technology. But companies can relish the fruits only when they understand the true potential of AI and use it systematically to resolve the right challenges. However, observing the ongoing trends, it is safe to declare that AI is going to be highly instrumental in offering two major advantages in near future-
- Automation: AI can be used to help companies automate previously manual processes, like inventory management and routing.
- Predictive analytics: AI can be used to analyse data in real-time, giving businesses a better idea of product trends, supply demands gap, better location, and route planning.
Final thoughts
Over the years, the supply chain and logistics industry has faced myriad challenges in streamlining operations, providing excellent customer service, and scaling up businesses.
AI has the potential to lead the industry in a new direction for a better outcome. In conclusion, it is evident that in future years, businesses will lean on AI to resolve increasing demand for efficiency at every stage of the production process and deliver products faster to the doorstep of thousands of customers.
