Businesses need to consider their supply chain management’s future and the opportunities that Artificial Intelligence provides in this arena. They also have the responsibility of incorporating innovation into product design, creation, and delivering the same to customers, efficiently, by integrating Artificial Intelligence in supply chain management system.
Artificial Intelligence helps businesses by automating, augmenting, and enhancing customer experience and decision-making processes. Thus improving productivity in the supply chain management space creating a better product of higher value for companies to operate.
Supply Chain Management
Supply chain management (SCM) includes logistics, inventory management, and storage. These are the visible elements of SCM, as they involve the transportation of materials as well as warehousing them for future use. Supply chain management allows companies and divisions to coordinate their long-term plans, control the daily flow of suppliers’ materials up and down the supply chain.
Artificial Intelligence
Artificial intelligence enables machines the ability to learn and perform actions based on experience or data inserted into their system rather than being process-oriented as for humans.
As introduced and classified by Gartner analyst, Noha Tahomy, Artificial Intelligence is categorized as follows:
- Augmentation – Artificial intelligence(AI) which assists humans with their day-to-day tasks such as virtual assistants, data analysis, and software solutions, is becoming more popular. Such AI reduces human bias errors providing solutions for problems.
- Automation – Artificial Intelligence machines that work autonomously without any human intervention; like robots performing key process steps in manufacturing plants, come under this category.
The application of Artificial Intelligence in Supply Chain Management related-tasks holds high potential for boosting both, top-line and bottom-line value of an organization.
Artificial Intelligence In Supply Chain Management
Artificial Intelligence is changing the face of the supply chain management industry by identifying and eliminating deep-rooted inefficiencies and uncertainties. It drives visibility into all aspects of the supply chain with methodologies that humans are incapable to emulate at scale.
AI transforms complex supply chain management processes for companies making them more efficient, freeing up time spent on mundane tasks so they can engage in strategic actions.
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Here are six ways, where Artificial Intelligence can assist various Supply chain management functions of a company:
1. Artificial Intelligence In Operational Procurement
Streamlining procurement-related tasks through the automation and augmentation of Chabot’s capability requires access to robust, intelligent data sets that will be available as a frame or reference point for robots. A chatbot can be used for daily tasks too, like:
- Speaking with suppliers during trivial conversations
- Placing purchasing requests
- Setting and sending compliance materials when necessary
- Receiving invoices and payments from vendors alongside filing various documents
- Research and answer internal questions regarding procurement functionalities
2. Machine Learning For Supply Chain Planning
Supply chain planning has been a crucial activity in the world of business, but it is even more important today because companies need concrete plans to stay competitive. With powerful work tools and intelligent technology for building these plans, you can be sure your company will have an advantage over other businesses. The machine-learning algorithm could revolutionize how we plan inventory demands with its ability to predict future needs before they happen or what types of goods may sell well based on customers’ preferences. Machine learning can revolutionize supply chain planning agility and optimization.
Supply chain management professionals have the power to create optimized scenarios for the optimal delivery of goods based on big data sets. With machine learning technology, they can set parameters to ensure success, reducing human input or intervention.
3. Machine Learning For Warehouse Management
The success of any company’s supply chain relies on how well they manage their inventory. As demand for goods continues to increase, so does the importance of supply chain planning. It is important to ensure there are enough products and inventory available at all times. A forecasting engine with machine learning just keeps looking ahead using different algorithms depending upon whether you want more detailed information regarding day-to-day sales trends, thus optimizing the warehouse management system.
Machine Learning has revolutionized the way companies store their inventory. With self-adaptive forecasting, warehouses can plan for future needs and stay ahead of the ever-changing market trends, providing an endless loop that is constantly updating and upgrading itself with smarter information every day.
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4. Autonomous Vehicles For Logistics And Shipping
The rise of artificial intelligence in logistics and shipping is no secret. It has become a focal point for attention within supply chain management, as it helps reduce lead times with faster transportation that reduces costs while also being environmentally friendly efforts to make these operations more efficient which impacts both labor rates among other things; if autonomous vehicles were developed at their potential that certain business analysts have hypothesized about, the impact on logistics optimization would be astronomical.
5. NLP For Data Cleansing And Building Data Robustness
Natural Language Processing(NLP) is an Artificial Intelligence and machine learning technology that bridges the language barrier between countries. NPL can be used to build large sets of data on suppliers with little information because of their lack of literacy rates. The potential benefits from this development include streamlining auditing procedures due to increased accessibility through easily decipherable datasets; also, it may even allow companies to access unceasingly renewable energy sources.
6. Ease Of Supplier Selection And SRM
With more and more companies being forced to consider supply chain sustainability, CSR, or even just basic ethics as they do their business; supplier selection has become a critical aspect. Risk management is key for ensuring that you don’t make any costly mistakes. But what if there was always someone on hand who knew how best to protect yourself throughout every interaction with these suppliers?
The future of supplier selection is now more intelligent than ever. Supplier data gathering has become a tool for success, with Machine Learning and intelligible algorithms to create an active process that will help the company make informed decisions about who they work closely with from day one – all while being easily accessible by humans.
Benefits And Challenges Of AI In SCM
| Benefits | Challenges |
| Informed decision making | Wrong problem |
| Increased efficiency | Wrong calculations for ROI of AI |
| Customer satisfaction | Lack of data |
| Scaling organization | Organizational changes |
When it comes to adoption of Artificial Intelligence in supply chain management, the question is no longer ‘why?’ but rather ‘when’ and ‘how’. As technology improves, data point numbers increase and business needs change, there is no telling what companies can accomplish with this exciting new tool.
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