AI in Supply chain Management: An Overview
Next-day and same-day delivery services provided by leading e-commerce and logistics businesses have raised customer expectations. With the increase in demand, the entire supply chain is rapidly evolving from having a functional orientation to a global network of processes. Several businesses are now transforming their supply chains by integrating cutting edge technologies like artificial intelligence (AI), Blockchain and Machine learning to fulfill modern customer demands. Read this blog post to discover the benefits of using AI in supply chain management.
According to market research firm IDC, by 2020, 50% of supply chains will use AI and advanced analytics for planning. It also predicts that companies will eliminate sole reliance on short-term demand forecasts.
Artificial Intelligence has an essential role to play in modern supply chain optimization. For instance, in warehousing goods, AI and location intelligence enable retailers to maintain a competitive edge for supply chain operations and product delivery. Retailers can also use AI to predict which products are more cost-efficient to stock in a warehouse based on its proximity to certain areas. The demographics and behavioral information in that location determine what will be stocked. Retailers can also change this information depending on shifts in behavior or other external factors.
To Read More: Transforming Supply Chain and Logistics with Blockchain
How Businesses are Using AI to Improve their Supply Chain Process
The main aim of integrating AI in the supply chain is to create a fully automated and self-adjusted decision-making system. AI-powered supply chain management enables businesses to accurately predict demand spikes and adjust the routes and volumes of material flows.
For instance, AI can be used to gather comprehensive data (weather patterns, GPS information and reroutes) that may affect delivery times. The collected data enables the sales team to predict more accurate delivery times. It immediately notifies the users of real-time inventory adjustments. As a result, businesses can provide better customer service to current and potential customers.
AI Applications within Supply Chain Activities
Machine Learning for Supply Chain Planning
Supply chain planning is an essential component of SCM. Machine learning (ML) applied within supply chain planning enables businesses to forecast inventory, demand, and supply. ML can revolutionize the agility and optimization of supply chain decision making.
By utilizing ML technology, supply chain professionals can provide the best possible scenarios with machine-to-machine analysis and intelligent algorithms of big data sets. ML in the supply chain enables retailers to optimize the delivery of goods while balancing supply and demand.
Chatbots in Operational Procurement
Chatbots can provide several benefits to businesses including reduced costs of transactions and sales cycle time. Chatbots can streamline procurement related tasks through the automation and augmentation process.
How chatbots can be utilized in the supply chain:
* Chat with suppliers about most common queries
* Research and answer internal questions regarding procurement functionalities
* Send actions to suppliers regarding governance and compliance materials
* Documentation of invoices and payment requests
Natural Language Processing (NLP) in Supply Chain:
NLP is a combination of AI and ML which enables humans to interact with machines and data through text/voice-based natural conversations. It can be used in several ways for the supply chain. NLP can eliminate administrative overhead in managing the supply chain.
NLP has abundant potential to decipher large amounts of foreign language data in a streamlined manner. NLP has the potential to build data sets regarding suppliers and decipher untapped information due to the language barrier. From a sustainability and governance perspective, NLP technology can streamline auditing and compliance actions that were previously not possible because of existing language barriers between buyers and suppliers.
Machine Learning for Warehouse Management:
The success of supply chain planning depends on proper warehouse and inventory based management. For any consumer-based company, supply flaws (overstock or understock) can be a grave problem. A forecasting engine with ML enables retailers to view the combinations of algorithms and data streams to have the most predictive power for different forecasting hierarchies.
According to Mckinsey global survey (November 2018), supply chain management is among the top three industries that will benefit most from the adoption of AI. Reinventing supply chain with AI enables businesses to transform customer experience while unlocking capital to drive growth. AI in supply chain management enables business managers to analyze and track data, detect anomalies and generate predictions to improve supply chain operations. Additionally, artificial intelligence can enable exceptional agility and precision in supply chains.
At Oodles ERP, we have experience in providing end-to-end customized supply chain development services to businesses. Our team integrates AI in supply chain systems while catering to specific business requirements. With our AI application development services, businesses can gain a high level of accuracy and improve the customer experience.