The mainstream use of business intelligence tools and data analytics has brought transformative changes to the manufacturing industry. From managing production pipelines and warehouse operations to logistics and supply chain management, we now have software tools to enable automation at every level. Besides, AI-powered applications and machine learning algorithms have paved the way for smart manufacturing and intelligent supply chain management. It involves the use of BI tools, IoT devices, RFIDs, and machines equipped with advanced sensors, powered by AI algorithms.
In this blog post, we shall have our main focus on the essential components of intelligent supply chain management. Read further to learn what these components are and how they help you achieve agile, efficient, and data-intensive supply chain management.
Intelligent supply chain management refers to the use of advanced AI algorithms and the derivatives of artificial intelligence to enhance operational efficiency through improved decision-making. Being an apt example of what the fourth industrial revolution brought to enterprises, we often call it supply chain 4.0. Apart from artificial intelligence, the intelligent supply chain incorporates several next-gen technologies like IoT, cloud, big data, and software robotics.
The main idea here is to gain better visibility into data and capitalize on the available data resources to enhance supply chain productivity. Here, we also use a number of BI tools, data visualization techniques, predictive analytics, and ETL methodologies that ultimately contribute to a more advanced and efficient supply chain.
As we already discussed, intelligent supply chain management represents a better and improved version of the supply chain by virtue of the next-gen technologies. Therefore, to establish an intelligent supply chain, you must equip your software systems (ERPs) with the following technologies.
The internet of things happens to be the core component of an intelligent supply chain network. It plays a crucial role in enabling automation at different levels by facilitating seamless machine-to-machine communication. Manufacturing and eCommerce companies usually have an extensive network of connected devices to efficiently run their routine business processes. The use of IoT devices is conducive to increasing supply chain visibility and automating complex, repetitive tasks. As a matter of fact, we now also have intelligent internet of things (IIoT) to improve the quality of supply chain operations. IIoT processes the data in line with AI and machine learning algorithms to generate actionable insights, leading to agile operations and higher productivity.
As we know, business intelligence is one of the most crucial aspects of intelligent supply chain management. We use a number of BI tools to extract maximum value from data pertaining to different SCM activities. With their main focus on big data analytics, BI tools help you gain valuable insights into business data using effective data visualization techniques. Besides, the use of predictive analytics can reveal useful information about a product and the potential response of customers. In more simple terms, it may predict future events with sheer accuracy, leading to improved decision-making. Accordingly, enterprises can optimize their marketing strategies to create maximum impact and channelize sales growth.
Machine learning is a derivative of artificial intelligence that renders self-learning capabilities to computer-based systems with a focus on continuous improvement algorithms. The ML algorithms self-optimize different stages of the supply chain based on the data generated by AI-powered software systems. As such, it significantly reduces the scope of errors due to manual handling of the supply chain activities and offers higher operational efficiency by automating repetitive tasks.
Robotic process automation or software robotics has gained traction worldwide owing to its transformative features that are poised to disrupt the manufacturing value chain. RPA is a software technology that incorporates AI algorithms and metaphorical software bots to automate complex business processes. As opposed to machine learning, it mainly focuses on automating labor-intensive manufacturing processes and supply chain activities. The RPA bots can replace human workers to handle repetitive tasks while offering improved performance and faster task execution. At the same time, it reduces the capital expenditure, overhead costs and brings significant cost-savings to the organization.
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Here, we have discussed the most crucial components of an intelligent supply chain that mainly focus on capitalizing on your organization’s data resources. All things considered, the intelligent supply chain would facilitate improved decision-making for every situation that you may come across. As such, it helps you efficiently run routine supply chain activities and brings a multifold increase in the overall SCM productivity. At the same time, it self-optimizes and quickly reacts to the changing customer needs and market trends.
We are an ERP development company that provides custom enterprise solutions to address the diverse business needs of our customers. At Oodles, we provide end-to-end supply chain software development services to accelerate the order fulfillment cycle and boost productivity. Our development team is skilled at implementing BI tools and Industry 4.0 technologies to strengthen and streamline SCM activities with improved decision-making. Besides, we use open-source software platforms like Odoo, ERPNext, and OFBiz to build scalable business applications at cost-effective rates. To learn more about our supply chain software development services, drop us a line at [email protected].