Supply Chain Digitalization
Expert-defined terms from the Advanced Certificate in Digital Twins in Supply Chain course at London School of Business and Administration. Free to read, free to share, paired with a professional course.
Advanced Analytics refers to the use of data mining, predictive mo… #
Related terms include business intelligence, data science, and statistics. Advanced analytics is used in supply chain digitalization to forecast demand, optimize inventory levels, and identify potential disruptions. For example, a company can use advanced analytics to analyze historical sales data and weather patterns to predict demand for a particular product and adjust its production and shipping schedules accordingly.
Application Programming Interface (API) is a set of rules and protocol… #
Related terms include data exchange, integration, and interoperability. APIs are used in supply chain digitalization to connect different systems and applications, such as transportation management systems and warehouse management systems, and to enable the exchange of data between them. For example, a company can use an API to connect its transportation management system with its warehouse management system, allowing it to automatically update shipment status and inventory levels.
Artificial Intelligence (AI) refers to the use of machine learning and <i… #
Related terms include machine learning, deep learning, and cognitive computing. AI is used in supply chain digitalization to analyze complex data sets, optimize business processes, and make informed decisions. For example, a company can use AI to analyze sensor data from its production equipment to predict when maintenance is required, reducing downtime and improving overall efficiency.
Big Data refers to the large amounts of structured and unstructured</i… #
Related terms include data analytics, data mining, and business intelligence. Big data is used in supply chain digitalization to gain insights into supply chain operations, identify trends and patterns, and make informed decisions. For example, a company can use big data to analyze data from its sensors, GPS trackers, and other devices to optimize its logistics and transportation operations.
Blockchain is a distributed ledger technology that allows multiple partie… #
Related terms include distributed ledger technology, cryptocurrency, and smart contracts. Blockchain is used in supply chain digitalization to enable secure and transparent tracking of goods, verification of authenticity, and automation of payments. For example, a company can use blockchain to track the movement of goods through its supply chain, ensuring that they are authentic and have not been tampered with.
Cloud Computing refers to the use of remote servers and cloud #
based applications to store, process, and manage data. Related terms include software as a service, infrastructure as a service, and platform as a service. Cloud computing is used in supply chain digitalization to provide scalable and on-demand access to computing resources, reducing the need for upfront capital investments and enabling greater flexibility and agility. For example, a company can use cloud-based transportation management systems to manage its logistics and transportation operations, without having to invest in expensive hardware and software.
Cybersecurity refers to the protection of supply chain systems and data f… #
Related terms include data security, network security, and incident response. Cybersecurity is used in supply chain digitalization to protect against hacking, phishing, and other types of cyber attacks, ensuring the integrity and confidentiality of supply chain data. For example, a company can use cybersecurity measures such as firewalls and encryption to protect its supply chain systems and data from cyber threats.
Data Analytics refers to the use of statistical and mathematical t… #
Related terms include data mining, business intelligence, and predictive analytics. Data analytics is used in supply chain digitalization to identify trends and patterns, optimize business processes, and make informed decisions. For example, a company can use data analytics to analyze data on shipment volumes and transportation costs to identify opportunities for cost savings and optimization.
Digital Twin refers to a virtual replica of a physical supply chain syste… #
Related terms include simulation, modeling, and virtualization. Digital twin is used in supply chain digitalization to optimize supply chain operations, predict and prevent disruptions, and improve overall efficiency. For example, a company can use a digital twin of its supply chain to simulate the impact of different scenarios, such as changes in demand or supply, and identify the most effective strategies for responding to them.
Electronic Data Interchange (EDI) refers to the electronic exchange of bu… #
Related terms include data exchange, integration, and interoperability. EDI is used in supply chain digitalization to automate the exchange of business documents, reduce errors and manual processing, and improve overall efficiency. For example, a company can use EDI to exchange purchase orders and invoices with its suppliers and customers, reducing the need for manual processing and improving the speed and accuracy of transactions.
Global Trade Management (GTM) refers to the use of software and servic… #
Related terms include global logistics, trade compliance, and supply chain visibility. GTM is used in supply chain digitalization to simplify and streamline global trade operations, reduce costs and risks, and improve overall efficiency. For example, a company can use GTM software to automate customs compliance, track shipments, and optimize logistics operations.
Internet of Things (IoT) refers to the use of sensors and connected</i… #
Related terms include machine to machine, sensors, and device management. IoT is used in supply chain digitalization to track and monitor supply chain assets, optimize logistics and transportation operations, and improve overall efficiency. For example, a company can use IoT sensors to track the location and condition of its shipments, optimizing logistics and transportation operations and reducing the risk of loss or damage.
Inventory Management refers to the use of software and techniques … #
Related terms include inventory control, warehousing, and supply chain optimization. Inventory management is used in supply chain digitalization to optimize inventory levels, reduce costs and risks, and improve overall efficiency. For example, a company can use inventory management software to analyze demand patterns and optimize inventory levels, reducing the need for excess inventory and improving cash flow.
Logistics refers to the planning and execution of the movement and… #
Related terms include supply chain management, transportation, and warehousing. Logistics is used in supply chain digitalization to optimize the movement and storage of goods, reduce costs and risks, and improve overall efficiency. For example, a company can use logistics software to optimize transportation routes, reduce fuel consumption, and improve delivery times.
Machine Learning (ML) refers to the use of algorithms and statistical<… #
Related terms include artificial intelligence, deep learning, and cognitive computing. ML is used in supply chain digitalization to analyze complex data sets, optimize business processes, and make informed decisions. For example, a company can use ML to analyze data on shipment volumes and transportation costs to identify opportunities for cost savings and optimization.
Order Management refers to the use of software and techniques to m… #
Related terms include order fulfillment, inventory management, and supply chain optimization. Order management is used in supply chain digitalization to optimize the order fulfillment process, reduce costs and risks, and improve overall efficiency. For example, a company can use order management software to automate the order fulfillment process, reducing manual errors and improving the speed and accuracy of transactions.
Predictive Analytics refers to the use of statistical and mathematical… #
Related terms include data analytics, machine learning, and forecasting. Predictive analytics is used in supply chain digitalization to identify trends and patterns, optimize business processes, and make informed decisions. For example, a company can use predictive analytics to analyze data on demand patterns and forecast future demand, optimizing inventory levels and reducing the risk of stockouts or overstocking.
Procurement refers to the process of acquiring goods and services from ex… #
Related terms include sourcing, purchasing, and contract management. Procurement is used in supply chain digitalization to optimize the procurement process, reduce costs and risks, and improve overall efficiency. For example, a company can use procurement software to automate the sourcing and purchasing process, reducing manual errors and improving the speed and accuracy of transactions.
Radio Frequency Identification (RFID) refers to the use of radio frequenc… #
Related terms include barcode scanning, GPS tracking, and sensor technology. RFID is used in supply chain digitalization to track and monitor supply chain assets, optimize logistics and transportation operations, and improve overall efficiency. For example, a company can use RFID tags to track the location and condition of its shipments, optimizing logistics and transportation operations and reducing the risk of loss or damage.
Return Merchandise Authorization (RMA) refers to the process of managing… #
Related terms include returns management, reverse logistics, and warranty management. RMA is used in supply chain digitalization to optimize the returns process, reduce costs and risks, and improve overall efficiency. For example, a company can use RMA software to automate the returns process, reducing manual errors and improving the speed and accuracy of transactions.
Supply Chain Management (SCM) refers to the planning and execution … #
Related terms include logistics, inventory management, and supply chain optimization. SCM is used in supply chain digitalization to optimize supply chain operations, reduce costs and risks, and improve overall efficiency. For example, a company can use SCM software to optimize inventory levels, reduce transportation costs, and improve delivery times.
Supply Chain Visibility refers to the ability to track and monitor supply… #
Related terms include track and trace, real time visibility, and supply chain transparency. Supply chain visibility is used in supply chain digitalization to optimize supply chain operations, reduce costs and risks, and improve overall efficiency. For example, a company can use supply chain visibility software to track the location and condition of its shipments, optimizing logistics and transportation operations and reducing the risk of loss or damage.
Transportation Management System (TMS) refers to the use of software and… #
Related terms include logistics, freight management, and transportation optimization. TMS is used in supply chain digitalization to optimize transportation operations, reduce costs and risks, and improve overall efficiency. For example, a company can use TMS software to optimize transportation routes, reduce fuel consumption, and improve delivery times.
Warehouse Management System (WMS) refers to the use of software and te… #
Related terms include inventory management, order fulfillment, and warehouse optimization. WMS is used in supply chain digitalization to optimize warehouse operations, reduce costs and risks, and improve overall efficiency. For example, a company can use WMS software to automate the inventory management process, reducing manual errors and improving the speed and accuracy of transactions.
Yield Management refers to the use of software and techniques to m… #
Related terms include production planning, scheduling, and inventory management. Yield management is used in supply chain digitalization to optimize production and distribution operations, reduce costs and risks, and improve overall efficiency. For example, a company can use yield management software to analyze demand patterns and optimize production schedules, reducing the risk of overproduction or underproduction.