Supply Chain Technology and Integration Flashcards
6 cards from real CSCP practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 Supply Chain Technology and Integration flashcards as text
What is the primary benefit of an Enterprise Resource Planning (ERP) system in supply chain management?
Answer: Integrating data from finance, procurement, production, and logistics into a single system of record
ERP systems eliminate data silos by providing a unified database that all business functions access, enabling real-time visibility across the enterprise.
What does 'Electronic Data Interchange' (EDI) enable between trading partners?
Answer: Automated, structured exchange of business documents like purchase orders and invoices in standardized formats
EDI replaces paper documents with electronic equivalents in standardized formats (like ANSI X12 or EDIFACT), enabling automated processing between trading partners.
How does RFID technology improve supply chain operations compared to traditional barcode scanning?
Answer: RFID reads multiple items simultaneously without line-of-sight, enabling faster and more automated tracking
RFID tags can be read in bulk without scanning each item individually and don't require line-of-sight, dramatically speeding up receiving, picking, and inventory counts.
What is 'supply chain analytics' used for in the CSCP context?
Answer: Analyzing supply chain data to identify performance gaps, trends, and improvement opportunities
Supply chain analytics transforms raw operational data into actionable insights about performance, costs, risks, and opportunities across the supply chain.
In supply chain management, 'cloud computing' benefits include:
Answer: Scalable infrastructure, reduced IT capital investment, and easier collaboration with supply chain partners
Cloud-based supply chain systems reduce upfront IT costs, scale elastically, and enable easier integration and data sharing with trading partners.
What is the role of 'machine learning' in demand forecasting?
Answer: Identifying complex patterns in large data sets to improve forecast accuracy beyond traditional statistical models
Machine learning algorithms can incorporate many variables (weather, promotions, economic indicators) and self-adjust over time, outperforming traditional time series models.