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CSCP Supply Chain Technology and Systems 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 CSCP Supply Chain Technology and Systems flashcards as text

  1. In supply chain analytics, 'prescriptive analytics' differs from descriptive and predictive analytics because it:

    Answer: Recommends specific actions to achieve desired outcomes

    Prescriptive analytics goes beyond prediction to suggest optimal decisions or actions, such as recommending the best inventory reorder quantity.

  2. A Manufacturing Execution System (MES) primarily operates at which level of the supply chain technology stack?

    Answer: Shop-floor production monitoring and control

    MES bridges the gap between ERP planning and physical production by tracking and controlling manufacturing operations in real time.

  3. Cloud-based supply chain software offers a key advantage over on-premise solutions in that it:

    Answer: Provides automatic updates and scalability without major IT infrastructure investment

    Cloud solutions reduce capital expenditure, scale on demand, and are maintained by the vendor, lowering IT burden for supply chain teams.

  4. When a company implements a Vendor-Managed Inventory (VMI) program supported by technology, the primary data shared with the supplier is:

    Answer: Real-time inventory levels and sales data at the customer's location

    VMI technology enables suppliers to access real-time stock and sales data so they can proactively replenish inventory without purchase orders.

  5. In the APICS CSCP context, 'supply chain visibility' enabled by technology means:

    Answer: Access to real-time data on inventory, orders, and shipments across the entire supply chain network

    Supply chain visibility gives all relevant stakeholders access to timely, accurate information across tiers to support better decisions and faster responses.

  6. A key benefit of using machine learning for demand forecasting over traditional statistical methods is that it:

    Answer: Can identify complex, non-linear patterns across large datasets to improve accuracy

    Machine learning algorithms detect subtle, non-linear relationships in large datasets — including external signals — that traditional models cannot capture.