Oracle 1Z0-1163-1 Exam Dumps

Global Order Promising (C) provides real-time order commitment dates by analyzing supply (e.g., inventory, production) and demand (e.g., orders, forecasts) constraints enterprise-wide. For instance, if 100 units are requested and 70 are available with a 3-day lead time, it commits to 3 days. Option A is false---no universal same-day guarantee exists. Option B is incorrect---supplier data often informs promises. Option D is wrong---it considers global, not just local, availability. This feature ensures reliable promises, reduces cancellations, and aligns customer expectations with operational capacity.

Supplier Qualification Management in Oracle Fusion Cloud SCM evaluates and approves suppliers based on predefined compliance and performance criteria, ensuring reliable partnerships. Option A is incorrect as it focuses on payments, not qualification. Option C is wrong---performance reviews are integral to the process. This benefit mitigates risks and ensures quality suppliers.

The Back-to-Back Order Fulfillment process (A) in Oracle Fusion Cloud SCM links customer orders directly to supplier purchase orders, ensuring seamless fulfillment without relying solely on existing inventory. When a customer order is placed, the system automatically generates a corresponding PO to the supplier, who ships the goods directly or via the warehouse to the customer. For example, if a retailer orders a custom machine not in stock, Back-to-Back triggers a PO to the manufacturer, streamlining delivery. Option B is incorrect---it aims for efficiency, not delays. Option C is wrong---it prioritizes supplier sourcing over warehouse stock when needed. This feature reduces inventory holding costs, improves cash flow, and ensures timely delivery, making it ideal for make-to-order scenarios.

For the Demand to Management OMBP, Forecast Accuracy is the primary metric, as it evaluates how precisely demand predictions match actual market demand, a foundational step in effective supply chain planning. Calculated as a percentage (e.g., actual demand of 800 units versus a forecast of 850 yields 94% accuracy), it directly reflects the OMBP's ability to drive downstream processes like procurement and production. Option B (Supplier Lead Time) measures supplier performance, which affects supply execution but not demand forecasting accuracy. Option C (Inventory Turnover) tracks inventory movement efficiency, an outcome influenced by forecast accuracy, not a direct measure of the OMBP itself. Accurate forecasts prevent overproduction or shortages---for example, overestimating demand by 20% could lead to $50,000 in excess inventory costs, underscoring the metric's importance.

The Predict Demand process within the Demand to Management OMBP in Oracle Fusion Cloud SCM leverages advanced capabilities to enhance demand planning. Collaborative Forecasting Platform (A) enables stakeholders---such as sales teams, suppliers, and distributors---to collaborate in real time, inputting qualitative insights (e.g., market trends or promotions) that refine forecasts beyond pure data analysis. For example, a retailer might adjust forecasts based on an upcoming sale confirmed via the platform, improving accuracy. Machine Learning-based Forecasting (B) uses algorithms to analyze historical data, detect patterns (e.g., seasonality or anomalies), and adapt predictions dynamically, making it more precise than traditional methods. For instance, it might identify a spike in demand for umbrellas during unexpected rainy seasons. Option C (Statistical Forecasting) is a traditional method relying on statistical models but lacks the adaptive intelligence of machine learning, though it's still used as a foundation. Option D (Demand Sensing) focuses on short-term demand signals (e.g., point-of-sale data) rather than long-term planning, making it complementary but not a core strength of Predict Demand. Together, A and B empower businesses with both human collaboration and cutting-edge AI, ensuring robust demand planning that balances quantitative and qualitative inputs.