SAMPLE SAP C-IBP-2502 QUESTIONS PDF | VALID C-IBP-2502 TEST LABS

Sample SAP C-IBP-2502 Questions Pdf | Valid C-IBP-2502 Test Labs

Sample SAP C-IBP-2502 Questions Pdf | Valid C-IBP-2502 Test Labs

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SAP Certified Associate - SAP IBP for Supply Chain Sample Questions (Q76-Q81):

NEW QUESTION # 76
You created a key figure and want to add calculations. Which of the following rules do you consider? Note:
There are 2 correct answers to this question.

  • A. All key figure calculations have calculation inputs, which can be marked as stored or calculated
  • B. The calculation chain for a key figure must always result in a calculated key figure
  • C. Key figures can be calculated across the different planning levels
  • D. Aggregation calculations using SUM or MAX functions must be based on a higher aggregation level

Answer: A,C

Explanation:
Key figure calculations in SAP IBP, configured in the Planning Areas app, follow specific rules, per SAP IBP' s calculation engine documentation.
* Option A: All key figure calculations have calculation inputs, which can be marked as stored or calculatedThis is correct. Calculations (e.g., KF3 = KF1 + KF2) use inputs that are either stored (persisted data) or calculated (derived), a fundamental rule, per SAP IBP's guides.
* Option B: The calculation chain for a key figure must always result in a calculated key figureThis is incorrect. The chain can result in a stored key figure if configured to persist, notalways calculated.
* Option C: Aggregation calculations using SUM or MAX functions must be based on a higher aggregation levelThis is incorrect. Aggregation can occur at any level, not strictly higher; it depends on the planning level definition.
* Option D: Key figures can be calculated across the different planning levelsThis is correct.
Calculations can span levels (e.g., aggregating from PERPROD to PERPRODLOC), using disaggregation/aggregation, per SAP IBP's flexibility.
Thus, A and D are key rules, per SAP IBP's official calculation principles.


NEW QUESTION # 77
Which Master Data Types are used in time-series-based planning within SAP IBP for response and supply?
Note: There are 3 correct answers to this question.

  • A. DS Order Fulfillment
  • B. Location
  • C. Transportation Lane
  • D. Product
  • E. Customer

Answer: B,D,E

Explanation:
SAP IBP for Response and Supply includes time-series-based planning (e.g., heuristics, optimization) alongside order-based planning. Time-series planning relies on master data types to define the supply chain network and planning objects.
* Option A: DS Order FulfillmentThis is incorrect. "DS Order Fulfillment" is not a standard master data type in SAP IBP. Order fulfillment is an outcome of response planning (order-based), not a time- series master data type.
* Option B: Transportation LaneThis is incorrect in this context. While Transportation Lane is a master data type in SAP IBP, it is primarily used in supply planning (e.g., defining sourcing relationships). However, in the specific scope of "time-series-based planning within SAP IBP for response and supply," it's less prominent, as response planning often emphasizes order-based logic over time-series constraints like lanes. The correct answers focus on foundational master data.
* Option C: CustomerThis is correct. The Customer master data type (e.g., Customer ID) is essential in time-series planning to model demand at the customer level (e.g., in Sales and Operations Planning or supply planning). It's a core component of planning levels like PERPRODCUST.
* Option D: LocationThis is correct. The Location master data type (e.g., Plant, Warehouse) defines nodes in the supply chain network. Time-series planning uses locations to calculate supply, inventory, and transportation quantities across the planning horizon.
* Option E: ProductThis is correct. The Product master data type (e.g., Product ID) is fundamental to time-series planning, representing the items being planned. It's used in key figures like production quantities or demand forecasts.
Thus, C, D, and E (Customer, Location, Product) are core master data types in SAP IBP's time-series-based planning for response and supply, as per official documentation on planning area setup.


NEW QUESTION # 78
You want to maintain key figure values for a new attribute and value combination, using SAP IBP, add-in for Microsoft Excel, and you are receiving an error related to missing combinations. How can you resolve this problem? Note: There are 2 correct answers to this question.

  • A. Use the Copy Operator to create the missing combinations
  • B. Use the Manage Master Data app to create missing combinations
  • C. Use the function New Planning Object in Excel UI to create missing combination
  • D. Use the Data Integration app to upload the missing combinations

Answer: C,D

Explanation:
Errors for missing combinations in SAP IBP Excel occur when key figure data references non-existent planning objects (e.g., Product-Location pairs), per SAP IBP's documentation.
* Option A: Use the Data Integration app to upload the missing combinationsThis is correct. The Data Integration Jobs app can import new planning object combinations (e.g., via CSV), resolving the error, per SAP IBP's data management guides.
* Option B: Use the Manage Master Data app to create missing combinationsThis is incorrect. The Manage Master Data app edits existing master data, not compound combinations directly for planning objects.
* Option C: Use the function New Planning Object in Excel UI to create missing combinationThis is correct. The "New Planning Object" feature in the Excel add-in creates missing combinations (e.g., PERPRODLOC) on the fly, per SAP IBP's Excel capabilities.
* Option D: Use the Copy Operator to create the missing combinationsThis is incorrect. The Copy Operator transfers key figure data, not creates new planning object combinations.
Thus, A and C resolve the issue, per SAP IBP's official tools and processes.


NEW QUESTION # 79
You are implementing a demand process in SAP IBP for sales and operations, and consider using the standard forecast key figures available in the sample planning area SAPIBP1. What are the first and last key figures in the logical progression of demand in the S&OP process?

  • A. Statistical Forecast Qty first and Consensus Demand Plan Qty last
  • B. Local Demand Plan first and Consensus Demand Plan Qty last
  • C. Local Demand Plan first and Combined Final Demand last
  • D. Statistical Forecast Qty first and Global Demand Plan Qty for S&OP last

Answer: A

Explanation:
In SAP IBP for Sales and Operations Planning (S&OP), the demand planning process follows a logical progression of key figures, as exemplified in the sample planning area SAPIBP1. Thisprogression starts with raw forecast data and ends with an agreed-upon demand plan.
* Option A: Local Demand Plan first and Combined Final Demand last"Local Demand Plan" is not a standard key figure in SAPIBP1; it's a vague term. "Combined Final Demand" is also not a recognized key figure. This option misaligns with the S&OP process flow.
* Option B: Statistical Forecast Qty first and Consensus Demand Plan Qty lastThis is correct. In SAPIBP1, the demand process begins withStatistical Forecast Qty(e.g., generated via statistical models like moving average or exponential smoothing), representing the initial unconstrained forecast.
The process progresses through adjustments (e.g., manual overrides, market inputs) and collaboration, culminating inConsensus Demand Plan Qty, the final agreed-upon demand plan after S&OP meetings.
This reflects SAP IBP's S&OP workflow: forecast generation # review # consensus.
* Option C: Local Demand Plan first and Consensus Demand Plan Qty lastAs noted, "Local Demand Plan" is not a standard key figure in SAPIBP1 or S&OP terminology, making this incorrect despite the valid end point.
* Option D: Statistical Forecast Qty first and Global Demand Plan Qty for S&OP lastWhile
"Statistical Forecast Qty" is a valid starting point, "Global Demand Plan Qty for S&OP" is not a standard key figure in SAPIBP1. The correct term is "Consensus Demand Plan Qty," which is more specific to the S&OP output.
Thus, B aligns with SAP IBP's S&OP demand planning progression per SAPIBP1's standard key figures and official S&OP process documentation.


NEW QUESTION # 80
Which options can be used to reduce the runtimes of a time-series optimizer run? Note: There are 3 correct answers to this question.

  • A. Increase the use of incremental lot size beyond the frozen horizon
  • B. Use non-overlapping networks by using Subnetwork ID maintained at Location-Products to reduce the size of the problem
  • C. Split into multiple planning areas to support weekly vs. daily planning needs
  • D. Eliminate the usage of telescopic time buckets
  • E. Keep the number of fair share segments small

Answer: B,D,E

Explanation:
The Time-Series-Based Supply Optimizer in SAP IBP is a powerful tool for supply planning, but its runtime can be significant due to the complexity of constraints and variables. Reducing runtime involves optimizing the problem size and configuration, as outlined in SAP's performance best practices.
* Option A: Keep the number of fair share segments smallThis is correct. Fair share segments (used in demand prioritization or allocation) increase the optimizer's complexity by adding variables and constraints. Limiting segments (e.g., fewer priority tiers) reduces the computational load, a recommended practice in SAP IBP's optimizer configuration documentation.
* Option B: Split into multiple planning areas to support weekly vs. daily planning needsThis is incorrect. Splitting into multiple planning areas might simplify individual runs but doesn't directly reduce the runtime of a single optimizer run. Planning areas are structural, not runtime-specific, and this approach addresses granularity needs, not performance.
* Option C: Use non-overlapping networks by using Subnetwork ID maintained at Location- Products to reduce the size of the problemThis is correct. Subnetwork IDs (e.g., assigned to Location- Product combinations) partition the supply chain network into smaller, independent subproblems. The optimizer solves these separately, significantly reducing runtime by shrinking the problem scope, as per SAP IBP's network optimization guidelines.
* Option D: Eliminate the usage of telescopic time bucketsThis is correct. Telescopic time buckets (e.
g., daily near-term, weekly mid-term, monthly long-term) increase complexity by requiring the optimizer to handle variable time granularities. Using uniform buckets (e.g., all weekly) simplifies the model and cuts runtime, a known performance tweak in SAP IBP.
* Option E: Increase the use of incremental lot size beyond the frozen horizonThis is incorrect.
Incremental lot sizes affect planning quantities, not optimizer runtime directly. Adjusting lot sizes might influence solution feasibility but doesn't inherently optimize performance.
Thus, A, C, and D are proven methods to reduce time-series optimizer runtimes, per SAP IBP's official performance optimization documentation.


NEW QUESTION # 81
......

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