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SAP Certified Associate - SAP IBP for Supply Chain Sample Questions (Q24-Q29):
NEW QUESTION # 24
Which of the following are features of lag-based snapshots? Note: There are 2 correct answers to this question.
- A. Lag-based snapshots are created in the Configuration app for a fixed time range
- B. The number of lag-based snapshots are limited to nine levels
- C. Target key figures for these snapshots must have lag as a root attribute in the base planning level
- D. Target key figures for these snapshots are exposed to the user in planning view
Answer: C,D
Explanation:
Lag-based snapshots in SAP IBP capture historical key figure values with a specified time offset (lag), useful for tracking past data (e.g., demand from 3 weeks ago). Their configuration and behavior are defined in SAP IBP's time-series planning framework.
* Option A: The number of lag-based snapshots are limited to nine levelsThis is incorrect. There's no documented limit of nine snapshots in SAP IBP; the number depends on configuration and performance, not a fixed cap.
* Option B: Lag-based snapshots are created in the Configuration app for a fixed time rangeThis is incorrect. Snapshots are configured in the Planning Areas app (via key figure settings), not a generic
"Configuration app," and they dynamically adjust based on lag, not afixed range.
* Option C: Target key figures for these snapshots are exposed to the user in planning viewThis is correct. Lag-based snapshot key figures (e.g., SNAPSHOT_LAG1) are visible and usable in planning views (e.g., Excel), allowing users to analyze historical data, per SAP IBP's documentation.
* Option D: Target key figures for these snapshots must have lag as a root attribute in the base planning levelThis is correct. The lag attribute (e.g., LAG = 1, 2) must be part of the base planning level (e.g., PERPRODLOCLAG) to store snapshot values distinctly, a requirement in SAP IBP's snapshot setup, per official guides.
Thus, C and D are features of lag-based snapshots, per SAP IBP's official functionality.
NEW QUESTION # 25
What do you need to be aware of when using multiple pairs of key figures in one copy operator? Note: There are 2 correct answers to this question.
- A. Copying multiple key figures on different planning levels is not possible
- B. Copying multiple key figures can be processed sequentially
- C. Necessary source key figures values are disaggregated
- D. Necessary target key figures values are disaggregated
Answer: B,D
Explanation:
The Copy Operator in SAP IBP transfers data between key figures, supporting multiple source-target pairs in one run. Its behavior is defined by SAP IBP's data management rules.
* Option A: Copying multiple key figures can be processed sequentiallyThis is correct. When multiple pairs are defined, the Copy Operator processes them sequentially within the job, ensuring dependencies are respected, per SAP IBP's operator documentation.
* Option B: Copying multiple key figures on different planning levels is not possibleThis is incorrect.
The Copy Operator supports different planning levels (e.g., PERPROD to PERPRODLOC), adjusting aggregation/disaggregation as needed.
* Option C: Necessary source key figures values are disaggregatedThis is incorrect. Source key figures are copied as-is; disaggregation occurs on the target side if required, not the source.
* Option D: Necessary target key figures values are disaggregatedThis is correct. If the target key figure's planning level is more detailed than the source, SAP IBP disaggregates values (e.g., using proportional factors), a standard behavior, per documentation.
Thus, A and D are key considerations for the Copy Operator, per SAP IBP's official rules.
NEW QUESTION # 26
How do you achieve rolling aggregation with SAP IBP?
- A. Using a key figure calculation
- B. Using an attribute as a key figure
- C. Using a local member
- D. Using an appropriate period weight factor
Answer: A
Explanation:
Rolling aggregation in SAP IBP refers to calculating a cumulative or moving total across a time horizon (e.g., year-to-date sales). This is a common requirement in planning and reporting, achieved through specific configuration methods.
* Option A: Using an attribute as a key figureThis is incorrect. Attributes as key figures provide static values (e.g., Product Category), not dynamic time-based aggregations like rolling totals.
* Option B: Using an appropriate period weight factorThis is incorrect. Period weight factors adjust proportional disaggregation (e.g., splitting monthly data to weeks), not rolling aggregation across periods.
* Option C: Using a key figure calculationThis is correct. Rolling aggregation is achieved in SAP IBP via key figure calculations, such as the CUMULATE function (e.g., KF2 = CUMULATE(KF1)), which sums values from the start of the horizon to the current period. This is configured in the Planning Areas app and is a standard method for time-series calculations, per SAP IBP's official documentation on key figure calculations.
* Option D: Using a local memberThis is incorrect. Local members in the Excel add-in allow ad-hoc calculations within a planning view, but they are user-specific and not a system-configured method for rolling aggregation across the planning area.
Thus, C is the correct method for achieving rolling aggregation, aligning with SAP IBP's calculation capabilities.
NEW QUESTION # 27
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. Eliminate the usage of telescopic time buckets
- B. Use non-overlapping networks by using Subnetwork ID maintained at Location-Products to reduce the size of the problem
- C. Keep the number of fair share segments small
- D. Increase the use of incremental lot size beyond the frozen horizon
- E. Split into multiple planning areas to support weekly vs. daily planning needs
Answer: A,B,C
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 # 28
You want to display and edit data in different Units of Measure (UOM). Which of the following must you consider before you use the UOM? Note: There are 3 correct answers to this question.
- A. Units of measure are an attribute of a master data type, such as Product
- B. Units of measure are usually not time-independent
- C. Conversion to the target unit of measure is handled by the SAP IBP Excel add-in
- D. Units of measure are usually not time-dependent
- E. Analytics allow the user to select the target unit of measure
Answer: A,D,E
Explanation:
Units of Measure (UOM) in SAP IBP allow data to be displayed and edited in different units (e.g., kg, lbs), configured via master data and UI settings, per SAP IBP's documentation.
* Option A: Analytics allow the user to select the target unit of measureThis is correct. Analytics apps (e.g., Advanced Dashboards) and Excel planning views let users choose the target UOM for display, leveraging conversion factors, per SAP IBP's visualization capabilities.
* Option B: Units of measure are usually not time-independentThis is incorrect. UOMs are typically static (time-independent) unless explicitly modeled as time-dependent (rare), making this a misstatement.
* Option C: Units of measure are an attribute of a master data type, such as ProductThis is correct.
UOM (e.g., Base UOM) is an attribute of the Product master data type, with conversion factors defined in UOM Conversion master data, per SAP IBP's setup.
* Option D: Units of measure are usually not time-dependentThis is correct. UOMs are generally static attributes, not varying by time unless custom-configured, aligning with SAP IBP's standard behavior.
* Option E: Conversion to the target unit of measure is handled by the SAP IBP Excel add-inThis is incorrect. While the Excel add-in displays converted values, the conversion logic is defined in the planning area (via UOM Conversion factors), not handled solely by the add-in.
Thus, A, C, and D are key considerations, per SAP IBP's official UOM handling.
NEW QUESTION # 29
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