SAP C_IBP_2502 Dumps Questions Answers

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.

In SAP IBP, key figure calculations often involve disaggregation or aggregation across planning levels. Here, the task is to distribute (disaggregate) values from a higher aggregation level (PERPRODCUSTREGION, i.e., Product-Customer-Region) to a more detailed level (PERPRODCUST, i.e., Product-Customer). This is a common requirement in supply chain planning to allocate regional data to individual customer levels.

Option A: Splitting the values from detailed to aggregated level by using a copy operatorThis is incorrect because the question specifies moving from PERPRODCUSTREGION (aggregated) to PERPRODCUST (detailed), not the reverse. A copy operator typically copies values without transformation, and aggregation moves data upward, not downward.

Option B: Splitting the values from aggregated to detailed level using multiplication by the proportionsThis is correct. In SAP IBP, disaggregation can use proportional factors to split aggregated data. For example, if PERPRODCUSTREGION has a total value (e.g., 100 units), it can be distributed to PERPRODCUST based on predefined proportions (e.g., Customer A gets 60%, Customer B gets 40%). This is configured in the key figure’s disaggregation settings using a proportional calculation, a standard feature in SAP IBP’s time-series planning.

Option C: Splitting the values from aggregated to detailed level, based on the time profile attributeThis is incorrect. Time profile attributes (e.g., week, month) govern temporal granularity, not the structural disaggregation between planning levels like PERPRODCUSTREGION and PERPRODCUST. Disaggregation in SAP IBP is driven by key figure settings, not time profile attributes directly.

Option D: Splitting the values from aggregated to detailed level, based on a stored split-factor key figureThis is correct. SAP IBP supports disaggregation using a stored key figure as a split factor. For instance, a key figure like "Customer Distribution Ratio" (stored at PERPRODCUST) can define how the aggregated value (e.g., 100 units at PERPRODCUSTREGION) is split (e.g., 70 units to Customer A, 30 units to Customer B). This method is widely used in SAP IBP for precise, data-driven disaggregation, as documented in SAP’s configuration guides.

Thus, B and D align with SAP IBP’s disaggregation capabilities, leveraging proportions or stored split factors to move data from an aggregated to a detailed level.

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.