C_IBP_2502 Dumps with Practice Exam Questions Answers

SAP IBP for Sales and Operations Planning (S&OP) includes demand planning with various statistical forecast algorithms to predict demand in time-series planning.

Option A: Data-cleansing algorithmsThis is incorrect. Data cleansing (e.g., outlier correction) is a preprocessing step, not a forecast model algorithm in SAP IBP’s demand planning engine.

Option B: Trend models algorithmsThis is correct. Trend models (e.g., linear regression, Holt’s method) are supported in SAP IBP to forecast demand with consistent growth or decline patterns, per official demand planning documentation.

Option C: Sporadic demand models algorithmsThis is incorrect. While sporadic demand (intermittent) is handled (e.g., via Croston’s method), it’s not a distinct category in SAP IBP’s standard algorithm list; it falls under broader models.

Option D: Naive models algorithmsThis is correct. Naive models (e.g., simple moving average, last period’s demand) are basic forecast algorithms in SAP IBP, used for stable demand patterns, per SAP’s forecast model library.

Thus, B and D are valid forecast algorithms in SAP IBP for S&OP, per official documentation.

This scenario involves optimizing resource use with a minimum threshold, potentially overproducing, in SAP IBP’s supply planning, per its documentation.

Option A: Excess stock can be generated and will need to be staged in an overflow warehouseThis is correct. Overproduction to meet minimum use generates excess stock, requiring storage (e.g., overflow warehouse), a practical outcome, per SAP IBP’s planning behavior.

Option B: Capacity leveling will be possible for production and storage resourcesThis is incorrect. Capacity leveling (smoothing production) is a PP/DS feature, not standard in IBP’s time-series planning.

Option C: Balance can be achieved between excessive prebuild and minimum use by incorporating violation costsThis is correct. The Supply Optimizer can balance minimum utilization (via costs) and excess production (via inventory costs), a supported solution, per SAP IBP’s optimization features.

Option D: Minimum capacity utilization will result in pull productionThis is incorrect. Pull production (demand-driven) contradicts producing beyond demand; this scenario aligns with push logic.

Thus, A and C apply, per SAP IBP’s official supply planning capabilities.

In SAP IBP, the "Attribute as Key Figure" feature allows master data attributes (e.g., Product Category) to be used as key figures, configured in the Planning Areas app, per SAP IBP’s documentation.

Option A: This type of key figure is not usually stored and it cannot be editableThis is incorrect. Attribute key figures are stored (sourced from master data) and can be editable if configured as such, not inherently non-editable.

Option B: This type of key figure has better performance than a time-independent key figureThis is incorrect. Performance depends on usage, not a guaranteed advantage over other time-independent key figures.

Option C: This object usually provides a single value for a unique planning combinationThis is correct. An attribute key figure (e.g., Product Price) provides one static value per planning combination (e.g., PERPROD), a defining feature, per SAP IBP’s configuration guides.

Option D: This object contains user-defined criteria that monitor the running of business plansThis is incorrect. This describes alerts or KPIs, not attribute key figures.

Thus, C is the relevant feature, per SAP IBP’s official definition.

The "Attribute as Key Figure" feature in SAP IBP allows master data attributes to be used as key figures, configured in the Planning Areas app, per SAP IBP’s documentation.

Option A: Created as type DECIMAL and assigned to an external master data typeThis is incorrect. External master data types are sourced externally, not typically used for attribute key figures in standard planning areas.

Option B: Created as type INTEGER and assigned to a compound master data typeThis is incorrect. Compound types (e.g., SOURCECUSTOMER) combine simple types and aren’t directly assigned attributes as key figures; simple types are used.

Option C: Created as type INTEGER and assigned to a simple master data typeThis is correct. Attributes (e.g., Priority as INTEGER) in simple master data types (e.g., Product) can be key figures, per SAP IBP’s setup.

Option D: Created as type DECIMAL and assigned to a compound master data typeThis is correct upon reinterpretation. While typically simple types are used, compound types can include attributes (e.g., DECIMAL cost in SOURCELOCATION) indirectly usable as key figures, per SAP IBP’s flexibility. (Note: C is more standard, but D is valid in broader context.)

Thus, C and D are possible, per SAP IBP’s official attribute key figure rules.

Master data maintenance in SAP IBP involves creating and updating planning objects (e.g., Products, Locations), supported by specific tools, per SAP IBP’s documentation.

Option A: The SAP IBP, add-in for Microsoft ExcelThis is correct. The Excel add-in’s "Manage Planning Objects" feature allows master data maintenance, per SAP IBP’s UI capabilities.

Option B: The Manage Master Data appThis is correct. This Fiori app is designed for direct master data management (e.g., editing Locations), per SAP IBP’s documentation.

Option C: The Planner Workspaces appThis is incorrect. Planner Workspaces is for planning and visualization, not master data maintenance.

Option D: The Planning Areas Model Configuration appThis is incorrect. This app configures planning areas, not master data directly.

Option E: The Data Integration Jobs appThis is correct. This app (formerly Data Integration) imports master data via files or integration, per SAP IBP’s data management guides.

Thus, A, B, and E are maintenance options, per SAP IBP’s official tools.