Free Practice Questions for SAP C_IBP_2502 Exam

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.

Analytical charts in SAP IBP enhance visualization and decision-making. The apps supporting this depend on SAP IBP’s UI framework (Fiori-based).

Option A: Web-based PlanningThis is incorrect. "Web-based Planning" is not a specific SAP IBP app; it’s a general term. Planning is primarily via Excel or Planner Workspaces, not a standalone web app for charts.

Option B: Intelligent VisibilityThis is incorrect. Intelligent Visibility is a feature in SAP Supply Chain Control Tower, not an app enhanced with analytical charts in the core IBP planning context.

Option C: Planner WorkspaceThis is correct. Planner Workspaces (Fiori app) can embed analytical charts (e.g., from Analytics Stories) alongside planning data, enhancing the UI, per SAP IBP’s documentation.

Option D: Dashboards - AdvancedThis is correct. The Advanced Dashboards app allows users to create and customize analytical charts for insights, a core visualization tool in SAP IBP, per official app descriptions.

Thus, C and D are apps enhanced with analytical charts, per SAP IBP’s UI capabilities.

Time-series-based optimization in SAP IBP for Response and Supply balances demand and supply constraints over a horizon. Modeling customer demand involves prioritization and cost considerations.

Option A: Ensure discounting does not result in negative costs for each customer-product combinationThis is incorrect. Discounting (e.g., price reductions) isn’t a standard concept in time-series optimization; costs (e.g., non-delivery) are positive penalties, not negative adjustments.

Option B: Assign a high cost value (1 million or more) for non-delivery to priority customersThis is correct. In the optimizer, assigning high non-delivery costs (e.g., 1M) to priority customers ensures their demand is met first, a common prioritization technique in SAP IBP, per optimization documentation.

Option C: Ensure product prioritization with the combination of customer and productThis is correct. Time-series optimization can prioritize demand at the Customer-Product level (e.g., via demand priority rules or costs), ensuring key combinations are favored, per SAP IBP’s supply planning features.

Option D: Try to go as granular as possible with the customer productThis is incorrect. Excessive granularity increases complexity without guaranteeing better results; optimization balances granularity with performance, not mandating maximum detail.

Thus, B and C are valid approaches to modeling customer demand, per SAP IBP’s optimization capabilities.

Network charts in SAP IBP (via the Supply Chain Network app) visualize supply chain relationships, a feature of the Control Tower module.

Option A: To display the network chart, you need the Ship-From Location master data type in the planning areaThis is incorrect. The Ship-From Location is a concept (e.g., in Transportation Lanes), not a specific master data type requirement. Location and Transportation Lane data suffice.

Option B: You can create a network chart from the dedicated app, or use the Analytics Advanced appThis is correct. The Supply Chain Network app (dedicated) and Analytics Advanced app both support network chart creation, per SAP IBP’s visualization documentation.

Option C: You can create a network chart from the dedicated app, or use the Manage Analytics Stories appThis is incorrect. Manage Analytics Stories creates dashboards, not network charts specifically; it’s less focused on network visualization.

Option D: The network charts visualize relationships between warehouse, plants, customer, and supplier, for finished goodsThis is correct. Network charts depict nodes (e.g., plants, warehouses, customers, suppliers) and edges (e.g., Transportation Lanes) for finished goods, per SAP IBP’s network visualization features.

Thus, B and D are accurate features, per SAP IBP’s official documentation.

Master data types in SAP IBP define planning objects, with "Component" typically referring to a specific type like Production Source Item Component, per SAP IBP’s documentation.

Option A: Virtual master data typeThis is incorrect. Virtual types are temporary or derived, not standard for components.

Option B: Compound Master Data TypeThis is incorrect. Compound types (e.g., SOURCECUSTOMER) combine multiple simple types, not specifically "Component."

Option C: Reference Master Data TypeThis is correct. The Component master data type (e.g., in Production Source Item) is a Reference type, linking to a Product, per SAP IBP’s master data hierarchy (e.g., referencing Product ID).

Option D: External Master Data TypeThis is incorrect. External types are sourced externally, not a fit for Component.

Thus, C is the correct type, per SAP IBP’s official master data definitions.

Value-based filters in SAP IBP planning views (Excel add-in) restrict data based on key figure values (e.g., "Sales > 1000"). Their behavior is defined by SAP IBP’s UI capabilities.

Option A: These filters can be used together with attribute totals in the same planning viewThis is correct. Value-based filters (e.g., filtering high-demand products) coexist with attribute totals (e.g., summing by Region), allowing combined analysis in the same view, per SAP IBP’s planning view flexibility.

Option B: The alerts dashboard is not available if a value-based filter is set for the open planning viewThis is incorrect. The alerts dashboard remains accessible regardless of filters in the planning view. Alerts are independent of view-specific filters.

Option C: You can add (or delete) planning objects to a planning view after these filters are appliedThis is correct. Planning objects (e.g., Product-Location combinations) can be maintained (added/deleted) via master data apps or Excel, and the planning view reflects updates even with filters applied, per SAP IBP’s dynamic data handling.

Option D: You can only apply one value-based filter per planning viewThis is incorrect. Multiple value-based filters can be applied (e.g., "Sales > 1000 AND Inventory < 500"), offering layered filtering in SAP IBP.

Thus, A and C are valid conditions for value-based filters, per SAP IBP’s planning view documentation.

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.

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.

Key figure fixing in SAP IBP allows planners to lock values (e.g., in Excel) to prevent changes during planning runs, a feature in time-series planning.

Option A: Fixing is possible for key figures with negative valuesThis is incorrect. Fixing applies to any value (positive, negative, zero), but this isn’t a specific option or limitation in SAP IBP’s fixing functionality.

Option B: Fixing is possible for a part of a key figure value on a certain planning levelThis is incorrect. Fixing locks the entire value at a planning level, not a portion of it. Partial adjustments require separate key figures or manual edits before fixing.

Option C: You can change a fixed key figure only with administrative rightsThis is incorrect. Fixed key figures can be unfixed or edited by users with appropriate planning permissions, not just administrators, via the Excel UI.

Option D: Fixing is possible for a certain period, including all child values in the hierarchyThis is correct. In SAP IBP, fixing a key figure (e.g., Demand Plan Qty) for a period locks that value and propagates the fix to all child levels in the hierarchy (e.g., disaggregated Product-Customer combinations), ensuring consistency, as per SAP IBP’s fixing documentation.

Thus, D is the correct option for key figure fixing, reflecting SAP IBP’s hierarchical locking mechanism.