C_IBP_2502 SAP Certified Associate - SAP IBP for Supply Chain Questions and Answers

Planning operators in SAP IBP (via the Application Jobs app) manage data, including deletions. The question likely intends "delete key figure data for planning objects" in a version, not the objects themselves, per SAP IBP’s terminology.

Option A: Purge Master DataThis is incorrect. This deletes master data (e.g., Products), not key figure data tied to planning objects in a version.

Option B: Purge Key Figure Data Outside Planning Area Planning HorizonThis is incorrect. This deletes data outside the horizon across versions, not specific to a version’s planning objects.

Option C: Purge Key Figure DataThis is correct. The Purge Key Figure Data operator deletes key figure values for specified planning objects (e.g., by filter) in a selected version, per SAP IBP’s data management documentation.

Option D: Purge Non-Conforming DataThis is incorrect. This removes inconsistent data (e.g., orphaned records), not targeted deletion in a version.

Thus, C is the correct operator, per SAP IBP’s official job capabilities.

SAP IBP for Response and Supply focuses on order-based planning and short-term supply optimization, per its official module documentation.

Option A: Gating FactorThis is correct. Gating factors (e.g., capacity constraints driving supply decisions) are analyzed in response planning to prioritize orders, a key capability, per SAP IBP’s documentation.

Option B: Analyze Supply UsageThis is correct. Analyzing supply usage (e.g., allocation of supply to demand) is a core feature in response and supply, supported by tools like the Supply Usage app, per SAP IBP’s guides.

Option C: Detailed Production SchedulingThis is incorrect. Detailed scheduling is handled by SAP PP/DS or external systems, not IBP Response and Supply, which focuses on higher-level planning.

Option D: Calculating Buffer ProposalsThis is incorrect. Buffer proposals are part of Demand-Driven Replenishment (DDR), a separate IBP feature, not Response and Supply.

Thus, A and B are included capabilities, per SAP IBP’s official Response and Supply scope.

SAP IBP integrates with SAP S/4HANA and legacy ERP systems to transfer master and transactional data, using specific tools designed for cloud-based planning.

Option A: SAP Cloud Integration for Data ServicesThis is correct. SAP Cloud Integration for Data Services (CI-DS) is the primary tool for integrating SAP IBP with S/4HANA and legacy systems. It supports batch data transfers (e.g., master data, key figures) via predefined templates, as per SAP IBP’s integration framework.

Option B: SAP Smart Data IntegrationThis is correct. SAP Smart Data Integration (SDI), part of SAP HANA, enables real-time or batch integration from S/4HANA and legacy ERPs to SAP IBP, particularly for complex data mappings, a supported method in SAP’s documentation.

Option C: Core InterfaceThis is incorrect. Core Interface (CIF) is used in SAP ECC/APO, not SAP IBP. IBP relies on cloud-based tools like CI-DS, not ECC’s CIF.

Option D: Real-time IntegrationThis is incorrect. "Real-time Integration" is a concept, not a specific tool. While SDI supports real-time, it’s the tool itself (B), not a standalone option.

Thus, A and B (CI-DS and SDI) are the correct integration tools for SAP IBP, per official integration guides.

The Check Mode algorithm in SAP IBP validates planning area consistency, focusing on master data and key figure integrity, as per SAP IBP’s configuration documentation.

Option A: It checks whether the location products specified in the master data are connected by customer sourcing rules within the supply chain networkThis is correct. Check Mode ensures Location-Product combinations are linked via sourcing rules (e.g., SOURCECUSTOMER), validating network connectivity.

Option B: It reports input key figures for which no related master data existsThis is incorrect. While important, this is a data load check, not a core Check Mode function, which focuses on structural consistency.

Option C: It checks whether the location resource specified in the master data forms a cycle in the supply chain networkThis is incorrect. Location resources (e.g., capacity) don’t form cycles; cycles involve sourcing relationships, not resources.

Option D: It checks whether the heuristic detects cycles formed by nodes (such as location products) in the supply chain networkThis is correct. Check Mode identifies cycles (e.g., A → B → A) in Location-Product sourcing, ensuring heuristic feasibility, per SAP IBP’s documentation.

Option E: It checks whether the sourcing in the Production Source Item master datatype existsThis is correct. It verifies that Production Source Items have valid sourcing definitions, a key consistency check, per SAP IBP’s supply planning rules.

Thus, A, D, and E are triggered by Check Mode, per SAP IBP’s official validation scope.

The Planner Workspaces app in SAP IBP is a Fiori-based UI that integrates planning tools, analytics, and collaboration features for supply chain planners.

Option A: It supports simulating the effect of the changesThis is incorrect. While simulation is a feature in SAP IBP (e.g., via versions or scenarios in Excel), Planner Workspaces focuses on visualization and navigation, not direct simulation execution. Simulation occurs in other apps like Excel or Manage Scenarios.

Option B: It supports favorites created in SAP IBP, add-in for Microsoft ExcelThis is correct. Planner Workspaces integrates with the Excel add-in, allowing users to access their Excel favorites (e.g., planning views) directly within the workspace. This enhances usability by linking preferred tools, as per SAP IBP’s documentation on Planner Workspaces.

Option C: It supports embedding analytic stories as a workspace componentThis is correct. Analytic stories (created in the Manage Analytics Stories app) can be embedded in Planner Workspaces, providing charts and insights alongside planning data. This is a key visualization feature, per SAP IBP’s UI capabilities.

Option D: It supports sharing with other users or user groupsThis is incorrect. Sharing is available in Excel (e.g., templates) or analytics apps, but Planner Workspaces doesn’t have a native sharing function for workspaces themselves. Collaboration occurs via other mechanisms.

Thus, B and C are accurate capabilities of Planner Workspaces, aligning with SAP IBP’s official feature set.

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.

Co-products in SAP IBP represent items produced simultaneously with a main product (e.g., in chemical manufacturing). They are modeled in supply planning, typically via the Production Source of Supply master data.

Option A: The number of co-products that can be defined in the supply model is unlimitedThis is correct. SAP IBP’s Production Source Item allows multiple co-products to be linked to a main product via output coefficients. There’s no hardcoded limit, though practical constraints (e.g., performance) may apply, as per SAP IBP’s supply planning documentation.

Option B: The output coefficient is time-dependent and should be modeled as a time seriesThis is incorrect. The output coefficient (e.g., 1 unit of main product yields 0.5 units of co-product) is a static attribute in the Production Source Item master data, not a time-dependent key figure by default. Time-series modeling is possible but not required.

Option C: The relationship between main product and co-product is specified in the production source of supplyThis is correct. In SAP IBP, the Production Source of Supply (e.g., Production Source Header and Item) defines the main product and co-products, including output ratios, as a core feature of supply planning, per official documentation.

Option D: Co-production can be modeled only by supply optimizer and finite heuristicsThis is incorrect. Co-products are supported by both infinite heuristics (e.g., calculating unconstrained supply) and finite methods (optimizer, heuristics), not limited to finite planning.

Thus, A and C accurately describe co-production properties in SAP IBP, per its supply modeling capabilities.

Subtotals in SAP IBP planning views (typically in the Excel add-in) allow users to aggregate key figure values by attributes (e.g., Product, Location) for analysis. Configuration and display options govern their behavior.

Option A: The total value can be added before or after the selected attributeThis is correct. In the planning view, subtotals can be positioned flexibly—either before (above) or after (below) the attribute values in the layout. This is configurable in the Excel template design, a standard feature per SAP IBP’s planning view documentation.

Option B: The total number of attributes that can use subtotal in the planning view can be restrictedThis is correct. The number of attributes for subtotals can be limited by the planning view’s design or system performance settings (e.g., via global parameters or template complexity), ensuring usability and efficiency, as noted in SAP IBP’s UI guidelines.

Option C: The values of the attribute-based total at the highest attribute level in the planning level can be changedThis is incorrect. Subtotals are calculated aggregates and not directly editable at the highest level unless disaggregated. The planning level defines editable data, not subtotal overrides.

Option D: Only attribute-based totals can be added to the planning viewThis is incorrect. Subtotals can also be time-based (e.g., by week, month) or key figure-based, not just attribute-based, depending on the view’s configuration.

Thus, A and B reflect SAP IBP’s subtotal functionality in planning views, per official documentation.

The Create Time Periods job in SAP IBP (via the Application Jobs app) generates time periods (e.g., weeks, months) for a time profile, a prerequisite for planning.

Option A: The planning area to which the time profile is assigned must be activeThis is incorrect. The planning area doesn’t need to be active during time period creation; the job operates on the time profile independently.

Option B: This application job can also be triggered from SAP IBP, add-in for Microsoft ExcelThis is incorrect. The job is triggered via the Application Jobs app (Fiori), not the Excel add-in, which focuses on planning views.

Option C: A time profile has to be activated so that the application job can proceedThis is correct. The time profile must be activated (i.e., saved and valid) before the job can generate periods, ensuring configuration readiness, per SAP IBP’s time profile documentation.

Option D: It is mandatory to specify the planning area in the Parameter Section of the application jobThis is incorrect. The job requires the time profile ID, not the planning area, as parameters, though the time profile is linked to a planning area.

Thus, C is the key awareness point, per SAP IBP’s official job requirements.

Time-series-based planning areas in SAP IBP support operators for demand, supply, and inventory planning, distinct from order-based operators.

Option A: Constrained Forecast RunThis is correct. The Constrained Forecast Run adjusts demand forecasts based on supply constraints, a time-series operator in SAP IBP for S&OP, per official documentation.

Option B: Shelf Life HeuristicsThis is incorrect. Shelf Life Heuristics is specific to SAP IBP for Response and Supply (order-based), not time-series planning.

Option C: Finite HeuristicsThis is correct. Finite Heuristics plans supply respecting capacity constraints in a time-series context, a standard operator, per SAP IBP’s supply planning guides.

Option D: Deployment OptimizerThis is incorrect. The Deployment Optimizer is an order-based operator in SAP IBP for Response and Supply, not time-series-based.

Thus, A and C are valid time-series operators, per SAP IBP’s official capabilities.

Planner Workspaces in SAP IBP is a Fiori-based UI that integrates planning tools, analytics, and workflows, enhancing planner productivity. Its value drivers are outlined in SAP IBP’s UI documentation.

Option A: Issues can be identified and solved with special functionsThis is correct. Alerts and playbooks in Planner Workspaces help identify and resolve issues (e.g., supply shortages), a key value driver, per SAP IBP’s features.

Option B: It combines various components into one user interfaceThis is correct. It integrates planning views, charts, and alerts into a single UI, streamlining workflows, a core benefit, per SAP IBP’s documentation.

Option C: It can trigger SAP S/4HANA transactions in real timeThis is incorrect. Planner Workspaces focuses on IBP planning, not real-time S/4HANA transaction execution, which requires integration tools like CI-DS.

Option D: It combines the data from multiple planning areas into one user interfaceThis is incorrect. It operates within one planning area; combining multiple areas requires separate configurations or views, not a native feature.

Option E: Application jobs can be started from this user interfaceThis is correct. Planners can trigger jobs (e.g., Copy Operator) directly from Planner Workspaces, enhancing efficiency, per SAP IBP’s UI capabilities.

Thus, A, B, and E are value drivers, per SAP IBP’s official Planner Workspaces description.

SAP Cloud Integration for Data Services (CI-DS) integrates master data into SAP IBP, with errors logged in the Data Integration Jobs app, per SAP IBP’s integration documentation.

Option A: Navigate to the Master Data Workbook in Excel and open the LogThis is incorrect. The Excel Master Data Workbook doesn’t provide integration job logs; it’s for manual maintenance.

Option B: Navigate to the Manage Master Data app and open the LogThis is incorrect. The Manage Master Data app manages data, not integration job logs.

Option C: Download the Initial Problem Report in the Data Integration appThis is correct. The Data Integration Jobs app provides detailed error reports (e.g., "Initial Problem Report") for failed jobs like "Fatal Error," per SAP IBP’s troubleshooting guides.

Option D: Download the Rejection Report in the Data Integration appThis is incorrect. The Rejection Report details rejected records, not the full error context of a "Fatal Error."

Thus, C is the correct method, per SAP IBP’s official integration error handling.

Disaggregation in SAP IBP distributes aggregated key figure values (e.g., KF1) to lower planning levels, configured in the Planning Areas app. Methods depend on SAP IBP’s calculation framework.

Option A: Disaggregation according to user-defined expressionThis is correct. Users can define custom expressions (e.g., based on attributes or calculations) in the key figure’s disaggregation settings, a flexible feature in SAP IBP, per configuration documentation.

Option B: Disaggregation according to an equal splitThis is incorrect in this context. While equal split is a default disaggregation method, it’s not explicitly configurable as a distinct option in the Planning Areas app; it’s automatic when no other method is specified.

Option C: Disaggregation in batch triggered by an application jobThis is incorrect. Disaggregation occurs in real-time or during planning runs, not as a batch job. Application jobs handle tasks like data copy, not disaggregation logic.

Option D: Disaggregation according to a helper key figureThis is correct. A helper key figure (e.g., historical sales) can guide disaggregation proportions, a standard method in SAP IBP, per key figure setup guides.

Option E: Proportional disaggregation by using KF2 in the expressionThis is correct. KF1 can disaggregate proportionally based on another key figure (KF2) via an expression (e.g., KF1 = KF1 * (KF2 / SUM(KF2))), a supported method in SAP IBP.

Thus, A, D, and E are configurable disaggregation methods, per SAP IBP’s official capabilities.

MRO parts planning in SAP IBP supports maintenance operations with demand, supply, and inventory processes, per SAP IBP’s supply chain planning scope.

Option A: Inventory OptimizationThis is correct. Inventory Optimization (e.g., safety stock for MRO parts) ensures availability for maintenance, a key MRO process, per SAP IBP’s documentation.

Option B: Demand Driven ReplenishmentThis is incorrect. Demand Driven Replenishment (DDR) is a specific methodology in SAP IBP, but it’s not standard for MRO; it’s more for manufacturing/retail.

Option C: Demand PlanningThis is correct. Demand Planning forecasts MRO parts needs (e.g., based on maintenance schedules), a core process, per SAP IBP’s demand module.

Option D: Supply PlanningThis is correct. Supply Planning ensures MRO parts are sourced and available, using heuristics or optimization, per SAP IBP’s supply planning features.

Option E: SAP Intelligent Asset ManagementThis is incorrect. SAP IAM is a separate solution, not an IBP process, though it can integrate with IBP for MRO planning.

Thus, A, C, and D are MRO processes in SAP IBP, per official documentation.

The Last Period Aggregation function (LASTPERIOD) in SAP IBP retrieves the most recent value in a time horizon for a key figure, useful for inventory analysis. Its applications align with SAP IBP’s calculation capabilities.

Option A: Calculating the value of inventory on a weekly basis, using static aggregation from the daily levelThis is incorrect. Static aggregation (e.g., sum, average) across periods isn’t what LASTPERIOD does; it returns the last period’s value, not an aggregate.

Option B: Calculating how many periods inventory is going to last based on the planned demandThis is correct. Using the last period’s inventory value (via LASTPERIOD) divided by planned demand can estimate inventory duration, a common scenario in inventory planning, per SAP IBP’s documentation.

Option C: Searching for and returning the last not-null value of the inventory key figureThis is correct. LASTPERIOD retrieves the most recent non-null value in the horizon, ideal for tracking current inventory levels, per SAP IBP’s calculation guides.

Option D: Calculating the value of inventory on any level from the time profile, ensuring flexibility of calculationThis is incorrect. LASTPERIOD is time-specific (last period), not flexible across all levels; it’s not a general aggregation method.

Thus, B and C are valid scenarios for Last Period Aggregation, per SAP IBP’s official use cases.

The Advanced Dashboards app in SAP IBP creates customizable dashboards with analytical charts,per SAP IBP’s visualization documentation.

Option A: Use drill-down functionalityThis is correct. Drill-down (e.g., from region to product) is supported in charts, enhancing analysis, per SAP IBP’s features.

Option B: Add process instancesThis is incorrect. Process instances relate to process management (e.g., Process Automation app), not dashboard actions.

Option C: Link two analytics chartsThis is incorrect. Linking charts (e.g., synchronized filters) is more a feature of Analytics Stories, not Advanced Dashboards directly.

Option D: Rename the chartsThis is correct. Users can rename charts in the dashboard for clarity, a standard customization, per SAP IBP’s documentation.

Option E: Display all assigned analytics on a single UIThis is correct. The app consolidates assigned charts into one dashboard UI, a core feature, per SAP IBP’s guides.

Thus, A, D, and E are actions, per SAP IBP’s official Advanced Dashboards capabilities.

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 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.

The Time-Series Supply Optimizer in SAP IBP minimizes an objective function (cost-based), penalizing violations of soft constraints, while hard constraints must be fully satisfied, per SAP IBP’s optimization documentation.

Option A: Violation of minimum resource utilizationThis is correct. Minimum resource utilization (e.g., machine usage) is a soft constraint; violations incur penalties (e.g., underutilization costs), influencing the objective function.

Option B: Not respecting production capacityThis is incorrect. Production capacity is a hard constraint in the optimizer; it cannot be violated, only respected, unlike soft constraints with penalties.

Option C: Not fully satisfied demandsThis is correct. Unsatisfied demand (non-delivery) is a soft constraint, penalized via high non-delivery costs in the objective function, a core optimizer feature.

Option D: Violation of minimum aggregated inventory valuesThis is correct. Minimum inventory levels (e.g., safety stock) are soft constraints; violations are penalized (e.g., stockout costs), affecting the objective function.

Thus, A, C, and D are penalized solutions, per SAP IBP’s optimizer behavior.

The SAP IBP S&OP module focuses on demand, supply, and inventory alignment using time-series planning, per its standard functionality documentation.

Option A: Review critical resources against demandThis is incorrect. Resource capacity planning (e.g., finite scheduling) is part of Supply or Response modules, not standard S&OP, which uses infinite heuristics by default.

Option B: Conduct Sales and Operations Planning meetings with cross-functional representativesThis is correct. Facilitating S&OP meetings to align demand and supply (e.g., via Consensus Demand Plan) is a core S&OP process, per SAP IBP’s documentation.

Option C: Build what-if scenarios for breaching supply-demand gapsThis is correct. What-if analysis using versions/scenarios (e.g., adjusting supply plans) is standard in S&OP, per SAP IBP’s capabilities.

Option D: Prepare versions of S&OP plan based on different optimizer modeling costsThis is correct. The S&OP optimizer can model cost-based scenarios (e.g., varying non-delivery costs), a standard feature, per SAP IBP’s documentation.

Option E: Get system-solving recommendations on how to react to production bottlenecksThis is incorrect. Detailed bottleneck resolution is part of Response or finite planning, not standard S&OP functionality.

Thus, B, C, and D are covered by S&OP, per SAP IBP’s official module scope.

SAP IBP for Demand enhances demand planning with advanced features, per SAP IBP’s demand module documentation.

Option A: Automated, exception-based processingThis is correct. Automated forecasting with exception handling (e.g., alerts for outliers) is a core capability, per SAP IBP’s demand planning features.

Option B: Statistical analysis using the predictive analytics toolsThis is incorrect. Predictive analytics (e.g., machine learning) is available via SAP HANA integration, not a native IBP Demand tool.

Option C: Determination of coefficient of variation (CV)This is correct. CV (variability measure) is calculated in ABC/XYZ segmentation and demand analysis, a standard feature, per SAP IBP’s documentation.

Option D: Classifying demand into zonesThis is incorrect. "Zones" is not a standard demand classification in SAP IBP; ABC/XYZ segmentation is used instead.

Option E: Embedded, on-the-fly demand analyticsThis is correct. Real-time analytics (e.g., in Excel or Planner Workspaces) provide instant demand insights, per SAP IBP’s demand capabilities.

Thus, A, C, and E are key capabilities, per SAP IBP’s official demand planning scope.