Pass the SAP SAP Certified Application Associate C_IBP_2502 Questions and answers with CertsForce

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.

SAP IBP offers multiple solvers for supply planning: finite heuristics, infinite heuristics, and the optimizer. Choosing the right solver for a complex supply chain involves evaluating their capabilities.

Option A: Finite heuristics work with demand prioritizationThis is correct. Finite heuristics respect capacity constraints and can prioritize demand (e.g., based on priority rules or fair share settings), making them suitable for complex scenarios, as per SAP IBP’s supply planning documentation.

Option B: Push and Pull production models are used by the optimizerThis is correct. The optimizer supports both push (supply-driven) and pull (demand-driven) models, optimizing production and inventory across the network, a key feature for complex supply chains, per SAP IBP’s optimizer capabilities.

Option C: Prioritization of demand elements one by one is achieved by unconstrained heuristicsThis is incorrect. Infinite (unconstrained) heuristics ignore capacity and don’t prioritize demand sequentially; they plan supply assuming unlimited resources, unlike finite methods.

Option D: Planning results can be generated faster by the optimizerThis is incorrect. The optimizer, while powerful, is typically slower than heuristics due to its complex constraint-solving, not faster, per SAP IBP’s performance comparisons.

Thus, A and B are critical review points for solver selection, per SAP IBP’s official solver descriptions.

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.

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.