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SAP C_IBP_2502 Exam Syllabus Topics:

Topic	Details
Topic 1	General Configuration of a Planning Area: This section is aimed at SAP solution consultants and covers the configuration of a planning area. It includes defining key planning parameters, setting up structures, and ensuring the system is configured to meet business needs. Candidates will be tested on their ability to customize planning areas for optimal performance.
Topic 2	Key Figures & Attributes: This section of the exam measures the skills of supply chain analysts and focuses on the key figures and attributes used in planning. It covers how to define and configure key figures to ensure accurate data representation and decision-making. Candidates are also tested on their ability to manage attributes that support various planning scenarios.
Topic 3	Planning Operators & Application: JobsThis section is designed for demand planners and focuses on the configuration and execution of planning operators and application jobs. It includes an understanding of how these tools automate planning processes and improve system performance. Candidates will be tested on their ability to configure and execute jobs that support various planning functions.
Topic 4	User Interface: This section assesses the knowledge of business users in navigating and utilizing the SAP interface effectively. It covers how to interact with different features, customize views, and leverage UI functionalities for efficient planning and reporting. Candidates are expected to demonstrate proficiency in accessing and interpreting data within the system.
Topic 5	Solution Architecture & Data Integration: his exam section is aimed at solution architects who work with SAP data integration. It covers the fundamental concepts of integrating external data sources with SAP, ensuring seamless data flow between systems. Candidates need to understand how to maintain system architecture for optimized performance and reliability.
Topic 6	Demand Planning: This section measures the skills of demand planners and focuses on the core concepts of demand planning. It includes understanding forecasting techniques, demand sensing, and demand propagation. Candidates are tested on their ability to manage demand signals and align planning with business objectives.

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SAP Certified Associate - SAP IBP for Supply Chain Sample Questions (Q63-Q68):

NEW QUESTION # 63
What are some of the features of the network charts in SAP Integrated Business Planning for Supply Chain?
Note: There are 2 correct answers to this question.

A. You can create a network chart from the dedicated app, or use the Manage Analytics Stories app
B. To display the network chart, you need the Ship-From Location master data type in the planning area
C. You can create a network chart from the dedicated app, or use the Analytics Advanced app
D. The network charts visualize relationships between warehouse, plants, customer, and supplier, for finished goods

Answer: C,D

Explanation:
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.

NEW QUESTION # 64
Which options can be used to reduce the runtimes of a time-series optimizer run? Note: There are 3 correct answers to this question.

A. Use non-overlapping networks by using Subnetwork ID maintained at Location-Products to reduce the size of the problem
B. Eliminate the usage of telescopic time buckets
C. Increase the use of incremental lot size beyond the frozen horizon
D. Split into multiple planning areas to support weekly vs. daily planning needs
E. Keep the number of fair share segments small

Answer: A,B,E

Explanation:
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.

NEW QUESTION # 65
You are implementing a demand process in SAP IBP for sales and operations, and consider using the standard forecast key figures available in the sample planning area SAPIBP1. What are the first and last key figures in the logical progression of demand in the S&OP process?

A. Local Demand Plan first and Combined Final Demand last
B. Local Demand Plan first and Consensus Demand Plan Qty last
C. Statistical Forecast Qty first and Global Demand Plan Qty for S&OP last
D. Statistical Forecast Qty first and Consensus Demand Plan Qty last

Answer: D

Explanation:
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.

NEW QUESTION # 66
You are working with inventory key figures. What are some of the business scenarios where you can use the Last Period Aggregation function? Note: There are 2 correct answers to this question.

A. Calculating the value of inventory on a weekly basis, using static aggregation from the daily level
B. Calculating how many periods inventory is going to last based on the planned demand
C. Searching for and returning the last not-null value of the inventory key figure
D. Calculating the value of inventory on any level from the time profile, ensuring flexibility of calculation

Answer: B,C

Explanation:
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 demand This 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.

NEW QUESTION # 67
Which constraints are taken into account by the Time-Series-Based Supply Planning Heuristic (Infinite)?
Note: There are 3 correct answers to this question.

A. Aggregated constraints
B. Maximum lot size
C. Minimum lot size
D. Adjusted transportation receipts
E. Transportation lead time

Answer: C,D,E

Explanation:
The Time-Series-Based Supply Planning Heuristic (Infinite) in SAP IBP generates an unconstrained supply plan, ignoring capacity limits (e.g., resource availability) but respecting logistical and material constraints.
"Infinite" indicates infinite capacity, not infinite disregard for all constraints.
* Option A: Adjusted transportation receiptsThis is correct. Adjusted transportation receipts (e.g., confirmed receipts adjusted for delays)are considered as inputs to ensure the heuristic aligns supply with available stock movements, a standard feature in SAP IBP's time-series planning.
* Option B: Aggregated constraintsThis is incorrect. Aggregated constraints (e.g., total capacity across locations) imply finite limits, which the infinite heuristic does not enforce. It focuses on detailed, not aggregated, constraints.
* Option C: Maximum lot sizeThis is incorrect. While maximum lot size is a constraint in finite heuristics or optimization, the infinite heuristic does not cap production or transportation quantities, focusing instead on minimums and lead times.
* Option D: Transportation lead timeThis is correct. The heuristic respects transportation lead times (from Transportation Lane master data) to schedule supply receipts accurately across the planning horizon, a core logistical constraint in SAP IBP.
* Option E: Minimum lot sizeThis is correct. Minimum lot size (from Production Source or Transportation Lane) ensures that planned quantities meet minimum thresholds, a constraint enforced even in infinite planning to reflect realistic batch sizes.
Thus, A, D, and E are constraints respected by the Time-Series-Based Supply Planning Heuristic (Infinite), per SAP IBP's supply planning documentation.

NEW QUESTION # 68
......

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C_IBP_2502 BEST STUDY MATERIAL, C_IBP_2502 VALID TEST TOPICS

C_IBP_2502 Best Study Material, C_IBP_2502 Valid Test Topics