C_IBP_2305 SAP Certified Application Associate - SAP SuccessFactors for Employee Central Payroll 2H/2022 Questions and Answers

Target key figures for these snapshots must have lag as a root attribute in its base planning level.

The number of lag-based snapshots are limited to nine levels.

Lag-based snapshots are created in the Configuration app for a fixed time range.

Target key figures for these snapshots are exposed to the user in planning views.

Time series analysis

Simple statistical forecast

Scenario analysis for operational supply planning

Multi-Level Supply Planning Heuristics

Changing the member names

Changing the layout of the master data workbooks

Changing the entries from the Name Manager

SAP IBP ribbon extension

IF("PERIODID4" ="$$PERIODID4CU$$...)

IF("PERIODID2" ="$$PERIODID2CU$$...)

IF("PERIODID3" ="$$PERIODID3CU$$...)

IF("PERIODID5" ="$$PERIODID5CU$$...)

The total number of attributes that can use subtotals in the planning view can be restricted.

The values of the attribute-based total at the highest attribute level in the planning level can be changed.

Only attribute-based totals can be added to the planning view.

The total value can be added before or after the selected attribute.

Use Excel Cell References in the Report Editor option is selected.

A key figure is selected in the Key Figures tab in the SAP IBP, add-in for Microsoft Excel.

Users should have authorization for template administration.

Activate Local Member Recognition setting is selected.

Add a new time profile level to the time profile.

Change the numbering hierarchy of the period IDs in the time profile.

Change the description of the attributes in the time profile.

Change the past and future horizon of the levels in the time profile.

Cloud Identity Authentication Service

Real-time Integration

Cloud Integration for Data Services

Smart Data Integration

Supply chain graph in Supply Chain Network app

Jobs in the Applications Jobs app

Planning view templates in the SAP IBP add-in for Microsoft Excel

Snapshot operator in the SAP IBP add-in for Microsoft Excel

Demand sensing of demand data using predictive analytics tools

Embedded, on-the-fly demand analytics

Detailed statistical analysis of demand data using predictive analytics tools

Consideration of demand-driven analysis for buffer positioning.

Quotas can be modeled for sourcing location, production, and consensus demand.

Because quota violations shouldn't be possible, the non-delivery cost rate is less than quota violation cost.

Min and Max Quotas have to be the same as sourcing ratios.

The optimizer will only violate quotas if quotas are maintained as time-dependent key figures.

Management business Review, by providing the inventory targets for endorsement

Demand Review, by using the output of demand planning as input into calculations

Supply Review, by providing an input to supply network planning

Reconciliation Review, by providing inventory parameters for one consolidated plan

Purge Key Figure Data

Purge Key Figure Data Outside Planning Area Planning Horizon

Purge Non-Confirming Data

Purge Master Data

This type of key figure is not usually stored and it cannot be set to editable.

This object is not exposed to the user in planning views or modeling.

This object contains user-defined criteria that monitor the running of business plans.

This object provides a single value for a unique planning combination.

Substitute missing values in case of sporadic demands.

Use forecasting algorithms that are specific to seasonal demands of SKUs in the segment "B".

Identify inventory items that require closer attention.

Choose time-independent key figures as segmentation measures.

Key figure type

Modified date

Scenario ID

Reason code

Attributes

Capacity leveling will be possible for production and storage resources.

Balance can be achieved between excessive prebuild and minimum use by incorporating violation costs.

Excess stock can be generated and will need to be staged in an overflow warehouse.

Minimum capacity utilization will result in pull production occurring.

Virtual Master Data Type

Reference Master Data Type

Compound Master Data Type

External Master Data Type

Adjust for forecast bias in Forecast Error CV calculations

Propagate forecast error to upstream locations in a supply chain network

Adjust Safety Stock Recommendations based on forecast error CV input

Identifiy intermittent demand for Forecast Error CV calculations

Comparison Chart Types

Seasonal Chart Types

Trend Chart Types

Geographic Chart Types

Simulation Chart Types

Simulate heuristics run in Supply Review stage

Simulate statistical forecast at the Demand Review stage

Simulate demand sensing inputs for Supply Review

Model inventory turns based on Target Safety stocks

Units of measure are usually not time-dependent.

Unit of measure is an attribute of a master data type, such as Product.

Units of measure are usually not time-independent.

Analytics provide the user with the option to select the target unit of measure.

Conversion to the target unit of measure is handled by SAP IBP Excel UI