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APO 7.0 Demand PlanningDelta Overview
SCM Solution ManagementOctober, 2008
© SAP 2008 / Summary developments APO 7.0 / Page 2
1. Customer Forecast Management2. Enhancements in Demand Forecasting3. Release and Consumption of Forecasts with Configuration
for VC4. Enhancements in APO Alert Monitor
Agenda
© SAP 2008 / Summary developments APO 7.0 / Page 3
Customer Forecast Management
1. Overview2. Basic settings3. Inbound processing4. Customer forecast analysis5. Waterfall analysis
© SAP 2008 / Summary developments APO 7.0 / Page 4© SAP 2008 / CFM - Claus Bosch, Page 4
Customer Forecast Management
My Company Customer
SAP APO
Forecast
Customer Forecast Management
CFMAnalyze customer
forecast
DPUse forecast for
downstreamplanning
© SAP 2008 / Summary developments APO 7.0 / Page 5© SAP 2008 / CFM - Claus Bosch, Page 5
Traditional Customer Forecast ManagementProcess
CustomerSupply Chain
Planner
Generatematerial
requirementsplan
Sendforecast to
supplier Use customerforecast fordownstreamsupply chain
planning
Key Pain PointsToo much variability in customer forecast impacting the MRP/Supply Planning processNo ability to intercept and analyze the incoming forecast (EDI/B2B) from customer -some companies adopt a manual Rip-and-Read processNo ability to track whether the new updated forecast has been received or not
© SAP 2008 / Summary developments APO 7.0 / Page 6© SAP 2008 / CFM - Claus Bosch, Page 6
Customer Forecast Management Process
Customer ServiceManager
Customer Supply ChainPlanner
Generatematerial
requirementsplan
Sendforecast to
supplier
Analyze Original Customer ForecastCheck forecast data for readinessand completenessCheck tolerances to comparedifferent versions of customerforecastsUse alerts and monitoringcapabilities
Load Original Customer ForecastUse IDoc functionality, Excel uploador manual input for entering data
Approve Customer Forecast for DemandPlanning
Integrate either original or adjustedcustomer forecast in demand and supplyplanning
Perform Waterfall AnalysisDownload customer forecast to Excelfor detailed analysis of data
Usecustomer
forecast forsupply chain
planning
© SAP 2008 / Summary developments APO 7.0 / Page 7© SAP 2008 / CFM - Claus Bosch, Page 7
Increased visibility of real customerdemandHigher responsiveness to short-termdemand fluctuationIncreased sales and lower lost salesthrough prevention of stock-outsOverall processing speed is improvedData entry errors and customer ordererrors are reduced due to automatedcommunicationImproved cooperation relationshipbetween the supplier and the customer
SAP APO Customer Forecast Management(CFM)
Powerful customer forecast analysisdashboardIntercept customer forecast and analyzetolerances, readiness and completenessof dataEfficient inbound processing – Usestandard IDoc functionality or CSV fileCustomizable profiles for forecastanalysisWaterfall analysis in structured ExcelformatStandard integration to APO DemandPlanning - use customer forecast tosense demand
Key BenefitsFeatures
Allows efficient management and understanding of the customerforecast by controlling, intercepting and analyzing incomingcustomer forecast.
© SAP 2008 / Summary developments APO 7.0 / Page 8© SAP 2008 / CFM - Claus Bosch, Page 8
Example scenario:Integrated scenario CFM with Consigned VMI
© SAP 2008 / Summary developments APO 7.0 / Page 9
Customer Forecast Management
1. Overview2. Basic settings3. Inbound processing4. Customer forecast analysis5. Waterfall analysis
© SAP 2008 / Summary developments APO 7.0 / Page 10© SAP 2008 / CFM - Claus Bosch, Page 10
Definition of basic settings
Define BI structures and objects to be used for datastorage and mapping You specify the settings for the
Demand Planning area from whichstatistical forecast can be read andused in forecast comparison
Specify tolerance value for bucketoffset in the inbound processing offorecast dataSpecify what to do if forecast datais incomplete
© SAP 2008 / Summary developments APO 7.0 / Page 11© SAP 2008 / CFM - Claus Bosch, Page 11
Maintenance of Forecast Release Profile
Define the release parameters for the release from Customer ForecastManagement to Demand PlanningUse BAdI /SAPAPO/CFM_DATA_RELEASE (CFM Data Release to SpecifiedDestination) if you want to release data to other applications than APO DP (e.g.APO SPP, SNP or ERP Demand Management)
© SAP 2008 / Summary developments APO 7.0 / Page 12© SAP 2008 / CFM - Claus Bosch, Page 12
Maintenance of Forecast Analysis Profile
Expected frequency ofreceiving customer
forecast
Expected horizon ofcustomer forecast
Definition of short-term,mid-term, long-term
horizon
Acceptable upside anddownside tolerance per
horizon
A product-location can be set to require a mandatory manual reviewDifferent versions of uploaded data can be compared
Make the settings necessary for performing an analysis of customer forecast data
© SAP 2008 / Summary developments APO 7.0 / Page 13© SAP 2008 / CFM - Claus Bosch, Page 13
Maintenance of key figure comparison andassignment
Determine the key figures to be compared and assign them to the forecast analysis profile
© SAP 2008 / Summary developments APO 7.0 / Page 14© SAP 2008 / CFM - Claus Bosch, Page 14
Assignment of release and forecast analysisprofile
You assign release and forecast analysis profile to location product master data onproduct, location or on a product group level.
Manual assignmentMass assignment (e.g. per customer location)
© SAP 2008 / Summary developments APO 7.0 / Page 15
Customer Forecast Management
1. Overview2. Basic settings3. Inbound processing4. Customer forecast analysis5. Waterfall analysis
© SAP 2008 / Summary developments APO 7.0 / Page 16© SAP 2008 / CFM - Claus Bosch, Page 16
Inbound Processing
You receive and store incoming original customer forecast data, and link it to aBusiness Intelligence (BI) InfoCube. This enables the vendor to process the data inCustomer Forecast Management.
Inbound processing supports both IDoc types PROACT and DELFOR with a newmessage variant CFM for both message types PROACT and DELINS.Additionally, data can be uploaded via CSV file.
If the forecast data provided by the customer has the form of an IDoc, the systemfirst loads the data to a temporary table (/SAPAPO/CFM_IDOC), and then abackground job uploads it to the InfoCube.
You can also enter the data manually on the CustomerForecast Management screen.
© SAP 2008 / Summary developments APO 7.0 / Page 17© SAP 2008 / CFM - Claus Bosch, Page 17
ManualAdjustment
Customer Forecast ManagementInbound Dataflow
Standard InfoCube9ACFM_C
ODS Object9ACFM_DS
MultiProvider9ACFM_MP
CFM application layercalculates reverse and
new records
Customer Forecast Management UI:Manual adjustmentof adjusted forecast
Customer Forecast Management UI:Manual adjustmentof adjusted forecast
Real Time InfoCube9ACFM_RC
Direct write accessagainst
Real Time InfoCube
IDoc table
/SAPAPO/CFM_IDOC
Takeover Adjusted Forecastkey figure from
previous version, if it was setin the CFM profile.
CSV File
Upload
© SAP 2008 / Summary developments APO 7.0 / Page 18© SAP 2008 / CFM - Claus Bosch, Page 18
BI structures
Predefined BI structures (InfoCubes,ODS,…) are available in thedata warehousing workbench
Predefined process chains are available toupload customer forecast either in a CSV file, oras an IDoc
© SAP 2008 / Summary developments APO 7.0 / Page 19© SAP 2008 / CFM - Claus Bosch, Page 19
Upload CSV file
For CSV upload use data format of data source 9ACFM_CSVMaintain the right file name in InfoPackage 9ACFM_CSV_LOAD or copyInfoPackage
© SAP 2008 / Summary developments APO 7.0 / Page 20
Customer Forecast Management
1. Overview2. Basic settings3. Inbound processing4. Customer forecast analysis5. Waterfall analysis
© SAP 2008 / Summary developments APO 7.0 / Page 21© SAP 2008 / CFM - Claus Bosch, Page 21
Forecast Analysis Run
You run a forecast analysis manually, or schedule it as a background job.The system checks forecast data for readiness and completeness, and comparesdifferent versions of forecasts performing a tolerance check.If violations occur, the system generates and outputs alerts.
© SAP 2008 / Summary developments APO 7.0 / Page 22© SAP 2008 / CFM - Claus Bosch, Page 22
Customer Forecast Analysis Dashboard
View customer forecast data grouped according to alerts generated during the forecastanalysis run.You can filter the forecasts, change predefined queries or create new ones, and you canalso personalize the table for displaying the results of the query.
Forecast notreceived per
expected frequency
Forecast durationnot for entire
expected horizon
New forecastexceeds specified
tolerance limits
New forecast received;requires mandatory manual
review/approval
GUI alternatives:NetweaverBusiness ClientInternet Browser
© SAP 2008 / Summary developments APO 7.0 / Page 23© SAP 2008 / CFM - Claus Bosch, Page 23
CFM Dashboard Detailed View
Per profile: Comparison ofnew customer forecast with
last customer forecast
Per profile: Comparison ofnew customer forecast with
new adjusted forecast
Adjust customer forecastas needed
Approve and release fordownstream planning
Make the necessary adjustments to the data, creating adjusted customer forecasts.Release the data to Demand Planning by approving the data on the CustomerForecast Management overview or detail screen.
© SAP 2008 / Summary developments APO 7.0 / Page 24© SAP 2008 / CFM - Claus Bosch, Page 24
Release customer forecast to DemandPlanning
You can release the customer forecast data in either of the following ways:You schedule an automatic forecast release run.You can specify the parameters for the run under Advanced Planning andOptimization Demand Planning Customer Forecast Management ForecastRelease Run (transaction /SAPAPO/CFM_FC_REL) .You manually approve the forecasts on the Customer Forecast Management UIscreen, and thus trigger a release of the data to the DP planning area defined inthe forecast release profile.
After releasing the data, the system automatically deletes the relevant forecasts fromthe work list.
© SAP 2008 / Summary developments APO 7.0 / Page 25
Customer Forecast Management
1. Overview2. Basic settings3. Inbound processing4. Customer forecast analysis5. Waterfall analysis
© SAP 2008 / Summary developments APO 7.0 / Page 26© SAP 2008 / CFM - Claus Bosch, Page 26
CFM Perform waterfall analysis
When needed, you can perform a waterfall analysis on the forecast data, whichenables you to view forecast quantities at different points in time.The output is exported to an Excel sheet.
© SAP 2008 / Summary developments APO 7.0 / Page 27
1. Customer Forecast Management2. Enhancements in Demand Forecasting3. Release and Consumption of Forecasts with Configuration
for VC4. Enhancements in APO Alert Monitor
Agenda
© SAP 2008 / Summary developments APO 7.0 / Page 28
Enhancements in Demand Forecasting
1. Forecasting Enhancement “MLR with POS”New Forecasting Algorithm to Incorporate AggregatedPOS Data in Forecasting
2. Statistical Forecast EnhancementReinitialization and trend dampening
© SAP 2008 / Summary developments APO 7.0 / Page 29
Using POS in Demand Planning & ForecastingMotivation and Business Benefits
MotivationLeveraging POS data in supply chain processes is becoming more important than ever to increase revenue,decrease costs and increase efficiency.
Consumer Products and Hi Tech companies continue to struggle with demand latency – „in both segments it takesmore than 2 weeks to sense channel sales.“ (Lora Cecere, AMR Research, May 2007)
Increasingly more CP companies are receiving consistent daily or weekly point-of-sale data directly from ansignificant number of retailers.
Demand Signal Repository (DSR) applications have reached a maturity level that allows POS data to be cleansedand mapped with the high level quality that is necessary for supply chain applications and processes.
Business BenefitsImprove demand visibility and response
typically shipment history includes effects such as logistic rounding, shipment scheduling, productsubstitution and availability effects and does not reflect the original demand.including POS data in forecasting counters the effects of historical inaccuracies and is closer to a forwardlooking view of demand patterns to come
Higher forecast accuracythe reduced demand latency and improved demand visibility leads to a higher forecast accuracy in the theshort to medium term forecast horizon, typically 2-8 weeks.including POS data in forecasting dampens the short term variability („bull whip effect“) in all stages of thesupply chain – and makes supply chain planning more stable – even down to the production schedule.
© SAP 2008 / Summary developments APO 7.0 / Page 30
A Quick Look at Different Approaches to Use POSin Forecasting
Different approaches to using POS in forecasting:
„exact“ methodusing detailed POS data (e.g. by store/sku/day) to create a store level POS forecast and includereplenishment parameters to calculate impact on manufacturer supply chainhighest benefit potential, but . . .time & resource-intensive – cpu & user
„qualtitative“ methodsincluding POS data in existing processes with no or marginal process extensionbenefit potential maybe not as high as exact methods, but . . .faster and easier to implement – „lowhanging fruit“
Approach is often a question of cost-benefit trade-off and strategic importance to company andrelationship to customer/retailer)
© SAP 2008 / Summary developments APO 7.0 / Page 31
Highlights of the new MLR Forecasting Method„MLR with POS“
combines statistical forecasting with causalanalysis
calculates fluctuation due to inventory in theretail supply chain(which is not visible to the manufacturer)
works with Life Cycle Planning
has its own alertsdiagnosis group using MAPEnew MLR with POS alert types in Alert Monitor
© SAP 2008 / Summary developments APO 7.0 / Page 32
MLR With POS - Algorithm in a Nutshell
Several sets of MLR iterations
1st regression run:dependent variable: week-to-week changes in (shipment) historyindependent variables: lagged week-to-week changesin shipment history and POS with different lagscalculated coefficients: inventory fluctuation
2nd regression runinventory fluctuation and statistical forecast used to calculateflux-adjusted forecastdependent variable: shipment historyindependent variables: expost forecast, inventory fluctuations
Check whether the data is sufficient to run the algorithmmin. 52 weeks or 364 daysfor seasonal: 2 seasonsotherwise error
Statistical forecasting methods:constant (min. 25 periods)seasonalno trend
© SAP 2008 / Summary developments APO 7.0 / Page 33
MLR Forecasting Using POSEnhancements in SCM 7.0
The scope of the new development includes:
New forecasting algorithm for POS dataincorporation
UI adjustment for the end user to set up theforecasting method as well as changing parameters ininteractive planning
New alerts for forecasting errors
© SAP 2008 / Summary developments APO 7.0 / Page 34
MLR Profile Enhancements for MLRForecasting Using POS Data
Current MLR Profile usedAdditional subscreen to select MLR methodNew settings:
History key figure and versionPOS key figure and versionForecast models: constant or seasonalOther parameters:– Save flux to key figure– Ignore leading zeros– Diagnosis group for interactive alerts
© SAP 2008 / Summary developments APO 7.0 / Page 35
Forecast in Interactive Planning
Run & adjust forecast ininteractive planning
Key figures:ForecastShipment historyPOS historyStatistical forecastInventory flux
Adjust forecast parameters ininteractive planning on the fly:
Forecast / history horizon ornumber of periodsStatistical forecast model &smoothing factorsKey Figure & versionOther parameters
View messages
© SAP 2008 / Summary developments APO 7.0 / Page 36
New Alert Types
Alerts
Insufficient data to execute algorithm
MAPE upper limit exceeded
Calculated MAPE greater than statistical forecast MAPE
© SAP 2008 / Summary developments APO 7.0 / Page 37
Enhancements in Demand Forecasting
1. Forecasting Enhancement “MLR with POS”New Forecasting Algorithm to Incorporate AggregatedPOS Data in Forecasting
2. Statistical Forecast EnhancementReinitialization and trend dampening
© SAP 2008 / Summary developments APO 7.0 / Page 38
Motivation and Business Benefits
MotivationCompanies struggle with dynamic market conditions leading to changes in sales history basis used for statisticalforecasting e.g.
changing numbers of ship-to destinations by changing customer locations
fast growth by entering new markets
In such an environment traditional forecast methods can lead to over forecast by not considering dampening trends
Improvements in competitive, state-of-the-art and scientific algorithms should be reflected as enhancements in DPforecasting
Business Benefits
Improve forecasting accuracy in a dynamic supply chain environmentShift planner’s time to more value added analytical tasksLess over forecasting in an automated system forecast
© SAP 2008 / Summary developments APO 7.0 / Page 39
SAP APO DP Forecast Improvements (1)
Introduce new means of limiting or dampening the trend while also providing a means tomake more generally applicable settings
Settings will be possible to maintain for a planning area as well as for UnivariateProfile
There are several possibilities to dampen the trend:use a trend dampening profileset an upper limit for the trend valueset an upper limit for the forecastuse the trend dampening factor Phi (applicable only for exponential smoothingmethods).
© SAP 2008 / Summary developments APO 7.0 / Page 40
SAP APO DP Forecast Improvements (2)
Improve reaction of exponential smoothing methods (for certain smoothing parameters) tostructural changes in the data by reinitialization.Reinitialization means the re-estimation of the forecast parameters basic value, trendvalue and seasonal indices when a structural change is detected in the historical data.Reinitalization settings apply only to exponential smoothing class of forecast methods.
A structural change is detected in the historical data by means of 2 measures:tracking signal (TS)normalized error (NE)
When the structural change was identified the forecast parameters (basic value, trendvalue, seasonal indices) are reinitialized from the historical values of the period that wasprocessed and the periods that follow.
© SAP 2008 / Summary developments APO 7.0 / Page 41
Structural change in history
© SAP 2008 / Page 41
Structural change
© SAP 2008 / Summary developments APO 7.0 / Page 42
SAP APO DP Forecast Improvements (3)
Offer new BAdI method for additional white noise test calculationNew white noise test is based on the Box-Pierce testUse BADI method /SAPAPO/SCM_FCSTPARA -> WHITE_NOISE_TEST to activate theBADI implementation containing the new white noise test
© SAP 2008 / Summary developments APO 7.0 / Page 43
1. Customer Forecast Management2. Enhancements in Demand Forecasting3. Release and Consumption of Forecasts with Configuration
for VC4. Enhancements in APO Alert Monitor
Agenda
© SAP 2008 / Summary developments APO 7.0 / Page 44
Overview
Motivation for CBCL Planning
Globalization leads to planning across locations and visibility of the entire supplynetwork.
Increasing customization of products leads to increasing requirement of planningwith characteristics.
ObjectiveTo enhance the cross location planning functionalities for the industries that are usingcharacteristics (e.g. Industries: Mill, Machinery & Components)To enable the industries, using cross location planning, to use characteristics(e.g. Industries: High Tech, Chemicals, Life Sciences)
© SAP 2008 / Summary developments APO 7.0 / Page 45
Release and Consumption of Forecasts withConfiguration for VC
Sales Order CreationForecasting
Demand Planning
Sales Orderwith Rqmt. Class Det.
Assignment ofCharacteristic Values
ATP Check
Delivery
Detailed Scheduling
Production Planning
Sales ProductionDistribution
Distribution Planning
Production ExecutionDeployment
Transport Load Building
Transport Execution
Forecast Release
Forecast ConsumptionIntegrated Distribution & Production Planning
© SAP 2008 / Summary developments APO 7.0 / Page 46
Release and Consumption of Forecasts withConfiguration for VC
ObjectiveEnable the planner to release forecasts with their own configuration for the VC schemeThese released forecasts can be consumed by the sales orders subsequently in caseof identical configuration
FeaturesThe planner can choose between releasing forecasts with own configuration or not, inthe customizing.
© SAP 2008 / Summary developments APO 7.0 / Page 47© SAP 2008 / CBCL Planning in APO 7.0 / Page 47
Characteristics Based Forecasting
Forecasting done using the CBF (Characteristics Based Forecasting) technique
© SAP 2008 / Summary developments APO 7.0 / Page 48© SAP 2008 / CBCL Planning in APO 7.0 / Page 48
Release of Forecasts with Configuration
Forecasts are released to SNP orPP/DS for planning (usingtransaction: /SAPAPO/MC90)Configuration are created accordingto the values in the CBF profile forthe characteristics restricted by theconsumption group.Requirement Strategy group chosen:35 (Planning Without Final AssemblyFor Configuration
© SAP 2008 / Summary developments APO 7.0 / Page 49
Forecasts with Configuration for VC
Released forecasts are available in a new planning segment –“Characteristic Based Planning without Final Assembly”
– The segment can contain multiple configurations– Stock transfer demands and dependent demands can also be created in this
segment
© SAP 2008 / Summary developments APO 7.0 / Page 50
Planning for Forecasts with Configuration forVC
– Forecasts in the segment can be planned with CTM and PP/DS planning run– Orders within this planning segment are not integrated with ERP
© SAP 2008 / Summary developments APO 7.0 / Page 51
Consumption of Forecasts with Configurationfor VC
Consumption of the forecasts by the sales orders happen only for matchingconfiguration
Possibility to release back the orders to DP/CBF considering configurationForecasts can be created from dependent demands for the components for the sameplanning version (using transaction /SAPAPO/DMP2)Filter for configuration available in Product View
Limitations:Multi-level configuration is not supported
© SAP 2008 / Summary developments APO 7.0 / Page 52
1. Customer Forecast Management2. Enhancements in Demand Forecasting3. Release and Consumption of Forecasts with Configuration
for VC4. Enhancements in APO Alert Monitor
Agenda
© SAP 2008 / Summary developments APO 7.0 / Page 53
Enhancements in APO Alert Monitor
1. Alert Profile Maintenance2. Overall Profile Maintenance3. Application Profile Maintenance
© SAP 2008 / Summary developments APO 7.0 / Page 54
APO Alert Monitor
Improve usability of alert profile maintenanceIn order to display and manage alerts the Alert Monitor uses alert profiles that specifyselection criteria for the checked business area. The alert profiles are created and maintainedby the users. In order to make the process of alert profile maintenance easier and friendlier anew user interface is to be implemented.
Improve performance of alert determination processIn case of large amount of alerts it can happen that the alert determination process runs for along time. In order to reduce response time of populating the overview screen of alert monitor,collection the detailed alert information, not necessary to populate the overview screens, willbe omitted.Moving the execution of alert determination process from ABAP to liveCache, as other way ofimproving performance, is also part of the development.
© SAP 2008 / Summary developments APO 7.0 / Page 55
Alert Profile Maintenance (main screen)
Check area:
When profile check performed,the result is displayed in thecheck area.
Profile can be activated only if noerror item is generated.
Profile Selection:
List existing profiles
Profile Detail:
Display and maintain profilesettings
© SAP 2008 / Summary developments APO 7.0 / Page 56
Alert Profile Maintenance (toolbar)
General profile functions (also available from context menu of selection tree)
• Display/change mode
• Create new profile
• Copy existing profile
• Delete profile
• Transport profile
• Search profile based on different criteria (name, description, alert type, transported, assignment, etc…)
• Check profile (consistency check, performance prediction, etc …)
• Activate profile (check performed successfully, ready to use)
• Run overall/application profile (for application profile „planning version + period” asked)
• User specific settings (favorite profiles, hierarchy, substitute settings)
© SAP 2008 / Summary developments APO 7.0 / Page 57
Alert Profile Maintenance (profile tree)
Provides an easy way to access alert profiles (overall & application)
Displays profiles grouped by profile type (overall, application)
Context menus for accessing general functions (create, copy, delete,etc) are available
© SAP 2008 / Summary developments APO 7.0 / Page 58
Enhancements in APO Alert Monitor
1. Alert Profile Maintenance2. Overall Profile Maintenance3. Application Profile Maintenance
© SAP 2008 / Summary developments APO 7.0 / Page 59
Overall Profile Maintenance
The overall alert profilecollects application-specific alert profiles anddefines the time periodfor which the systemdetermines alerts.
In the overall alert profile,you make the followingsettings:
• Period for which thesystem determines alerts
• Planning version
• Application-specificalert profiles assignment
© SAP 2008 / Summary developments APO 7.0 / Page 60
Enhancements in APO Alert Monitor
1. Alert Profile Maintenance2. Overall Profile Maintenance3. Application Profile Maintenance
© SAP 2008 / Summary developments APO 7.0 / Page 61
Application Profile Maintenance
Defines application-specificselection criteria for alertdetermination.
If you want to use the AlertMonitor to monitor anapplication, you must define anapplication-specific alert profilefor the application.
If you are working with SAPAPO, the following alert profilesare available to you:
• Available-to-Promise (ATP)Alert Profile
• Forecast Alert Profile
• Supply and Demand Planning(SDP) Alert Profile
•Transport Load Builder (TLB)Alert Profile
• Production Planning andDetailed Scheduling (PP/DS)Alert Profile
• Vehicle Scheduling (VS) AlertProfile
• Vendor-Managed Inventory(VMI) Alert Profile
© SAP 2008 / Summary developments APO 7.0 / Page 62
Application Profile Maintenance (attributes)
General attributes of application profile:
• Name (unique)
• Description (language dependent)
• Application
• Administrative data (actions performed by/at)
© SAP 2008 / Summary developments APO 7.0 / Page 63
Application Profile Maintenance (alert types)
Select alert types
• Displayed alert types are applicationdependent
• Configurable hierarchy ?
(corrently only fix hierarchy: alertobject type/alert type)
© SAP 2008 / Summary developments APO 7.0 / Page 64
Application Profile Maintenance (selection)
Specify selection:
Application dependent selection criteria
© SAP 2008 / Summary developments APO 7.0 / Page 65
Application Profile Maintenance (overallprofile assign)
Overall Profiles:
• List of overall profiles the application profile isassigned to
• Direct navigation to overall profile screen
© SAP 2008 / Summary developments APO 7.0 / Page 66
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