Susanne Hess, Stefanie Lenz, Jochen Scheibler

Sales and Distribution Controlling with SAP® NetWeaver BI

Bonn � Boston

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Contents

Acknowledgments ..................................................................................... 9

1 Introduction .............................................................................. 11

1.1 Goals and Basic Principles ........................................................... 111.2 Sales in SAP ERP with the Sales and Distribution Component ..... 121.3 Overview of SAP NetWeaver BI .................................................. 15

1.3.1 SAP NetWeaver BI and Its Components ............................ 151.3.2 Benefits and Advantages of a Data Warehouse ................. 16

1.4 Summary .................................................................................... 18

2 SAP NetWeaver BI .................................................................... 19

2.1 The Basic Principles of Modeling in SAP NetWeaver BI ............... 192.1.1 Data Structures in a Data Warehouse ................................ 202.1.2 Extract, Transform, and Load (ETL) .................................... 23

2.2 The Basic Principles of Data Retrieval .......................................... 262.2.1 Extraction from SAP Source Systems ................................. 272.2.2 Document Extraction versus Extraction from SIS ............... 302.2.3 Delta Capability of DataSources ........................................ 312.2.4 Extension of DataSources ................................................. 322.2.5 The Extraction Process ...................................................... 32

2.3 Reporting Options in Microsoft Excel .......................................... 332.3.1 Defining Queries in the BEx Query Designer ..................... 342.3.2 Executing Queries with the BEx Analyzer .......................... 37

2.4 Web Reporting ........................................................................... 592.4.1 Web Application Designer ................................................ 602.4.2 Web Analyzer ................................................................... 702.4.3 Report Designer ............................................................... 712.4.4 SAP NetWeaver Visual Composer ..................................... 72

2.5 Summary .................................................................................... 73

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Contents

3 SD Sample Scenario .................................................................. 75

3.1 The Basic Principles of Data Models ............................................ 753.2 DataSources ................................................................................ 763.3 Data Staging ............................................................................... 77

3.3.1 DSOs for the Sales Document Area ................................... 773.3.2 DSOs for the Delivery Area .............................................. 813.3.3 DSOs for the Order Delivery Area ..................................... 823.3.4 DSO Objects for the Billing Document Area ..................... 85

3.4 InfoProviders .............................................................................. 873.5 MultiProviders ............................................................................ 883.6 Extended Data Model ................................................................. 88

3.6.1 Incoming Orders/Orders on Hand ..................................... 893.6.2 Cross-Company Stock Transfers/Purchase Orders .............. 943.6.3 Follow-on Documents ...................................................... 98

3.7 Summary .................................................................................... 100

4 Key Figures in the Sales and Distribution Process ................... 101

4.1 Sales and Distribution Key Figures — General Basics .................. 1014.2 Quotation Key Figures ................................................................ 102

4.2.1 Quotation Value, Quotation Quantity, Number of Quotations ....................................................................... 103

4.2.2 Order Probability and Expected Order Value .................... 1054.2.3 Open Quotations .............................................................. 1074.2.4 Success Quota and Accepted Quotation ........................... 1094.2.5 Rejected Quotations ......................................................... 1124.2.6 Expired Quotations ........................................................... 1174.2.7 Sales Cycle ........................................................................ 117

4.3 Order Key Figures ....................................................................... 1184.3.1 Incoming Orders and Orders on Hand .............................. 1184.3.2 Orders with Delivery or Billing Blocks ............................... 1394.3.3 Analysis of Business Processes .......................................... 139

4.4 Excursus: Orders on Hand and Incoming Orders via the SIS ......... 1414.5 Delivery Key Figures ................................................................... 144

4.5.1 Delivery Quantity, Delivery Value, and Documents ........... 1444.5.2 On-Time Delivery Performance ......................................... 1504.5.3 Delivery Time ................................................................... 153

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Contents

4.6 Billing Key Figures ....................................................................... 1544.6.1 Sales, Sales Volume .......................................................... 1544.6.2 Pricing Analysis ................................................................ 1554.6.3 Margin ............................................................................. 155

4.7 Key Figures in the Cross-Company Business ................................ 1564.7.1 Scenarios of the Cross-Company Processes ....................... 1564.7.2 System Examples .............................................................. 157

4.8 Summary .................................................................................... 162

5 Implementing the Key Figures in SAP NetWeaver BI .............. 163

5.1 Quotation Key Figures ................................................................ 1645.1.1 Quotation Value, Quotation Quantity, Number of

Quotations ....................................................................... 1645.1.2 Order Probability and Expected Order Value .................... 1685.1.3 Open, Rejected, and Accepted Quotations ....................... 1735.1.4 Success Quota and Rejection Quota ................................. 1765.1.5 Expired Quotations ........................................................... 1775.1.6 Sales Cycle ........................................................................ 178

5.2 Order Key Figures ....................................................................... 1805.2.1 General Order Key Figures ................................................ 1805.2.2 Incoming Orders/Orders on Hand ..................................... 1845.2.3 Implementing Different Standard Processes ...................... 1875.2.4 “Consignment” as an Example of Standard Processes ........ 1935.2.5 Evaluations for Outline Agreements .................................. 1945.2.6 Orders with Billing or Delivery Blocks ............................... 200

5.3 Delivery Key Figures ................................................................... 2035.3.1 Outstanding Deliveries per Order ..................................... 2045.3.2 Delivery Quantity, Volume, Number of Deliveries ............. 2055.3.3 Delivery Performance (On-Time Delivery Performance,

Delivery Time) .................................................................. 2075.4 Billing Key Figures ....................................................................... 211

5.4.1 General Billing Key Figures ............................................... 2115.4.2 Key Figures from Billing Conditions .................................. 2135.4.3 Margin Analysis ............................................................... 215

5.5 Key Figures in the Cross-Company Business ................................ 2165.5.1 Cross-Company Sales ........................................................ 217

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Contents

5.5.2 Cross-Company Stock Transfer .......................................... 2195.6 Summary .................................................................................... 220

6 Cross-Sectional Evaluations ..................................................... 221

6.1 Tools .......................................................................................... 2216.2 Evaluation via Visual Composer ................................................... 222

6.2.1 Details per Material .......................................................... 2226.2.2 Details per Customer ........................................................ 2276.2.3 Technical Background of the Visual Composer .................. 233

6.3 Evaluation via the Web Application Designer — The Sales and Distribution Overview Web Template ......................................... 235

6.4 Summary .................................................................................... 240

7 Summary ................................................................................... 241

The Authors ............................................................................................... 243

Index ........................................................................................................... 245

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SAP NetWeaver BI2

This chapter introduces you to SAP NetWeaver Business Intelligence (SAP NetWeaver BI) by first describing the basic principles of modeling in the SAP Business Information Warehouse (SAP BW) as well as the basic elements of data retrieval. Finally, the chapter describes the reporting options in Microsoft Excel and through the web.

The Basic Principles of Modeling in SAP NetWeaver BI2.1

The following sections provide an overview of the various SAP NetWeaver BI components, that is, the system’s data structures and the corresponding modeling or the definition of the basic objects in SAP BW. The description includes charac-teristics and key figures, as well as the DataStores that can integrate extracted and generated data.

You also define rules that must be adhered to when aggregating, correcting, chang-ing, consolidating, and updating extracted data. This is part of the extract, trans-form, and load (ETL) concept, which describes the areas of data extraction, data transformation, and data loading. The ETL concept also comprises the phases in which the data is extracted from the source systems and transferred into a SAP BW target structure according to specific transformation rules.

Another basic area of SAP NetWeaver BI is reporting. The goal and purpose of every SAP BW system is to store particular data in a format optimized for reporting. Based on this data, the evaluations are defined and made available to the users. The users have numerous navigation options to easily generate the required view for their data. They can also create new evaluations on the basis of existing data structures.

Reporting can either be carried out in a web-based portal or by means of a Micro-soft Excel-based tool called Business Explorer Analyzer. Sections 2.3, Reporting Options in Microsoft Excel, and 2.4, Web Reporting, provide more information on reporting.

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SAPNetWeaverBI2

Data Structures in a Data Warehouse2.1.1

In this context, we must first distinguish between the basic objects in SAP BW, that is, the InfoObjects and the InfoProviders that are necessary to store data. InfoObjects are the basic meta objects — the smallest units in SAP BW — which are key figures and characteristics.

Key figures are data fields that represent values or quantities. Examples of key fig-ures are amounts, such as sales order value or billing values; quantities, such as the delivered quantity; or numbers, such as the number of orders. The defining feature of a key figure is its aggregation behavior, which describes how a key figure is to be aggregated. Usually, the individual data records are summed; however, you can also use exception aggregations, for example, Last Value via an Aggregation Refer-ence Characteristic. The Last Value via the Month Characteristic option can be used for balance key figures because you can only create a correct balance in the course of time.

Characteristics further specify the key figures and define which view is supposed to be evaluated in reporting. They are the criteria that can be used to analyze the data. For example, the sales order value key figure can be analyzed per customer or per material. In this case, customer and material are the characteristics.

Characteristics can also have texts, attributes, and hierarchies. Texts are the descrip-tions of the characteristic attributes, for example, the name of the customer. Attri-butes are information that logically belongs to the characteristic. For the example of the customer characteristic, attributes could be the corresponding location, the sales district, the customer group, and so on. The hierarchy refers to the hierarchi-cal structure of the characteristic’s attributes, which are related to one another. For example, the customer characteristic can have a customer hierarchy that groups all customers of the enterprise by their location in the different countries.

Key figures and characteristics are summarized here:

Key figuresEE

EE Data fields that represent values and quantities (amounts, quantities, num-bers)

Particular aggregation behaviorEE

Example: sales order value, delivered quantity, number of billing doc-EE

uments

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TheBasicPrinciplesofModelinginSAPNetWeaverBI 2.1

CharacteristicsEE

Business reference objects for the key figures EE

Can have texts, attributes, and hierarchiesEE

Example: customerEE

The DataStore is a further important component in the data structure area. SAP BW includes various objects that can store data. Here, you must differentiate among the following data storage levels:

PSA Tables1.

DSOs2.

InfoCube3. s

PSA (Persistent Staging Area) tables are the lowest storage level. These flat tables depend on the source system and contain the fields that are provided by the source system. The data is stored unmodified and hasn’t been transformed in SAP BW yet. However, you can’t use the data within these tables for reporting. The data is only available as a kind of interim state for further updates within SAP BW. It may also be useful to analyze the data in the PSA tables for checking and testing purposes.

The DSOs (DataStore objects) make up the next data storage level, which are also flat tables. However, in contrast to the PSA tables, they can be used for reporting. DSOs contain the already mentioned InfoObjects as characteristics and key figures. DSOs are used in SAP BW for two reasons:

Storage of detailed dataEE They enable you to store detailed data, usually at document level. If neces-sary, you can use this data for reporting. However, this is more of an exception because evaluations are usually based on aggregated data. For example, if you want to analyze particular facts in a special case, you can access the detailed data (document level) by navigating to the data of a DSO.

ConsolidationEE and enrichment of data DSOs allow for a consolidation and enrichment of data across multiple levels. In this context, the lowest level usually includes data at document level. This data can be consolidated in several transformation steps and enriched with additional information. The resulting data is stored in additional DSOs, that is, the data is available at all stages in SAP BW and can be used for detailed or aggregated reporting as required.

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SAPNetWeaverBI2

Finally, you can store the data in InfoCubes, which are based on a multi-dimensional data model that enables optimum access to the data for reporting. An InfoCube also consists of various InfoObjects. Several dimension tables link the character-istics to the key figures that are defined in the fact table. This distribution of the characteristic combinations into various smaller dimension tables enables perfor-mance-optimized access to the data. In reporting, the characteristics contained in an InfoCube are used to access the attributes, texts, or hierarchies of this charac-teristic that are separately stored in master data, text, or hierarchy tables. Figure 2.1 shows an example of an InfoCube database schema.

Like DSOs and InfoObjects, InfoCubes are referred to as InfoProviders in the SAP BW system because they provide information for reporting.

Calendar Year/MonthCalendar YearMonthQuarterCalendar Day

Time Dimension ID

Dimension Table Time

Change Run IDRecord TypeRequest ID

Package Dimension ID

Dimension Table Package

Document CurrencySales Unit

Unit Dimension ID

DimensionTable Units/Currency

DivisionDistribution ChannelSales OrganizationCompany Code

Sales Area Dim. ID

Dimension Table Sales Area

Customer Number

Customer Dimension IDDimension Table Customer

Country of Sales Organization

Sales Organization

Master Data Table Sales Organization

Sales Staff Number

Text Table Sales & Distribution Staff

Country of Company Code

Company Code

Master Data TableCompany Code

Product HierarchyMaterial Number

Product Dimension ID

Dimension Product

Material GroupingMaterial Type

Material Number

Master Data Table Material

Customer Number

City, Street, Customer Group

Master Data Table Customer

Sales Staff Number

Sales Staff Dim. ID

DimensionTable Sales & Distr. Staff

Net Value of Billing ItemQuantity in Sales UnitCosts

Customer Dimension IDSales Area Dim. IDSales Staff Dim. IDProduct Dimension IDTime Dimension IDUnit Dimension IDPackage Dimension ID

FACT TABLE

Master Data Table

Dimension Tables

Fact Table

Sales Staff NameText Table

Net WeightNumber of Billing Items

Database Schema of an InfoCubeFigure 2.1

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TheBasicPrinciplesofModelinginSAPNetWeaverBI 2.1

In addition to the InfoCubes and DSOs, you can define MultiProviders in SAP BW. A MultiProvider links the data of multiple InfoProviders to allow cross-company reporting. You can use a MultiProvider, for example, to link the billing docu-ments to the open items of a customer to evaluate this information together in reporting.

MultiProviders don’t store data; instead, the data is read from the underlying Info-Cubes, DSOs, and InfoObjects for evaluations. MultiProviders only provide the structure that is used to link the data.

Extract, Transform, and Load (ETL)2.1.2

Now that you’re familiar with the data structures of SAP BW objects, you have to bring them to life, that is, fill them with data.

A critical prerequisite for extracting data from a source system is the DataSource. It contains all characteristics and key figures that are supposed to be extracted and filled via specific extraction logic. You’ll find further information in Section 2.2, The Basic Principles of Data Retrieval. To load sales order values and quantities into the SAP BW system, for example, you need a DataSource in the source system. Irrespective of whether a Business Content DataSource is available or whether you must define your own DataSource, this DataSource is made known in SAP BW through replication, which means the information on the delivered characteristics and key figures is provided in the source system and in SAP BW.

In the next step, you define the link between the information from the source system and the SAP BW objects. You must specify which characteristics and key figures of the DataSource correspond to the InfoObjects in the DataStores of the SAP BW system. This mapping is defined in transformation rules, which link a Data-Source to a data target, such as DSOs or InfoCubes.

There are various options to map information in accordance with these transfor-mation rules:

1:1 mappingEE A characteristic from the source system is mapped to an InfoObject in SAP BW without logic. This is the simplest transformation rule.

Mapping fixed valuesEE Fixed values are mapped to the InfoObjects, for example, for which no infor-mation from the source system can be delivered.

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SAPNetWeaverBI2

Creating a routineEE A routine enables you to use your own ABAP source code to map complex transformation logic. Routines are provided both for the individual InfoOb-jects that are contained in the data target and globally for the entire transfor-mation (start, end, and expert routine), for example, to enable cross-company calculations.

The transformation rules enable you to clean up, enrich, consolidate, or aggregate the data delivered from the source system. Consequently, the data can be stored in SAP BW in the best possible way according to your specific requirements.

In some cases, you may have to transform data across multiple stages, for example, when complex formatting and aggregations are required in addition to the actual logic or when data from different source systems is supposed to be standardized first and then processed using the same logic. To map such requirements, there are two different methods:

Storage via interim stepsEE To store data in interim steps means to use several DSOs in which data is respec-tively stored after a transformation step and then updated with the next trans-formation. This option can be used, for example, if you require stored data after specific transformation steps.

Interposing an InfoSourceEE If you don’t have to temporarily store data, you can also interpose an InfoSource. An InfoSource is a structure that consists of InfoObjects and can’t store data itself. It only provides the option to link two transformations to each other. First, the data is transformed from the source object (DataSource or DSO) to the InfoSource, and then transformed from the InfoSource to the target object (DSO or InfoCube).

To trigger and control the loading of data from the source system into the SAP BW system, two additional object categories are needed:

InfoPackages EE

Data transfer processes (DTPs) EE

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TheBasicPrinciplesofModelinginSAPNetWeaverBI 2.1

InfoPackages are used to request data from a source system and store it in the PSA tables in SAP BW. You can start the data extraction immediately or schedule it in the background, periodically if required. In the InfoPackage, you can use specific criteria to filter the data that you want to request. For this purpose, you’re pro-vided with the fields that were selected as selection fields in the DataSource of the source system. For example, if the Sales Organization field is a selection field, you can restrict the InfoPackage to a specific sales organization to load only this data into the SAP BW system. The system stores the imported data in the cor-responding PSA table. From there, you can update and store the data in further DataProviders within the SAP BW system.

Data transfer processes (DTPs) control the update of the data. Via DTPs, data origi-nally stored in the PSA table are updated into the data targets. For this process, you need an active transformation rule for the respective data target. If you must update data from a DSO or an InfoCube into additional data targets, both an active transformation rule and a DTP are required here as well.

The system can supply only one data target with data for each DTP. If various data targets must be supplied from one source, you will need to create multiple DTPs. You can load the data online via DTPs or by means of process chains by scheduling the process periodically in the background.

A process chain bundles several process steps and can include the entire data flow from the source system to the update of the data in the InfoCubes of SAP BW. A process chain can comprise various loading steps through InfoPackages, DTPs, or post-processing of the data targets, for example, setting up database indices and statistics or compressing data to ensure optimal performance.

You can execute process chains online with a direct start or initiate them in the background. Usually, they are periodically scheduled, for example, to supply the SAP BW system each night with the most up-to-date data from the source systems.

The data flow from the source system to the data targets in SAP BW is illustrated in Figure 2.2.

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SAPNetWeaverBI2

Process Chain

Business Warehouse System

DataSourceExtraction Logic

PSA Tables

Transformations

Data Transfer Process

InfoPackage

DSO Object

Transformations

Source System

InfoCube

InfoCube

Data Flow from the Source System to the Data Targets in SAP BW Figure 2.2

This section described the data flow from the source systems to the DataStores in SAP BW. The process and background of data retrieval in the source system were only outlined here, but the following section provides detailed information on these aspects.

The Basic Principles of Data Retrieval2.2

As already mentioned, SAP BW objects have to be supplied with data. The data supply begins with extracting the data from a source.

The DataSource is the central object in the data supply process because it provides the data for the extraction. The DataSource has a specific structure that is defined by the extract structure and is identical in the source and in SAP BW. An extractor selects and formats the data in the source system and transfers the data from the source to the input storage location of the SAP BW system, the PSA tables. The data is stored in the format in which it was determined by the extractor in the source and transferred into the SAP BW system through the DataSource. Data formatting as it’s carried out in transformations isn’t possible here.

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Key Figures in the Sales and 4 Distribution Process

The previous chapters introduced you to SAP NetWeaver Business Intelligence (SAP NetWeaver BI) and provided a sample scenario. To set up a key figure sys-tem in SAP NetWeaver BI, you must know the development process of data in the source system. This chapter deals with the key figures relevant for the sales and distribution (S&D) process. Initially, we address the general fundamentals of how basic information in SAP ERP is developed and look at which data is required for creating key figures in SAP NetWeaver BI. This is followed by a description of quo-tation key figures, order key figures, delivery key figures, billing key figures, and key figures for the cross-company business.

Sales and Distribution Key Figures4.1 — General Basics

In general, a key figure is an indicator for evaluating a subject. Business key figures are aggregated data, which is usually evaluated with reference to a period at char-acteristic level in order to measure the success or attainment of goals in specific areas. For the various enterprise areas (production, material management, sales, accounting and balancing, controlling, etc.), key figure systems have been devel-oped that correlate the individual key figures to achieve transparency of the suc-cess contribution of the respective subareas.

For the subarea of S&D, numerous key figures and key figure systems have been developed. Every enterprise must decide individually which key figures are sup-posed to be considered for the evaluation of S&D. The following criteria can be decisive:

Related industryEE

Business modelEE

Size of the enterpriseEE

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KeyFiguresintheSalesandDistributionProcess4

Market situationEE

Sales strategy and conceptEE

From this, it follows that for each enterprise, a suitable set of key figures needs to be configured, or rather that the relevant indicators must be selected from the existing key figure definitions. At this point, we don’t want to discuss a complete key figure system and map it in the system. We’d rather show you, using some sample key figures, how raw data is created in the S&D process of the SAP ERP application, which then is processed into key figures in SAP NetWeaver BI.

For this purpose, the S&D process is subdivided into the following steps: quota-tion, order, delivery, and billing. After we describe the corresponding key figures for each step, we outline the specifics in the cross-company business.

Quotation Key Figures4.2

The following key figures form the basis for evaluations in the quotation area:

Quotation valueEE

Quotation quantityEE (total of all items)

Number of quotation documentsEE

These key figures form the basis for the success analysis of the sales activity in this phase of the S&D process. The aim is to determine an enterprise’s success in the market, find the reasons for this success, and define the problem areas.

Building on that, the following questions must be considered for the success analysis:

What’s the total amount of quotation valueEE , quotation quantity, and number of doc-uments (or number of document items) within a certain period?

What are the absolute numbers of the open quotation valueEE (or quotation quantity, number of documents, number of document items)?

What’s the quota of open quotationsEE ?

What’s the absolute value of accepted quotations?EE

What’s the quota of accepted quotations (success quota of quotations)?EE

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QuotationKeyFigures 4.2

What’s the absolute value of rejected quotations?EE

What’s the quota of rejected quotations?EE

What’s the value of all quotations that have already expired?EE

What’s the quota of expired quotations?EE

For the description of key figures, the following pattern is used. First, you receive a brief description of the business background of key figures. Then, we outline where you can find the required raw data in the SAP ERP source documents for calculating the key figures. Following that, you learn which characteristics are interesting in addition to the “classic” characteristics (customer, country, material, sales area, etc.). The entire discussion is rounded off with a system example.

Quotation Value, Quotation Quantity, Number of Quotations4.2.1

Quotation value, quotation quantity, number of quotation documents, and num-ber of quotation items are counted among to the basic key figures in S&D. Here, no distinction is made with regard to the status (“open,” “accepted,” “rejected”). Rather, all quotations are considered that have been recorded within the analysis period specified as the selection period by the user. These values are also suitable to make period comparisons as well as target/actual comparisons.

Period comparisons and target/actual comparisons provide early indicators for the demand for products and services offered by the enterprise. The quotation value is the net value of all chargeable items of the quotation. The quotation quantity is the cumulative quantity of all items of a document. Here, you must make sure to not only evaluate the cumulative value of all items. Usually, the users want to know how the quotation value is distributed to the materials (or material groups and product hierarchies). This necessitates a quotation value for each quotation item.

We now gradually examine a source document in SAP ERP based on a system example. Figure 4.1 shows the item overview of a quotation.

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KeyFiguresintheSalesandDistributionProcess4

Item Overview in the Quotation in the SD Component (Transaction VA22)Figure 4.1

The quotation for the customer (DROBEDA Drugstore Trade Ltd. with Sold-to-party-number 1040) contains two items: one for material PR4711 and one for material PR4712. The Net value fi eld in the item row indicates the quotation valuefor the individual items. This value is stored in Table VBAP (Sales Documents: Item Data) in the NETWR fi eld. The order quantity is stored in the KWMENG fi eld of the same table. This information represents the source information for the key fi gures, quotation value and quotation quantity .

Figure 4.2 shows the same quotation as illustrated in Figure 4.1; now, however, the Sales tab is activated. The Order reason dropdown list provides the input options available, which are defi ned in the Customizing area of SAP ERP (Field AUGRU in Table VBAK Sales Document Header Data). This fi eld enables you to analyze the key fi gures quotation value, quotation quantity, and number of documents according to order reasons in addition to the classic key fi gures (sales area, country, customer, customer group, material, material group, etc.). This allows you to also evaluate the effi ciency of the different sales instruments (advertisement, fi eld sales, and campaigns). The fact that the fi eld is called Order reason and not quotation reason is confusing in this context because you need to specify here which sales activity the quotation is based on. In SAP ERP, however, all S&D documents (quota-tions, orders, returns orders, credit memo and debit memo requests ) are mapped in the same tables so that the fi elds are identical.

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QuotationKeyFigures 4.2

Selecting the Quotation Reason, Order Reason in the SD Component (Transaction Figure 4.2 VA22)

The order reasons are maintained in the sales and distribution (SD) component via the Customizing path SPRO • Sales and Distribution • Sales • Sales Documents • Sales Document Header • Defi ne Order Reasons. You must select the order reason during the quotation entry.

Order Probability and Expected Order Value4.2.2

You can specify the order probability for each item as an additional value in the quotation document. Via the order probability and based on the quotation value, the system calculates the expected order value.

Calculating the Expected Order Value

Net value : 4,300 EUR

Order probability: 70 %

Expected order value: 3,010 EUR

In the following sections, we continue with this example. Figure 4.1 shows that an order probability of 70% is specifi ed for each item respectively (VBAP-AWAHR

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245

A

ABAP source code, 24After image, 90Aggregated storage, 87Analysis, 83, 87Analysis of days overdue, 231, 232, 235Append structure, 32Attribute, 20Award, 98

B

Balance, 231Before image, 90BEx Analyzer, 37BEx Broadcaster, 237BEx Suite, 72Billing, 102, 121, 134, 148

Order-related billing, 154Billing block, 124, 139, 200, 202

Evaluation, 201Billing condition, 213Billing document, 85, 121, 124, 125, 128, 133, 134, 225, 230, 237

Delivery-related, 122, 154External, 156Internal, 156Order-related, 130

Billing item, 86, 211, 215Billing key figure, 154, 211, 212

Selection screen, 211Billing quantity, 230Business Content, 23, 27, 32, 76, 82, 85, 88, 89, 100Business Explorer Analyzer, 15, 33Business Explorer Broadcaster, 16Business Explorer Maps, 15Business Explorer Query Designer, 33Business process, 139Button bar, 236, 237

C

Cash discount, 213, 230, 231Characteristic, 20, 21, 45, 103, 119, 141

Free, 35Restrictions, 35Routine, 97

Chart view, 235Company code, 95Complexity, 83Condition, 54Condition data, 86Condition type, 78, 87, 155, 159

PI01, 159VPRS, 155

Consignment, 131, 232Consignment business, 134Consignment evaluation, 194Consignment fill-up, 131, 132, 140, 193Consignment issue, 131, 132, 133, 193Consignment pick-up, 131, 193Consignment process, 14Consignment returns, 131, 134, 193Consignment standard process, 193Consignment stock, 133, 223, 239Consignment store, 131, 132, 140Consolidation, 21Constant selection, 189, 197Container item, 65Contract, 136, 138, 194, 195, 196Contribution margin, 215, 216, 225Credit memo, 124

Credit memo item, 126Quantity credit memos, 125Value credit memo, 125

Credit memo and debit memo, 14Processing, 123Request, 104

Credit memo request, 123, 124Credit memos on hand, 125Cross company, 156

Business, 216Cross-company

Index

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Index

Process, 14, 144Sales, 94, 156, 157, 217Stock transfer, 89, 94, 219, 220, 157

Currency translation type, 214Currency unit, 172Customer discount, 213Customer master, 106

D

Data aggregation, 119Database schema, 22Data extraction, 77Data fields that represent values and quantities, 20Data flow, 25, 72, 81Data model, 75, 76, 82, 93, 95, 100

Multi-dimensional, 22DataProvider, 62Data retrieval, 26Dataset

Development, 91Data source, 27DataSource, 31, 32, 76, 77, 81, 83, 85, 86

Customer-specific, 29Generic, 29

Data staging, 77DataStore, 21Data structure, 20Data transfer process, 25Data warehouse, 16, 19, 163Debit memos, 126Default value, 35Delay in delivery, 229Deletion record, 91Delivery, 78, 102, 121, 122, 133, 142, 152, 158

Free of charge, 134Open, 144Picked, 144

Delivery block, 139, 200Delivery date, 137, 230Delivery detail, 83Delivery deviation, 239Delivery document, 121, 122, 146Delivery header data, 81

Delivery key figures, 144, 148, 204Delivery performance, 207Delivery processing, 144Delivery quantity, 144

Open, 146, 149Delivery quantity performance, 203Delivery status, 206Delivery time, 153Delivery value, 144, 147, 149

Determine, 144Open, 146, 149

Delta creation, 82Delta direct, 32Delta management, 79Delta procedure, 32Delta update, 77Design, 236Detailed data, 21Determination

Contribution margin, 215Expected sales order value, 98Incoming orders value, 91Margin, 215Number of quotations, 166On-time delivery performance, 150, 207Open quotations, 176Rejected quotations, 175Target value, 198Weighted average score, 210

Dimension table, 22, 87Document extraction, 28Document flow, 110, 120, 122, 127, 131, 135Document item, 96Document status, 110, 114DSO, 21, 22, 25, 27, 75, 77, 78, 81, 90, 93, 99

E

Early indicators, 103, 118End customer, 128End routine, 78ERP system, 12ETL, 19, 23Evaluation, 33Exception, 54

266 Book.indb 246 2/3/09 8:26:10 AM

247

Index

Exception aggregation, 167, 171Extraction, 96Extractor, 26, 27, 30Extract structure, 26

F

Flexibility, 75Follow-on document, 89, 98Formula variable, 168, 169, 170, 171, 178Form view, 235Form view element, 234, 235

Search manually, 234Function module, 29

G

Goods issue date, 152Goods issue posting, 121, 132, 133, 147Goods receipt posting, 126

H

Header status, 78Hierarchy, 20

I

Incoming orders, 89, 90, 93, 118, 120, 124, 130, 132, 134, 135, 138, 156, 157, 159, 184, 186InfoCube, 21, 22, 25, 27, 75, 80, 87, 93InfoObject, 20, 22InfoPackage, 25InfoProvider, 20, 22, 87Information structures, 141, 144InfoSet, 29InfoSource, 24Initialization, 32, 77Internal billing document, 217, 219Item, 152Item category, 126, 128, 129, 134, 139, 187, 188

Item overview, 114iView element, 234, 235

K

Key figure routine, 84Key figures, 20, 101, 104, 141

Basic key figures, 103Billing key figures, 101Condition key figures, 214Delivery key figures, 101Limit, 174, 187, 193Quotation key figures, 101Totals key figures, 192

Key figure system, 101

L

Line-item dimension, 87Loading performance, 75, 87Local formula, 51LO Data Extraction

Customizing Cockpit, 28

M

Mapping fixed values, 23Margin, 155, 215, 216, 225Master data, 239Master data ID table, 87Material management (MM), 128Material requirements planning (MRP), 12Menu area, 237Model, 221, 233Modeling, 19, 75, 234Monitor, 33MultiProvider, 75, 87, 88

N

Navigation attribute, 88Net value, 104, 105, 108, 198, 213, 215, 216, 218, 229, 230

266 Book.indb 247 2/3/09 8:26:10 AM

248

Index

New record, 90Number of accepted items, 173Number of billing documents, 211, 212Number of deliveries, 144Number of delivery items, 144Number of documents, 102Number of quotation items, 164, 165, 167Number of quotations, 103, 164, 165, 166, 167, 229

Formula, 166Number quotation documents, 102Number range, 97numbers), 20

O

Offset, 185, 186OLAP function, 17OLTP system, 16On-order stock, 129On-time delivery performance, 84, 141, 150, 203, 207, 208, 210, 229, 230

Formula, 207Scoring scheme, 151

Order, 95, 102, 200, 229, 239Open, 141, 143, 144Rejected, 183

Order condition, 77Order item, 142, 150, 229Order key figure, 118, 180Order on stock, 134Order probability, 105, 106, 107, 108, 168, 169, 170, 171, 178

Selection screen, 168Order quantity, 180, 225

Expected, 168, 170, 171Order reason, 104, 105, 108, 110, 113, 124Order schedule line, 79, 82, 83Orders on hand, 76, 89, 93, 118, 120, 124, 130, 132, 135, 138, 156, 157, 159, 184, 186

Determine, 118Orders with delivery or billing blocks, 139Order type, 129, 134, 139, 188Order value, 105, 180, 181, 229

Dynamic calculation, 107Expected, 107, 168, 170, 171

Outline agreement, 14, 134, 194Overhead rate, 213

P

Performance, 22, 75, 77Period, 101Portal role, 222, 236Preceding document, 98Pricing analysis, 155Pricing procedure, 155Process chain, 25Product hierarchy, 182, 206PSA table, 25Purchase order, 128Purchase order history, 130Purchase order value

Business volume, 130Purchase requisition, 128Purchasing document, 97

Q

Quantities, 20Quantity conversion type, 215Quantity reliability, 151Query, 29, 34, 79Query definition, 35, 40, 50, 68, 83, 163, 179, 210

Target value, 198Query Designer, 34Query property, 47Queued delta, 32Quota, 184Quota of open quotations, 102Quotation, 102, 103, 104, 112, 117, 120, 122, 239

Accepted, 109, 173, 229Expired, 117, 177Key figure, 228Open, 107, 173, 176, 207Rejected, 173, 175, 229Value, 229

Quotation item, 103, 111, 114, 115, 166, 171

266 Book.indb 248 2/3/09 8:26:10 AM

249

Index

Rejected, 173Quotation key figure, 101, 102, 164, 165, 166Quotation quantity, 102, 103, 104, 164

Accepted, 173, 175Open, 108Rejected, 175

Quotation value, 102, 103, 104, 107, 114, 164, 171, 173

Accepted, 173Open, 102, 108

Quote, 176

R

Rate, 229Raw data, 119Reason for rejection, 98, 115, 116, 174Rebate, 213Record mode, 90Reduced workload, 83Refresh a query, 53Rejection quota, 176Release order, 134, 136Release order statistics, 136Replication, 23, 32Report, 87, 93Report Designer, 71Reporting, 19, 33Reporting performance, 75, 87Requested delivery date, 150, 151, 164, 207, 230Returns credit memo, 127Returns delivery, 126Returns order, 104, 126Returns process, 14Returns processing, 126Returns stock, 126Revenue, 85, 184, 185, 191, 211, 218, 225, 231Reverse image, 90Routine, 24, 77

S

Sales, 122, 123, 124, 125, 126, 130, 141, 144, 154, 159Sales and distribution key figures, 101Sales and distribution process, 101Sales and distribution (SD), 14, 105Sales area, 95Sales cycle, 117, 229

Average per customer, 179Sales document, 77, 89

Item, 78Sales document type, 106Sales Information System (SIS), 119, 141, 156, 157, 184

SIS update, 119Sales order, 110, 111, 113, 117, 120, 121, 122, 133, 134, 142, 143, 146, 158, 218, 219

Item, 89Quantity, 98Value, 98

Sales quantity, 154, 211Sales volume, 154SAP Business Information Warehouse (SAP BW), 15SAP ERP, 104SAP NetWeaver Portal, 222Schedule lines, 138Scheduling agreement, 134, 137, 195, 198

Item, 137Processing, 138

Selection screen, 37, 227Quotation, 165

Signal element, 234Source code, 79Source document, 103, 126Source system, 19, 75, 77SQL statement, 87Staging area, 77, 78Standard order processing, 120Standard process, 187, 193Start routine, 90, 95, 96, 98Statistics date, 91Status information, 78Stock, 223Stock overview, 132Stock transfer order, 156, 161

266 Book.indb 249 2/3/09 8:26:10 AM

250

Index

Balaji Gaddam

Capable to Match (CTM) with SAP APO

This is the first book that explains and teaches all of the core functions ofSAP’s Capable-to-Match (CTM) functionality. This step-by-step guide forconfiguring CTM, including CTM Master Data selection, Order Selection,CTM Profile maintenance, and CTM configuration, educates readers on the basic aspects of CTM, such as Demand Prioritization, Supply Categorization, Multilevel Inventory, and Production Planning, as well asseveral advanced topics including, CTM planning for Safety Stock, SafetyDays of Supply, and Maximum Earliness.

approx. 260 pp., 85,– Euro / US$ 85

ISBN 978-1-59229-244-8, April 2009

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Stock transport order, 96, 219Submission of quotation, 98Subtotal, 213Success analysis, 102Success quota, 109, 112, 113, 115, 117, 176, 177, 184

T

Tab design, 65Table view, 29Table view element, 234

Top 10, 235Target/actual comparisons, 103Third-party business processing, 14Third-party item, 128, 129Third-party order item, 130, 131Third-party order processing, 127, 140Third-party purchase order, 130Time characteristic, 89Toolbox

BEx Analysis, 37BEx Design, 37

Tool tip, 223Top 10 list, 227Totals row, 170Transaction

LBW0, 30LBWE, 28VA02, 113, 123, 133, 136VA22, 105, 108, 111, 114, 115VA32, 137, 138VA42, 135, 136VD02, 107VOV8, 106

Transaction data, 27, 223

Transformation, 23, 76, 77, 78, 79, 93, 98Transparency, 83

U

Unit of measure, 172, 215Update, 76, 81, 119, 143, 144Update rules, 144Usage level, 136

V

Value chain, 13Value contract, 135, 137Vendor invoice, 129, 130, 162Visual Composer, 72, 221, 222, 233, 235

BI kit, 72Model-driven architecture, 72

W

Web Analyzer, 70Web Application Designer, 60, 221, 235, 237Web item, 62, 237, 239Web reporting, 59, 222Web template, 60, 221, 222, 231, 235, 238, 239Wizard, 227Workbook, 58

X

XHTML code, 61

266 Book.indb 250 2/3/09 8:26:11 AM