Critical Component of ES Is Application Platforms
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Critical Component of ES Is Application Platforms
APPLICATION PLATFORMS
Another critical component of ES is application platforms. Much like the role of the operating system for your personal computer, application platforms serve as a type of “enterprise operating system” for a company’s ES landscape by allowing all of the various systems to communicate seamlessly with one another as well as with systems outside the company. SAP introduced its application platform, SAP NetWeaver, in 2003. SAP NetWeaver is now an integral part of SAP ERP and the SAP Business Suite. It contains the SOA capabilities needed to integrate SAP systems with non-SAP systems. In addi- tion, it provides companies with a toolset to build new composite applications or to plug in independent software vendor (ISV) applications on top of their core ERP and suite applications. Figure 2-5 illustrates how SAP NetWeaver interacts with the SAP Business Suite of applications.
Figure 2-5: SAP NetWeaver. Copyright SAP AG 2011
The SAP Business Suite, which includes SAP ERP, SAP® CRM, SAP® SCM, SAP® PLM, and SAP® SRM, runs on SAP NetWeaver. You can think of the relationship between the SAP Business Suite and SAP NetWeaver in terms of the relationship between Microsoft Offi ce and the Microsoft Windows oper- ating system. The SAP Business Suite consists of the applications that com- panies use to manage and execute their business processes, just as Microsoft Offi ce contains the applications that you use to accomplish tasks such as creat- ing a presentation, a document, or a spreadsheet. SAP NetWeaver orchestrates the communication among the applications, transporting the master data and technical information needed by the applications at different points in the pro- cess. Similarly, Microsoft Windows is an operating system that the Microsoft Offi ce applications use to communicate with one another and to access other
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capabilities and tools. SAP NetWeaver also contains several technical tools to help companies extend the SAP Business Suite applications, integrate with other non-SAP applications, and build (compose) new applications. In essence, SAP NetWeaver is the “operating system” for a company’s entire range of business processes.
DATA IN AN ENTERPRISE SYSTEM As we discussed earlier, a central component of any ERP system is the com- mon database that stores data related to all the processes. Without this func- tion, integrating the various processes would be diffi cult, if not impossible. Therefore it is essential to understand how data are organized in an ERP system. We address this topic in the following section. We then introduce the different types of data that are stored in an ERP system, and we identify basic data elements that are common to many processes. We will develop these top- ics and introduce additional data elements in later chapters that discuss spe- cifi c processes. For the purposes of this chapter we will restrict our discussions to the procurement and fulfi llment processes introduced in Chapter 1.
Data in an ERP system are used to represent the physical system in which process steps such as creating a purchase order and receiving goods are carried out. These steps generate data, which represent the outcomes of the steps. There are three types of data in an ERP system: organizational data, master data, and transaction data.
ORGANIZATIONAL DATA
Organizational data are used to represent the structure of an enterprise. Examples of organizational structure are companies, subsidiaries, factories, warehouses, storage areas, and sales regions. The three organizational data elements discussed in this chapter are client, company code, and plant (see Figure 2-6). Note that the terms organizational data, organizational levels, and
Figure 2-6: Organizational data
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30 CHAPTER 2 Introduction to Enterprise Systems
organizational elements are often used interchangeably, depending on the con- text. These data are relevant to many of the processes discussed in Chapter 1. We will introduce additional organizational data as needed in the various pro- cess chapters.
Client and Company Code
A client is the highest organizational level in SAP ERP. It represents an enter- prise consisting of many companies or subsidiaries. Each company within the enterprise is represented by a company code. Each company code represents a separate legal entity, and it is the central organizational element in fi nancial accounting. That is, fi nancial statements required for legal reporting purposes are maintained at the company code level. A client can have multiple company codes, but a company code must belong to only one client.
Figure 2-7 shows organizational data for GBI. Recall from Chapter 1 that GBI consists of two companies, one in the United States and one in Germany. GBI is represented by a client, and each of the two companies is represented by a company code, US00 and DE00, respectively.
Figure 2-7: GBI organizational data
Plant
A plant is an organizational element that performs multiple functions and is relevant to several processes. It is essentially a facility in which the following functions are performed:
- Products and services are created.
- Materials are stored and used for distribution.
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- Production planning is carried out.
- Service or maintenance is performed.
A plant can be a factory, a warehouse, a regional distribution center, a service center, or an offi ce. It can be a part of a building, an entire building, or a collection of buildings. In addition, a single building can house multiple plants. Consider, for example, a company that has several offi ces in a build- ing. Different services or activities, such as processing customer returns and providing technical support to customers, are performed in these offi ces. Each of these offi ces is defi ned as a separate plant. Just as a client can have multiple company codes, a company code can contain multiple plants. However, a plant can belong to only one company code.
As illustrated in Figure 2-7, GBI operates fi ve plants for the manufacture and storage of bicycles and accessories. Three plants are located in the United States—in Dallas (DL00), San Diego (SD00), and Miami (MI00). The Dallas plant is a manufacturing facility, whereas the other two are distribution centers from which products are shipped to customers. The Dallas plant ships prod- ucts to customers as well. The other two plants are located in Germany—in Hamburg (HB00) and Heidelberg (HI00). The Heidelberg plant operates as both a manufacturing facility and a distribution center, while the Hamburg plant is exclusively a distribution center.
Coca-Cola Enterprises provides us with a good example of a company that has several types of plants. Coca- Cola operates factories that produce both raw materials and fi nished goods. Some factories produce the syrup that forms the basis of the Coca-Cola products you are familiar with. Other factories combine the syrup with carbonated water during the bottling process to make the fi nished Coca-Cola products. The fi nished goods, which consist of cases of bottles and cans of Coca-Cola
products, are then shipped to regional distribution cen- ters for storage until they are transported to end cus- tomers, such as retailers. The syrup factory, the bottling factory, and the distribution center are all considered plants in Coca-Cola’s SAP ERP system.
Source: Coca-Cola Company Reports & CCE CIO presentation
at SAP Sapphire 2008.
Business Processes in Practice 2.1: Coca-Cola® Enterprises
MASTER DATA
Master data represent entities associated with various processes. For exam- ple, processes involve buying materials from vendors and selling materials to customers. In this example, customers, vendors, and materials are represented in an ERP system using master data.
The most commonly used master data in an organization is the material master. Materials are used in numerous processes. They are purchased, sold, produced, and planned for. They are used in maintenance and service, and in projects. Consequently, material master data are some of the most com- plex and extensively utilized data in an ERP system. In contrast, other master
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32 CHAPTER 2 Introduction to Enterprise Systems
data are relevant only to certain processes. For example, vendor master data apply to procurement, and customer master data are utilized in fulfi llment. This chapter will focus exclusively on material master data. We will consider other master data in the appropriate process chapters.
Material Master
Although materials are relevant to many processes, each process uses the materials differently. For example, the procurement process buys materials, the production process makes materials, and the fulfi llment process sells mate- rials. Each process, therefore, requires data about the material that may or may not be needed by other processes. For example, the procurement process requires data concerning who is responsible for purchasing the material and how much should be ordered. Similarly, the fulfi llment process utilizes data concerning product availability and shipping conditions.
It should be evident that because the material master is used in numer- ous processes, it must include a large amount of data. To manage these data, the material master groups them into different categories or views, each of which is relevant to one or more processes. Figure 2-8 illustrates the major views of data in the material master. Basic data, such as material number, description, and weight, are relevant to almost all processes. The other views are relevant only to certain processes. For example, purchasing data are rel- evant to the procurement process and sales data to the fulfi llment process. The data in each of the views will be explained in detail in the appropriate process chapters.
Material Types
Another factor that infl uences the type of data or view needed is the type of material. Materials are categorized into different material types based on the
Figure 2-8: Material master data
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way they are used in the fi rm’s operations. Each material type has different characteristics and is used for different purposes and in different ways. The material type determines which business processes are permitted to use the material. This, in turn, determines which types of data must be maintained for the material. Therefore, the data in the material master will vary for dif- ferent types of materials. Specifi cally, material type determines, for example, the screens that appear in the material master record, the department or function-specifi c data that must be maintained, how the material numbers are determined, the appropriate procurement types (in-house or external), and the general ledger accounts that need to be updated. Table 2-1 provides a list of commonly used material types.
Material Type Description
DIEN Services
ERSA Spare parts
FERT Finished goods
FHMI Production resources/tools
HALB Semifi nished goods
HAWA Trading goods
HIBE Operating supplies
IBAU Maintenance assembly
KMAT Confi gurable material
LEER Empty containers
NLAG Nonstock, nonvaluated material
PROD Product group
ROH Raw materials
UNBW Nonvaluated, stocked material
VERP Customer returnable packaging
WETT Competitive products
Table 2-1: SAP material types
The four most common material types are raw materials, semifi nished goods, fi nished goods, and trading goods. We describe and discuss these mate- rial types below. The terms in parentheses following the names are the SAP ERP abbreviation for that material type. These abbreviations are based on the German term for each type. GBI’s product structure (fi nished goods and trad- ing goods) is presented in Figure 2-9. Table 2-2 lists GBI materials grouped by material type.
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34 CHAPTER 2 Introduction to Enterprise Systems
Figure 2-9: GBI product structure
- Raw materials (ROH) are purchased from an external source—a vendor—and used in the production process. Typically, raw materi- als are not sold to end-customers. Consequently, the material mas- ter will contain data related to procurement and production but not fulfi llment. Examples of raw materials utilized by GBI are frames, wheels, tires, and tubes.
- Semifinished goods (HALB) are typically produced in-house from other materials (e.g., raw materials) and are used in the production of a fi nished good. Consequently, data related to production must be maintained for semifi nished goods. Front wheel assemblies are
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Data in an Enterprise System 35
Raw Materials Semifi nished Goods Finished Goods Trading Goods
- Derailleur gear assembly
- Wheel assembly • Deluxe touring bike (3 colors)
- Professional touring bike (3 colors)
- Men’s standard off-road bike
- Women’s standard off-road bike
- Elbow ads
- Knee pads
- Off-road helmet
- Road helmets
- Repair kit
- Air pump
- Water bottle cage
- First aid kit
- T-shirt
- Frame
- Seat kit
- Handle bar
- Pedal assembly
- Chain
- Brake kit
- Warranty document
- Packaging
- Tire
- Tube
- Wheel
- Nuts and bolts
Table 2–2: GBI material list
an example of semifi nished goods from GBI. GBI purchases tires, wheels, and tubes and then uses these raw materials to create wheel assemblies.
- Finished goods (FERT) are created by the production process from other materials, such as raw materials and semifi nished goods. They are generally not purchased. As a result, the material master for fi nished goods will include data related to production and ful- fi llment, but not procurement. An example of a fi nished good from GBI is the deluxe touring bicycle, which is produced from raw mate- rials (e.g., frames) and semifi nished goods (e.g., wheel assemblies).
- Trading goods (HAWA), like raw materials, are purchased from a vendor. Unlike raw materials, however, trading goods are resold to customers. Signifi cantly, the company does not perform any addi- tional processing of the material prior to reselling it. Therefore, the material master for trading goods will include data related to pur- chasing and selling but not production. An example of a trading good from GBI is a helmet. GBI simply purchases the helmets from a sup- plier and resells them to its customers; no other steps are involved.
Material Groups
Related to material type is the concept of a material group, which includes materials with similar characteristics. For example, all of the materials used in the production of bicycles, such as tires and tubes—which are raw materials—and wheel assemblies—which are semifi nished goods—can be included in one material group called production. As another example, all bicycles, which are
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36 CHAPTER 2 Introduction to Enterprise Systems
generally fi nished goods but can also be trading goods, can be placed into one group called sales. Alternatively, bicycles can be grouped based on how they are used, such as touring and off-road. In the retail industry, material groups repre- sent merchandise categories such as footwear, clothes, and beverages. Materials are grouped so that they can be managed collectively. For example, planning for off-road bicycles is performed for all of the bikes in that material group rather than for individual bikes or brand names.
Organizational Level
A fi nal factor that determines the type of data included in the material mas- ter is organizational level. Materials can be defi ned differently for different organizational levels. For example, the same material can be used in multiple plants, but the ways it is used can vary from one plant to another. If a company exports materials from only one of its plants, for instance, then data related to exporting that material must be included in the material’s defi nition for that plant. These data are not necessary, however, for the other plants. As another example, GBI may choose not to ship bikes to customers from its Dallas plant. Rather, it sends the bikes to its two distribution centers (Miami or San Diego), which then ship them to customers. In this case, sales-related data for the bikes are included in the material master’s defi nition for the Miami and San Diego plants but not for the Dallas plant.
Demo 2.1: Review material types
Demo 2.2: Review material master data
TRANSACTION DATA
Processes are executed in the context of organizational levels, involve mas- ter data, and result in transaction data. Transaction data refl ect the conse- quences of executing process steps, or transactions. Examples of transaction data are dates, quantities, prices, and payment and delivery terms. Thus, trans- action data are a combination of organizational data, master data, and situ- ational data—that is, data that are specifi c to the task being executed, such as who, what, when, and where. The composition of transaction data is illustrated in Figure 2-10.
SAP ERP uses several different types of documents to record transac- tion data. Some of these documents are created or utilized as the process is being executed; others record data after the process steps are completed. We refer to the fi rst category as transaction documents. Examples are purchase orders, packing lists, and invoices. A purchase order communi- cates the company’s order to its vendor. A packing list accompanies the shipment sent by the vendor, and an invoice is a request for payment for materials shipped.
Documents that record data generated after the process steps have been completed include financial accounting [FI] documents, management
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Reporting 37
accounting or controlling [CO] documents, and material documents. These three documents are “virtual” documents in that they reside in the enterprise system and are printed only occasionally as needed. FI and CO documents record the fi nancial impact of process steps. For example, when a company receives a payment from a customer, there is a fi nancial impact, and an FI document is created. Material documents record materials movements, such as when materials are received from a vendor or shipped to a customer.
Documents typically consist of two sections, a header section and a detail or line item section. Figure 2-11 illustrates the concept of headers and items using an example of a purchase order, which is a type of transaction document. The top part of the document is the header. The three materials included in the purchase order—knee pads, elbow pads, and off-road helmets—are the line items. The header includes data such as purchase order number, date, and payment terms that are relevant to all line items, meaning that these data are relevant to the entire document. In contrast, the data in the line items, such as quantity and price, are specifi c to each item. A document can include multiple line items, as illustrated in the fi gure.
Demo 2.3: Review a purchase order
REPORTING As you have probably concluded from the discussions of master data, organi- zational data, and transaction data, enterprise systems produce and consume massive amounts of data in the day-to-day execution of business processes. In fact, it is not uncommon for companies to have several terabytes (trillions of bytes) of “live” data passing through their ERP systems on a weekly basis. More importantly, after data are no longer needed for process execution, they
Figure 2-10: Transaction data
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38 CHAPTER 2 Introduction to Enterprise Systems
Figure 2-11: Purchase order
then become historical data and must be archived securely and made available for many types of data analysis. This process generates many more terabytes of historical data that are stored in complex data repositories called data ware- houses. With such a massive volume of data to deal with, how can a company extract the meaningful information it needs to make better decisions and oper- ate more effi ciently?
At the most basic level, every enterprise system contains transaction and historical data in its main database. Transaction data relate to processes that are currently in use or have been completed recently, within days or weeks.
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Reporting 39
Conversely, historical data are typically comprised of transaction data for pro- cesses that have been completed within months or years. Reporting is a general term used to describe the ways that users can view and analyze both transac- tion and historical data to help them make decisions and complete their tasks. Reporting capabilities range from simple lists of information for basic users to analytical tools that can perform powerful statistical analysis and advanced cal- culations to produce extremely detailed information for specialist users. The data used in the different types of reporting are the same, but the ways in which they are extracted, fi ltered, and presented differ greatly and involve varying lev- els of complexity and expertise, depending on how employees plan to use them.
SAP ERP provides two reporting options—simple lists of data and docu- ments and analytics. Before we examine these options, however, we need to distinguish between the transactional environment and the analytic environ- ment of SAP ERP (see Figure 2-12). The transactional environment of SAP ERP is an online transaction processing (OLTP) system, which, as the name suggests, is designed to capture and store detailed transaction data. The primary function of OLTP is to execute process steps quickly and effi ciently; it is optimized for this purpose. OLTP is not used to generate sophisticated reports because it lacks the computing power to parse through and analyze the vast stores of data that most companies accumulate. Consequently, businesses employ OLTP to generate only simple lists and reports.
For detailed data analysis, SAP ERP includes an online analytic processing (OLAP) environment in the form of information systems. Instead of using detailed transaction data, these systems use information structures to provide analytic capabilities. Information structures capture and store specifi ed transaction data in an aggregated and summarized form that enables users to analyze the data as needed. Each information structure in the OLAP environment is defi ned in terms of three features: characteristics, key fi gures, and period defi nition (Figure 2-13). Characteristics are the objects for which
Figure 2-12: Reporting options within SAP ERP
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40 CHAPTER 2 Introduction to Enterprise Systems
Figure 2-13: Components of information structures
data are collected. These objects are typically organizational data such as plant and sales organization and master data such as materials, vendors, and cus- tomers. An information structure can include up to nine characteristics. Key figures are performance measures, such as quantities and counts that are associated with the characteristics. Examples are number of orders, quanti- ties ordered, order value, and invoice amounts. Thus, instead of recording the details of orders and invoices, key fi gures maintain only statistical summaries, such as the total number of orders placed by a customer. This is one level of aggregation of transaction data, and it is qualitative in nature because the selec- tion of key fi gures is subjective. Finally, data are collected or aggregated for specifi ed time periods, such as daily, weekly, and monthly, which are specifi ed in the period definition. In contrast to key fi gures, period defi nition represents a quantitative aggregation of data. Thus, information structures can be defi ned as aggregated and summarized forms of transaction data that are periodically updated.
In sum, then, the OLTP environment provides reporting in the form of lists, and the OLAP environment provides reporting in the form of analyt- ics via information systems. Going further, lists fall into two categories—work lists and online lists.
WORK LISTS
Work lists identify tasks that are scheduled to be completed in a process. In the fulfi llment process, for example, once customer orders are recorded in the system by the salespersons, warehouse personnel can retrieve a list of orders that are ready for picking. Picking is the fi rst step in preparing a shipment. It involves retrieving, or picking, materials from storage. A picking due list (Figure 2-14) identifi es all customer orders that must be prepared for delivery so that they can be shipped in a timely manner. The user selects the appropri- ate data, such as shipping location, due dates, and other relevant parameters (see inset in Figure 2-14). The resulting work list shows three orders that must be picked to ensure that they will be delivered on time. The user will select one of the orders and complete the picking task.
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Reporting 41
Figure 2-14: Work list—picking due list. Copyright SAP AG 2011
Demo 2.4: Review a work list
ONLINE LISTS
Online lists display lists of master data—such as materials, vendors, and pur- chasing info records—and documents—such as transaction documents, FI, CO, and material documents—that are generated during the execution of a process. The content and appearance of these lists are defi ned using selec- tion parameters and scope-of-list parameters. Selection parameters determine which documents will be included in the list, while the scope-of-list parameters defi ne which data will be included for the selected documents. In addition, numerous other parameters such as dates, master data (e.g., vendors), and organizational data (e.g., plant) can be used to narrow the data in the report. Figure 2-15 shows the initial screen for the display of purchasing documents. The inset shows choices for the selection parameters.
The reports are displayed in one of two available formats—a standard list format using the SAP list viewer or a grid format using the ABAP list viewer (ALV) grid control. Examples of these formats are provided in Figure 2-16 and Figure 2-17, respectively.
The list viewer and grid control provide several options for displaying the report output. These options are illustrated in Figure 2-18 and are explained as follows.
- The select detail allows the user to select a line on the report and drill down for more details.
- The set fi lter option is used to limit the list to only those items that meet specifi ed values. For example, the list can be restricted to purchase orders where the quantity ordered (one of the columns) exceeds a specifi ed value.
- Lists can be sorted in ascending or descending order in a selected column.
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42 CHAPTER 2 Introduction to Enterprise Systems
Figure 2-15: Online list—list display for documents. Copyright SAP AG 2011
Figure 2-16: Online list—report using SAP list viewer. Copyright SAP AG 2011
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Reporting 43
Figure 2-17: Online list—report using ALV grid control. Copyright SAP AG 2011
Figure 2-18: Functions of the list viewer and grid control
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44 CHAPTER 2 Introduction to Enterprise Systems
- The total values and create subtotals options enable users to calcu- late totals and subtotals for selected columns, respectively.
- The layout options allow users to change the appearance of the dis- play. The layout option displays a list of available fi elds that can be included in the report. Fields appear as columns in the report and can be added or removed as desired. The modifi ed layout can be saved as a variant of the report, which can be used to re-create the report at a later time.
- Several options are available to export the data in various formats, such as MS Word, Excel, and HTML. In addition, the data can be e-mailed using the system’s messaging capabilities.
Demo 2.5: Review an online list
INFORMATION SYSTEMS
Numerous information systems are available within SAP ERP to support most of the processes that we will discuss in this book. Information systems (IS) can be divided into three broad categories: logistics information systems (LIS), fi nancial information systems (FIS), and human resources information systems (HRIS). Logistics information systems support all of the logistics processes. Recall from Chapter 1 that logistical processes are concerned with acquiring, storing, creating, and distributing materials. The components of LIS include purchasing IS, sales IS, inventory control IS (IWM processes), quality man- agement IS, plant maintenance IS, and shop fl oor IS (production processes). The fi nancial information system supports reporting related to the general led- ger (e.g., balance sheet, income statement, statement of cash fl ows), accounts receivable, and accounts payable. The HRIS is used to retrieve information about different HR components such as personnel, positions, and jobs.
Recall that information systems are part of the OLAP component of SAP ERP, and they utilize information structures to provide analytic capabili- ties. There are two types of information structures—standard and user-defi ned. Standard information structures are predefi ned in the SAP ERP system, and they collect the data needed to generate the most commonly used reports. SAP ERP also enables users to defi ne their own structures, known as user- defined information structures, to meet specifi c reporting requirements.
Finally, information structures enable users to conduct two types of anal- ysis—standard and fl exible. Standard analysis provides predefi ned analytics for data in standard information structures. This type of analysis is suffi cient for most analytic requirements. When standard analysis is insuffi cient, users can conduct fl exible analysis to customize the reporting. In contrast to stan- dard analysis, flexible analysis allows users to defi ne the content and format of the analysis. Specifi cally, it enables users to combine available characteris- tics and key fi gures as needed and to create new key fi gures using user-speci- fi ed formulas. It also provides users with several layout options.
To summarize, the OLTP component of SAP ERP offers reporting in the form of work lists and online lists that are based on detailed transaction data. In contrast, the OLAP component offers reporting via information systems,
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Reporting 45
based on aggregated data in information structures. These capabilities are lim- ited to data within the SAP ERP system. Today, however, companies need even more powerful reporting capabilities that combine data from multiple sources. This is the domain of business intelligence, which we discuss next.
Critical Component of ES Is Application Platforms
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