How do information systems enhance core competencies

how do information systems provide competitive advantages and how information systems contribute to total quality management
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Dr.SamuelHunt,United Arab Emirates,Teacher
Published Date:21-07-2017
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1 Information Systems: Introduction and Concepts Information systems have become the backbone of most organizations. Banks could not process payments, governments could not collect taxes, hospitals could not treat patients, and supermarkets could not stock their shelves without the support of infor- mation systems. In almost every sector—education, finance, government, health care, manufacturing, and businesses large and small—information systems play a prominent role. Every day work, communication, information gathering, and decision making all rely on information technology (IT). When we visit a travel agency to book a trip, a collection of interconnected information systems is used for checking the availability of flights and hotels and for booking them. When we make an electronic payment, we interact with the bank’s information system rather than with personnel of the bank. Modern supermarkets use IT to track the stock based on incoming shipments and the sales that are recorded at cash registers. Most companies and institutions rely heavily on their information systems. Organizations such as banks, online travel agencies, tax authorities, and electronic bookshops can be seen as IT companies given the central role of their information systems. This book is about modeling business processes. A business process describes the flow of work within an organization. It is managed and supported by an information system. In this chapter, we first introduce information systems (section 1.1) and dis- cussdifferenttypesofinformationsystemsandtheirrolesinorganizations(section1.2). After introducing information systems, we look at the life cycle of these systems and concentrate on the important role that models play in this life cycle (section 1.3). Next, we show how to describe information systems in terms of states and state transi- tions (section 1.4). Although transition systems are not suitable for modeling industrial information systems and business processes, they illustrate the essence of modeling. Finally, we discuss the role of modeling and provide an outlook on the next chapters (section 1.5).2 Chapter 1 1.1 Information Systems Organizationsofferproductstocustomerstomakemoney. Theseproductscanbegoods or services. In most organizations, huge volumes of data accumulate: data of products, data of customers, data of employees, data of the delivery of products, and data of other sources. Thesedatathereforeplayanimportantroleincontemporaryorganizationsand must be stored, managed, and processed, which is where information systems come into play. Because there is no unique understanding of what an information system is, we developadefinitionofaninformationsysteminthissectionbyconsideringanexample organization everybody should be familiar with: a family doctor. Example 1.1 A patient who consults a family doctor usually first tells the doctor about the symptoms. With this information, the doctor examines the patient and makes a diagnosis. Afterward, the doctor determines the treatment to heal the patient. For ex- ample, based on the diagnosis, the doctor may write the patient a prescription for some medication. Finally, the doctor must document the symptoms, the diagnosis, and the treatments. Today, most doctors use a software system to record this information. Before we provide our definition of an information system, we first explain the term “information,” which can mean any of the following: 1. The communication act of one agent—the term “agent” may refer to any entity rang- ing from a person or a software component to an organization—informing another agent (e.g., by exchanging messages); 2. The knowledge or beliefs of agents as a part of their mental state; or 3. (Data) objects that represent knowledge or beliefs. Example 1.2 In the example of the family doctor, the situation in which a patient informs the doctor about the symptoms is an example of a communication act. The patient and the doctor are the agents in this example. The doctor uses her knowledge and the symptoms described by a patient to examine the patient. The doctor may have beliefs about possible causes based on earlier interactions with the patient. Based on the outcomes of the examination and on prior knowledge, the doctor makes a diagnosis. Thedocumentationofthesymptoms, ofthediagnosis, andofthetreatments in a software system leads to the creation of data objects. These data objects represent the new knowledge and may be used for various purposes—for example, for billing the insurance company of the patient. There are textbooks in which the authors distinguish between data, information, and knowledge. In these textbooks, the term “data” refers to the syntax, “information”Information Systems: Introduction and Concepts 3 refers to the interpretation, and “knowledge” refers to the way information is used. The data element “29-01-1966,” for example, may be seen as a string; in a particular context it may, however, be interpreted as the birthdate of a person, and people may use this information to congratulate this person on the twenty-ninth of January each year. In this chapter, we use the term “information” in a broader sense, as described earlier. Having explained “information,” we can define the term “information system.” The standard definition is that an information system manages and processes information. This definition is general and allows different interpretations. For example, it is not clear whether “information system” refers only to software systems or also to humans, such as a family doctor who manages and processes information. For this reason, we develop a more refined definition. The reason for “information system” having several meanings becomes clear when we consider Alter’s framework for information systems (Alter 2002) in figure 1.1. It shows an integrated view of an information system encompassing six entities: cus- tomers, products (and services), business processes, participants, information, and technology. Customersaretheactorsthatinteractwiththeinformationsystemthrough the exchange of products or services. These products are being manufactured or assembled in business processes that use participants, information, and technology. Participants are the people who do the work. Information may range from informa- tion about customers to information about products and business processes. Business processes use technology, and new technologies may enable new ways of doing work. Customers and participants are examples of agents. As figure 1.1 shows, business pro- cesses play a central role in larger information systems. A business process describes the flow of work within an organization. In this book, we use the following definition of a business process adapted from work by Weske (2007). Figure 1.1 An integrated view of an information system.4 Chapter 1 Definition 1.3 (Business process) A business process consists of a set of activities that is performed in an organizational and technical environment. These activities are coordinated to jointly realize a business goal. Each business process is enacted by a single organization, but it may interact with business processes performed by other organizations. Accordingtothisdefinition, abusinessprocessconsistsofcoordinatedactivities. Typ- ically, these activities must be performed in a particular order. For example, the family doctor first examines a patient and then makes a diagnosis. Although a business process is enacted by a single organization, it may interact with other business processes within and across organizational boundaries. For example, the family doctor may bill the insurance company of the patient. Diagrams like the one in figure 1.1 illustrate why it is difficult to provide a standard definition of an information system. Some researchers and practitioners hold a view thatallsixelementsconstituteaninformationsystem; otherresearchersandpractition- ers argue that only a subset (e.g., just business processes, information, and technology) constitutes an information system. Example 1.4 Let us pick up again the example of the family doctor. A patient serves as a customer, according to figure 1.1, and the product is health care. The business pro- cess describes the procedure of the medical treatment. It has five activities: a patient informs the doctor about the symptoms, then the doctor examines the patient, makes a diagnosis, determines the treatments, and finally the doctor enters the data into the software system. The doctor is a participant, pieces of information are the symptoms of the patient and the data added to the software system, and the doctor’s software system is the technology involved. Given these considerations, we present the following definition of an information system, which is adapted from Alter’s definition (Alter 2002). Definition 1.5 (Information system) Aninformationsystemisasoftwaresystemtocap- ture, transmit, store, retrieve, manipulate, or display information, thereby supporting people, organizations, or other software systems. In contrast to other definitions, we consider an information system to be a software system. A family doctor is, hence, not part of an information system. Furthermore, an information system may support not only an organization or a person but also other software systems and, hence, information systems. In addition, our definition of an information system does not require the existence of a business process; a text editorInformation Systems: Introduction and Concepts 5 is an example of an information system that has no business process. In this book, however, we concentrate on information systems in which business processes play a central role. Example 1.6 In the example of the family doctor, the information system is the soft- ware system that stores the data of the patient. This information system supports a person: the doctor. 1.2 Types of Information Systems In the previous section, we defined “information system.” Many types of information systems exist on the market. To illustrate this, this section first provides a broad classifi- cation of information systems. We then narrow our view to enterprise information sys- tems and present for this class of information systems an overview of existing types of software systems. Moreover, we provide examples of typical enterprise information systems in various industries. 1.2.1 Classifying Information Systems It is ambitious to classify the many types of information systems that have emerged in practice. Many classifications for information systems exist in the literature; see classi- fications by Alter (2002), Dumas, Van der Aalst, and Ter Hofstede (2005), and Olivé (2007), for instance. The problem is that classification is in flux; that is, a classification developed a few years ago is not necessarily current. As another and main limiting fac- tor, thecategoriesofaclassificationaretypicallynotdisjointed: onetypeofinformation system belongs to multiple categories. Given these problems, we present a high-level classification that distinguishes three classes of information systems. The first class of information systems is personal information systems. Such an infor- mation system can manage and store information for a private person. Examples are an address book or address database and an audio CD collection. Enterprise (or organizational) information systems are the second class of information systems. An enterprise information system is tailored toward the support of an organi- zation. We distinguish between generic types and technologies of information systems and information systems for certain types of organizations. The former class of enter- prise information systems supports functionality that can be used by a wide range of organizations. Examples are workflow management systems, enterprise resource planning systems, data warehouse systems, and geographic information systems. In contrast, information systems for certain types of organizations offer functionality that is tailored toward certain industries or organizations. Examples are hospital infor- mation systems, airline reservation systems, and electronic learning systems.6 Chapter 1 The third class of information systems is public information systems. Unlike personal information systems, public information systems can manage and store information that can be accessed by a community. Public libraries, information systems for muse- ums, Web-basedcommunityinformationsystems, andWeb-basedstock-portfolioinfor- mation systems are examples of public information systems. In this book, we concetrate on enterprise information systems. These systems play a crucial role in a wide variety of organizations and have an enormous economic value. The complexity and importance of such systems provide serious challenges for IT professionals ranging from software engineers to management consultants. Business processes and business process models play a dominant role in enterprise information systems. This explains why business process modeling is the focus of later chapters. 1.2.2 Types of Enterprise Information Systems There are many types of enterprise information systems in practice. This section gives an overview of the most important types. Enterprise Resource Planning Systems An enterprise resource planning (ERP) system is an information system that supports the main business processes of an organization— for example, human resource management, sales, marketing, management, financial accounting, controlling, and logistics. In the past, each business process was encapsu- lated in a separate information system. As most of these business processes use related data, much redundant data had to be stored within the respective information systems. The increasing number and complexity of information systems forced organizations to spend much effort in synchronizing the data of all information systems. An ERP system is a solution to overcome these synchronization efforts by integrating different information systems. It is a software system that is built on a distributed com- puting platform including one or more database management systems. The computing platform serves as an infrastructure on which the individual business processes are implemented. First-generation ERP systems now run the complete back office functions of the world’s largest corporations. ERP systems run typically in a three-tier client/server architecture consisting of a user interface (or presentation) tier, an application server tier, and a database server tier. ERP systems provide multi-instance database management, configuration manage- ment, andversion(orcustomization)managementfortheunderlyingdatabaseschema, for the user interface, and for the many application programs associated with them. As ERP systems are typically designed for multinational companies, they have to sup- port multiple languages, multiple currencies, and country-specific business practices. The sheer size and the tremendous complexity of these software systems make them complicated to deploy and maintain.Information Systems: Introduction and Concepts 7 ERP systems are large and complex software systems that integrate smaller and more focused applications; for example, most ERP systems include functionality that is also present in other enterprise information systems, such as procurement systems, manufacturing systems, sales and marketing systems, delivery systems, finance sys- tems, and workflow management systems. We introduce these systems in the following discussion. The market leader in the ERP market is SAP, with 43,000 customers for its system SAP ERP (data from 2009). Other important vendors are Oracle, Sage Company, and Microsoft. Procurement Systems A procurement system is an information system that helps an organization automate the purchasing process. The aim of a procurement system is to acquire what is needed to keep the business processes running at minimal cost. With the available inventory, the expected arrival of ordered goods, and forecasts based on sales and production plans, the procurement system determines the requirements and generates new orders. At the same time, it tracks whether ordered goods arrive. The key point is to order the right amount of material at the right time from the right source. If the material arrives too early, money for buying the material and warehouse space to store the material will be tied up. If, in contrast, the material arrives too late, then production is disrupted. Hence, the goal is to balance reducing inventory costs with reducing the risk of out-of-stock situations. Procurement is an important ingredient of supply chain management (SCM), in which coordination of the purchasing processes is not limited to two actors. Instead, SCM aims at closely coordinating an organization with its suppliers so that inefficiencies are avoided by optimizing the entire purchasing process. For example, by synchronizing the production process of an organization with its suppliers, all parties may reduce their inventories. The market leader in the SCM market is SAP with SAP SCM; competitors are Oracle and JDA Software (data from 2007). Procurement is related to electronic data interchange (EDI), the electronic exchange of information based on a standard set of messages. EDI can be used to avoid delays and errors in the procurement process as a result of rekeying information. In the classical (pre-EDI) situation, a purchase order is entered into the procurement system of one organization, it is printed, and the printed purchase order is sent to the order process- ing department or to another organization. The information on the printed purchase order is then reentered into the procurement system. By using EDI or technology such as Web services, organizations can automate these parts of the procurement process. The purchase order is electronically sent to the processing department or to the other organization. This automation makes the overall procurement process faster and less error-prone, thereby reducing the costs for each purchase order.8 Chapter 1 Manufacturing Systems Manufacturing systems support the production processes in organizations. Driven by information, such as the bill of materials (BOM), inventory levels, and available capacity, they plan the production process. With increasing automation of production processes, manufacturing systems have become more and moreimportant. Forexample, moststepsintheproductionlineofacar, suchaswelding the auto body, are performed by robots. This requires precise scheduling and material movement and, hence, a manufacturing system that supports these processes. Material requirements planning (MRP) is an approach to translate requirements (i.e., the number of products for each period), inventory status data, and the BOM into a production plan without considering capacities. Successors, such as manufacturing resources planning (MRP2), also take capacity information into account. Software based on MRP and MRP2 has been the starting point for many ERP systems. Consider an organization that produces different flavors of yogurt (e.g., strawberry, peach, and pear). The organization has several machines to produce yogurt; each mac- hine can produce any flavor. Production planning means scheduling each machine for the flavor of yogurt it must produce. The production plan depends on the demand for each flavor and on the delivery of ingredients. Furthermore, each machine has to be cleaned at regular intervals and when the production changes to a new flavor. Calculating a production plan is a complex optimization problem, often depending on several thousand constraints. Consequently, the aim is to find a good solution rather than an optimum solution. Sales and Marketing Systems Sales and marketing systems need to process customer orders by taking into account issues such as availability. These systems are driven by software addressing the four p’s: product, price, place, and promotion. Organizations undertake promotional activities and offer their products at competitive prices to boost sales, but a product that is not available or not at the right location cannot be sold. One prominent example of a promotional activity is a bonus card in supermarkets. Customers who register for a bonus card get a discount or a voucher. Bonus cards are an instrument for organizations to obtain personal data about their customers (e.g., age, address) and data about the buying behavior of customers (i.e., what they buy and whentheybuyit). Thesedataarecollectedandprocessedbyaninformationsystem. The information extracted from these data can help to improve marketing and to determine the range of products to offer. New technologies are increasingly used to support sales over the Internet. Electronic commerce uses the Internet to inform (potential) customers, to execute the purchase transaction, and to deliver the product. Again, this functionality is typically embedded in an ERP system. To manage the contact with their customers, organizations use ded- icated customer relationship management (CRM) systems. A CRM system has a database to store all customer-related information, such as contact details and past purchases.Information Systems: Introduction and Concepts 9 This information helps tailor the marketing efforts to expected customer needs. As an example, a car dealer does not need to send information about a new expensive sports car to customers who recently bought a van or a compact car. Delivery Systems A delivery system is an information system that supports the delivery of goods to customers. The task of these systems is to plan and schedule when and in what order customers receive their products. Consider, for example, a transportation company with hundreds of trucks. The planning of trips, the routing of these trucks, and reacting to on-the-fly changes require dedicated software. Creating an optimal schedule is a complex optimization problem. As circumstances—for example, traffic jams and production problems—may force rescheduling, contemporary delivery sys- tems aim to find a good solution rather than a theoretical optimum solution. More and more delivery systems offer tracking-and-tracing functionality; for example, customers of package delivery companies, such as UPS, can track down the location of a specific parcel via the Internet. FinanceSystems Among the oldest information systems arefinancesystems. These sys- tems support the flow of money within and between organizations. Finance systems typically provide accounting functionality to maintain a consistent and auditable set of books for reporting and management support. Another important application of finance systems is the stock market. At a stock market, dedicated information systems are essential to process the operations. Again, the functionality of finance systems is absorbed by ERP systems. The origin of the SAP system, for example, was in finance rather than production planning. ProductDesignSystems Enterprise information systems not only support the produc- tion of products, they also support the design of products. Examples are computer-aided design (CAD)systems andproductdatamanagement (PDM)systems. CAD systems support the graphical representation and the design of product specifications. PDM systems support the design process in a broader sense by managing designs and their documen- tation. Typically, there are many versions of the same design, and designs of different components need to be integrated. To support such complex concurrent engineering processes, PDM systems offer versioning functionality. Workflow Management Systems Many organizations aim to automate their business processes. To this end, they have to specify in which order the activities of a business process must be executed and which person has to execute an activity at which time. A workflow refers to the automation of a business process, in whole or in part. Each activity of the workflow is implemented as software. The workflow logic specifies the order of the activities. A workflow management system (WfMS) is an information system10 Chapter 1 that defines, manages, and executes workflows. The execution order of the workflow’s activities is driven by a computer representation of the workflow logic. The ultimate goal of workflow management is to make sure that the proper activities are executed by the right people at the right time (Aalst and Hee 2004). Not every business process corresponds to a single workflow. Workflows are case- based; that is, every piece of work is executed for a specific case. One can think of a case as a workflow instance, such as a mortgage, an insurance claim, a tax declaration, a purchase order, or a request for information. Each case is handled individually accord- ing to the workflow definition (often referred to as the workflow schema). Examples of business processes that do not correspond to a single workflow are stock-keeping processes; for example, in make-to-stock and assemble-to-order processes, end products or materials already exist before the order is placed (i.e., before the case is created, manufacturing or assembly activities have already occurred). For this reason, only frag- ments of such business processes (i.e., in-between stocking points) are considered to be workflows. Interestingly, WfMSs are embedded in some of the enterprise information systems alreadymentioned; forexample, mostERPandPDMsystemsincludeoneormoreWfMS components. Besides enterprise information systems, middleware software (e.g., IBM’s WebSphere) and development platforms (e.g., the .NET framework) embed work- flow functionality; see the WebSphere Process Server and the Windows Workflow Foundation. Examples of stand-alone WfMSs are BPMone, FileNet, and YAWL. Data Warehouses A data warehouse is a large database that stores historical and up- to-date information from a variety of sources. It is optimized for fast query answering. To allow this, there are three continuous processes: The first process extracts data at regular intervals from its information sources, loads the data into auxiliary tables, and then cleans and transforms the loaded data to make it suitable for the data warehouse schema. Processing queries from users and from data analysis applications is the task of the second process. The third process archives the information that is no longer needed by means of tertiary storage technology. Nowadays, mostorganizationsemployinformationsystemsforfinancialaccounting, purchasing, sales and inventory management, production planning, and management control. To efficiently use the vast amount of information that these operational sys- tems have been collecting over the years for planning and decision-making purposes, the information from all relevant sources must be merged and consolidated in a data warehouse. Whereas an operational database is accessed by online transaction processing (OLTP) applications that update its content, a data warehouse is accessed by ad hoc user queries and by special data analysis programs, referred to as online analytical processing (OLAP) applications. Inabankingenvironment, forexample, theremaybeanOLTPapplicationInformation Systems: Introduction and Concepts 11 for controlling the bank’s automated teller machines (ATMs). This application performs frequent updates to tables storing current account information in a detailed format. There may also be an OLAP application for analyzing the behavior of bank customers. A typical query that could be answered by such a system would be to calculate the average amount that customers of a certain age withdraw from their accounts by using ATMs in a certain region. To minimize response times for such complex queries, the bank would maintain a data warehouse into which all relevant information (including historical account data) from other databases is loaded and suitably aggregated. Queries in data warehouses typically refer to business events, such as sales transac- tions or online shop visits that are recorded in event history tables (i.e., fact tables) with designated columns for storing the time and the location at which the event occurred. An event record usually has numeric parameters (e.g., an amount, a quantity, or a dura- tion) and additional parameters (e.g., references to the agents and objects involved in the event). Whereas the numeric parameters are the basis for forming statistical queries the time, location, and reference parameters are the dimensions of the requested statistics. There aremultidimensionaldatabases for representing and processing this type of multidimensional data. The leader in the data warehouse market is Oracle (data from 2009). Business Intelligence Systems A business intelligence system provides tools to analyze the performance—that is, the efficiency and the effectiveness—ofrunning business pro- cesses. Thesetoolsextractinformationonthebusinessprocessesfromthedataavailable in an organization. Different tools and techniques exist, among them business per- formance management, business activity monitoring, querying and reporting, data mining, and process mining. Businessperformancemanagement concentratesonimprovingtheperformanceofbusi- ness processes. The goal is to extract information from the history of running business processes and to display this information on a management dashboard. For example, one could monitor a credit approval process to get insight into the length of time required to make the decision. In contrast to business performance management, business activity monitoring aims at providing real-time information on business processes and the activities in these business processes. The goal is to support decision making at runtime. Such a tool may monitor inventory levels, response times, or queues and take action whenever needed. Querying and reporting tools explore data (e.g., stored in a data warehouse) to provide insight into efficiency and effectiveness of business processes and trends in the envi- ronment. Typically, statistical analysis is applied to the data to distinguish between trends and isolated events. The term data mining refers to a collection of techniques to extract patterns from examples. Originally, the term “data mining” had a negative connotation (i.e., data12 Chapter 1 dredging, data snooping, and data fishing), but nowadays data mining is an estab- lished research domain with a huge impact. Examples of classical data mining tasks are classification (which arranges the data into predefined groups), clustering (like classifica- tion, but the groups are not predefined), regression (which attempts to find a function that models the data with the least error), and association rule learning (which searches for relationships between variables). Data mining techniques can be applied to any type of data and do not explicitly consider business processes. Processmining looks at data from the viewpoint of a particular business process. Infor- mation systems usually log the occurrences of events—for example, accepting an order, sending an invoice, or receiving a payment. The availability of such event logs, which contain footprints of a business process, enables the discovery of models describing reality. The resulting business process model can be compared with the specification of the business process and used for simulation and performance analysis. Process mining is discussed in section 8.5. Business intelligence is still a young discipline that will receive more acceptance and attention soon. Most commercial tools support business performance management, business activity monitoring, and querying and reporting rather than the more sophis- ticatedtechniquesofdataandprocessmining. Businessintelligenceissofarrestrictedto reporting information on running business processes and offers little support in terms of how a business process can be improved. The market leader in business intelligence is SAP (data from 2008) with SAP BusinessObjects; other main vendors are SAS, IBM, Oracle, and Microsoft. Examples of open-source projects providing data and process mining software are WEKA (Witten and Frank 2005) and ProM (Aalst, Reijers, et al. 2007). 1.2.3 Enterprise Information Systems in Different Industries The various types of enterprise information systems have different levels of granularity. For example, SAP Business Workflow is just one component in the large SAP ERP sys- tem, but its functionality is comparable to many stand-alone WfMSs. Functionality of software systems is more and more wrapped into services that can be accessed over the Internet, which allows software systems to be viewed at different levels of granularity. Organizations do not develop their enterprise information systems from scratch; they instead purchase large software suites that must to be customized, or they assemble a software system from components. Configuration corresponds to specifying informa- tionabouttheorganizationanditsbusinessprocessesandtoswitchingfunctionalityon or off. Organizations typically use only a small percentage of the functionality provided by software vendors, such as SAP. Similarly, few hospitals use all of the functionality provided by software vendors, such as ChipSoft and Siemens. The abundance of functionality in today’s enterprise information systems can be explained by looking at the cost of software. Development of enterprise informationInformation Systems: Introduction and Concepts 13 systems is extremely expensive, because these systems are—from an engineering point of view—highly complicated. However, once developed, software can be copied with- out much effort. This development cycle is completely different from that of physical products. For this reason, software vendors are tempted to provide an abundance of functionality that can be adapted to the customer’s specific requirements. As a result, software vendors shift efforts from software implementation to configuration of enterprise information systems. The application of a particular enterprise information system and its configuration depends on the industry an organization is operating in. For example, a hospital, a bank, a manufacturer, and a municipality may all use an ERP system, such as SAP, but the configurations will vary. Although all four organizations may use the financial com- ponent or the procurement component of SAP, it is likely that only the manufacturer is using the MRP component for production planning. In addition to standard compo- nents, theseorganizationswilluseindustry-specificenterpriseinformationsystems. For example, the hospital may use a dedicated radiology information system and an infor- mation system to create and maintain electronic patient records. The bank will have software to make calculations related to interest and mortgages, and the municipality will have software to access governmental administrations. The hospital, the bank, the manufacturer, and the municipality in this example may use the same WfMS (e.g., BPMone or YAWL), but the workflow schemas that are used to configure the systems of the four organizations are different. For example, the municipality will need to specify the business process for registering a newborn. This business process is irrelevant for the other three organizations. Given the various types of enterprise information systems and the many ways they can be configured, this chapter does not target specific industries or specific types of enterprise information systems. Instead, we concentrate on general principles of (enterprise) information systems. 1.3 The Life Cycle of an Information System There are various ways to develop an enterprise information system. Accordingly, the most important question a designer of such a system has to deal with is: how do I dev- elop an enterprise information system? To answer this question, we introduce a life cycle model of enterprise information systems. This life cycle model covers the phases of the development process of an enterprise information system. Enterprise information systems are complex software systems that are modified to reflect organizational needs and changes rather than developed from scratch. For this reason, the life cycle model includes phases that address change and redesign of existing enterprise information systems. Inthissection, weaimatbeingmoregenericandconsiderinformationsystems rather than enterprise information systems.14 Chapter 1 1.3.1 Introduction to the Life Cycle Model According to the integrated view of an information system shown in figure 1.1, an information system may include each of the six entities. In definition 1.5, we restricted informationsystemstosoftwaresystems, therebyrequiringthepresenceofthetechnol- ogyoffigure1.1. Whenconsideringthedevelopmentprocessofaninformationsystem, however, we interpret the information system in a more narrow sense in which just the software is taken into account. Information systems typically have two development processes. In the first development process, a generic information system is imple- mented; in the second development process, this system is customized. For example, for an ERP system, software vendors, such as SAP, implement new releases of their ERP system for other organizations. The implementation of the ERP system is guided by the development process of the software vendor. After an organization purchases an ERP system, this ERP system passes through the development process of the organization. In this second development process, the ERP system needs to be installed, configured, customized, and introduced in the organization. There can be mixtures of these two development processes. For example, the infor- mation system of a bank may be composed of selected components of an ERP system and of self-developed software components that provide specific functionality. In this case, the development process for building the information system for the bank includes a software development process similar to that of software vendors. Because of their tremendous complexity, existing information systems are usually redesigned and iteratively improved rather than replaced by a new system. As a consequence, the development process of an information system contains phases, such as maintenance and improvement. For example, in the information system of a bank, the ERP system may be reconfigured or upgraded to a newer version. Organizations develop and run information systems, which may involve software componentspurchasedfromotherorganizations. Peoplewhoaregoingtousetheinfor- mation system are the users or participants. People who design the information system or the products that are used to assemble the information system are the designers.In this section, we concentrate on the work of designers. Many life cycle models are described in the literature and used in practice. Some aim at the software development process (e.g., within companies), and others aim at the de- velopment of an information system in an organization (e.g., a bank). Our life cycle model, depicted in figure 1.2, is a mixture of both. Each rectangle illustrates a phase in the life cycle, and arcs represent the order of the phases. The main cycle models the development process of a new information system. It takes into account the develop- ment process of generic software, the development process of information systems that are customized from generic software, and a mixture of these development processes. The two smaller cycles, which contain shaded rectangles, model the development pro- cess of existing information systems—that is, the maintenance and the improvementInformation Systems: Introduction and Concepts 15 Figure 1.2 The life cycle model of an enterprise information system. of running information systems. In the following sections, we discuss the life cycle model of figure 1.2 in more detail. 1.3.2 A Software Development–Oriented Life Cycle The life cycle model in figure 1.2 is based on the observation that information systems are complex, customized (i.e., made-to-order) software systems whose development requires many man-years. Developing an information system can be compared to con- structingatunnelormanufacturingacar. Itisusuallyorganizedintheformofaproject. The main cycle in figure 1.2 specifies the development process of a new customized information system, which is the focus of this section. We distinguish the following eleven phases for customized information systems: requirements phase, design phase, design analysis phase, implementation phase, production phase,distributionphase,deploymentphase,configurationphase,executionphase,monitoring phase, and runtime analysis phase. Not all of these phases are relevant for all informa- tion systems; for example, production, distribution, and deployment phases are only relevant in the case of generic (i.e., made-to-stock) information systems, such as ERP systems, Microsoft Office tools, or database management systems.16 Chapter 1 Models play an important role in the development process of an information system. A model describes the information system to be designed in a certain form (e.g., textual or graphical). Models can be displayed in many ways, but they are always intended to describe the information system or the business processes supported by it. The way in which such a description is expressed depends on the point of view from which we want to look at the information system and is determined by the purpose of the description. A model abstracts away from aspects that are considered not relevant for the model. There are countless modeling formalisms. Most of them are grounded in logic, set theory, algebra, or graph theory. Example 1.7 A bicycle map is a model of a geographic area and is intended to support cyclists. Not all aspects of the real landscape are present in the model. The bicycle map represents only those aspects that are important to the cyclists, that is, an overview of all bicycling tracks in the designated area. The map may display the bicycling tracks as blue, even though they have a different color in reality. Only the purpose of the model is important: cyclists want to see bicycling tracks on the map. A map of the same area designed for another means of transport (e.g., car or boat) would look different. Models may serve as anabstractdescription or as aspecification. An abstract description modeldescribesanalreadyexistinginformationsystem. Thismodelallowsustoanalyze the information system. In contrast, a specification model serves as a specification of what an information system is supposed to do. Such a model is intended to be used for constructing a new information system. The modeling of existing information systems and of information systems to be developed are considered in this book. We investigate business process–related aspects of information systems and use Petri nets extended with data, time, and hierarchy as a modeling formalism. In the following sections, we discuss the eleven phases of the main life cycle in fig- ure 1.2. The requirements phase and the design phase are of particular interest, because developing models is an essential part of these two phases. We further concentrate on the software development process of information systems. The configuration-oriented life cycle (e.g., configuring a customized information system) is discussed in section 1.3.3. Requirements Phase The requirements phase is the first phase in the main life cycle in figure 1.2. It involves collecting the various requirements for the information sys- tem and assembling a coherent requirements specification. In many cases, there is an existing information system that does not satisfy all requirements. It is then wise to analyze thoroughly what the existing information system does for its environment. The result of this analysis will inform which functionality of the existing information system should be preserved in the new one. We can also obtain valuable insights by analyzing the deficiencies of the existing information system and the reasons why aInformation Systems: Introduction and Concepts 17 new information system is being developed. After this analysis, we can formulate the requirements of the new information system. Example 1.8 The requirements phase in the development of a new (simplified) ATM leads to the following requirements. The ATM should allow its clients to query their current account balances and to withdraw money. If clients want to withdraw money, then the ATM should offer them several amounts, but it should also allow them to choose an amount of money. There are several restrictions. For example, the amount of money clients withdraw should be less than a maximum amount (e.g., 500 euros for each day), and it should not lower the client’s account balance below a predefined lower bound. Furthermore, if clients just query their current account balance, then their account balance should not change. The requirements refer to the functionality of the new information system and also to other (nonfunctional) aspects, such as costs, maintenance, and reliability. In the early requirements phase, requirements are expressed in ordinary language. This is important, because key users should be able to understand the requirements. Users typically express requirements in cooperation with designers. In the late requirements phase, requirementsareexpressedbyspecificationlanguagesandbymodelsresultingin adomainmodel thatcapturestheconceptsofthedomainunderstudy. Thedevelopment of requirements specifications is known as requirements engineering (Hull, Jackson, and Dick 2004). Exercise 1.1 Express the main requirements for an information system that advises travelers about a travel scheme (route and time) when they want to make a holiday trip. DesignPhase Thepurposeofthedesignphase istodeveloptwomodelsthataresuitable to communicate with the users and the software developers of the information system. First, designers derive a functional design model from the domain model. The functional design model is expressed in terms of general software modeling constructs, but it still abstracts away from specific implementation. Second, designers derive an implementa- tionmodel fromthefunctionaldesignmodelbytakingthetargetprogramminglanguage or implementation framework into account. A functional design model captures the functionality of the information system. This model typically consists of several diagrams that visualize (static) data models and (dynamic) business process models. It abstracts away from implementation details. This is especially important for the communication between users and designers. Users are laymen and should not be confronted with all details of the information system; instead, end users must understand relevant parts of the model to investigate whether the designer has correctly taken their requirements into account.18 Chapter 1 Designers can construct a functional design model for an information system in the form of an executable specification providing a formal description and a prototype of the information system. A prototype is an experimental first version that is used for testing a design and for gaining more insight into the requirements of the information system to be built. It does not normally implement the entire functionality of the information system. For instance, it may lack an ergonomic user interface, it may not provide the necessary security mechanisms, or it may not provide the required performance. At the beginning of the design process, the requirements of an information system are often incompletely and ambiguously specified. By constructing a model and doing experi- ments with a prototype, ambiguities and hidden requirements may be discovered. This helps ensure that the final information system satisfies the requirements of its users and avoids costly and time-consuming revisions at a later stage. The second model, which designers construct during the design phase, is an imple- mentation model. It is a detailed work design for the software developers who are going to implement the information system. There are usually several work designs, each reflecting a certain aspect or detail of the information system. Because it is essential that the implementation model conforms to the functional design model, the designer has to verify that these models match. Example 1.9 In the example of the ATM, the designer constructs a functional design model of the ATM on the basis of the previously developed domain model. The func- tional design model can be an algebraic specification of the static information (e.g., querying the current account balance returns an account balance in euros) and a busi- ness process model describing the order of activities (e.g., clients choose to withdraw money, next they can choose between a standard amount or a customized amount, and so on). In addition, the functional design model can contain a prototype showing the user the possible interactions with the ATM. With this model, the user and designer can discuss all open issues of the final design of the ATM. In the next step, the designer develops an implementation model based on the func- tional design model. This model may contain detailed information about how the database of the bank must be queried, how the chosen security mechanisms must be implemented, and how the interplay of the information system with the hardware of the ATM must be implemented. The implementation model serves as a basis for dis- cussion between the designer and the software developer to identify the way in which the ATM should be implemented. In the ATM example, the mediator role of the designer and the benefit of the two models becomes clear. The designer uses the functional design model to communicate with the user and the implementation model to communicate with the software developers.Information Systems: Introduction and Concepts 19 In the software development process, usually one person or a group of people plays the role of the designer and of the software developer. The distinction between the functional design model and the implementation model may then become blurred. In these circumstances, often the user cannot understand the model because it is too detailed, or the model does not sufficiently support the implementation because it is unclear or incomplete. Design Analysis Phase The role of the functional design model and the implemen- tation model is not only to serve as a basis for discussion between the designer and the user and between the designer and the software developer. Models abstract away from facts that are considered not relevant for the model, are less complex than the information system, and can, therefore, be analyzed. Analyzing the functional design model and the implementation model is the subject of the third phase of the life cycle, the design analysis phase. The goal of this phase is to gain insight into the model and, hence, into the infor- mation system to be implemented. If the model is an abstract description to be used to analyze an existing information system, the model must first be validated. Valida- tion checks whether the model correctly reflects the information system. A validated abstract description model and a specification model can be analyzed. There are several ways to analyze a model. Verification is an analysis technique to prove that the model conforms to its specification. A specification can be another more abstract model or a set of properties that the model must satisfy. Most verification techniques must explore (parts of) the states of the model and analyze whether the desired properties hold in every state. As the functional design model and the implementation model of an infor- mation system typically have many states, verification is often hard to achieve. For this reason, another analysis technique is used more frequently: simulation. The idea of simulation is to make the model executable and to run certain experiments (known as runs or scenarios). A model may allow infinitely many scenarios. Because only a finite number of scenarios can be executed, simulation does not typically visit all states of a model. Consequently, unlike verification, simulation can be applied to verify only the presence of errors but not their absence. Simulation is often applied for performance analysis. Performance analysis assesses key performance indicators, such as response time and flow time, to detect possible bottlenecks in the system during the design. Example 1.10 Using the ATM example, we can specify a scenario of a client who first queries an account balance and afterward withdraws 100 euros. By using simulation, we can execute this scenario on the model and check whether this model behaves as expected. Simulation also allows performance analysis; for example, we could check whether the database system can retrieve the current account balance within a certain time interval. It would be important to verify that clients cannot crash the ATM.20 Chapter 1 An overview of existing analysis techniques is provided in chapter 8. Implementation Phase The fourth phase in the life cycle model is the implementation phase. In this phase, the information system is constructed. Because an informa- tion system is a software system, construction means either programming the entire functionality from scratch or extending or reimplementing existing functionality. Nowadays, software projects increasingly develop generated code. Development tools, such as Eclipse, may generate template code to create a graphical user interface, for instance. The programmer can later modify and refine this generated code. This significantly increases a programmer’s productivity. ProductionPhase Thefifthphaseistheproductionphase, inwhichsoftwareofaninfor- mation system in prepared for distribution. Unlike classical manufacturing processes, it is relatively easy to produce software, because this boils down to copying and down- loading. For widely used standard products, such as database management systems and the Microsoft Office tools, however, the production of manuals, CDs, and so forth may be nontrivial. For product software, licensing issues may also require effort. Distribution Phase In the case of mass production, there is a sixth phase, the distri- bution phase. The goal of this phase is to make the information system available to its future users. The marketing for the information system is also a part of this phase. The production and distribution phases do not apply to customized information systems. Deployment Phase In the deployment phase, the information system is installed in its target environment, and the users of the information system are trained to use it or to work with it. For example, in the case of a health care system in a hospital, professionals must be trained. Training is important in other domains as well, because information systems, such as ERP systems and database management systems, provide a multitude of functionality. The deployment phase is the seventh phase in the life cycle model. Configuration Phase Many organizations do not implement their information sys- tems from scratch but instead buy standard software, which is often referred to as com- mercial off-the-shelf software or product software. In this case, the information system needs to be configured and customized to the organization and its business processes. Even when organizations develop their own software, there is often the need for config- uration. This is the subject of the eighth phase in the life cycle model, the configuration phase. For sectors such as financial accounting, inventory management, or production plan- ning, there are customizable standard software packages: ERP systems. These packages have many adjustable parameters, among them the standard currency and the date

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