TUGAS SISTEM INFORMASI MANAJEMENCHAPTER 6MANAGERIAL SUPPORT SYSTEMS

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CHAPTER 6MANAGERIAL SUPPORT SYSTEMSManagerial support systems are the topic of this second of three chapters devoted to our survey of information technology (IT) application areas. Managerial support systems are designed to provide support to a specific manager or a small group of managers, and they include applications to support managerial decision making such as group support systems, executive information systems, and expert systems. Decision Support SystemsA Decision support systems (DSS) is a computer-based systems, almost always interactive, designed to assits a manager (or anoter decision maker) in making decisions. A DSS incorporates both data and models to help a decision maker solve a problem, especially a problem that is not well structured. The data are often extracted from a transaction processing system or a data warehouse, but that is not always the case. The model might be simple, such as a profit-and-loss model to calculate profit given certain assumptions, or complex, such as an optimization model to suggest loading for each machine in job shop.

All of the DSS examples cited are more properly called specific DSSs. These are the actual applications that assist in the decision-making process. In contrast, a DSS generator is a software package that provides a set of capabilities to build a specific DSS quickly and easily.Data MiningData Mining employs a variety of technologies (such as decision trees and neural networks) to search for, or mine, nuggets, of information from the vast quantities of data stored in an organizations data warehouse. Data mining, which is sometimes considered a subset of decision support systems, is especially useful when the organization has large volumes of transaction data in its warehouse.Uses of Data Mining1. Cross-sellingIdentify products and services that will most appeal to existing customer segments and develop cross-sell and up-sell offers tailored to each segment.2. Customer churnPredict which customers are likely to leave your company and go to a competitor and target those customers at highest risk.3. Customer retentionIdentify customer characteristics associated with highest lifetime value and develop strategies to retain these customers over the long term.4. Direct marketingidentify which prospects should be included in a mailing list to obtain the highest response rate.5. Fraud detectionIdentify which transactions are most likely to be fraudulent based on purchase patterns and trends; identify insurance claims that are most likely to be fraudulent based on similar past claims.6. Interactive marketingPredict what each individual accessing a web site is most likely interested in seeing.7. Market basket analysisUnderstand what products or services are commonly purchased together and develop appropriate marketing strategies.8. Market segmentationSegment existing customers and prospects into appropriate groups for promotional and evaluation purposes and determine how to approach each segment for maximum results.9. Payment or default analysisIdentify specific patterns to predict when and why customers default on payments.10. Trend analysisInvestigate the difference between an average purchase this month versus last month and prior months.Group Support SystemGroup support system (GSS) are an important variant of DSSs in which the system is designed to support a group rather than an individual. GSSs, sometimes called group DSSs or electronic meeting sytems, strive to take advantage of the power of a group to make better decisions than individuals acting alone. GSSs represent an attempt to make these group sessions more productive.Geographic Information SystemsGeographic information system (GIS), spatial decision support system (SDSS), location intelligence, geodemographics, computer mapping, and automated routing are names for a family of applications based on manipulation of relationships in space. Geographic technologies such as a GIS capture, store, manipulate, display, and analyze data spatially referenced to the Earth.1. Business Adopts Geographic TechnologiesGeographic technologies in business were a well-kept secret for many years; the earliest business adopters of GISs seldom talked about it because of its competitive value.2. Whats behind geographic technologiesTwo approaches to representing spatial data are widely used :a. Raster-based GISsRaster-based GISs rely on dividing space into small, equal-sized cells arranged in a grid. In a GIS, these cells (raters) can take on a range of values and are aware of their location relative to other cells.b. Vector-based GISsVector-based GISs are widely used in public administration and utilities and, arguably, are the most common approach used in business. Vector systems associate features in the landscape with either a point, a line, or a polygon.3. Issues for Information systems organizationsBusiness applications of GISs are often initially introduced into a company to support a single function such as market research or field service. Experience shows us that GISs soon spread within and across groups. Thanks to the maturity of GIS tools, organizations can acquire off-the-shelf geographic technologies with scripting languages, application program interfaces with popular desktop software packages, ad internet-based interactive mapping packages.Executive Information Systems/business intelligence systemsThe key concept behind an Executive information system (EIS) is that such a system delivers online current information about business conditions in an aggregate form easily accessible to senior executives and other managers. An EIS is designed to be used directly by these managers without the assistance of intermediaries. An EIS uses state-of-the-art graphics, communications, and data storage methods to provide the executive easy online access to current information about the status of the organization.As a result, today the user base in most companies has been broadened to encompass all levels of management in the firm-and sometimes even managers in customer and supplier organizations. Largely because of this broadening of the user base, today the EIS label has often been replaced with the broader term performance management (PM) software. The emphasis on competitive information has become so important in the last few years that many organizations now call their EISs business intelligence (BI) systems or competitive intelligence systems.

Knowledge Management SystemsKnowledge management systems (KMSs) are systems that enable individuals and organizations to enhance learning, improve performance, and, hopefully, produce long-term sustainable competitive advantage. Simply stated, a KMS is a system for managing organizational knowledge. A KMS is typically designed to support one of three connection strategies: connections from people to people, connections from people to knowledge, and connections from people to tools.KMSs use various hardware and software applications to facilitate and support knowledge management (KM) activities. What then is KM? KM is a set of management practices that is practical and action oriented. In other words, KM involves the strategies and processes of identifying, creating, capturing, organizing, transferring, and leveraging knowledge to help individuals and firms compete. KM is concerned with behavior changes to reflect new knowledge and insights. Therefore, a KMS is the technology or vehicle that facilities the sharing and transferring of knowledge for the purpose of disseminating and reusing valuable knowledge that, once applied, enhances learning and improves performances.Two recent KMS Initiatives within a Pharmaceutical Firm1. Corporate KMS A KM team was formed to develop an organization-wide KMS serving multiple communities of practice. The operation of a community of practice involves a combination of software and processes. Each community has a designated coordinator whose job is to ensure that the community thrives (some communities have two or three coordinators). The coordinators are volunteers and receive no extra compensation; however, they do tend to become highly visible members of their communities.2. FIELD SALES KMSA different KM team was formed to lead the development of the field sales KMS. Unlike the corporate KMS, this KMS teams mission was to design and build both the content and the structure of the KMS. Therefore, a knowledge taxonomy was developed so that knowledge about each of the drugs sold by the firm was organized separately.KMS SuccessWhat does it take for a KMS to be a success? One stream of research suggests that both the supply and the demand sides of KM must be considered simultaneously. In other words, organizational support factors on the supply side involving leadership commitment, manager and peer support for KM initiatives, and knowledge quality control and on the demand side involving incentives and reward systems, relevance of knowledge, ease of using the KMS, and satisfication with the use of the KMS are as important as the KMS itself and that these factors must be managed carefully and concurrently.Artificial IntelligenceThe idea of artificial intelligence (AI), the study of how to make computers do things that are currently done better by people, is well over 50 years old, but only in the last 30 years have computers become powerful enough to make AI applications commercially attractive. AI research has evolved into six separate but related areas; these are natural languages, robotics, perceptive systems (vision and hearing), genetic programming (also called evolutionary design), expert systems, and neural networks.Expert SystemsHow does one capture the logic of an expert in a computer system? To design an expert system, a specialist known as a knowledge engineer (a specially trained systems analyst) works very closely with one or more experts in the area under study. Knowledge engineers try to learn everything they can about the way in which the expert makes decisions. If one is trying to build an expert system for estate planning, for example, the knowledge engineer works with experienced estate planners to see how they do their job.

Obtaining an Expert SystemIt is necessary to build all these pieces each time your organization wants to develop and use an expert system? Absolutely not. There are three general approaches to obtaining an expert system, and only one of them requires construction of all these pieces. First, an organization can buy a fully developed system that has been created for a specific application. Second, an organization can develop an expert system itself using an artificial intelligence shell (also called an expert systems shell). Third, an organization can have internal or external knowledge engineers custom-build the expert system.

Neural NetworksWhereas expert systems try to capture the expertise of humans in a computer program, neural networks attempt to tease out meaningful patterns from vast amounts of data. Neural networks can recognize patterns too obscure for humans to detect, and they adapts as new information is received. The key characteristic of neural networks is that they learn. The neural network program is originally given a set of data consisting of many variables associated with a large number of cases, or events, in which the outcomes are known.Uses of Neural Networks

CategorizationPrediction/Forecasting

Credit rating and risk assessmentShare price forecast

Insurance risk evaluationCommodity price forecast

Fraud detectionEconomic indicator predictions

Insider trading detectionProcess control

Direct mail profilingWeather prediction

Machinery defect diagnosisFuture drug performance

Character recognitionProduction requirements

Medical diagnosis

Bacteria identification

Virtual RealityVirtual reality is a fascinating application are with rapidly growing importance. Virtual reality (VR) refers to the use of computer-based systems to create an environment that seems real to one or more senses (usually including sight) of the human user or users. VR exists today, but with nowhere near the reality of the Enterprises holodeck. You might have played a video game where you dont a head-mounted computer display and a glove to get directly into the action. The use of VR in a nonentertainment setting falls primarily into three categories-training, design, and marketing. Training examples will be presented first, followed by examples of the use of VR in design and in marketing.