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Level of Managerial Decision Making Information, Decision and Management DSS and Its Components Management Information Systems (MIS) Online Analytical Processing (OLAP) Geographic Information Systems (GIS) and Data Visualization Systems (DVS) Using Decision Support Systems Data Mining Executive Information Systems (EIS) Enterprise Information Portals
Decision Support in Business: •
Companies are investing in data-driven decision support application frameworks to help them respond to o o •
Changing market conditions Customer needs
This is accomplished by several types of o Management information o Decision support o Other information systems
Levels of Managerial Decision Making:
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Information Quality Information products made more valuable by their attributes, characteristics, or qualities o Information that is outdated, inaccurate, or hard to understand has much less value Information has three dimensions o Time o Content o Form Attributes of Information Quality:
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Decision Structure: Structured (operational) o The procedures to follow when decision is needed can be specified in advance Unstructured (strategic) o It is not possible to specify in advance most of the decision procedures to follow Semi-structured (tactical) o Decision procedures can be pre-specified, but not enough to lead to the correct decision BUSINESS INTELLIGENCE APPLICATIONS Figure shown below highlights several major information technologies that are being customized, personalized, and Web-enabled to provide key business information and analytical tools for managers, business professionals, and business stakeholders.
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Decision Support Systems: •
Decision support systems are computer-based information systems that provide interactive information support to managers and business professionals during the decision making process.
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A decision support system (DSS) is an information system designed to help users reach a decision when a decision-making situation arises.
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Decision support systems use the following to support the making of semi-structured business decisions
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Analytical models
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Specialized databases
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A decision-maker’s own insights and judgment
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An interactive, computer-based modeling process
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DSS systems are designed to be ad hoc, quick-response systems that are initiated and controlled by decision makers.
DSS Components: •
Decision support systems rely on model bases, as well as databases, as vital system resources.
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A DSS model base is a software component that consists of models used in computational and analytical routines that mathematically express relationships among variables. Page # 4
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For example, a spreadsheet program might contain models that express simple accounting relationships among variables, such as Revenue 2 Expenses 5 Profit. A DSS model base could also include models and analytical techniques used to express much more complex relationships.
Applications of Statistics and Modeling • • • • •
Supply Chain: simulate and optimize supply chain flows, reduce inventory, reduce stock-outs Pricing: identify the price that maximizes yield or profit Product and Service Quality: detect quality problems early in order to minimize them Research and Development: improve quality, efficacy, and safety of products and services Customer selection, loyalty: Identify customers with the greatest profit potential
Management Information Systems (MIS): •
The original type of information system that supported managerial decision making
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Produces information products that support many day-to-day decision-making needs
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Produces reports, display, and responses
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Satisfies needs of operational and tactical decision makers who face structured decisions
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Management Reporting Alternatives: Management information systems provide a variety of information products to managers. Four major reporting alternatives are provided by such systems. •
Periodic Scheduled Reports o Pre-specified format on a regular basis
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Exception Reports o Reports about exceptional conditions o May be produced regularly or when an exception occurs
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Demand Reports and Responses o Information is available on demand
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Push Reporting o Information is pushed to a networked computer o Thus, many companies are using Webcasting software to broadcast selectively reports and other information to the networked PCs of managers and specialists over their corporate intranets.
Online Analytical Processing (OLAP): •
Online analytical processing enables managers and analysts to interactively examine and manipulate large amounts of detailed and consolidated data from many perspectives.
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OLAP involves analyzing complex relationships among thousands or even millions of data items stored in data marts, data warehouses, and other multidimensional databases to discover patterns, trends, and exception conditions.
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An OLAP session takes place online in real time, with rapid responses to a manager’s or analyst’s queries so that the analytical or decision-making process is undisturbed.
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Common business areas where OLAP can solve complex problems include: o o o o o o
Marketing and sales analysis Database marketing Budgeting Financial reporting and consolidation Profitability analysis Quality analysis
ONLINE ANALYTICAL OPERATIONS: •
Consolidation o Aggregation of data Page # 7
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DECISION SUPPORT SYSTEMS Example: data about sales offices rolled up to the district level
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Drill-Down o Display underlying detail data o Example: sales figures by individual product
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Slicing and Dicing o o
Viewing database from different viewpoints Often performed along a time axis
Geographic Information Systems (GIS) and Data Visualization Systems (DVS) •
Geographic information systems (GIS) and data visualization systems (DVS) are special categories of DSS that integrate computer graphics with other DSS features.
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A geographic information system is a DSS that uses geographic databases to construct and display maps, as well as other graphics displays that support decisions affecting the geographic distribution of people and other resources.
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Many companies are using GIS technology along with global positioning system (GPS) devices to help them choose new retail store locations, optimize distribution routes, or analyze the demographics of their target audiences.
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For example, companies like Levi Strauss, Arby’s, Consolidated Rail, and Federal Express use GIS packages to integrate maps, graphics, and other geographic data with business data from spreadsheets and statistical packages. GIS software such as MapInfo and Atlas GIS is used for most business GIS applications.
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DVS Represents complex data using interactive, three-dimensional graphical forms (charts, graphs, maps)
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DVS Helps users interactively sort, subdivide, combine, and organize data while it is in its graphical form
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Using Decision Support Systems: A decision support system involves an interactive analytical modeling process. For example, using a DSS software package for decision support may result in a series of displays in response to alternative what-if changes entered by a manager. This differs from the demand responses of management information systems because decision makers are not demanding prespecified information; rather, they are exploring possible alternatives. Thus, they do not have to specify their information needs in advance. Instead, they use the DSS to find the information they need to help them make a decision. This is the essence of the decision support system concept. Four basic types of analytical modeling activities are involved in using a decision support system: (1) (2) (3) (4)
what-if analysis sensitivity analysis goal-seeking analysis optimization analysis
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Data Mining: Provides decision support through knowledge discovery • Analyzes vast stores of historical business data • Looks for patterns, trends, and correlations • Goal is to improve business performance Types of analysis • Regression (regression analysis is a statistical process for estimating the relationships among variables.) • Decision tree • Neural network • Cluster detection (clustering is the task of grouping a set of objects) • Market basket analysis
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Market Basket Analysis: •
One of the most common uses for data mining is Market Basket Analysis (MBA).
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Determines what products customers purchase together with other products
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Typical applications of MBA:
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Cross Selling: o
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Offer the associated items when customer buys any items from your store.
Product Placement: o
Items that are associated (such as bread and butter, tissues and cold medicine, potato chips and beer) can be put near each other
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Affinity Promotion: o
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Design the promotional events based on associated products.
Survey Analysis. o
The fact that both independent and dependent variables of market basket analysis are nominal (categorical) data type makes MBA very useful to analyze questionnaire data.
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Fraud Detection:
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DECISION SUPPORT SYSTEMS Based on credit card usage data, we may be able to detect certain purchase behaviors that can be associated with fraud.
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Customer Behavior: o
Associating purchase with demographic, and socio economic data (such as age, gender, and preference) may produce very useful results for marketing. Once it is known that
Executive Information Systems (EIS): •
EIS Combines many features of MIS and DSS
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Provide top executives with immediate and easy access to information
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Identify factors that are critical to accomplishing strategic objectives (critical success factors)
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So popular that it has been expanded to managers, analysis, and other knowledge workers
Features of MIS: •
Information presented in forms tailored to the preferences of the executives using the system o Customizable graphical user interfaces o Exception reports o Trend analysis o Drill down capability
ENTERPRISE INFORMATION PORTALS: An EIP is a Web-based interface and integration of MIS, DSS, EIS, and other technologies • • • • •
Available to all intranet users and select extranet users Provides access to a variety of internal and external business applications and services Typically tailored or personalized to the user or groups of users Often has a digital dashboard Also called enterprise knowledge portals
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Expert Systems An expert system is an information system that captures and stores the knowledge of human experts and then imitates human reasoning and decision-making processes for those who have less expertise. Expert systems are composed of two main components: a knowledge base and inference rules. A knowledge base is the combined subject knowledge and experiences of the human experts. The inference rules are a set of logical judgments applied to the knowledge base each time a user describes a situation to the expert system. Although expert systems can help decision-making at any level in an organization, nonmanagement employees are the primary users who utilize them to help with job-related decisions. Expert systems also successfully have resolved such diverse problems as diagnosing illnesses, searching for oil and making soup. Expert systems are one part of an exciting branch of computer science called artificial intelligence. Artificial intelligence (AI) is the application of human intelligence to computers. AI technology can sense your actions and, based on logical assumptions and prior experience, will take the appropriate action to complete the task. AI has a variety of capabilities, including speech recognition, logical reasoning, and creative responses. Experts predict that AI eventually will be incorporated into most computer systems and many individual software applications. Many word processing programs already include speech recognition.
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