STUDENT LEARNING OBJECTIVES Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge What are the different types of decisions, and how does the decision-making process work? How do information systems help people working individually and in groups make decisions more effectively? What are the business benefits of using intelligent techniques in decision making and knowledge management? What types of systems are used for enterprise-wide knowledge management, and how do they provide value for businesses? What are the major types of knowledge work systems, and how do they provide value for firms?

Eastern Mountain Sports Forges a Trail to Better Decisions Problem: Dated and clumsy information systems, unnecessary labor, poor inventory decisions. Solutions: Deploy a business intelligence system to more efficiently collect and communicate important data. Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge

Eastern Mountain Sports Forges a Trail to Better Decisions WebFOCUS and iWay middleware from Information Builders extracts key data and displays it through dashboards accessible via the Web. Demonstrates IT’s role in revamping outdated information systems. Illustrates digital technology’s role in improving decision making. Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge

Eastern Mountain Sports Forges a Trail to Better Decisions Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge

Decision Making and Information Systems Business Value of Improved Decision Making Possible to measure value of improved decision making Decisions made at all levels of the firm Some are common, routine, and numerous Although value of improving any single decision may be small, improving hundreds of thousands of “small” decisions adds up to large annual value for the business Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge

Business Value of Improved Decision Making Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Decision Making and Information Systems

Types of Decisions Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Unstructured Decision maker must provide judgment to solve problem Novel, important, nonroutine No well-understood or agreed-on procedure for making them Structured Repetitive and routine Involve definite procedure for handling them so do not have to be treated as new Semistructured Only part of problem has clear-cut answer provided by accepted procedure Decision Making and Information Systems

Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Figure 10-1 Senior managers, middle managers, operational managers, and employees have different types of decisions and information requirements. Information Requirements of Key Decision-Making Groups in a Firm Decision Making and Information Systems

The Decision-Making Process Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Intelligence: Discovering, identifying, and understanding the problems occurring in the organization—why is there a problem, where, what effects it is having on the firm Design: Identifying and exploring various solutions Choice: Choosing among solution alternatives Implementation: Making chosen alternative work and monitoring how well solution is working Decision Making and Information Systems

Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Figure 10-2 The decision-making process can be broken down into four stages. Stages in Decision Making Decision Making and Information Systems

Quality Dimensions of Decisions Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Accuracy: Decision reflects reality Comprehensiveness: Decision reflects a full consideration of the facts and circumstances Fairness: Decision faithfully reflects the concerns and interests of affected parties Speed (efficiency): Decision making is efficient with respect to time and other resources Coherence: Decision reflects rational process that can be explained to others and made understandable Due process: Decision is the result of a known process and can be appealed to a higher authority Decision Making and Information Systems

Systems and Technologies for Supporting Decisions Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Management information systems (MIS) Decision-support systems (DSS) Executive support systems (ESS) Group-decision support systems (GDSS) Intelligent techniques Decision Making and Information Systems

Management Information Systems (MIS) Systems for Decision Support Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Help managers monitor and control a business by providing information on the firm’s performance Typically produce fixed, regularly scheduled reports based on data from TPS E.g., summary of monthly or annual sales for each of the major sales territories of a company. Exception reports: Highlighting exceptional conditions only

Decision-Support Systems (DSS) Support semistructured and unstructured problem analysis Earliest DSS were model-driven “What-if” analysis: Model is developed, various input factors are changed, and the output changes are measured Data-driven DSS Use OLAP and data mining to analyze large pools of data in major corporate systems Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Systems for Decision Support

Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Interactive Session: People Too Many Bumped Fliers: Why? Read the Interactive Session and then discuss the following questions: Is the decision support system being used by airlines to overbook flights working well? Answer from the perspective of the airlines and from the perspective of customers. What is the impact on the airlines if they are bumping too many passengers? What are the inputs, processes, and outputs of this DSS? What people, organization, and technology factors are responsible for excessive bumping problems? How much of this is a “people” problem? Explain your answer. Systems for Decision Support

Components of DSS Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge DSS database: Collection of current or historical data from a number of applications or groups DSS software system Software tools that are used for data analysis OLAP tools Data mining tools Mathematical and analytical models DSS user interface Systems for Decision Support

Decision Making and Information Systems Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Figure 10-3 The main components of the DSS are the DSS database, the DSS software system, and the user interface. The DSS database may be a small database residing on a PC or a large data warehouse. Overview of a Decision Support System

Systems for Decision Support Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Models: Abstract representation that illustrates the components or relationships of a phenomenon Statistical modeling helps establish relationships E.g., relating product sales to differences in age, income, or other factors Optimization models, forecasting models Sensitivity analysis models Ask “what-if” questions repeatedly to determine the impact on outcomes of changes in one or more factors E.g., What happens if we raise product price by 5 percent

Decision Making and Information Systems Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Figure 10-4 This table displays the results of a sensitivity analysis of the effect of changing the sales price of a necktie and the cost per unit on the product’s break-even point. It answers the question, “What happens to the break-even point if the sales price and the cost to make each unit increase or decrease?” Sensitivity Analysis

Using Spreadsheet Tables to Support Decision-Making Systems for Decision Support Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Spreadsheet tables can answer multiple dimensions of questions Time of day and average purchase Payment type and average purchase Payment type, region, and source Pivot table Displays two or more dimensions of data in a convenient format

Decision Making and Information Systems Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Figure 10-5 This list shows a portion of the order transactions for Online Management Training Inc. on October 28, 2007. Sample List of Transactions for Online Management Training Inc. on October 28, 2007

Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Figure 10-6 This pivot table was created using Excel 2007 to quickly produce a table showing the relationship between region and number of customers. A Pivot Table That Examines the Regional Distribution of Customers Decision Making and Information Systems

Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Figure 10-7 In this pivot table, we can examine where customers come from in terms of region and advertising source. It appears nearly 30 percent of the customers respond to e-mail campaigns, and there are some regional variations. A Pivot Table That Examines Customer Regional Distribution and Advertising Source Decision Making and Information Systems

Data Visualization and Geographic Information Systems (GIS) Systems for Decision Support Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Data visualization tools: Present data in graphical form to help users see patterns and relationships in large quantities of data Geographic information systems (GIS): Use data visualization technology to analyze and display data in the form of digitized maps Support decisions that require knowledge about the geographic distribution of people or other resources

Decision Making and Information Systems Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge South Carolina used a GIS-based program called HAZUS to estimate and map the regional damage and losses resulting from an earthquake of a given location and intensity. HAZUS estimates the degree and geographic extent of earthquake damage across the state based on inputs of building use, type, and construction materials. The GIS helps the state plan for natural hazards mitigation and response.

Web-Based Customer Decision-Support Systems (CDSS) Systems for Decision Support Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Support customers in the decision-making process Include: Search engines, intelligent agents, online catalogs, Web directories, newsgroups, e-mail, etc. Many firms have customer Web sites where all the information, models, or other analytical tools for evaluating alternatives are concentrated in one location E.g., T. Rowe Price online tools, guides for college planning, retirement planning, estate planning, etc.

Executive Support Systems (ESS) Bring together data from many different internal and external sources, often through a portal Digital dashboard: Gives senior executives a picture of the overall performance of an organization Drill down capability: Enables an executive to zoom in on details or zoom out for a broader view Used to monitor organizational performance, track activities of competitors, identify changing market conditions, spot problems, identify opportunities, and forecast trends Systems for Decision Support Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge

Group Decision-Support Systems (GDSS) Interactive, computer-based systems that facilitate solving of unstructured problems by set of decision makers Used in conference rooms with special hardware and software for collecting, ranking, storing ideas and decisions Promote a collaborative atmosphere by guaranteeing contributors’ anonymity Support increased meeting sizes with increased productivity Systems for Decision Support Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge

Intelligent techniques for enhancing decision making Many based on artificial intelligence (AI) Computer-based systems (hardware and software) that attempt to emulate human behavior and thought patterns Include: Expert systems Case-based reasoning Fuzzy logic Neural networks Genetic algorithms Intelligent agents Intelligent Systems for Decision Support Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge

Expert systems Model human knowledge as a set of rules that are collectively called the knowledge base 200 – 10,000 rules, depending on complexity The system’s inference engine searches through the rules and “fires” those rules that are triggered by facts gathered and entered by the user Useful for dealing with problems of classification in which there are relatively few alternative outcomes and in which these possible outcomes are all known in advance Intelligent Systems for Decision Support Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge

Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Figure 10-8 An expert system contains a set of rules to be followed when used. The rules are interconnected; the number of outcomes is known in advance and is limited; there are multiple paths to the same outcome; and the system can consider multiple rules at a single time. The rules illustrated are for a simple credit-granting expert system. Rules in an Expert System Intelligent Systems for Decision Support

Case-based reasoning Knowledge and past experiences of human specialists are represented as cases and stored in a database for later retrieval System searches for stored cases with problem characteristics similar to new one, finds closest fit, and applies solutions of old case to new case. Successful and unsuccessful applications are tagged and linked in database Used in medical diagnostic systems, customer support Intelligent Systems for Decision Support Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge

Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Figure 10-9 Case-based reasoning represents knowledge as a database of past cases and their solutions. The system uses a six-step process to generate solutions to new problems encountered by the user. How Case-Based Reasoning Works Intelligent Systems for Decision Support

Fuzzy logic Rule-based technology that represents imprecision in categories (e.g. ,“cold” vs. “cool”) by creating rules that use approximate or subjective values Describes a particular phenomenon or process linguistically and then represents that description in a small number of flexible rules Provides solutions to problems requiring expertise that is difficult to represent in the form of crisp IF-THEN rules E.g., Sendai, Japan subway system uses fuzzy logic controls to accelerate so smoothly that standing passengers need not hold on Intelligent Systems for Decision Support Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge

Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Figure 10-10 The membership functions for the input called temperature are in the logic of the thermostat to control the room temperature. Membership functions help translate linguistic expressions, such as warm, into numbers that the computer can manipulate Intelligent Systems for Decision Support Fuzzy Logic for Temperature Control

Neural networks Use hardware and software that parallel the processing patterns of a biological brain “Learn” patterns from large quantities of data by searching for relationships, building models, and correcting over and over again the model’s own mistakes Humans may “train” the network by feeding it data for which the inputs produce a known set of outputs or conclusions. Useful for solving complex, poorly understood problems for which large amounts of data have been collected Intelligent Systems for Decision Support Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge

Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Figure 10-11 A neural network uses rules it “learns” from patterns in data to construct a hidden layer of logic. The hidden layer then processes inputs, classifying them based on the experience of the model. In this example, the neural network has been trained to distinguish between valid and fraudulent credit card purchases. Intelligent Systems for Decision Support How a Neural Network Works

Genetic algorithms Find the optimal solution for a specific problem by examining very large number of alternative solutions for that problem. Based on techniques inspired by evolutionary biology: inheritance, mutation, selection, etc. Work by representing a solution as a string of 0s and 1s, then searching randomly generated strings of binary digits to identify best possible solution Used to solve complex problems that are very dynamic and complex, involving hundreds or thousands of variables or formulas Intelligent Systems for Decision Support Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge

Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Figure 10-12 This example illustrates an initial population of “chromosomes,” each representing a different solution. The genetic algorithm uses an iterative process to refine the initial solutions so that the better ones, those with the higher fitness, are more likely to emerge as the best solution. Intelligent Systems for Decision Support The Components of a Genetic Algorithm

Intelligent agents Programs that work in the background without direct human intervention to carry out specific, repetitive, and predictable tasks for user, business process, or software application Shopping bots Procter & Gamble (P&G) programmed group of semiautonomous agents to emulate behavior of supply-chain components, such as trucks, production facilities, distributors, and retail stores and created simulations to determine how to make supply chain more efficient Intelligent Systems for Decision Support Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge

Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Figure 10-13 Intelligent agents are helping Procter & Gamble shorten the replenishment cycles for products, such as a box of Tide. Intelligent Agents in P&G’s Supply Chain Network Intelligent Systems for Decision Support

Systems for Managing Knowledge Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Knowledge management: Business processes developed for creating, storing, transferring, and applying knowledge Increases the ability of organization to learn from environment and to incorporate knowledge into business processes and decision making Knowing how to do things effectively and efficiently in ways that other organizations cannot duplicate is major source of profit and competitive advantage

Three kinds of knowledge Structured: Structured text documents (reports, presentations) Semi-structured: E-mail, voice mail, digital pictures, bulletin-board postings Tacit knowledge (unstructured): Knowledge residing in heads of employees, rarely written down Enterprise-wide knowledge management systems Deal with all three types of knowledge General-purpose, firm-wide systems that collect, store, distribute, and apply digital content and knowledge Enterprise-Wide Knowledge Management Systems Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Systems for Managing Knowledge

Enterprise content management systems Capabilities for knowledge capture, storage Repositories for documents and best practices Capabilities for collecting and organizing semi-structured knowledge such as e-mail Classification schemes Key problem in managing knowledge Each knowledge object must be tagged for retrieval Enterprise-Wide Knowledge Management Systems Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Systems for Managing Knowledge

Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Figure 10-14 An enterprise content management system has capabilities for classifying, organizing, and managing structured and Semi-structured knowledge and making it available throughout the enterprise. An Enterprise Content Management System Intelligent Systems for Decision Support

Digital asset management systems Manage unstructured digital data like photographs, graphic images, video, audio Knowledge network systems (Expertise location and management systems) Provide online directory of corporate experts in well-defined knowledge domains Use communication technologies to make it easy for employees to find appropriate expert in firm Enterprise-Wide Knowledge Management Systems Systems for Managing Knowledge Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge

Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Figure 10-15 A knowledge network maintains a database of firm experts, as well as accepted solutions to known problems, and then facilitates the communication between employees looking for knowledge and experts who have that knowledge. Solutions created in this communication are then added to a database of solutions in the form of frequently asked questions (FAQs), best practices, or other documents. An Enterprise Knowledge Network System Intelligent Systems for Decision Support

Collaboration tools Blogs Wikis Social bookmarking Learning management systems (LMS) Provide tools for management, delivery, tracking, and assessment of various types of employee learning and training Enterprise-Wide Knowledge Management Systems Systems for Managing Knowledge Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge

Interactive Session: Organizations Managing With Web 2.0 Read the Interactive Session and then discuss the following questions: How do Web 2.0 tools help companies manage knowledge, coordinate work, and enhance decision making? What business problems do blogs, wikis, and other social networking tools help solve? Describe how a company such as Wal-Mart or Procter & Gamble would benefit from using Web 2.0 tools internally. What challenges do companies face in spreading the use of Web 2.0? What issues should managers be concerned with? Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Systems for Managing Knowledge

Knowledge Work Systems (KWS) Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Requirements of knowledge work systems Specialized tools Powerful graphics, analytical tools, and communications and document management Computing power to handle sophisticated graphics or complex calculations Access to external databases User-friendly interfaces Systems for Managing Knowledge

Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Figure 10-16 Knowledge work systems require strong links to external knowledge bases in addition to specialized hardware and software. Requirements of Knowledge Work Systems Intelligent Systems for Decision Support

Knowledge Work Systems (KWS) Systems for Managing Knowledge Essentials of Business Information Systems Chapter 10 Improving Decision Making and Managing Knowledge Examples of knowledge work systems Computer-aided design (CAD) systems Virtual reality systems Virtual Reality Modeling Language (VRML) Investment workstations

Key Terms Artificial intelligence (AI), 346 Case-based reasoning (CBR), 348 Choice, 335 Customer decision-support systems (CDSS), 345 Data visualization, 343 Design, 335 Digital asset management systems, 354 Digital dashboard, 345 Drill down, 345 DSS database, 340 DSS software system, 340 Enterprise content management systems, 353 Enterprise-wide knowledge management systems, 353 Expert systems, 346 Fuzzy logic, 349 Genetic algorithms, 351 Geographic information systems (GIS), 344 Group decision-support systems (GDSS), 345 Implementation, 335 Intelligence, 335 Inference engine, 347

Key Terms Intelligent agents, 352 Intelligent techniques, 337 Investment workstations, 359 Knowledge base, 346 Knowledge management, 353 Knowledge network systems, 354 Knowledge work systems (KWS), 357 Learning management system (LMS), 355 Model, 340 Neural networks, 349 Pivot table, 343 Semistructured decisions, 335 Sensitivity analysis, 341 Social bookmarking, 355 Structured decisions, 335 Structured knowledge, 353 Tacit knowledge, 353 Unstructured decisions, 335 Virtual reality systems, 358 Virtual Reality Modeling Language (VRML), 358