Supporting Decision Making Chapter 10 Supporting Decision Making McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.

Learning Objectives Identify the changes taking place in the form and use of decision support in business Identify the role and reporting alternatives of management information systems Describe how online analytical processing can meet key information needs of managers Explain the decision support system concept and how it differs from traditional management information systems

Learning Objectives Explain how the following information systems can support the information needs of executives, managers, and business professionals Executive information systems Enterprise information portals Knowledge management systems Identify how neural networks, fuzzy logic, genetic algorithms, virtual reality, and intelligent agents can be used in business

Learning Objectives Give examples of several ways expert systems can be used in business decision-making situations

Structured (operational) Unstructured (strategic) Decision Structure Structured (operational) Procedures can be specified in advance Unstructured (strategic) Not possible to specify procedures in advance Semi-structured (tactical) Decision procedures can be pre-specified, but not enough to lead to the correct decision Structured (operational) Procedures to follow when decision is needed can be specified in advance Unstructured (strategic) It is not possible to specify in advance most of the decision procedures to follow Semi-structured (tactical) Decision procedures can be pre-specified, but not enough to lead to the correct decision

Provides decision support through knowledge discovery 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 Decision tree Neural network Cluster detection Market basket analysis

Market Basket Analysis One of the most common uses for data mining Determines what products customers purchase together with other products Other uses Cross Selling Product Placement Affinity Promotion Survey Analysis Fraud Detection Analyze Customer Behavior Consider some of the typical applications of MBA: • Cross Selling. Offer the associated items when customer buys any items from your store. • Product Placement. Items that are associated (such as bread and butter, tissues and cold medicine, potato chips and beer) can be put near each other. If the customers see them, it has higher probability that they will purchase them together. • Affinity Promotion. Design the promotional events based on associated products. • Survey Analysis. 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. • Fraud Detection. Based on credit card usage data, we may be able to detect certain purchase behaviors that can be associated with fraud. • Customer Behavior. Associating purchase with demographic, and socio economic data (such as age, gender, and preference) may produce very useful results for marketing.

Executive Information Systems (EIS) Combines many features of MIS and DSS Provides immediate and easy information Identifies critical success factors Features Customizable graphical user interfaces Exception reports Trend analysis Drill down capability Combines many features of MIS and DSS Provide top executives with immediate and easy access to information Identify factors that are critical to accomplishing strategic objectives (critical success factors) So popular that it has been expanded to managers, analysis, and other knowledge workers

Benefits of Expert Systems Captures human experience in a computer-based information system Limitations of Expert Systems Limited focus Inability to learn Maintenance problems Development cost Can only solve specific types of problems in a limited domain of knowledge Benefits of Expert Systems Captures the expertise of an expert or group of experts in a computer-based information system Faster and more consistent than an expert Can contain knowledge of multiple experts Does not get tired or distracted Cannot be overworked or stressed Helps preserve and reproduce the knowledge of human experts The major limitations of expert systems Limited focus Inability to learn Maintenance problems Development cost Can only solve specific types of problems in a limited domain of knowledge

Knowledge Engineering A knowledge engineer Works with experts to capture the knowledge they possess Facts and rules of thumb Builds the knowledge base if necessary, the rest of the expert system Similar role to systems analysts A knowledge engineer Works with experts to capture the knowledge (facts and rules of thumb) they possess Builds the knowledge base, and if necessary, the rest of the expert system Performs a role similar to that of systems analysts in conventional information systems development 10-10

Neural Networks Modeled after the brain’s mesh-like network of interconnected processing elements (neurons) Interconnected processors operate in parallel and interact with each other Allows the network to learn from the data it processes Computing systems modeled after the brain’s mesh-like network of interconnected processing elements (neurons) Interconnected processors operate in parallel and interact with each other Allows the network to learn from the data it processes

Genetic algorithm software Uses Darwinian, randomizing, and other mathematical functions Simulates an evolutionary process, yielding increasingly better solutions to a problem Used to model a variety of scientific, technical, and business processes Useful when thousands of solutions are possible

Virtual reality is a computer-simulated reality Virtual Reality (VR) Virtual reality is a computer-simulated reality Fast-growing area of artificial intelligence Originated from efforts to build natural, realistic, multi-sensory human-computer interfaces Relies on multi-sensory input/output devices Creates a three-dimensional world through sight, sound, and touch Telepresence Using VR to perform a task in a different location Current applications of virtual reality Computer-aided design Medical diagnostics and treatment Scientific experimentation Flight simulation Product demonstrations Employee training Entertainment

Software robots or bots Intelligent Agents Software surrogate for an end user or a process that fulfills a stated need or activity Uses built-in and learned knowledge base to accomplish tasks Software robots or bots Software surrogate for an end user or a process that fulfills a stated need or activity Uses built-in and learned knowledge base to make decisions and accomplish tasks in a way that fulfills the intentions of a user Also called software robots or bots Interface Tutors – observe user computer operations, correct user mistakes, provide hints/advice on efficient software use Presentation Agents – show information in a variety of forms/media based on user preferences Network Navigation Agents – discover paths to information, provide ways to view it based on user preferences Role-Playing – play what-if games and other roles to help users understand information and make better decisions

Types of Intelligent Agents User Interface Agents Interface Tutors Presentation Agents Network Navigation Agents Role-Playing Agents Information Management Agents Search Agents Information Brokers Information Filters User Interface Agents Interface Tutors – observe user computer operations, correct user mistakes, provide hints/advice on efficient software use Presentation Agents – show information in a variety of forms/media based on user preferences Network Navigation Agents – discover paths to information, provide ways to view it based on user preferences Role-Playing – play what-if games and other roles to help users understand information and make better decisions Information Management Agents Search Agents – help users find files and databases, search for information, and suggest and find new types of information products, media, resources Information Brokers – provide commercial services to discover and develop information resources that fit business or personal needs Information Filters – Receive, find, filter, discard, save, forward, and notify users about products received or desired, including e-mail, voice mail, and other information media