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CHAPTER 4. DECISION SUPPORT AND ARTIFICIAL INTELLIGENCE Brainpower for Your Business. AN NFL TEAM NEEDS MORE THAN ATHLETIC ABILITY. The Patriots football team is a very successful one The team uses a decision support system to analyze the opposition’s game
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CHAPTER 4 DECISION SUPPORT AND ARTIFICIAL INTELLIGENCE Brainpower for Your Business
AN NFL TEAM NEEDS MORE THAN ATHLETIC ABILITY • The Patriots football team is a very successful one • The team uses a decision support system to analyze the opposition’s game • The software breaks down the game day video into plays and player actions • With this information the Patriots can better formulate their strategy
INTRODUCTION • Computer-aided decision support
DECISIONS, DECISIONS, DECISIONS • Phases of decision making • Intelligence • Design • Choice • Implementation
Types of Decisions • Structured decision • Semi-Structured decision • Nonstructured decision
Types of Decisions You Face • Recurring decision • Nonrecurring (ad hoc) decision
DECISION SUPPORT SYSTEMS • Decision support system (DSS) • Help you analyze, but you must know how to solve the problem, and how to use the results of the analysis
Components of a DSS • Model management component • Data management component • User interface management component
GEOGRAPHIC INFORMATION SYSTEMS • Geographic information system (GIS) • Spatial information is any information in map form • Used to analyze information, generate business intelligence, and make decisions
ARTIFICIAL INTELLIGENCE • Artificial intelligence (AI) • Types of AI systems used in business • Expert systems • Neural networks • Genetic algorithms • Intelligent agents • AI systems deliver the conclusion (rather than helping you analyze the options)
EXPERT SYSTEMS • Expert (knowledge-based) system • Used for • Diagnostic problems (what’s wrong?) • Prescriptive problems (what to do?)
Components of an Expert System • Information Types • Domain expertise • “Why?” information • Problem facts • People • Domain expert • Knowledge engineer • Knowledge worker
Components of an Expert System • IT Components • Knowledge acquisition • Explanation module • User interface • Inference engine • Knowledge base
What Expert Systems Can and Can’t Do An expert system can Reduce errors Improve customer service Reduce cost An expert system can’t Use common sense Automate all processes
NEURAL NETWORKS • Neural network (artificial neural network or ANN)
Neural Networks Can… Learn and adjust to new circumstances on their own Take part in massive parallel processing Function without complete information Cope with huge volumes of information Analyze nonlinear relationships
Fuzzy Logic Fuzzy logic – a mathematical method of handling imprecise or subjective information Used to make ambiguous information such as “short” usable in computer systems Applications Google’s search engine Washing machines Antilock breaks
GENETIC ALGORITHMS • Genetic algorithm • Takes thousands or even millions of possible solutions, combining and recombining them until it finds the optimal solution • Work in environments where no model of how to find the right solution exists
INTELLIGENT AGENTS • Intelligent agent • Information agents • Monitoring-and-surveillance or predictive agents • Data-mining agents • User or personal agents
In Class Team Activity A music owner wants to keep enough hot CDs in stock, so as not to lose sales and disappoint customers. CDs that are not sold for some time, go on the sale table, and are sold at below cost, if they sell at all. She wants to design a DSS to try and predict how many copies of each future CD she should order, and for how long she should keep them on a rack, before putting them on sale. As Strategic Consultants to her, our team needs to list some of the considerations that would go into such a system. What kind of DSS should she use? Hint: Some examples: how often does her customers base change, previous sales of particular types of music with her customer base Management Information Systems for the Information Age