Chapter 10
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Chapter10 Decision Support Systems
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
Decision Support in Business • Companies are investing in data-driven decision support application frameworks to help them respond to • Changing market conditions • Customer needs • This is accomplished by several types of • Management information • Decision support • Other information systems
Information Quality • Information products made more valuable by their attributes, characteristics, or qualities • Information that is outdated, inaccurate, or hard to understand has much less value • Information has three dimensions • Time • Content • Form
Decision Structure • Structured (operational) • The 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
Decision Support Trends • The emerging class of applications focuses on • Personalized decision support • Modeling • Information retrieval • Data warehousing • What-if scenarios • Reporting
Decision Support Systems • Decision support systems use the following to support the making of semi-structured business decisions • Analytical models • Specialized databases • A decision-maker’s own insights and judgments • An interactive, computer-based modeling process • DSS systems are designed to be ad hoc, quick-response systems that are initiated and controlled by decision makers
DSS Model Base • Model Base • A software component that consists of models used in computational and analytical routines that mathematically express relations among variables • Spreadsheet Examples • Linear programming • Multiple regression forecasting • Capital budgeting present value
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
Management Information Systems • The original type of information system that supported managerial decision making • Produces information products that support many day-to-day decision-making needs • Produces reports, display, and responses • Satisfies needs of operational and tactical decision makers who face structured decisions
Management Reporting Alternatives • Periodic Scheduled Reports • Prespecified format on a regular basis • Exception Reports • Reports about exceptional conditions • May be produced regularly or when an exception occurs • Demand Reports and Responses • Information is available on demand • Push Reporting • Information is pushed to a networked computer
Example of Push Reporting • Insert Figure 10.10 here
Online Analytical Processing • OLAP • Enables managers and analysts to examine and manipulate large amounts of detailed and consolidated data from many perspectives • Done interactively, in real time, with rapid response to queries
Online Analytical Operations • Consolidation • Aggregation of data • Example: data about sales offices rolled up to the district level • Drill-Down • Display underlying detail data • Example: sales figures by individual product • Slicing and Dicing • Viewing database from different viewpoints • Often performed along a time axis
OLAP Configuration • Insert Figure 10.11
Geographic Information Systems • GIS • DSS uses geographic databases to construct and display maps and other graphic displays • Supports decisions affecting the geographic distribution of people and other resources • Often used with Global Positioning Systems (GPS) devices
Data Visualization Systems • DVS • Represents complex data using interactive, three-dimensional graphical forms (charts, graphs, maps) • Helps users interactively sort, subdivide, combine, and organize data while it is in its graphical form
DVS Example • Insert Figure 10.14 here
Using Decision Support Systems • Using a decision support system involves an interactive analytical modeling process • Decision makers are not demanding pre-specified information • They are exploring possible alternatives • What-If Analysis • Observing how changes to selected variables affect other variables
Using Decision Support Systems • Sensitivity Analysis • Observing how repeated changes to a single variable affect other variables • Goal-seeking Analysis • Making repeated changes to selected variables until a chosen variable reaches a target value • Optimization Analysis • Finding an optimum value for selected variables, given certain constraints
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 • Results affect how companies • Market products • Place merchandise in the store • Lay out catalogs and order forms • Determine what new products to offer • Customize solicitation phone calls
Executive Information Systems • EIS • 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
Features of an EIS • Information presented in forms tailored to the preferences of the executives using the system • Customizable graphical user interfaces • Exception reports • Trend analysis • 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
Case 2: Automated Decision Making • Automated decision making has been slow to materialize • Early applications were just solutions looking for problems, contributing little to improved organizational performance • A new generation of AI applications • Easier to create and manage • Decision making triggered without human intervention • Can translate decisions into action quickly, accurately, and efficiently
Artificial Intelligence (AI) • AI is a field of science and technology based on • Computer science • Biology • Psychology • Linguistics • Mathematics • Engineering • The goal is to develop computers than can simulate the ability to think • And see, hear, walk, talk, and feel as well
Attributes of Intelligent Behavior • Some of the attributes of intelligent behavior • Think and reason • Use reason to solve problems • Learn or understand from experience • Acquire and apply knowledge • Exhibit creativity and imagination • Deal with complex or perplexing situations
Attributes of Intelligent Behavior • Attributes of intelligent behavior (continued) • Respond quickly and successfully to new situations • Recognize the relative importance of elements in a situation • Handle ambiguous, incomplete, or erroneous information
Cognitive Science • Applications in the cognitive science of AI • Expert systems • Knowledge-based systems • Adaptive learning systems • Fuzzy logic systems • Neural networks • Genetic algorithm software • Intelligent agents • Focuses on how the human brain works and how humans think and learn
Robotics • AI, engineering, and physiology are the basic disciplines of robotics • Produces robot machines with computer intelligence and humanlike physical capabilities • This area include applications designed to give robots the powers of • Sight or visual perception • Touch • Dexterity • Locomotion • Navigation
Natural Interfaces • Major thrusts in the area of AI and the development of natural interfaces • Natural languages • Speech recognition • Virtual reality • Involves research and development in • Linguistics • Psychology • Computer science • Other disciplines
Latest Commercial Applications of AI • Decision Support • Helps capture the why as well as the what of engineered design and decision making • Information Retrieval • Distills tidal waves of information into simple presentations • Natural language technology • Database mining
Latest Commercial Applications of AI • Virtual Reality • X-ray-like vision enabled by enhanced-reality visualization helps surgeons • Automated animation and haptic interfaces allow users to interact with virtual objects • Robotics • Machine-vision inspections systems • Cutting-edge robotics systems • From micro robots and hands and legs, to cognitive and trainable modular vision systems
Expert Systems • An Expert System (ES) • A knowledge-based information system • Contain knowledge about a specific, complex application area • Acts as an expert consultant to end users
Components of an Expert System • Knowledge Base • Facts about a specific subject area • Heuristics that express the reasoning procedures of an expert (rules of thumb) • Software Resources • An inference engine processes the knowledge and recommends a course of action • User interface programs communicate with the end user • Explanation programs explain the reasoning process to the end user
Methods of Knowledge Representation • Case-Based • Knowledge organized in the form of cases • Cases are examples of past performance, occurrences, and experiences • Frame-Based • Knowledge organized in a hierarchy or network of frames • A frame is a collection of knowledge about an entity, consisting of a complex package of data values describing its attributes
