management information systems, sixth edition chapter 10: decision support and expert systems

Management Information Systems, Sixth Edition

Chapter 10:

Decision Support and Expert Systems

Management Information Systems, Sixth Edition 2

Objectives

• List and explain the phases in decision making• Articulate the difference between structured and

unstructured decision making• Describe the typical software components that

decision support systems and expert systems comprise

• Give examples of how decision support systems and expert systems are used in various domains

• Describe the typical elements and uses of geographic information systems


Decision Support

• Success of an organization largely depends on the quality of decisions made by employees

• Computer-based systems can help when:– There are large amounts of information– There is a lot of processing involved

• Two types of decision support aids:– Decision support systems (DSSs)– Expert systems (ESs)

• Applications today may combine both types– Provide single optimal solution or set of solutions

Decision Support (continued)

• Decision support modules today may be part of larger enterprise applications

• Are also called business analysis tools or business intelligence applications

• Are designed to streamline the decision-making process

• Data warehouses and online processing (OLAP) technologies have enhanced the ability to use data for decision making



The Decision-Making Process

• A decision must be made whenever more than one possible action is available

• It can be difficult to make decisions when many reasonable alternatives are present– In business, there may be dozens, hundreds, or

even millions of different courses of actions available to achieve a desired result

The Decision-Making Process (continued)

• Decision making is a three-phase process:– Intelligence phase: collect facts, beliefs, and

ideas

– Design phase: design the method for considering the collected data, to reduce the alternatives to a manageable number

– Choice phase: select an alternative from the remaining choices




• Businesses collect data internally within the organization and externally from outside sources

• Model: a representation of reality, such as:– Map: represents a geographical area

– Tabletop representation of a building

– Mathematical equations representing relationships among variables

• Managers either choose universal models or design their own models


Structured and Unstructured Problems

• Structured problem: one in which an optimal solution can be reached through a single set of steps

• Algorithm: a sequence of steps to complete a task

• Parameters: categories of data that are considered in an algorithm

• Most mathematical and physical problems are structured, but many business problems are not


Structured and Unstructured Problems (continued)

• Unstructured problem: one for which there is no algorithm that leads to an optimal solution– May not be enough information

– May be a large number of potential factors

• Unstructuredness is closely related to uncertainty

• Examples of unstructured problems include:– Weather prediction

– Stock market prediction


• Semistructured problem: one that is neither fully structured nor totally unstructured

• Professionals encounter semistructured problems almost daily in many different industries

• The goal is to choose the one alternative that will bring about the best outcome



Decision Support Systems

• Decision support system (DSS): a computer-based information system designed to help knowledge workers select one of many alternative solutions to a problem

• Advantages of DSSs include:– Help increase market share– Help reduce costs– Help increase profitability– Help enhance product quality

Decision Support Systems (continued)

• Most DSSs consist of three components:– Data management module– Model management module– Dialog module

• These components help users:– Enter a request in a convenient manner– Search vast amounts of data– Process the data through desired models– View the results in a desired format



The Data Management Module

• Data management module: a database or data warehouse that provides data for the intelligence phase– Accesses the data

– Provides a means to select data by specified criteria

• Many DSSs are intertwined with other organizational systems, including data warehouses, data marts, and ERP systems


The Model Management Module• Model management module: turns data into

useful information• May offer a fixed model, a dynamically modified

model, or a collection of models– Dynamically modified model: one that is

automatically adjusted based on changing relationships among variables

• A sequence of events or a pattern of behavior can become a useful model

• Models are often based on mathematical research


The Model Management Module (continued)

• Patterns or models may be unique to a certain industry, such as:– ATM placement– Truck route planning– Airline ticket pricing– Car rental pricing

• A linear regression model is a general statistical model that is often used– Gives a best-fit linear relationship between two

variables


The Model Management Module (continued)

• A linear relationship can be translated into a program in a DSS

• The actual data points rarely lie directly on the regression line, illustrating the uncertainty

• Regression models are not necessarily always straight lines; they may be curves

• Models often describe relationships between more than two variables

• Some DSSs simulate physical environments


The Dialog Module

• Dialog module: part of a DSS that allows user interaction with the program– Prompts the user to select a model and data to

process

– Allows the user to change parameters and view the results of the changes (“what if” analysis)

– Displays the results of the analysis in textual, tabular, or graphical format

• Many DSSs are available through the Internet


Sensitivity Analysis

• An outcome is often affected by more than one parameter, but changes to parameter values usually affect outcomes differently

• It is important to determine which parameters have the most effect on the outcome

• Sensitivity analysis: tests the degree to which the outcome goal grows with each factor– Indicates the relative sensitivity of the outcome to

changes in a parameter

Sensitivity Analysis (continued)

• If a small change in a parameter causes a significant change to the outcome, the sensitivity of the outcome to the parameter is high

• If the outcome is affected very little by a large change in a parameter, the sensitivity of the outcome to the parameter is low

• Sensitivity analysis is also called what if analysis• Can perform sensitivity analysis on multiple

parameters simultaneously



Decision Support Systems in Action

• DSSs can be used on demand or integrated into a scheme that enforces corporate policy

• DSSs help maintain standard criteria in decision making throughout the organization

• Automated decision production is becoming very popular– The only labor required is for data entry


Decision Support Systems in Action (continued)

• DSSs are used in many industries:– Food production and retailing: to forecast the

number of patrons, the amount of ingredients to purchase, etc.

– Agriculture: allows farmers to make decisions about how to control specific pests, and for picking farm locations

– Tax planning: tax helper applications such as TurboTax and TaxCut



• DSSs are used in many industries (continued):– Web site planning and adjustment: to analyze

shopper behavior, and to design Web sites based on page usage

– Yield management: to maximize revenue from airline trips or lodging

– Financial services: to determine loan amounts, and to qualify customers based on credit history

– Benefits selection: to allow employees to make decisions about their benefits


Expert Systems

• Expert system (ES): emulates the knowledge of a human expert– Solves problems– Makes decisions in a relatively narrow domain

• Domain: a specific area of knowledge• Purpose is to replicate the unstructured and

undocumented knowledge of experts, and make that expertise available to novices

• Neural network: a program that emulates how the human brain works


Expert Systems (continued)


Expert Systems (continued)• ESs are part of artificial intelligence (AI) research• AI focuses on methods and technologies that

emulate how humans learn and solve problems• Knowledge base: used by an ES

– A collection of facts and the relationships among them

– Built as a series of IF-THEN rules

– Uses an inference engine

• Inference engine: software that combines data input by the user with the data relationships

Expert Systems (continued)

• Neural networks: used by more sophisticated ESs to mimic the way a human brain learns– Constructed with a set of rules, but then it refines

itself based on its decision success rate

– Very effective for detecting fraud

• Intelligent agent: software that is dormant until it detects a certain event, and then performs a prescribed action

• There are also case-based ESs– Especially useful in medical decision making



Expert Systems in Action

• ESs have been implemented in many industries:– Medical diagnosis:

• Help doctors with the diagnosis of symptoms and treatment advice

• Can help enhance the accuracy of Alzheimer’s disease diagnosis

– Medical management:• Help discern which treatments patient should

receive• Help with administrative decisions

– Telephone network maintenance:• Used to help diagnose and fix network failures


Expert Systems in Action (continued)



• ESs have been implemented in many industries (continued):– Credit evaluation:

• Used to approve credit card charges• Used to analyze financial reports submitted with

credit applications• Local loan officers may periodically update the

knowledge base to customize it for current loan policy

– Detection of insider securities trading:• Help prevent trading of stocks based on private

information by analyzing the stock’s history



• ESs have been implemented in many industries (continued):– Detection of common metals:

• Help nonexperts identify common metals and alloys outside laboratories

• Based on results of simple chemical tests and other information available at the scene

– Irrigation and pest management:• Provide recommendations on irrigation, application

of fungicides, and likelihood of pest conditions

• Can significantly improve crop yields


• ESs have been implemented in many industries (continued):– Diagnosis and prediction of mechanical failure:

• Diagnose cause of component failure• Can provide a set of instructions for fixing the

problem• Help companies know when to replace

components before a failure occurs


Group Decision Support Systems

• Group decision support system (GDSS): – Also called a group intelligence system,

collaborative system, or simply a group system

– Facilitates the contribution of ideas, brainstorming, and choosing promising solutions

• Typically allows participants to define a problem, contribute ideas, then vote on the decision

• GDSSs help structure the decision-making process while allowing participants to remain anonymous



Geographic Information Systems• Geographic information system (GIS): a

decision aid for map-related decisions– Processes location data to aid in decision making

• GISs are used to help:– Find shortest paths for deliveries or school bus

routes

– City planning for police coverage and health care resources

– Find oil drilling locations

– Locate suitable outdoor recreation sites

– Businesses determine locations for service kiosks


Geographic Information Systems (continued)

• A typical GIS consists of three components:– A database of quantitative and qualitative data

– A database of maps

– A program that displays information on maps

• Web technology helps promote the use of GISs:– Examples: Google Earth, Mapquest, Yahoo Maps

• HTML and XML support the presentation of marked maps

• Used to aid sales and government work


Summary

• Decision aids include decision support systems, expert systems, group decision support systems, and geographic information systems

• Three major phases of decision-making process: intelligence, design, and choice

• Two types of problems: unstructured and structured

• Most DSSs have three components: data management module, model management module, and dialog module


Summary (continued)

• Sensitivity analysis measures how parameters affect results, and allow “what if” analysis

• Spreadsheets allow users to create DSSs without expertise

• Expert systems are designed to emulate the knowledge of an expert, using artificial intelligence techniques

• Neural network software may be integrated into an expert system to emulate learning


Summary (continued)

• Expert systems are used in narrow domains where decisions are unstructured

• Geographic information systems are used when decisions involve locations and routes

• Computerized decision aids may overlook important circumstances, leading to inaccuracies or unfairness to individuals

management information systems, sixth edition chapter 10: decision support and expert systems

Documents

geographic information

unstructured decision

types of decision support

edition6 slide

edition4 slide

phase process

large amounts of information

business problems