Chapter 12

Chapter 12 1

Management Decision Support and Intelligent

Systems

Managers and Decision Making

• Management:– Is a process by which organizational goals are

achieved through the use of resources :• People

• Money

• Energy

• Materials

• Space

• Time

Chapter 12 2

Managers and Decision Making

• Resources are Inputs.

• Attainment of the goals is Output of the process.

• Managers undertake many activities as per;– Their position in the organization– The type & size of the organization– Organizational policies and culture– Personalities of he himself.

Chapter 12 3

Mintzberg’s classification

• Interpersonal– Figurehead, leader, liaison

• Informational– Monitor, disseminator, spokesperson

• Decisional– Entrepreneur, problem solver, allocator, negotiator.

Chapter 12 4

Decision making & Problem Solving

• Decision:– Refers to a choice made between two or more

alternatives.– It is diverse in nature– Made continuously by individuals & groups– Classified by organization as

• Problem solving

• Opportunity exploiting

Chapter 12 5

Computerized Decision Aids

• Basic ?????– Why do managers need the support of IT in

making decisions?– Can the manager’s job be fully automated?– What IT aids are available to support managers?– How are the information needs of managers

determined?

Chapter 12 6

Decision Process

Chapter 12 7

Decision Complexity

Chapter 12 8

Modeling and Models

• A model ( in decision making) is a simplified representation, or abstraction of reality.

• With modeling, one can perform virtual experiments and an analysis on a model of reality, rather than on reality itself.

Chapter 12 9

Benefits of modeling

• Low cost• Allows simulation compression time• Manipulation much easier• Lowers cost of making errors• Better deal with uncertainty• Allows analysis & comparison of large, infinite

alternatives through mathematical models• Enhances & reinforce learning & support training

Chapter 12 10

Chapter 12 11

12

Decision Support System

DSSs are computer-based information systems that provide interactive information support to managers and business professionals during the decision-making process.

DSSs use Analytical Models, Specialized Databases, A decision maker’s own insights & judgment & An interactive, computer based modeling process to support the making of semi-structured business decisions.

13

Concept

• Gory and Scott-Morton coined the phrase ‘DSS’ in 1971, about ten years after MIS became popular

• Structured problems could be solved by algorithms and decision rules

• Unstructured problems have no structure

• Semi structured problems have structured and unstructured phases

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Factors Affecting Decision-Making

• New technologies and better information distribution have resulted in more alternatives for management.

• Complex operations have increased the costs of errors, causing a chain reaction throughout the organization.

• Rapidly changing global economies and markets are producing greater uncertainty and requiring faster response in order to maintain competitive advantages.

• Increasing governmental regulation coupled with political destabilization have caused great uncertainty.

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Decision Support FrameworksType of Control

Type of Decision:

Operational Control Managerial Control Strategic Planning

Structured(Programmed)

Accounts receivable, accounts payable, order entry

Budget analysis, short-term forecasting, personnel reports

Investments, warehouse locations, distribution centers

Semistructured Production scheduling, inventory control

Credit evaluation, budget preparation, project scheduling, rewards systems

Mergers and acquisitions, new product planning, compensation, QA, HR policy planning

Unstructured

(Unprogrammed)

Buying software, approving loans, help desk

Negotiations, recruitment, hardware purchasing

R&D planning, technology development, social responsibility plans

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Technologies for Decision-Making Processes

Type of Decision Technology Support Needed

Structured

(Programmed)

MIS, Management Science Models, Transaction Processing

Semistructured DSS, KMS, GSS, CRM, SCM

Unstructured

(Unprogrammed)

GSS, KMS, ES, Neural networks

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Technology Support Based on Anthony’s Taxonomy

Type of Control

Operational Control

Managerial Control

Strategic Planning

Technology Support Needed

MIS, Management Science

Management Science, DSS, ES, EIS, SCM, CRM, GSS, SCM

GSS, CRM, EIS, ES, neural networks, KMS

18

Manager + Computer(DSS)

Solution

ComputerSolution

ManagerSolution

Structured Semi structured Unstructured

DEGREE OF PROBLEM STRUCTUREDEGREE OF PROBLEM STRUCTURE

The DSS Focuses on Semi structured The DSS Focuses on Semi structured ProblemsProblems

19

DSS Types• The least degree of problem-solving

support comes from retrieval of information elements

• More support comes from retrieving information files

• Still more support comes from reports from multiple files

20

DSS Types (continued)• Even more support from systems that can

estimate decision consequences

• More support from systems that can propose decisions

• And the most support comes from systems that can make decisions

21

Retrieve Retrieve information information

elementselements

Analyze Analyze entire filesentire files

Prepare Prepare reports reports

from from multiple multiple

filesfiles

Estimate Estimate decision decision

consequencesconsequences

Propose Propose decisionsdecisions

Degree of Degree of complexity of the complexity of the problem-solving problem-solving

systemsystem

LittleLittle MuchMuch

DSS TypesDSS Types

Make Make decisionsdecisions

Degree Degree

of of

ProblemProblem

solving solving

supportsupport

Characteristics and Capabilities of DSSs

• Sensitivity analysis is the study of the impact that changes in one (or more) parts of a model have on other parts.

• What-if analysis is the study of the impact of a change in the assumptions (input data) on the proposed solution.

• Goal-seeking analysis is the study that attempts to find the value of the inputs necessary to achieve a desired level of output.

Chapter 12 22

Structure and Components of DSSs

• Data management subsystem contain all the data that flow from several sources.

• Model management subsystem contains completed models and the building blocks necessary to develop DSS applications.

• User interface covers all aspects of the communications between a user and the DSS.

• Users are the persons faced with the problem or decision that the DSS is designed to support.

• Knowledge-based subsystems provide the required expertise for solving some aspects of the problem.

Chapter 12 23

DSS Process

Chapter 12 24

Group Decision Support Systems

• a DSS whose design, structure, and usage reflect the way in which people cooperate to make a particular decision or type of decision

• an interactive, computer-based system which facilitates the solution of unstructured problems by a set of decision makers working together as a group

GDSS

• consisting of a set of software, hardware, language components, and procedures that support a group of people engaged in a decision-related meeting

Chapter 12 27

Time/Place Framework

• Time– synchronous– asynchronous

• Place– same place– different place

Time/Place Framework

• Same Time/Same Place– decision room

• Same Time/Different Place– telephone conferencing, video conferencing

• Different Time/Same Place– project/team rooms, shared offices

• Different Time/Different Place– email, workflow management systems

Databases

Model base GDSS processor GDSS software

Dialoguemanager

External databaseaccess

Users

Access to the internetand corporate intranet,

networks, and othercomputer system

Externaldatabases

Components of a GDSS and GDSS Software

• Database• Model base• Dialogue manager• Communication capability• Special software (also called GroupWare)• E.g., Lotus Notes

– people located around the world work on the same project, documents, and files, efficiently and at the same time

GDSS Alternatives

Local areadecision network

Wide areadecision network

Decisionroom

Teleconferencing

Location of group members

close distant

high

low

Dec

isio

n f

req

uen

cy

Decision Room

• Decision Room– For decision makers located in the same

geographic area or building

– Use of computing devices, special software, networking capabilities, display equipment, and a session leader

– Collect, coordinate, and feed back organized information to help a group make a decision

– Combines face-to-face verbal interaction with technology-aided formalization

Benefits of GDSS

• supports parallel generation of ideas

• supports larger groups

• rapid and easy access to external information

• parallel computer discussion

• anonymous input

• automatic documentation of the group meetings

Organizational Decision Support System (ODSS)

• Organizational Decision Support System (ODSS) is a DSS that focuses on an organizational task or activity involving a sequence of operations and decision makers

Chapter 12 36

ODSS provides

– It affects several organizational units or corporate problems;

– It cuts across organizational functions or hierarchical layers;

– It involves computer-based and (usually) communications technologies.

Chapter 12 37

Executive Information (Support) Systems

• Executive information system (EIS) also

known as an executive support system

(ESS), is a computer-based technology

designed specifically for the information

needs of top executives

Chapter 12 38

ESS

• It is a comprehensive support system that

goes beyond EIS to include analysis

support, communications, office

automation and intelligence support.

Chapter 12 39

ESS provides

– Rapid access to timely information;– Direct access to management reports;– Very user friendly and supported by graphics.– Exception reporting – reporting of only the results

that deviate from a set of standards.– Drill down reporting – investigating information in

increasing detail.– Easily connected within online information services

and e-mail.– Include analysis support, communications, office

automation and intelligence support.

Chapter 12 40

Intelligent Support Systems

• Intelligent systems describes AI.

• AI= Artificial Intelligence– Involves studying of thought process of

human.– Deals with representing those processes via

machines.

Chapter 12 41

Overview of AI• Artificial intelligence (AI)

– Computers with the ability to mimic or duplicate the functions of the human brain

• Artificial intelligence systems

– The people, procedures, hardware, software, data, and knowledge needed to develop computer systems and machines that demonstrate the characteristics of intelligence

Intelligent Behavior

– Learn from experience

– Apply knowledge acquired from experience

– Handle complex situations

– Solve problems when important

information is missing

– Determine what is important

Chapter 12 43

Intelligent Behavior

– React quickly and correctly to a new

situation

– Understand visual images

– Process and manipulate symbols

– Be creative and imaginative

– Use heuristics

Chapter 12 44

Knowledge & AI

• Knowledge consists of

– Facts

– Concepts

– Theories

– Heuristic methods

– Procedures

– Relationships

Chapter 12 45

Knowledge & AI

• It is organized and analyzed information.

• The above information is made understandable and applicable to problem solving or decision making.

• Knowledge base: collection of knowledge related to a specific problem to be used in an intelligent system is organized and stored in a KB.

Chapter 12 46

Benefits of AI

• Makes computers easier to use

• Wide availability of knowledge

• Significantly increases the speed of

problem solving procedures (psps).

• Increases consistency of psps.

Chapter 12 47

Benefits of AI

• Increases productivity of performing tasks.

• Summarizing of information

• Interpretation of information

• Rule-based systems to automated

decision making.

Chapter 12 48

Intelligent Agents

• Small programs that reside on computers to conduct certain task automatically.

• IA runs in the background, monitors the environment.

• IA reacts to certain trigger conditions.

• Includes rule-based expert systems, case-base reasoning.

Chapter 12 49

Intelligent Agents

• Applications

– Personal assistant devices

– E-mails

– News filtering

– Distribution appointment handling

– Web applets for e-commerce

– Information gathering

Chapter 12 50

Intelligent Systems (cont’d)

Chapter 12 51

Expert Systems

Chapter 12 52

Expert systems (ESs) are attempts to mimic

human experts.

It is decision-making software that can

reach a level of performance comparable to

a human expert in some specialized and

usually narrow problem area.

The idea is simple: expertise is transferred

from an expert or other source of expertise

to the computer.

-cont… The transfer of expertise from an expert to a computer and then to the

user involves four activities:

Knowledge acquisition (from experts or other sources)

Knowledge representation (organized as rules or frames in the computer)

Knowledge inferencing is performed in a component called the inference engine of the ES and results in the recommendation.

Knowledge transfer to the user (the expert’s knowledge has been transferred to users).

Chapter 12 53

The Benefits of Expert Systems

Benefit Description

Increased output and productivityESs can configure for each custom order. Increasing production capabilities

Increased qualityESs can provide consistent advise and reduce error rates.

Capture and dissemination of scarce expertise

Expertise from anywhere in the world can be obtained and used.

Operation in hazardous environments

Sensors can collect information that an ES interprets, enabling human workers to avoid hot, humid, or toxic environments.

Accessibility to knowledge and help desks

ESs can increase the productivity of help – desk employee, or even automate this function.

Reliability ESs do not become tired or bored, call in sick or go on strike. They consistently pay attention to details.

Chapter 12 54

Benefits of EX

Chapter 12 55

Benefits Description

Ability to work with incomplete or uncertain information

Even with answer of ‘ don’t know ‘ an ES can produce an answer, though it may not be a definite one.

Provision of training The explanation facility of an ES can serve as a teaching device and knowledge base for novices.

Enhancement of decision- making and problem-solving capabilities

ESs allow the integration of expert judgment into analysis (e.g., diagnosis of machine malfunction and even medical diagnosis).

Decreased decision-making time ESs usually can make faster decision than humans working alone.

Reduce downtimeESs can quickly diagnose faster decisions than humans and prescribe repairs.

Limitations of ES

• Not widely used or tested

• Limited to relatively narrow problems

• Cannot readily deal with “mixed” knowledge

• Possibility of error

• Cannot refine own knowledge base

• Difficult to maintain

• May have high development costs

• Raise legal and ethical concerns

Natural Language Processing & Voice Technologies

• Natural language processing (NLP): Communicating with a computer in English or whatever language you may speak.

• Natural language understanding/speech (voice) recognition: The ability of a computer to comprehend instructions given in ordinary language, via the keyboard or by voice.

• Natural language generation/voice synthesis: Technology that enables computers to produce ordinary language, by “voice” or on the screen, so that people can understand computers more easily.

Chapter 12 57

Neural Networks

• Neural networks are a system of programs and data structures that approximates the operation of the human brain.

• Neural networks are particularly good at recognizing subtle, hidden, and newly emerging patterns within complex data as well as interpreting incomplete inputs.

Chapter 12 58

Fuzzy Logic

• Fuzzy logic deals with the uncertainties by simulating the process of human reasoning, allowing the computer to behave less precisely and logically than conventional computers do. – Involves decision in gray areas.– Uses creative decision-making processes.

Chapter 12 59