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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
14
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.
15
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
16
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
17
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
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