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Principles of Decision Support Systems

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Title: Principles of Decision Support Systems


1
Principles of Decision Support Systems
Introduction to Decision Support Systems
  • Abe Feinberg
  • California State University,
  • Northridge

1
2
Managers and Managerial Work
  • Managing within an Organization
  • Definition A System of Resources Structured by
    Power Centers to Achieve some Objectives within
    an Environment
  • Orientation Public lt---gt Private
  • Size of the Organization
  • Durability of the Organization

2
3
Structuring the Resources
INPUTS
ORGANIZATION
OUTPUTS
Money
Funds
Monetary Resources Material Resources Human
Resources
Materials
Products
People
Services
Knowledge
Knowledge Resources
Knowledge
3
4
Organizational Aspects
  • Power Centers
  • Organizational Purposes or Objectives
  • Organizational Environment External and
    Internal

4
5
Managerial Functions
  • Planning
  • Organizing
  • Commanding
  • Coordinating
  • Controlling

5
6
Mangerial Roles
  • Informational
  • Interpersonal
  • Decisional Entrepreneur Disturbance Handler
    Resource Allocator and Negotiator

6
7
Types of Knowledge
  • Descriptive Information or Data
  • Examples Demand for Service, Inventories,
    Personnel Records
  • Procedural How to do something or steps to
    follow to do something or an Algorithm

7
8
Decisions
  • What is Decision Making?
  • Choosing among Alternatives?
  • Generating Alternatives?
  • Selecting a Course of Actions?
  • Handling Risk?
  • All of the Above!!

8
9
Decision Context
  • Organizational Setting Planning vs. Control
  • Emergent vs. Established Situation
  • Timing of Decisions
  • Organizational Design Centralized vs.
    Decentralized
  • Decision Type Strategic or Tactical

9
10
Decision Structuredness
  • Programmed
  • Structured
  • Semi-Structured
  • Unstructured
  • The Degree of Structuredness Can Change over Time
  • Negotiated vs. Unilateral Decisions

10
11
Contributions of DSSs
  • Answering What-If Questions
  • Assessing Potential Outcomes
  • Aiding Negotiations
  • Providing Consistent Decisions
  • Evaluating and Limiting Risk

11
12
Some DSS examples
  • Forecasting Demand for Service
  • Staffing
  • Resource Allocation
  • Project Management
  • Vehicle Routing
  • Waste Disposal

11A
13
DECISION MAKING AND COMPUTERIZED SUPPORT
  • Management Support Systems (MSS)Computerized
    technologies
  • Objectives
  • Support managerial work
  • Support decision making

12
14
Management Support SystemsAn Overview
  • Emerging and Advanced Computer Technologies for
    Supporting Managerial Problem Solution
  • Changing Organizational Structure
  • Enabling Business Transformation
  • Changing Management Methods

14
15
Managers and Decision MakingWhy Computerized
Support?
  • Competition
  • Speed
  • The MANAGERS are always responsible for decision
    making

15
16
Factors AffectingDecision Making
  • Technology / Information / Computers
  • Structural Complexity / Competition
  • International Markets / Political Stability /
    Consumerism
  • Changes, Fluctuations

16
17
Managers and Computerized Support
  • Information Technology vital to the business
  • Support technologies extensively implemented

17
18
  • Computer Applications Evolving
  • from Transaction Processing Systems (TPS) and MIS
  • to Proactive Applications (DSS)
  • New modern management tools in
  • Data access
  • Online analytical processing (OLAP)
  • Internet / Intranet / Web
  • for decision support

18
19
Need for Computerized Decision Support and the
Supporting Technologies
  • Speedy computations
  • Overcome cognitive limits in processing and
    storage
  • Cognitive limits may restrict an individuals
    problem-solving capability
  • Cost reduction
  • Technical support
  • Quality support
  • Competitive edge

19
20
Decision Support Technologies
  • Management Support Systems (MSS)
  • Decision Support Systems (DSS)
  • Group Support Systems (GSS)
  • Enterprise (Executive) Information Systems (EIS)
  • Enterprise Resource Planning (ERP) and
    Supply-Chain Management (SCM)
  • Knowledge Management Systems
  • Expert Systems (ES)
  • Artificial Neural Networks (ANN)
  • Hybrid Support Systems
  • Intelligent DSS

19
21
Decision Support Framework
Type of Control
Tech Supp. Needs
Type of Decision
Operational Managerial Strategic Control
Control Control
MIS, OR, TP
Fin. Mgt., Distribution
Structured Semi-structured Unstructured
A/R, order entry
Budget Analysis
DSS
Budget Prep., Facility Layout Project Sched.
Build New Facility, Quaity Assurance
Scheduling
Brochure Design
DSS ES, N Nets
Negotiating, Recruiting
New Tech. Devel., Social Resp. Planning
MIS Mgt. Science
EIS, ES Neural Nets.
DSS, ES, EIS Mgt. Science
Tech Support Needed
21
22
  • Unstructured problem has no structured phases
  • Semistructured problem has some (or some parts
    with) structured phases
  • Structured problem has all structured phases
  • Procedures for obtaining the best solution are
    known
  • Objectives are clearly defined
  • Management support systems can be useful

22
23
  • Unstructured problems often solved with human
    intuition
  • Semistructured problems in between
  • Solve with standard solution procedures and human
    judgment
  • A Decision Support System can help managers
    understand problems in addition to providing
    solutions
  • Goal of DSS Increase the effectiveness of
    decision making

23
24
Computer Support for Structured Decisions
  • Since the 1960s
  • Repetitive in nature
  • High level of structure
  • Can abstract and analyze them, and classify them
    into prototypes
  • Solve with quantitative formulas or models
  • Management Science (MS) / Operations Research
    (OR)

24
25
Management Science
  • Scientific approach to automate managerial
    decision making1. Define problem2. Classify
    problem 3. Construct mathematical model4.
    Find and evaluate potential solutions5. Choose
    and recommend a solutionModeling Transforming
    the real-world problem into an appropriate
    prototype structure

25
26
Decision Support Systems Concept
  • DSS are interactive computer-based systems, which
    help decision makers utilize data and models to
    solve unstructured problems
  • Decision support systems couple the intellectual
    resources of individuals with the capabilities of
    the computer to improve the quality of decisions.
    It is a computer-based support system for
    management decision makers who deal with
    semi-structured problems
  • Content-free expression
  • There is no universally accepted definition of
    DSS
  • Umbrella term vs. narrow definition (specific
    technology)

26
27
Major DSS Characteristics
  • DSS Example for Mineral Exploration
  • Initial risk analysis (management science)
  • Model scrutiny using experience, judgment, and
    intuition
  • Initial model mathematically correct, but
    incomplete
  • DSS provided very quick analysis
  • DSS flexible and responsive. Allows managerial
    intuition and judgment

27
28
Why Use DSS?
  • Perceived benefits
  • decision quality
  • improved communication
  • cost reduction
  • increased productivity
  • time savings
  • improved customer and employee satisfaction

28
29
Major Reasons
  • Unstable economy
  • Difficulty in tracking numerous business
    objectives
  • Increased competition
  • Electronic commerce
  • Existing systems did not support decision making
  • IS Department is too busy
  • Special analysis
  • Need accurate information
  • Organizational winner
  • New or timely information needed
  • Mandated by management
  • Cost reductions
  • End-user computing

29
30
Group Support Systems (GSS)
  • Decisions often made by groups
  • Supports groupwork, anytime, anyplace
  • Also called
  • Groupware
  • Electronic meeting systems
  • Collaborative computing

30
31
Executive Information (Support) Systems (EIS, ESS)
  • Organizational view
  • Information needs of executives / managers
  • Customized user seductive interface
  • Timely and effective tracking and control
  • Drill down
  • Filter, compress, and track critical data /
    information
  • Identify problems / opportunities

31
32
EIS
  • Mid-1980s - large corporations
  • Now global
  • Affordable to smaller companies
  • Serves managers as enterprise-wide systems

32
33
Expert Systems (ES)
  • Experts solve complex problems
  • Experts have specific knowledge and experience
  • Expert systems mimic human experts
  • ES performance comparable to or better than
    experts in a specialized and usually narrow
    problem area

33
34
Intelligent Agents
  • Help automate various tasks
  • Increase productivity and quality
  • Learn how you work

34
35
Artificial Neural Systems
  • Artificial Neural Networks (ANN)
  • Mathematical models of the human brain
  • ANN learn patterns in data
  • ANN can work with partial, incomplete, or inexact
    information

35
36
Knowledge Management Systems (KMS)
  • Capture and reuse knowledge at the organizational
    level
  • Knowledge repository for storage
  • Organizational impacts can be dramatic

36
37
ERP and SCM
  • Enterprise Resource Planning (Management)
  • Supply Chain Management including Customer
    Resource Management (CRM)
  • Enterprise-level cost cutters

37
38
Cutting Edge Intelligent Systems
  • Genetic AlgorithmsWork in an evolutionary
    fashion
  • Fuzzy LogicContinuous logic (NOT just True /
    False)
  • Intelligent AgentsIn search engines, e-mail,
    electronic commerce

38
39
Hybrid Support Systems
  • Combines MSS technologies
  • Use strengths of each
  • Goal successful solution of the managerial
    problem
  • Tools support each other
  • Tools can add intelligence to traditional MSS

39
40
Computerized Decision Aids Evolution and
Attributes
  • Computerized procedures development aids decision
    making
  • Early Calculations
  • Intermediate Find, organize and display
    information
  • Current Decision relevant computations, displays
    and interactions
  • Starting Complex fuzzy decision support,
    collaborative decision making and machine
    learning

40
41
DSS supports specific questions
  • Raw Data Status
  • General Analysis
  • Repres. Causal Models
  • Solution Suggestions/ Evals.
  • Solution Selection

What is ?
What is or Why?
What will be? Why?
What if?
What if?
41
42
Evolutionary View of CBIS
  • 1. Time Sequence
  • mid-1950s Transaction Processing Systems (TPS)
  • 1960s MIS
  • 1970s Office Automation Systems DSS
  • 1980s DSS Expanded Commercial applications of
    expert systems Executive Information Systems
  • 1990s Group Support Systems Neural Computing
    Integrated, hybrid computer systems

42
43
  • 2. Computer evolved over time
  • 3. Systemic linkages in how each system processes
    data into information Relationship among these
    and other technologies

43
44
Relationship Among Technologies
  • Each technology unique
  • Technologies interrelated
  • Each supports some aspects of managerial decision
    making
  • Ever expanding role of information technology
    improving management
  • Interrelationship and coordination evolving

44
45
Summary
  • DSS has many definitions
  • Complexity of managerial decision making is
    increasing
  • Computer support for managerial decision making
  • Several MSS technologies including hybrids

45
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