Management Information System

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Management Information System

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Title: O'Brien MIS, 6th ed. Author: Lanny Wilke Last modified by: jpsugiono Created Date: 6/3/2000 2:02:17 PM Document presentation format: On-screen Show –

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Title: Management Information System


1
Management Information System
8
  • Decision Support System

Judi Prajetno Sugiono jpsugiono_at_gmail.com (2008)
2
Learning Objectives
  • Identify the changes taking place in the form and
    use of decision support in e-business
    enterprises.
  • Identify the role and reporting alternatives of
    management information systems.

3
Learning Objectives (continued)
  • 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.

4
Learning Objectives (continued)
  • Explain how the following information systems can
    support the information needs of executives,
    managers, and business professionals
  • Executive information systems
  • Enterprise information portals
  • Enterprise knowledge portals

5
Learning Objectives (continued)
  • Identify how neural networks, fuzzy logic,
    genetic algorithms, virtual reality, and
    intelligent agents can be used in business.
  • How can expert systems be used in business
    decision-making situations?

6
Section I
  • Decision Support in Business

7
Business and Decision Support
  • To succeed, companies need information systems
    that can support the diverse information and
    decision-making needs of their managers and
    business professionals.

8
Business and Decision Support (continued)
  • Information, Decisions, Management
  • The type of information required by decision
    makers is directly related to the level of
    management and the amount of structure in the
    decision situations.

9
Business and Decision Support (continued)
10
Business and Decision Support (continued)
  • Information Quality
  • Timeliness
  • Provided WHEN it is needed
  • Up-to-date when it is provided
  • Provided as often as needed
  • Provided about past, present, and future time
    periods as necessary

11
Business and Decision Support (continued)
  • Information Quality (continued)
  • Content
  • Free from errors
  • Should be related to the information needs of a
    specific recipient for a specific situation
  • Provide all the information that is needed
  • Only the information that is needed should be
    provided
  • Can have a broad or narrow scope, or an internal
    or external focus
  • Can reveal performance

12
Business and Decision Support (continued)
  • Information Quality (continued)
  • Form
  • Provided in a form that is easy to understand
  • Can be provided in detail or summary form
  • Can be arranged in a predetermined sequence
  • Can be presented in narrative, numeric, graphic,
    or other forms
  • Can be provided in hard copy, video, or other
    media.

13
Business and Decision Support (continued)
14
Business and Decision Support (continued)
  • Decision Structure
  • Structured decisions
  • Involve situations where the procedures to be
    followed can be specified in advance
  • Unstructured decisions
  • Involve situations where it is not possible to
    specify most of the decision procedures in advance

15
Business and Decision Support (continued)
  • Decision structure (continued)
  • Semistructured decisions
  • Some decision procedures can be specified in
    advance, but not enough to lead to a definite
    recommended decision

16
Business and Decision Support (continued)
  • Amount of structure is typically tied to
    management level
  • Operational more structured
  • Tactical more semistructured
  • Strategic more unstructured

17
Decision Support Trends
  • The growth of corporate intranets, extranets and
    the Web has accelerated the development and use
    of executive class information delivery
    decision support software tools to virtually
    every level of the organization.

18
Management Information Systems
  • The original type of information system
  • Produces many of the products that support
    day-to-day decision-making
  • These information products typically take the
    following forms
  • Periodic scheduled reports
  • Exception reports
  • Demand reports and responses
  • Push reports

19
Management Information Systems (continued)
  • Management reporting alternatives
  • Periodic scheduled reports
  • Prespecified format
  • Provided on a scheduled basis
  • Exception reports
  • Produced only when exceptional conditions occur
  • Reduces information overload

20
Management Information Systems (continued)
  • Management reporting alternatives (continued)
  • Demand reports and responses
  • Available when demanded.
  • Ad hoc
  • Push reports
  • Information is sent to a networked PC over the
    corporate intranet.
  • Not specifically requested by the recipient

21
Online Analytical Processing
  • Enables managers and analysts to interactively
    examine manipulate large amounts of detailed
    and consolidated data from many perspectives
  • Analyze complex relationships to discover
    patterns, trends, and exception conditions
  • Real-time

22
Online Analytical Processing (continued)
  • Involves..
  • Consolidation
  • The aggregation of data.
  • From simple roll-ups to complex groupings of
    interrelated data
  • Drill-Down
  • Display detail data that comprise consolidated
    data

23
Online Analytical Processing (continued)
  • Slicing and Dicing
  • The ability to look at the database from
    different viewpoints.
  • When performed along a time axis, helps analyze
    trends and find patterns

24
Decision Support Systems
  • Computer-based information systems that provide
    interactive information support during the
    decision-making process
  • DSSs use
  • Analytical models
  • Specialized databases
  • The decision makers insights judgments
  • An interactive, computer-based modeling process
    to support making semistructured and unstructured
    business decisions

25
Decision Support Systems (continued)
  • Designed to be ad hoc, quick-response systems
    that are initiated and controlled by the decision
    maker
  • DSS Models and Software
  • Rely on model bases as well as databases
  • Might include models and analytical techniques
    used to express complex relationships

26
Decision Support Systems (continued)
  • DSS models and software (continued)
  • Can combine model components to create integrated
    models in support of specific types of business
    decisions

27
Decision Support Systems (continued)
  • Geographic Information Data Visualization
    Systems
  • Special categories of DSS that integrate computer
    graphics with other DSS features
  • GIS
  • A DSS that uses geographic databases to construct
    and display maps and other graphics displays

28
Decision Support Systems (continued)
  • Geographic information and data visualization
    systems (continued)
  • Data visualization systems
  • Represent complex data using interactive
    three-dimensional graphic forms
  • Helps discover patterns, links, and anomalies

29
Using Decision Support Systems
  • An interactive modeling process
  • Four types of analytical modeling
  • What-if analysis
  • Sensitivity analysis
  • Goal-seeking analysis
  • Optimization analysis

30
Using Decision Support Systems (continued)
  • What-If Analysis
  • End user makes changes to variables, or
    relationships among variables, and observes the
    resulting changes in the values of other variables

31
Using Decision Support Systems (continued)
  • Sensitivity Analysis
  • A special case of what-if analysis
  • The value of only one variable is changed
    repeatedly, and the resulting changes on other
    variables are observed
  • Typically used when there is uncertainty about
    the assumptions made in estimating the value of
    certain key variables

32
Using Decision Support Systems (continued)
  • Goal-Seeking Analysis
  • Instead of observing how changes in a variable
    affect other variables, goal-seeking sets a
    target value (a goal) for a variable, then
    repeatedly changes other variables until the
    target value is achieved

33
Using Decision Support Systems (continued)
  • Optimization Analysis
  • A more complex extension of goal-seeking
  • The goal is to find the optimum value for one or
    more target variables, given certain constraints

34
Using Decision Support Systems (continued)
  • Data Mining for Decision Support
  • Software analyzes vast amounts of data
  • Attempts to discover patterns, trends,
    correlations
  • May perform regression, decision tree, neural
    network, cluster detection, or market basket
    analysis

35
Executive Information Systems
  • EISs combine many of the features of MIS and DSS
  • Originally intended to provide top executives
    with immediate, easy access to information about
    the firms critical success factors
  • Alternative names
  • Enterprise information systems
  • Executive support systems

36
Executive Information Systems (continued)
  • Features of an EIS
  • Information presented in forms tailored to the
    preferences of the users
  • Most stress use of graphical user interface and
    graphics displays
  • May also include exception reporting and trend
    analysis

37
Enterprise Portals and Decision Support
  • A Web-based interface and integration of intranet
    and other technologies that gives all intranet
    users and selected extranet users access to a
    variety of internal external business
    applications and services

38
Enterprise Portals and Decision Support
(continued)
  • Business benefits
  • More specific and selective information
  • Easy access to key corporate intranet website
    resources
  • Industry and business news
  • Access to company data for stakeholders
  • Less time spent on unproductive surfing

39
Knowledge Management Systems
  • IT that helps gather, organize, and share
    business knowledge within an organization
  • Hypermedia databases that store and disseminate
    business knowledge. May also be called knowledge
    bases
  • Best practices, policies, business solutions
  • Entered through the enterprise knowledge portal

40
Section II
  • Artificial Intelligence Technologies in Business

41
Business and AI
  • Designed to leverage the capabilities of humans
    rather than replace them,AI technology enables
    an extraordinary array of applications that forge
    new connections among people, computers,
    knowledge, and the physical world.

42
Artificial Intelligence
  • A field of science and technology based on
    disciplines such as computer science, biology,
    psychology, linguistics, mathematics,
    engineering
  • Goal is to develop computers that can think, see,
    hear, walk, talk, and feel
  • Major thrust development of computer functions
    normally associated with human intelligence
    reasoning, learning, problem solving

43
Artificial Intelligence (continued)
  • Domains of AI
  • Three major areas
  • Cognitive science
  • Robotics
  • Natural interfaces

44
Artificial Intelligence (continued)
  • Cognitive science
  • Focuses on researching how the human brain works
    how humans think and learn
  • Applications
  • Expert systems
  • Adaptive learning systems
  • Fuzzy logic systems
  • Neural networks
  • Intelligent agents

45
Artificial Intelligence (continued)
  • Robotics
  • Produces robot machines with computer
    intelligence and computer controlled, humanlike
    physical capabilities
  • Natural interfaces
  • Natural language and speech recognition
  • Talking to a computer and having it understand
  • Virtual reality

46
Neural Networks
  • Computing systems modeled after the brains
    meshlike network of interconnected processing
    elements, called neurons
  • Goal the neural network learns from data it
    processes

47
Fuzzy Logic Systems
  • A method of reasoning that resembles human
    reasoning
  • Allows for approximate values and inferences
  • Allows for incomplete or ambiguous data
  • Allows fuzzy systems to process incomplete data
    and provide approximate, but acceptable,
    solutions to problems

48
Genetic Algorithms
  • Uses Darwinian, randomizing, other mathematical
    functions to simulate an evolutionary process
    that can yield increasingly better solutions
  • Especially useful for situations in which
    thousands of solutions are possible must be
    evaluated

49
Virtual Reality
  • Computer-simulated reality
  • Relies on multisensory input/output devices
  • Allows interaction with computer-simulated
    objects, entities, and environments in three
    dimensions

50
Intelligent Agents
  • A software surrogate for an end user or a
    process that fulfills a stated need or activity
  • Uses built-in and learned knowledge base about a
    person or process to make decisions and
    accomplish tasks

51
Expert Systems
  • A knowledge-based information system that uses
    its knowledge about a specific, complex
    application area to act as an expert consultant
  • Provides answers to questions in a very specific
    problem area
  • Must be able to explain reasoning process and
    conclusions to the user

52
Expert Systems (continued)
  • Components
  • Knowledge base
  • Software resources

53
Expert Systems (continued)
  • Knowledge base
  • Contains
  • Facts about a specific subject area
  • Heuristics that express the reasoning procedures
    of an expert on the subject

54
Expert Systems (continued)
  • Software Resources
  • Contains an inference engine and other programs
    for refining knowledge and communicating
  • Inference engine processes the knowledge, and
    makes associations and inferences
  • User interface programs, including an explanation
    program, allows communication with user

55
Developing Expert Systems
  • Begin with an expert system shell
  • Add the knowledge base
  • Built by a knowledge engineer
  • Works with experts to capture their knowledge
  • Works with domain experts to build the expert
    system

56
The Value of Expert Systems
57
The Value of Expert Systems (continued)
  • Benefits
  • Can outperform a single human expert in many
    problem situations
  • Helps preserve and reproduce knowledge of experts
  • Limitations
  • Limited focus, inability to learn, maintenance
    problems, developmental costs

58
Discussion Questions
  • Is the form and use of information and decision
    support in e-business changing and expanding?
  • Has the growth of self-directed teams to manage
    work in organizations changed the need for
    strategic, tactical, and operational decision
    making in business?

59
Discussion Questions (continued)
  • What is the difference between the ability of a
    manager to retrieve information instantly on
    demand using an MIS and the capabilities provided
    by a DSS?
  • In what ways does using an electronic spreadsheet
    package provide you with the capabilities of a
    decision support system?

60
Discussion Questions (continued)
  • Are enterprise information portals making
    executive information systems unnecessary?
  • Can computers think? Will they EVER be able to?

61
Discussion Questions (continued)
  • What are some of the most important applications
    of AI in business?
  • What are some of the limitations or dangers you
    see in the use of AI technologies such as expert
    systems, virtual reality, and intelligent agents?
    What could be done to minimize such effects?

62
Real World Case 1 AmeriKing Others
  • AmeriKings old system
  • Relied on an antiquated corporate information
    system.
  • Involved mailing or faxing paper reports to
    managers.
  • AmeriKings new system
  • An intranet-based enterprise information portal
  • Enables employees to use Web browsers to
    instantly access financial, marketing, human
    resource, and other reports.

63
Real World Case 1 (continued)
  • What is the business value to a company of an
    enterprise portal like AmeriKings?
  • What are several ways AmeriKing could improve the
    business value of its portal?

64
Real World Case 1 (continued)
  • How might an enterprise portal help you as a
    business professional or manager in your work
    activities?
  • Is it becoming necessary for all companies to
    provide an enterprise information portal to their
    employees?

65
Real World Case 2 BAE Systems
  • Problems
  • Wasted time trying to find information to do the
    job.
  • Duplication of effort
  • Information overload
  • Inadequate search capability
  • Solution
  • An intranet-based knowledge management system

66
Real World Case 2 (continued)
  • What problems was BAE having in knowledge
    sharing? Are such problems common to many
    companies?
  • How does BAEs knowledge management system help
    solve such problems?

67
Real World Case 2 (continued)
  • What are some of the business benefits and
    potential limitations of BAEs knowledge
    management system?
  • What is the difference between a corporate
    intranet and a knowledge management system? What
    is the difference in their business value?

68
Real World Case 3 Cisco Systems, NetFlix,
Office Depot
  • What are the business benefits and limitations of
    Ciscos Web-based system for its channel
    managers?
  • Do you agree that NetFlixs real-time
    personalization system is critical to their
    success?

69
Real World Case 3 (continued)
  • Do you think salespeople will appreciate and
    benefit from the real-time alert system
    envisioned for Office Depot?

70
Real World Case 4 Producers Assistance,
Kinkos, Champion Printing
  • Using Spatial Information Systems to
  • Find workers
  • Find services
  • Find customers

71
Real World Case 4 (continued)
  • What is the business value of spatial information
    systems?
  • How else could spatial information systems be
    used in business?

72
Real World Case 4 (continued)
  • How helpful is Kinkos location finder service?
    What else can they do to improve this spatial
    information management application?

73
Real World Case 5 Schneider National
  • The business value of business intelligence (BI)
  • We were drowning in data but starving for
    information.

74
Real World Case 5 (continued)
  • What problem was Schneider National having with
    their business data?
  • How did business intelligence solve the problem?

75
Real World Case 5 (continued)
  • What are the benefits and limitations of business
    intelligence software as demonstrated by
    Schneider National?
  • What is the business value of business
    intelligence as defined by Cognos?
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