Chapter 14 by PW6UO1


									              Enhancing Decision Making

                    Chapter 12 (10E)

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            The Decision-Making Process

   Simon’s four stages
   Mintzberg’s managerial roles
   Real-world decision making
     – Relationship between roles and decision
     – Information quality dimensions
     – Management filters
     – Organizational inertia and politics

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               Types of Decisions (Simon)

   Structured decisions are repetitive, routine, and
    involve a definite procedure for handling (e.g.,
    restock inventory)
   Unstructured decisions are nonroutine decisions in
    which the decision maker must provide judgment,
    evaluation, and insights; there is no agreed-upon
    procedure for making the decision (e.g., decide on
    corporate objectives).
   Semistructured decisions are ones where only part
    of the problem has a clear-cut answer provided by
    an acceptable procedure (e.g., develop a marketing

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         Simon’s Decision Making Process

Is there a problem?           Intelligence

What are the alternatives?       Design

Which should you choose?        Choice

Is the choice working?       Implementation

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    Mintzberg’s Managerial Roles
Role                               Support System
   Figurehead                        None
   Leader                            None
   Liaison                           E-mail
   Nerve Center                      MIS, ESS
   Disseminator                      Mail, office systems
   Spokesperson                      Office systems
   Entrepreneur                      None
   Disturbance handler               None
   Recourse allocator                DSS
   Negotiator                        None

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          Information Quality Dimensions

   Accuracy (representation of reality)
   Integrity
   Consistency
   Completeness
   Validity
   Timeliness
   Accessibility

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              Real World Decision Making

   Often decision support do not work because
    – One or more dimensions of information
      quality are poor (e.g., accuracy,
      completeness, timeliness, etc.)
    – Managerial filters or bias (only see the
      good news and ignore the bad)
    – Organizational inertia (e.g., Britannica,

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            Systems for Decision Support

   MIS (covered in chapter 2)

   DSS

   GIS

   CDSS

   ESS

   GDSS (not covered)

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              A Definition of a DSS
A DSS is a computer system at the
  management level of an organization that
  combines data, sophisticated analytical
  models, and user-friendly software to
  support semi structured and unstructured
  decision making.

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                    Components of a DSS
     DSS database
       – collection of current or historical data and possibly
         some external data
       – may be small dataset downloaded from corporate
         mainframes to a PC
       – may be a massive data warehouse
     DSS software system contains the software tools for data
      analysis, with models, data mining, and other analytical
       – collection of mathematical models (statistical models,
         linear programming, forecasting, sensitivity analysis

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                    Characteristics of a DSS

   DSS offer users flexibility, adaptability, and a quick
    response (usually interactive)
   DSS allow users to initiate and control the input and
   DSS operate with little or no assistance from
    professional programmers
   DSS provide support for decisions and problems
    whose solutions cannot be specified in advance
   DSS use sophisticated analysis and modeling tools

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    Some Specifics About How a DSS Can
     Improve Managerial Decision Making
   In the intelligence phase
     – produce more timely data
     – increase the use of quantitative data
     – make more data available
   In the design phase
     – generate more alternatives
     – generate more accurate alternatives
   In the choice phase
     – make faster decisions
     – sometimes rank the choices

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                        Types of DSS
   Model-driven DSS are primarily standalone systems that
    use some type of quantitative model to perform “what-if”
    and other types of analysis.
   Data-driven DSS are systems that analyze large pools of
    data collected stored in a data warehouse; these
    systems permit managers to extract useful relationships
    that are hidden in the data. Two techniques are used
     – On-line analytical processing (OLAP)
     – Datamining as knowledge discovery (search for
       hidden patterns)
   Web-based DSS exist for both types (customer decision
    support systems)

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      Differences Between a DSS and MIS
   DSS Philosophy                   MIS Philosophy
     – provide integrated              – provide structured
       tools, data, models               information to end
       and language to                   users
       users                         MIS Systems Analysis
   DSS Systems Analysis               – identify information
     – establish what tools              requirements up
       are needed in the                 front
       decision process              Design
   Design                             – deliver system based
     – iterative process                 on frozen

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