Chapter 9 – Enabling the Organization-Decision Making


Decision Making 
  • Ø  Reasons for Growth of Decision Making Information System
-          People need to analyze large amounts of information – Improvements in technology itself, innovations in communication, and globalization have resulted in a dramatic increase in the alternatives and dimensions people need to consider when making a decision or appraising an opportunity
-          People must make decisions quickly – Time is of the essence and people simply do not have time to sift through all the information manually
-          People must apply sophisticated analysis techniques, such as modeling and forecasting, to  make good decisions – Information systems substantially reduce the time required to perform these sophisticated analysis techniques
-          People must protect the corporate asset of organizational information – Information systems offer the security required to ensure organizational information remains safe.




 MODEL
model is a simplified representation or abstraction of reality.
 -Models can calculate risks, understand uncertainly , change variable, and manipulate time.
- Decision-making information systems work by building models out of organization information to lend insight into important business issues and opportunities.
Each system uses different models to assist in decision making, problem solving, and opportunity capturing. This system includes:
    -Transaction Processing System.
    -Decision Support Systems.
    -Executive Information Systems.   



  • Ø  IT systems in an enterprise


  •  Transaction Processing Systems
The structure of a typical organization is similar to a pyramid. Organizational activities occur at different levels of the pyramid. People in the organization have unique information needs and thus require various sets of IT tools.
   
 - Online transaction processing is the manipulation of information to create business intelligence in support of strategic decision making.


Transaction Processing System
  • Ø  Moving up through the organizational pyramid users move from requiring transactional information to analytical information

  • Ø  Transaction processing system – the basic business system that serves the operational level (analysis) in an organization
  •   Online transaction processing (OLTP) – the capturing of transaction and event information using technology to (1) process the information according to defined business rules, (2) store the information, (3) update existing information to reflect the new information
Ø  Online analytical processing (OLAP) – the manipulation of information to create business intelligence in support of strategic decision making

Decision support systems
  • Ø  Decision support system (DSS) – models information to support managers and business professionals during the decision-making process
  • Ø  Three quantitative models used by DSSs include;
1.       Sensitivity analysis – the study of the impact that changes in one (or more) parts of the model have on other parts of the model
2.       What-if analysis – checks the impact of a change in an assumption on the proposed solution
3.       Goal-seeking analysis – finds the inputs necessary to achieve a goal such as a desired level of outputs

What-if analysis


Goal-seeking analysis


Executive information system 
  • Ø  Executive information system (EIS) – A specialized DSS that supports senior level executives within the organization
  • Ø  Most EISs offering the following capabilities;
-          Consolidation – involves the aggregation of information and features simple roll-ups to complex groupings of interrelated information
-          Drill-down – enables users to get details, and details of information
-          Slice-and-dice – looks at information from different perspectives

  • Ø  Interaction between a TPS and an EIS


  • Ø  Interaction between a TPS and a DSS


  • Ø  Digital dashboard – integrates information from multiple components and presents it in a united display



Artificial Intelligence (AI) 

Executive information systems are starting to take advantage of artificial intelligence to help executives make strategic decisions.
Phili Lumish said that competing in the internet arena is competing with the entire world rather than a store down the block or a few miles away.
Intelligent Systems are various commercial applications of artificial intelligence. --
Artificial inteligence(AI) simulates human intelligence such as ability to reason and learn.

 AI systems dramatically increase the speed and consistency of decision making, solve problems with incomplete information, and solve complicated issues that cannot be solved by conventional computing. There are many categories of AI systems:


    -Expert System

    -Neural Networks
    -Genetic Algorithms
    -Intelligent agents

Expert system are computerized advisory program that imitate the reasoning processes of experts in solving difficult problems.

    
+neural Network, also called an artificial neural network, is a category of AI that attempts to emulate the way the human brain works.
    - Fuzzy logic: It is an artificial method of handing imprecise or subjective information.
  
 +A genetic algorithms is an artificial intelligence system that mimic the evolutionary, survival-of-the-fittest process to generate increasingly better solutions to a problem.

Intelligent agents is a special-purpose knowledge-based information system that accomplished specific task as on behalf of its users. A shopping both is simple example of an intelligent agent.
    - Shopping bot is the software that will search several retailer websites and provide a comparison of each retailer's offering including price and availability.



Multi-Agent Systems and Agent Modeling
By observing the ecosystem like ant or bee colonies, artificial intelligence scientists can use hardware and software models that incorporate insect characteristics and behavior to:
 - Learn how people-based system behave
 - predict how they will behave under a given set of circumstances
 - improve human system to make them more efficient and effective.
This concept of learning from ecosystems and adapting their characteristics to human and organizational situations is called biomimicry.
Data Mining
Data miming system sift instantly through the information to uncover patterns and relationships that would elude an army of human research.
Data-mining software typically includes many forms of AI such us networks and expert system.



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