CHAPTER 9: ENABLING THE ORGANIZATION- DECISION MAKING

DECISION MAKING

lReasons for the growth of decision making information systems:

ØPeople need to analyze large amount of information

ØPeople must make decisions quickly

ØPeople must apply sophisticated analysis techniques, such as modeling and forecasting, to make good decisions.

ØPeople must protect the corporate asset of organizational information.

TRANSACTIONAL PROCESSING SYSTEMS

• Transactional processing system - The basic bussiness system that serves the operational level ina an organization
• Online transaction processing (OLTP)- the capturing of transactional 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.
• Online analytical processing (OLAP) - the manipulation of information to create business intelligence in support of strategic decision making.

Decision Support Systems

• Decision support system (DSS) - models information to support managers and business professionals during the decision-making process
• 3 quatitative models used by DDs include:

1.  Sensitivitiy 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 neccessary to achieve a goal such as a desired level of output.

WHAT-IF ANALYSIS

GOAL-SEEKING ANALYSIS

 

INTERACTING BETWEEN A TPS AND A DSS

EXECUTIVE INFORMATION SYSTEMS

• Executive information system (EIS) - a specialized DSS that supports senior level executives within the organization
• Most EISs offering th following capabilities:
• Consolidation - involves the aggregation of information and features simple roll-ups to complex groupings of interelated information
• Drill-down- enables users to get details, and details of details, of information
• Slice-and dice - looks a information from different perspective.

• Digital dashboard- integrates information from multiple components and presents it in a unified display.

ARTIFICIAL INTELLIGENCE (AI)

• Intelligent system- various commercial appplications of artificial intelligence
• Artificial intelligence (AI) - simulates human intelligence such as the ability to reason and learn.
• 4 most common categories of AI include:

1. Expert system- computerized advisory programs that imitate the reasoning processes of exports in solving difficult problems
2. Neural Network - attempts to emulate the way human brain works
3. Genetic algorithm - an artificial intelligent system taht mimics the evoluntionary, survival of the fittest process to generate increasingly better solutions to a problem.
4. Intelligent agent - special-proposed knowledge-based information system that accomplishes specific tasks on behalf of its users.

DATA MINING

• Cluster analysis
• Association detection
• Statiscal analysis