Chapter 9 : Enabling The Organization - Decision Making

Decision Making

• Model – a simplified representation or abstraction of reality.
• IT systems in an enterprise.

Transaction Processing Systems

• Moving up through the organizational pyramid users move from requiring transactional information to analytical information.

• Transaction processing system - the basic business system that serves the operational level (analysts) 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 

•  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.
• 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 output.

• Interaction between TPS and DSS :

Executive Information Systems

• Executive information system (EIS) – a specialized DSS that supports senior level executives within the organization.
• Most EISs offering the following capabilities :

1. Consolidation – involves the aggregation of information and features simple roll-ups to complex groupings of interrelated information.
2. Drill-down – enables users to get details, and details of details, of information.
3. Slice-and-dice – looks at information from different perspectives

• Interaction between TPS and EIS :

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

Artificial Intelligence

• Intelligent system – various commercial applications of artificial intelligence.
• Artificial intelligence (AI) – simulates human intelligence such as the ability to reason and learn.
• The ultimate goal of AI is the ability to build a system that can mimic human intelligence :

• Four most common categories of AI include :

1. Expert system – computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems.
2. Neural Network – attempts to emulate the way the human brain works Fuzzy logic – a mathematical method of handling imprecise or subjective information.
3. Genetic algorithm – an artificial intelligent system that mimics the evolutionary, survival-of-the-fittest process to generate increasingly better solutions to a problem.
4. Intelligent agent – special-purposed knowledge-based information system that accomplishes specific tasks on behalf of its users.

Data Mining

• Data-mining software includes many forms of AI such as neural networks and expert systems.