Chapter 9: Enabling the Organization - Decision Making

DECISION MAKING

• Reasons for the growth of decision-making information systems:

          * People need to analyze large amounts of information

          * People must make decisions quickly

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

           * People must protect the corporate asset of organizational information.

Model

A simplified representation or abstraction of reality.

• Models can calculate risks, understand uncertainty, change variables and manipulate time.
• IT systems in an enterprise

Executive information systems (EIS)

A specialized DSS that supports senior level executives within the organization.

Decision support system (DSS)

Models information to support managers and business professionals during the decision-making process.

Artificial intelligence (AI)

Stimulates human intelligence such as the ability to reason and learn.

Data mining

Typically includes many forms of AI such as neural networks and expert systems. Data mining tools apply algorithms to information sets to uncover inherent trends and patterns in the information.

Transaction Processing Systems

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

• At the lower levels of the pyramid, people perform daily tasks such as processing transactions.
• Moving up through the organizational pyramid, people typically the managers deal less with the details and more with meaningful aggregations of information that help them to make broader decisions for the organization.

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:

• process the information according to defined business rules.
• store the information
• 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

• Models information to support managers and business professionals during the decision-making process.
• Three quantitative models used by DSSs:

           * Sensitivity analysis - the study of the impact that changes in one or more parts of the model have on other parts of the model.

         

            * What-if analysis - checks the impact of a change in an assumption on the proposed solution.

          

       * Goal-seeking analysis - finds the inputs necessary to achieve a goal such as a desired level of output.

•  What-if analysis

   * This figure displays Excel being used as a DSS to determine "what-if" analysis by using Excel's Scenario Manager to determine what will happen to total sales as the price and quantity of units sold changes.

• Goal-seeking analysis

    * This figure displays Excel being used as a DSS to determine "goal-seeking" by using Excel's Goal Seek tool to determine how much money a person can borrow with an interest rate of 5.5 % and a monthly payment of $ 1,300.

• Interaction between a TPS and a DSS.

         * The TPS supplies transaction-based data to the DSS.

     * The DSS summarizes and aggregates the information from the different TPS systems which assists managers in making informed decisions.

Executive Information Systems

•  A specialized DSS that supports senior level executives within the organization.
• 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 details of information.

            

              * Slice-and-dice - Looks at information from different perspectives.

• Interaction between a TPS and an EIS 

         * The EIS needs information fron the TPS to help executives makes decisions.

               

  * Without knowing the order information, inventory information and shipping information from the TPSs, it would be difficult for the CEO to make strategic decisions for the organization.

Digital dashboard 

Integrates information from multiple components and presents it in a unified display.

Artificial Intelligence (AI)

Intelligent system

Various commercial applications of artificial intelligence.

Artificial intelligence

Stimulates human intelligence such as the ability to reason and learn.

• It advantages is it can check info on competitor.

> Four most common categories of AI include:

  

 * Expert system - Computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems.

   

     * Neural Network - A mathematical method of handling imprecise or subjective information.

  * Genetic algorithm - An artificial intelligent system that mimics the evolutionary, survival-of-the-fittest process to generate increasingly better solutions to a problem.

   

 * Intelligent agent - Special-purposed knowledge-based information system that accomplishes specific tasks on behalf of its user

   - Multi-agent systems

      -Agent-based modeling.

Data Mining

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

• Data-mining tools apply algorithms to informations sets to uncover inherent trends and patterns in the information.
• Analysts use this information to develop new business strategies and business solutions.
• Common forms of data-mining analysis capabilities include:

Cluster Analysis

A technique used to divide an information set into mutually exclusive groups such that the members of each group are as close together as possible to one another and the different groups are as far apart as possible.

• CRM systems depend on cluster analysis to segment customer information and identify behavioral traits.

Association detection

Reveals the degree to which variables are related and the nature and frequency of these relationships in the information.

   * Market basket analysis - Analyzes such items as Web sites and checkout scanner information to detect customers' buying behavior and predict future behavior by identifying affinities among customers choices of products and services.

Statistical analysis 

Performs such functions as information correlations, distributions, calculations and variance analysis.

   * Forecast - Predictions made on the basis of time-series information.

   * Time-series information - Time-stamped information collected at a particular frequency.