CHAPTER 9: ENABLING THE ORGANIZATION DECISION MAKING

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DECISION MAKING

Model: 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:

                                          i.            Transaction Processing System (TPS).

                                        ii.            Decision Support Systems (DSS).

                                      iii.            Executive Information Systems (EIS).

Figure 1: 3 common types of decision-making information systems used in organization today.

Reason for Growth of Decision Making Information System:

a)      People need to analyze large amounts of information

Ø  Improvement in technology itself, innovations in communication, and globalization have resulted in a dramatic increase in the alternatives and dimension people need to consider when making a decision or appraising an opportunity.

b)      People must make decision quickly

Ø  Time is of the essence and people simply do not have time to sift through all the information manually.

c)      People must apply sophisticated analysis technique such as modeling and forecasting to make good decision

Ø  Information systems substantially reduce the time required to perform this sophisticated analysis technique.

d)      People must protect the corporate asset of organizational information

Ø  Information systems offer the security required to ensure organization information remains safe.

                                 i.            TRANSACTION PROCESSING SYSTEM (TPS)

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.

a)      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

b)      Transaction processing system : the basic business system that serves the operational level (analysis) in an organization

c)      Online analytical processing (OLAP) : the manipulation of information to create business intelligence in support of strategic decision making

 Figure 2: enterprise view of information and information technology

       ii.            DECISION SUPPORT SYSTEM (DSS)

A decision support system (DSS) models information to support managers and business professionals during the decision making process.

Three quantitative models are typically used by DSSs:

a)      Sensitivity analysis: the study of the impact that changes in one (or more) parts of the model have on other parts of the model.

b)      What-if analysis: checks the impact of change in an assumption on the proposed solution.

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

Figure 3: Interaction between TPS and DSS

It shows how a TPS is used within a DSS. The TPS supplies transaction –based data to the DSS. The DSS summarizes and aggregates the information from the many different TPS system, which assists manager in making informed decisions.

                       iii.            EXECUTIVE INFORMATION SYSTEMS (EIS)

Executive information system (EIS): A specialized DSS that supports senior level executives within the organization

 Figure 4: Interaction between TPS and EIS.

Most EISs offering the following capabilities:-

a)      Consolidation:  involves the aggregation of information and features simple roll-ups to complex groupings of interrelated information

b)      Drill-down:  enables users to get details, and details of information

c)      Slice-and-dice: looks at information from different perspectives

v DIGITAL DASHBOARDS

A common feature of EIA is digital dashboard.

Digital dashboards: integrate information from multiple components and tailor the information to individual preferences.

It commonly uses indicators to help executives quickly identify the status of the key information or critical success factors.

·         Digital dashboards, whether basic or comprehensive, deliver results quickly.

·         EIS systems such as digital dashboards, allow executives to move beyond reporting to using information to directly impact business performance.

·         Digital Dashboards help executives react to information as it becomes available and make decision, solve problems, and change strategies daily instead of monthly

The dashboard includes more than 300 measures of business performance that fall into one of 3 categories:-

a)      Market pulse: - example include daily sales numbers, market share and subscriber turnover.

b)      Customer service: - example include problems resolved on the first call, call center wait times and on-time repair calls.

c)      Cast driver: - example include number of repair trucks in the field, repair jobs completed per days and call enter productivities.

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: various commercial applications of artificial intelligence.

Artificial intelligence (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:

        i.            Expert System: computerized advisory programs that imitate the reasoning processes of expert in solving difficult problems

      ii.            Neural Networks: also called an artificial neural network is a category of AI that attempts to emulate the way the human brain works.

  iii.            Fuzzy Logic: a mathematical method of handling imprecise or subjective information

  iv.            Genetic Algorithms: is an artificial intelligence system that mimic the evolutionary, an AI system that mimics the evolutionary, survival-if-the-fittest process to generate increasingly better solutions to a problem

      v.            Intelligent agents: special-purposed-knowledge-based information system that accomplishes specific tasks on behalf of its users. A shopping both is simple example of an intelligent agent.

  vi.            Shopping bot: the software that will search several retailer websites and provide a comparison of each retailer's offering including price and availability

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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