McGraw-Hill/Irwin © 2008 The McGraw-Hill Companies, All Rights Reserved

Unit ThreeUnit Three

Streaming Business Streaming Business OperationsOperations

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Unit Three

• Chapter Nine – Enabling the Organization – Decision Making

• Chapter Ten – Extending the Organization – Supply Chain Management

• Chapter Eleven – Building a Customer-centric Organization – Customer Relationship Management

• Chapter Twelve – Integrating the Organization from End to End – Enterprise Resource Planning

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Unit Three

• Decision-enabling, problem-solving, and opportunity-seizing systems

McGraw-Hill/Irwin © 2008 The McGraw-Hill Companies, All Rights Reserved

Chapter 9Chapter 9

Enabling the Organization Enabling the Organization – Decision Making– Decision Making

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Learning Outcomes

9.1 Define the systems organizations use to make decisions and gain competitive advantages

9.2 Describe the three quantitative models typically used by decision support systems

9.3 Describe the relationship between digital dashboards and executive information systems

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Learning Outcomes

9.4 List and describe four types of artificial intelligence systems

9.5 Describe three types of data-mining analysis capabilities

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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 good decisions

– People must protect the corporate asset of organizational information

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Decision Making

• Model – a simplified representation or abstraction of reality

• IT systems in an enterprise

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Transaction Processing Systems

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

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Transaction Processing Systems

• 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

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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

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Decision Support Systems

• What-if analysis

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Decision Support Systems

• Goal-seeking analysis

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Decision Support Systems

• Interaction between a TPS and a DSS

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Executive Information Systems

• Executive information system (EIS) – 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

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Executive Information Systems

• Interaction between a TPS and an EIS

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Executive Information Systems

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

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Artificial Intelligence (AI)

• Intelligent system – various commercial applications of artificial intelligence

• Artificial intelligence (AI) – simulates human intelligence such as the ability to reason and learn

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Artificial Intelligence (AI)

• The ultimate goal of AI is the ability to build a system that can mimic human intelligence

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Artificial Intelligence (AI)

• 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

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Artificial Intelligence (AI)

• Four most common categories of AI include: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

• Multi-agent systems• Agent-based modeling

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Data Mining

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

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Data Mining

• Common forms of data-mining analysis capabilities include:

– Cluster analysis– Association detection– Statistical analysis

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Cluster Analysis

• 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

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Association Detection

• 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

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Statistical Analysis

• 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

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OPENING CASE STUDY QUESTIONS

Second Life1. How could companies use Second

Life to enhance decision making for a new product or service?

2. How could financial companies use neural networks in Second Life to help their businesses?

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OPENING CASE STUDY QUESTIONS

Second Life3. How could a company such as Nike

use decision support systems on Second Life to help its business?

4. How could an apparel company use Second Life to build a digital dashboard to monitor virtual operations?

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CHAPTER NINE CASE

DARPA Grand Challenge• The DARPA Grand Challenge was designed

to leverage American ingenuity to develop autonomous vehicle technologies that can be used by the military

• With the goal of saving lives on the battlefield, the DARPA Grand Challenge brings together individuals and organizations from industry, the R&D community, government, the armed services, and academia, and includes students, backyard inventors, and automotive enthusiasts

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Chapter Nine Case Questions

1. Describe how the DoD is using AI to improve its operations and save lives

2. Explain why the DoD would use an event, such as the DARPA Grand Challenge, to further technological innovation

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Chapter Nine Case Questions

3. Describe how autonomous vehicles could be used by organizations around the world to improve business efficiency and effectiveness

4. The Ansari X is another technological innovation competition focusing on spacecraft. To win the $10 million Ansari X Prize, a private spacecraft had to be the first to carry the weight equivalent of three people to an altitude of 62.14 miles twice within two weeks. SpaceShipOne, a privately built spacecraft, won the $10 million Ansari X Prize on October 4, 2004. Describe the potential business impacts of the Ansari X competition