管理信息系统精要版最新版英文教学课件第11章
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• Outdated statistical methods • Solutions: Use player and team data to identify
undervalued players.
Essentials of Management Information Systems
Chapter 11 Improving Decision Making and Managing Knowledge
Essentials of Management Information Systems
Chapter 11 Improving Decision Making and Managing Knowledge
Moneyball: Data-Driven Baseball
Essentials of Management Information Systems
Student Learning Objectives
• What are the different types of decisions, and how does the decision-making process work?
• How do business intelligence and business analytics support decision making?
Essentials of Management Information Systems
Chapter 11 Improving Decision Making and Managing Knowledge
Decision Making and Information Systems
Information Requirements of Key Decision-Making Groups in a Firm
• Demonstrates the use of analysis systems to identify key player characteristics and predict team performance
• Illustrates how information systems improve decision making
• What types of systems are used for enterprisewide knowledge management, and how do they provide value for businesses?
Essentials of Management Information Systems
Essentials of Management Information Systems
Chapter 11 Improving Decision Making and Managing Knowledge
Decision Making and Information Systems
Business Value of Improved Decision Making
Decision
MaΒιβλιοθήκη Baiduer
Allocate support to most valuable customers.
Predict call center daily demand.
Decide parts inventory level daily.
Identify competitive bids from major suppliers.
• How do information systems help people working individually and in groups make decisions more effectively?
Essentials of Management Information Systems
them
• Structured
• Repetitive and routine • Involve definite procedure for handling them so do not have to
be treated as new
• Semistructured
• Only part of problem has clear-cut answer provided by accepted procedure
Video Cases
Case 1: How IBM’s Watson Became a Jeopardy Champion Case 2: Alfresco: Open Source Document Management and Collaboration Case 3: FreshDirect Uses Business Intelligence to Manage Its Online Grocery. Case 4: Business Intelligence Helps the Cincinnati Zoo Work Smarter Instructional Video 1: Analyzing Big Data: IBM Watson After Jeopardy
Chapter 11 Improving Decision Making and Managing Knowledge
Decision Making and Information Systems
The Decision-Making Process 1. Intelligence
• Discovering, identifying, and understanding the problems occurring in the organization—why is there a problem, where, what effects it is having on the firm
making.
• Decisions made at all levels of the firm.
• Some are common, routine, and numerous.
• Although value of improving any single decision may be small, improving hundreds of thousands of “small” decisions adds up to large annual value for the business.
Chapter 11
Improving Decision Making and Managing
Knowledge
Essentials of Management Information Systems
Chapter 11 Improving Decision Making and Managing Knowledge
Annual value to firm
12 $100,000 $1,200,000
4
150,000
365
5,000
1 2,000,000
600,000 1,825,000 2,000,000
150
10,000
1,500,000
Essentials of Management Information Systems
2. Design
• Identifying and exploring various solutions
3. Choice
• Choosing among solution alternatives
4. Implementation
• Making chosen alternative work and monitoring how well solution is working
Senior managers, middle managers, operational managers, and employees have different types of decisions and information requirements.
Figure 11-1
Essentials of Management Information Systems
Chapter 11 Improving Decision Making and Managing Knowledge
Decision Making and Information Systems
Types of Decisions • Unstructured
• Decision maker must provide judgment to solve problem • Novel, important, nonroutine • No well-understood or agreed-upon procedure for making
Chapter 11 Improving Decision Making and Managing Knowledge
Student Learning Objectives
• What are the business benefits of using intelligent techniques in decision making and knowledge management?
Schedule production to fill orders.
Accounts manager
Call Center management Inventory manager
Senior management
Manufacturing manager
Number Value of / year decision
Chapter 11 Improving Decision Making and Managing Knowledge
Decision Making and Information Systems
Business Value of Improved Decision Making • Possible to measure value of improved decision
Chapter 11 Improving Decision Making and Managing Knowledge
LEARNING TRACKS AND VIDEO CASES
Learning Tracks
1. Building and Using Pivot Tables 2. The Expert System Inference Engine 3. Challenges of Knowledge Management Systems
Essentials of Management Information Systems
Chapter 11 Improving Decision Making and Managing Knowledge
Moneyball: Data-Driven Baseball
• Problem: Wealthier Major League baseball teams operate with an “unfair” advantage—the ability to hire the best players.
Moneyball: Data-Driven Baseball
• 2002 Oakland A’s operating with one of the smallest budgets in Major League baseball, $41 million, compared with wealthiest team, the New York Yankees, who had a budget of $126 million, used newly improved statistical methods, not yet used by bigger teams, to identify undervalued winning players
undervalued players.
Essentials of Management Information Systems
Chapter 11 Improving Decision Making and Managing Knowledge
Essentials of Management Information Systems
Chapter 11 Improving Decision Making and Managing Knowledge
Moneyball: Data-Driven Baseball
Essentials of Management Information Systems
Student Learning Objectives
• What are the different types of decisions, and how does the decision-making process work?
• How do business intelligence and business analytics support decision making?
Essentials of Management Information Systems
Chapter 11 Improving Decision Making and Managing Knowledge
Decision Making and Information Systems
Information Requirements of Key Decision-Making Groups in a Firm
• Demonstrates the use of analysis systems to identify key player characteristics and predict team performance
• Illustrates how information systems improve decision making
• What types of systems are used for enterprisewide knowledge management, and how do they provide value for businesses?
Essentials of Management Information Systems
Essentials of Management Information Systems
Chapter 11 Improving Decision Making and Managing Knowledge
Decision Making and Information Systems
Business Value of Improved Decision Making
Decision
MaΒιβλιοθήκη Baiduer
Allocate support to most valuable customers.
Predict call center daily demand.
Decide parts inventory level daily.
Identify competitive bids from major suppliers.
• How do information systems help people working individually and in groups make decisions more effectively?
Essentials of Management Information Systems
them
• Structured
• Repetitive and routine • Involve definite procedure for handling them so do not have to
be treated as new
• Semistructured
• Only part of problem has clear-cut answer provided by accepted procedure
Video Cases
Case 1: How IBM’s Watson Became a Jeopardy Champion Case 2: Alfresco: Open Source Document Management and Collaboration Case 3: FreshDirect Uses Business Intelligence to Manage Its Online Grocery. Case 4: Business Intelligence Helps the Cincinnati Zoo Work Smarter Instructional Video 1: Analyzing Big Data: IBM Watson After Jeopardy
Chapter 11 Improving Decision Making and Managing Knowledge
Decision Making and Information Systems
The Decision-Making Process 1. Intelligence
• Discovering, identifying, and understanding the problems occurring in the organization—why is there a problem, where, what effects it is having on the firm
making.
• Decisions made at all levels of the firm.
• Some are common, routine, and numerous.
• Although value of improving any single decision may be small, improving hundreds of thousands of “small” decisions adds up to large annual value for the business.
Chapter 11
Improving Decision Making and Managing
Knowledge
Essentials of Management Information Systems
Chapter 11 Improving Decision Making and Managing Knowledge
Annual value to firm
12 $100,000 $1,200,000
4
150,000
365
5,000
1 2,000,000
600,000 1,825,000 2,000,000
150
10,000
1,500,000
Essentials of Management Information Systems
2. Design
• Identifying and exploring various solutions
3. Choice
• Choosing among solution alternatives
4. Implementation
• Making chosen alternative work and monitoring how well solution is working
Senior managers, middle managers, operational managers, and employees have different types of decisions and information requirements.
Figure 11-1
Essentials of Management Information Systems
Chapter 11 Improving Decision Making and Managing Knowledge
Decision Making and Information Systems
Types of Decisions • Unstructured
• Decision maker must provide judgment to solve problem • Novel, important, nonroutine • No well-understood or agreed-upon procedure for making
Chapter 11 Improving Decision Making and Managing Knowledge
Student Learning Objectives
• What are the business benefits of using intelligent techniques in decision making and knowledge management?
Schedule production to fill orders.
Accounts manager
Call Center management Inventory manager
Senior management
Manufacturing manager
Number Value of / year decision
Chapter 11 Improving Decision Making and Managing Knowledge
Decision Making and Information Systems
Business Value of Improved Decision Making • Possible to measure value of improved decision
Chapter 11 Improving Decision Making and Managing Knowledge
LEARNING TRACKS AND VIDEO CASES
Learning Tracks
1. Building and Using Pivot Tables 2. The Expert System Inference Engine 3. Challenges of Knowledge Management Systems
Essentials of Management Information Systems
Chapter 11 Improving Decision Making and Managing Knowledge
Moneyball: Data-Driven Baseball
• Problem: Wealthier Major League baseball teams operate with an “unfair” advantage—the ability to hire the best players.
Moneyball: Data-Driven Baseball
• 2002 Oakland A’s operating with one of the smallest budgets in Major League baseball, $41 million, compared with wealthiest team, the New York Yankees, who had a budget of $126 million, used newly improved statistical methods, not yet used by bigger teams, to identify undervalued winning players