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Enhancing Management Decision Making
for the Digital Firm
Chapter 12
Objectives
1. How can information systems help
individual managers make better decisions
when the problems are nonroutine and
constantly changing?
2. How can information systems help people
working in a group make decisions more
efficiently?
Objectives
3. Are there any special systems that can
facilitate decision making among senior
managers? Exactly what can these systems
do to help high-level management?
4. What value can systems to support
management decision making provide for
the organization as a whole?
Management Challenges
1. Building information systems that can actually
fulfill executive information requirements
2. Create meaningful reporting and management
decision-making processes
Decision-Support Systems (DSS)
• Computer system at the management level of an
organization
• Combines data, analytical tools, and models
• Supports semistructured and unstructured decision
making
Decision-Support Systems (DSS)
MIS
• Provides reports based on routine flow
of data
• Assists in general control of the organization
MIS and DSS
Decision-Support Systems (DSS)
DSS
• Emphasizes change, flexibility, rapid response,
models, assumptions, ad-hoc queries, and display
graphics
MIS and DSS
Decision-Support Systems (DSS)
Model-Driven DSS
• Primarily stand-alone
• Uses model to perform “what-if” and other kinds
of analysis
Types of Decision-Support Systems
Decision-Support Systems (DSS)
• Data-driven DSS: Supports decision making by
allowing users to extract and analyze useful
information previously buried in large databases
• Datamining: Finds hidden patterns and
relationships in large databases to infer rules from
them and predict future behavior
Types of Decision-Support Systems
Decision-Support Systems (DSS)
Data Drive Customer Care at Intrawest
• How does this customer care DSS help Intrawest
make decisions?
• How has it provided value for the firm?
Window on Organizations
Decision-Support Systems (DSS)
Cargo revenue optimization of Continental Airlines
Figure 12-1
Decision-Support Systems (DSS)
• Associations: Occurrences linked to a single
event
• Sequences: Events linked over time
Types of Decision-Support Systems
Decision-Support Systems (DSS)
• Classification: Recognizing patterns that
describe the group to which an item belongs
• Clustering: Similar to classification when no
groups have yet been defined. Discovers different
groupings within data
Types of Decision-Support Systems
Decision-Support Systems (DSS)
Overview of a decision-support system (DSS)
Figure 12-2
Decision-Support Systems (DSS)
• DSS Database: Collection of current or
historical data from a number of applications or
groups. Can be a small PC database or a massive
data warehouse
Components of DSS
Decision-Support Systems (DSS)
• DSS Software System: Collection of software
tools used for data analysis, such as OLAP tools,
datamining tools, or a collections of mathematical
and analytical models
Components of DSS
Decision-Support Systems (DSS)
• Model: Abstract representation illustrating
components or relationships of a
phenomenon
• Sensitivity Analysis: Models that ask “what-
if” questions repeatedly to determine the
impact of changes in one or more factors on
the outcomes
Components of DSS
Decision-Support Systems (DSS)
Sensitivity analysis
Figure 12-3
Decision-Support Systems (DSS)
Examples of Decision-Support Systems
• General Accident Insurance: Customer buying
patterns and fraud detection
• Bank of America: Customer profiles
• Frito-Lay, Inc.: Price, advertising, and promotion
selection
DSS Applications and the Digital Firm
Decision-Support Systems (DSS)
Examples of Decision-Support Systems
• Southern Railway: Train dispatching and routing
• Texas Oil and Gas Corporation: Evaluation of
potential drilling sites
• The Gap: Inventory stocking and merchandising
DSS Applications and the Digital Firm
Decision-Support Systems (DSS)
Examples of Decision-Support Systems
• United Airlines: Flight scheduling, passenger
demand forecasting
• U.S. Department of Defense: Defense contract
analysis
DSS Applications and the Digital Firm
Decision-Support Systems (DSS)
• By analyzing several years of sales data for similar
items, the software estimates a “seasonal demand
curve” for each item and predicts how many units
would sell each week at various prices.
• The software uses sales history to predict how
sensitive customer demand will be to price
changes
DSS for Pricing Decisions
Decision-Support Systems (DSS)
• Can help firms model inventory stocking levels,
production schedules, or transportation plans
• Can provide firms with information on key
performance indicators such as lead time, cycle
time, inventory turns, or total supply chain costs
DSS for Supply Chain Management
Decision-Support Systems (DSS)
A DSS Makes Subaru More Parts-Savvy
• How does the Servigistics system provide value
for Subaru of New England?
• How did it change the way the company ran its
business?
Window on Technology
Decision-Support Systems (DSS)
DSS for customer analysis and segmentation
Figure 12-4
Decision-Support Systems (DSS)
Predictive Analysis
• Use of datamining techniques, historical data,
and assumptions about future conditions to
predict outcomes of events
DSS for Customer Relationship Management
Decision-Support Systems (DSS)
• Data Visualization: Technology for helping users
see patterns and relationships in large amounts
of data by presenting the data in graphical form
• Geographic Information System (GIS): System
with software that can analyze and display data
using digitized maps to enhance planning and
decision making
Data Visualization and Geographic Information Systems (GIS)
Decision-Support Systems (DSS)
Customer Decision-Support System (CDSS)
• System to support the decision-making process
of an existing or potential customer
Web-Based Customer Decision-Support Systems
Group Decision-Support Systems (GDSS)
• Group Decision-Support System (GDSS): An
interactive computer-based system to facilitate
the solution to unstructured problems by a set of
decision makers working together as a group
What is a GDSS?
Group Decision-Support Systems (GDSS)
• Hardware: Conference facility, electronic
hardware
• Software tools: Tools for organizing ideas,
gathering information, and ranking and seeking
priorities
• People: Participants, trained facilitator, staff
supporting hardware and software
Components of GDSS
Group Decision-Support Systems (GDSS)
• Electronic questionnaires
• Electronic brainstorming tools
• Idea organizers
• Questionnaire tools
Components of GDSS
Group Decision-Support Systems (GDSS)
• Tools for voting or setting priorities
• Stakeholder identification and analysis tools
• Policy formation tools
• Group dictionaries
Components of GDSS
Group Decision-Support Systems (GDSS)
• Each attendee has a workstation
• Workstations are networked and connected to the
facilitator’s console
• Data the attendees forward to the group are collected and
saved on a file server
• Facilitator projects computer images onto the projection
screen
Overview of a GDSS Meeting
Group Decision-Support Systems (GDSS)
Group system tools
Figure 12-5
Group Decision-Support Systems (GDSS)
• Number of attendees can increase while
productivity increases
• More collaborative atmosphere
• Software tools follow structured methods for
organizing and evaluating ideas and preserving
the results of meetings
How GDSS Can Enhance Group Decision Making
Group Decision-Support Systems (GDSS)
• Increase the number of ideas generated
• Can lead to more participative and democratic
decision making
How GDSS Can Enhance Group Decision Making
Group Decision-Support Systems (GDSS)
Organizational Memory
• Store learning from an organization’s history
that can be used for decision making and other
purposes
How GDSS Can Enhance Group Decision Making
Executive Support in the Enterprise
• Focus on the information needs of senior
management
• Combine data from internal and external sources
• Create a generalized computing and
communications environment that can be
focused and applied to a changing array of
problems
Executive Support Systems (ESS)
Executive Support in the Enterprise
• Monitor organizational performance
• Track activities of competitors
• Spot problems
• Identify opportunities
• Forecast trends
Executive Support Systems (ESS)
Executive Support in the Enterprise
• Bring together data from the entire organization
• Allow managers to select, access, and tailor data
• Enable executive and any subordinates to look at
the same data in the same way
The Role of Executive Support Systems in the Organization
Executive Support in the Enterprise
Drill Down
• The ability to move from summary data to lower
and lower levels of detail
The Role of Executive Support Systems in the Organization
Executive Support in the Enterprise
Developing ESS
• Ease of use
• Facility for environmental scanning
• External and internal sources of information to
be used for environmental scanning
The Role of Executive Support Systems in the Organization
Executive Support in the Enterprise
• Analyze, compare, and highlight trends
• Provide greater clarity and insight into data
• Speed up decision making
Benefits of Executive Support Systems
Executive Support in the Enterprise
• Improve management performance
• Increase management’s span of control
• Better monitoring of activities
Benefits of Executive Support Systems
Executive Support in the Enterprise
ESS for Competitive Intelligence
• Identify changing market conditions
• Formulate responses
• Track implementation efforts
• Learn from feedback
Executive Support Systems and the Digital Firm
Executive Support in the Enterprise
Executive Support Systems and the Digital Firm
Balanced Scorecard
• Model for analyzing firm performance that
supplements traditional financial measures with
measurements from additional business
perspectives, such as customers, internal
business processes, and learning and growth
Executive Support in the Enterprise
Enterprise-Wide Reporting and Analysis
Strategic performance management tools
for enterprise systems
• SAP: Web-enabled mySAP.com™,
Management Cockpit
• PeopleSoft: Web-enabled Enterprise
Performance Management (EPM)
Executive Support in the Enterprise
Enterprise-Wide Reporting and Analysis
Activity-Based Costing
• Model for identifying all the company activities
that cause costs to occur while producing a
specific product or service so that managers can
see which products or services are profitable or
losing money and make changes to maximize
firm profitability
Chapter 12 Case Study
Harrah’s and Mohegan Sun: A Tale of Two Casino DSS
1. Analyze Harrah’s and Mohegan Sun using the
competitive forces and value chain models.
2. Compare the business strategies of Harrah’s and
Mohegan sun. What role do customer reward
systems play in these strategies? How are they
similar? How are they different?
Chapter 12 Case Study
Harrah’s and Mohegan Sun: A Tale of Two Casino DSS
3. What kind of decision-support systems did Harrah’s and
Mohegan Sun develop? How are they related to their
business strategy?
4. Are Harrah’s and Mohegan Sun successful? Which
casino is more successful? Why? Can its competitive
advantage be sustained? Why or why not?
5. Are there any ethical problems raised by these casinos’
use of customer data? Explain your response.

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enhancing decision making.ppt

  • 1. Enhancing Management Decision Making for the Digital Firm Chapter 12
  • 2. Objectives 1. How can information systems help individual managers make better decisions when the problems are nonroutine and constantly changing? 2. How can information systems help people working in a group make decisions more efficiently?
  • 3. Objectives 3. Are there any special systems that can facilitate decision making among senior managers? Exactly what can these systems do to help high-level management? 4. What value can systems to support management decision making provide for the organization as a whole?
  • 4. Management Challenges 1. Building information systems that can actually fulfill executive information requirements 2. Create meaningful reporting and management decision-making processes
  • 5. Decision-Support Systems (DSS) • Computer system at the management level of an organization • Combines data, analytical tools, and models • Supports semistructured and unstructured decision making
  • 6. Decision-Support Systems (DSS) MIS • Provides reports based on routine flow of data • Assists in general control of the organization MIS and DSS
  • 7. Decision-Support Systems (DSS) DSS • Emphasizes change, flexibility, rapid response, models, assumptions, ad-hoc queries, and display graphics MIS and DSS
  • 8. Decision-Support Systems (DSS) Model-Driven DSS • Primarily stand-alone • Uses model to perform “what-if” and other kinds of analysis Types of Decision-Support Systems
  • 9. Decision-Support Systems (DSS) • Data-driven DSS: Supports decision making by allowing users to extract and analyze useful information previously buried in large databases • Datamining: Finds hidden patterns and relationships in large databases to infer rules from them and predict future behavior Types of Decision-Support Systems
  • 10. Decision-Support Systems (DSS) Data Drive Customer Care at Intrawest • How does this customer care DSS help Intrawest make decisions? • How has it provided value for the firm? Window on Organizations
  • 11. Decision-Support Systems (DSS) Cargo revenue optimization of Continental Airlines Figure 12-1
  • 12. Decision-Support Systems (DSS) • Associations: Occurrences linked to a single event • Sequences: Events linked over time Types of Decision-Support Systems
  • 13. Decision-Support Systems (DSS) • Classification: Recognizing patterns that describe the group to which an item belongs • Clustering: Similar to classification when no groups have yet been defined. Discovers different groupings within data Types of Decision-Support Systems
  • 14. Decision-Support Systems (DSS) Overview of a decision-support system (DSS) Figure 12-2
  • 15. Decision-Support Systems (DSS) • DSS Database: Collection of current or historical data from a number of applications or groups. Can be a small PC database or a massive data warehouse Components of DSS
  • 16. Decision-Support Systems (DSS) • DSS Software System: Collection of software tools used for data analysis, such as OLAP tools, datamining tools, or a collections of mathematical and analytical models Components of DSS
  • 17. Decision-Support Systems (DSS) • Model: Abstract representation illustrating components or relationships of a phenomenon • Sensitivity Analysis: Models that ask “what- if” questions repeatedly to determine the impact of changes in one or more factors on the outcomes Components of DSS
  • 19. Decision-Support Systems (DSS) Examples of Decision-Support Systems • General Accident Insurance: Customer buying patterns and fraud detection • Bank of America: Customer profiles • Frito-Lay, Inc.: Price, advertising, and promotion selection DSS Applications and the Digital Firm
  • 20. Decision-Support Systems (DSS) Examples of Decision-Support Systems • Southern Railway: Train dispatching and routing • Texas Oil and Gas Corporation: Evaluation of potential drilling sites • The Gap: Inventory stocking and merchandising DSS Applications and the Digital Firm
  • 21. Decision-Support Systems (DSS) Examples of Decision-Support Systems • United Airlines: Flight scheduling, passenger demand forecasting • U.S. Department of Defense: Defense contract analysis DSS Applications and the Digital Firm
  • 22. Decision-Support Systems (DSS) • By analyzing several years of sales data for similar items, the software estimates a “seasonal demand curve” for each item and predicts how many units would sell each week at various prices. • The software uses sales history to predict how sensitive customer demand will be to price changes DSS for Pricing Decisions
  • 23. Decision-Support Systems (DSS) • Can help firms model inventory stocking levels, production schedules, or transportation plans • Can provide firms with information on key performance indicators such as lead time, cycle time, inventory turns, or total supply chain costs DSS for Supply Chain Management
  • 24. Decision-Support Systems (DSS) A DSS Makes Subaru More Parts-Savvy • How does the Servigistics system provide value for Subaru of New England? • How did it change the way the company ran its business? Window on Technology
  • 25. Decision-Support Systems (DSS) DSS for customer analysis and segmentation Figure 12-4
  • 26. Decision-Support Systems (DSS) Predictive Analysis • Use of datamining techniques, historical data, and assumptions about future conditions to predict outcomes of events DSS for Customer Relationship Management
  • 27. Decision-Support Systems (DSS) • Data Visualization: Technology for helping users see patterns and relationships in large amounts of data by presenting the data in graphical form • Geographic Information System (GIS): System with software that can analyze and display data using digitized maps to enhance planning and decision making Data Visualization and Geographic Information Systems (GIS)
  • 28. Decision-Support Systems (DSS) Customer Decision-Support System (CDSS) • System to support the decision-making process of an existing or potential customer Web-Based Customer Decision-Support Systems
  • 29. Group Decision-Support Systems (GDSS) • Group Decision-Support System (GDSS): An interactive computer-based system to facilitate the solution to unstructured problems by a set of decision makers working together as a group What is a GDSS?
  • 30. Group Decision-Support Systems (GDSS) • Hardware: Conference facility, electronic hardware • Software tools: Tools for organizing ideas, gathering information, and ranking and seeking priorities • People: Participants, trained facilitator, staff supporting hardware and software Components of GDSS
  • 31. Group Decision-Support Systems (GDSS) • Electronic questionnaires • Electronic brainstorming tools • Idea organizers • Questionnaire tools Components of GDSS
  • 32. Group Decision-Support Systems (GDSS) • Tools for voting or setting priorities • Stakeholder identification and analysis tools • Policy formation tools • Group dictionaries Components of GDSS
  • 33. Group Decision-Support Systems (GDSS) • Each attendee has a workstation • Workstations are networked and connected to the facilitator’s console • Data the attendees forward to the group are collected and saved on a file server • Facilitator projects computer images onto the projection screen Overview of a GDSS Meeting
  • 34. Group Decision-Support Systems (GDSS) Group system tools Figure 12-5
  • 35. Group Decision-Support Systems (GDSS) • Number of attendees can increase while productivity increases • More collaborative atmosphere • Software tools follow structured methods for organizing and evaluating ideas and preserving the results of meetings How GDSS Can Enhance Group Decision Making
  • 36. Group Decision-Support Systems (GDSS) • Increase the number of ideas generated • Can lead to more participative and democratic decision making How GDSS Can Enhance Group Decision Making
  • 37. Group Decision-Support Systems (GDSS) Organizational Memory • Store learning from an organization’s history that can be used for decision making and other purposes How GDSS Can Enhance Group Decision Making
  • 38. Executive Support in the Enterprise • Focus on the information needs of senior management • Combine data from internal and external sources • Create a generalized computing and communications environment that can be focused and applied to a changing array of problems Executive Support Systems (ESS)
  • 39. Executive Support in the Enterprise • Monitor organizational performance • Track activities of competitors • Spot problems • Identify opportunities • Forecast trends Executive Support Systems (ESS)
  • 40. Executive Support in the Enterprise • Bring together data from the entire organization • Allow managers to select, access, and tailor data • Enable executive and any subordinates to look at the same data in the same way The Role of Executive Support Systems in the Organization
  • 41. Executive Support in the Enterprise Drill Down • The ability to move from summary data to lower and lower levels of detail The Role of Executive Support Systems in the Organization
  • 42. Executive Support in the Enterprise Developing ESS • Ease of use • Facility for environmental scanning • External and internal sources of information to be used for environmental scanning The Role of Executive Support Systems in the Organization
  • 43. Executive Support in the Enterprise • Analyze, compare, and highlight trends • Provide greater clarity and insight into data • Speed up decision making Benefits of Executive Support Systems
  • 44. Executive Support in the Enterprise • Improve management performance • Increase management’s span of control • Better monitoring of activities Benefits of Executive Support Systems
  • 45. Executive Support in the Enterprise ESS for Competitive Intelligence • Identify changing market conditions • Formulate responses • Track implementation efforts • Learn from feedback Executive Support Systems and the Digital Firm
  • 46. Executive Support in the Enterprise Executive Support Systems and the Digital Firm Balanced Scorecard • Model for analyzing firm performance that supplements traditional financial measures with measurements from additional business perspectives, such as customers, internal business processes, and learning and growth
  • 47. Executive Support in the Enterprise Enterprise-Wide Reporting and Analysis Strategic performance management tools for enterprise systems • SAP: Web-enabled mySAP.com™, Management Cockpit • PeopleSoft: Web-enabled Enterprise Performance Management (EPM)
  • 48. Executive Support in the Enterprise Enterprise-Wide Reporting and Analysis Activity-Based Costing • Model for identifying all the company activities that cause costs to occur while producing a specific product or service so that managers can see which products or services are profitable or losing money and make changes to maximize firm profitability
  • 49. Chapter 12 Case Study Harrah’s and Mohegan Sun: A Tale of Two Casino DSS 1. Analyze Harrah’s and Mohegan Sun using the competitive forces and value chain models. 2. Compare the business strategies of Harrah’s and Mohegan sun. What role do customer reward systems play in these strategies? How are they similar? How are they different?
  • 50. Chapter 12 Case Study Harrah’s and Mohegan Sun: A Tale of Two Casino DSS 3. What kind of decision-support systems did Harrah’s and Mohegan Sun develop? How are they related to their business strategy? 4. Are Harrah’s and Mohegan Sun successful? Which casino is more successful? Why? Can its competitive advantage be sustained? Why or why not? 5. Are there any ethical problems raised by these casinos’ use of customer data? Explain your response.