Transcript 10.3 business intelligence applications for data analysis

CHAPTER 10:
Business Intelligence
CHAPTER 10:
BUSINESS INTELLIGENCE
10.1 Managers and Decision Making
10.2 What Is Business Intelligence?
10.3 Business Intelligence Applications for
Data Analysis
10.4 Business Intelligence Applications for
Presenting Results
10.5 Business Intelligence in Action: Corporate
Performance Management
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LEARNING OBJECTIVES
1. Identify the phases in the decision-making process, and
use a decision-support framework to demonstrate how
technology supports managerial decision making.
2. Describe and provide examples of the three different
ways in which organizations use business intelligence
(BI).
3. Specify the BI applications available to users for data
analysis, and provide examples of how each might be
used to solve a business problem at your university.
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LEARNING OBJECTIVES
(CONTINUED)
4. Describe three BI applications that present the results
of data analyses to users, and offer examples of how
businesses and government agencies can use each of
these technologies.
5. Describe corporate performance management, and
provide an example of how your university could use
CPM.
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CASE 10.1 CHAPTER OPENING CASE
QUALITY ASSURANCE AT DAIMLER
AG
The Problem
– Dating back to the 1980s, German automaker Daimler AG
housed warranty data on its Quality Information System (QUIS),
a mainframe-based platform and the diagnostic and warranty
data were located in different information silos. The organization
was unable to take full advantage of the data and the diagnosis
database had reached the limits of its capacity.
Source: Alperium/Shutterstock
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CASE 10.1 CHAPTER OPENING CASE
QUALITY ASSURANCE AT DAIMLER
AG
The IT Solution
– Over a three-year period, Daimler consolidated its data on a data
warehouse, making these data available to users through a
shared interface. The new system is called Advanced Quality
Analysis (AQUA).The company intended AQUA to provide
support for two strategic goals: (1) to increase customer
satisfaction and (2) to reduce costs.
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CASE 10.1 CHAPTER OPENING CASE
QUALITY ASSURANCE AT DAIMLER
AG
The Results
– AQUA has enabled Daimler to achieve deeper insights into how
to optimize its production processes. Defects can be detected
more quickly, resolved, and eliminated from future models.
AQUA supports Daimler’s strategic goals of quality leadership,
customer satisfaction, and profitability.
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CASE 10.1 CHAPTER OPENING CASE
QUALITY ASSURANCE AT DAIMLER
AG
What We Learned From This Case
– BI enables decision makers to quickly ascertain the status of a
business enterprise by examining key information
– BI systems provide business intelligence that you can act on in a
timely fashion.
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10.1 Managers and Decision
Making
•
Management is a process by which an organization
achieves its goals through the use of resources (people,
money, materials, and information).
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THE MANAGER’S JOB AND
DECISION MAKING
•
Managers have three basic roles (Mintzberg 1973) :
– Interpersonal
– Informational
– Decisional
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THE MANAGER’S JOB & DECISION
MAKING (CONTINUED)
•
Decisions and Decision making
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FIGURE 10.1 DECISION MAKING
PROCESS
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WHY MANAGERS NEED IT
SUPPORT
•
•
•
•
The number of alternatives is constantly increasing.
Most decisions must be made under time pressure.
Decisions are becoming more complex.
Decision makers, as well as the information, can be
situated in different locations.
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FIGURE 10.2 A FRAMEWORK FOR
COMPUTERIZED DECISION ANALYSIS
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PROBLEM STRUCTURE
•
The first dimension deals with the problem structure,
where the decision making processes fall along the
continuum ranging from highly structured to highly
unstructured decisions.
Structured
Example:
Inventory Control
Semi-structured
Example:
Evaluating Employees
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Unstructured
Example:
New Services
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THE NATURE OF DECISIONS
•
•
the second dimension of decision support deals with
the nature of decisions.
Three categories of managerial decision making:
–
–
–
Operational control
Management control
Strategic planning
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10.2 WHAT IS BUSINESS
INTELLIGENCE?
•
Clicking on the links will take you to each company’s
home page
– SAS
– IMB
– SAP
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THE SCOPE OF BUSINESS
INTELLIGENCE
•
Smaller Organizations
– Excel spreadsheets
•
Larger Organizations
– Data mining, predictive analytics, dashboards and data
visualization
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THE SCOPE OF BI (CONTINUED)
•
Three specific BI targets that represent different levels
of change:
– development of one or a few related BI applications (Example:
campaign management in marketing)
– development of infrastructure to support enterprise-wide BI
(Example: enterprise data warehouse)
– support for organizational transformation (Example: support for
new business model)
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10.3 BUSINESS INTELLIGENCE
APPLICATIONS FOR DATA ANALYSIS
•
•
•
Multidimensional Analysis or Online Analytical
Processing (OLAP)
Data Mining
Decision Support Systems
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MULTIDIMENSIONAL ANALYSIS OR
ONLINE ANALYTICAL PROCESSING
(OLAP)
•
OLAP:
– “slices & dices” data stored in a dimensional format,
– drills down in the data to greater detail, and,
– aggregates the data.
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DATA MINING
•
Data mining can perform two basic operations:
– predicting trends and behaviours
– identifying previously unknown patterns
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10.1 IT’S ABOUT BUSINESS
•
Data Analytics Helps Kelley Blue Book Remain
Competitive
– Since 1926, Kelley Blue Book has been a publishing company
known for its guide to used and new car values. They needed to
devise new strategies to generate revenue and compete with
new on-line rivals. Kelley invested in a data warehouse and it
purchased business intelligence and data analytics software
from MicroStrategy and the SAS Institute in order to analyze its
warehouse data more efficiently and effectively. The bottom line
is that data analytics has enabled Kelley to provide more rapid
and accurate quotes, develop new sources of revenue, and
remain competitive with the on-line companies.
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DECISION SUPPORT SYSTEMS
(DSSS)
•
DSS capabilities
– Sensitivity analysis
– What-if analysis
– Goal-seeking analysis
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10.4 BUSINESS INTELLIGENCE
APPLICATIONS FOR PRESENTING
RESULTS
•
Capabilities of Dashboards:
–
–
–
–
–
–
Drill-down
Critical success factors (CSFs)
Key performance indicators (KPIs)
Status access
Trend analysis
Exception reporting
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FIGURE 10.3 SAMPLE
PERFORMANCE DASHBOARD
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FIGURE 10.4 BLOOMBERG
TERMINAL
Source: Carlos Osario/Zuma Press
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FIGURE 10.5 HUMAN RESOURCES
DASHBOARD/SCORECARD
.
Source: MicroStrategy
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FIGURE 10.6 MANAGEMENT
COCKPIT
Source: The Management Cockpit is a registered trademark of SAP, created by Professor Patrick M. Georges.
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DATA VISUALIZATION
TECHNOLOGIES
•
•
Geographic Information Systems is a computer-based
system for capturing, integrating, manipulating, and
displaying data using digitized maps
Reality Mining allows analysts to extract information
from the usage patterns of mobile phones and other
wireless devices.
– Example: integration of GIS and GPS
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FIGURE 10.7 REAL TIME BI
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10.5 BUSINESS INTELLIGENCE IN
ACTION: CORPORATE
PERFORMANCE MANAGEMENT
•
Click below to review corporate management
performance solutions at http://www.phophix.com
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CHAPTER CLOSING
1. The three-step decision-making process includes:
intelligence, design, and choice.
2. There are three major ways that organizations use BI:
– development of one or a few related BI applications
– development of infrastructure to support enterprise-wide BI
– support for organizational transformation
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CHAPTER CLOSING (CONTINUED)
3. BI applications available to analyze data include
multidimensional analysis, data mining, and decision
support systems.
4. Three BI applications that present the results of data
analyses to users include dashboards, geographic
information systems and reality mining
5. Corporate performance management (CPM) is involved
with monitoring and managing an organization’s
performance according to key performance indicators
(KPIs) and operational costs.
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Copyright
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