Section 6-1
IS with STRATEGIC
DECISION SUPPORTING
SYSTEM &
BUSINESS INTELLIGENCE
SYSTEM
DECISION SUPPORTING SYSTEM
(DSS)
LEARNING OUTCOMES
1.
Explain the difference between transactional information and
analytical information.
2.
Define TPS, DSS, and EIS and explain how an organization
can use these systems to make decisions and gain
competitive advantages
3.
Describe the three quantitative models typically used by
decision support systems
4.
Explain trend and technology of Business Intelligence System
5.
Describe the relationship between visualization and Business
Intelligence systems
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
DECISION MAKING
• Model – a simplified representation or
abstraction of reality
• IT systems in
an enterprise
TRANSACTION PROCESSING
SYSTEMS
• Moving up through the organizational pyramid users move
from requiring transactional information to analytical
information
Fine
Coarse
TRANSACTION PROCESSING
SYSTEMS
• Transaction processing system (TPS) - 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
• Cf. Online analytical mining (OLAM)
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
DECISION SUPPORT SYSTEMS
• What-if analysis
DECISION SUPPORT SYSTEMS
• Goal-seeking analysis
DECISION SUPPORT SYSTEMS
• Interaction between a TPS and a DSS
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
EXECUTIVE INFORMATION SYSTEMS
• Interaction between a TPS and an EIS
Digital Dashboards
• Digital dashboard – integrates information
from multiple components and presents it in a
unified display
BUSINESS INTELLIGENCE SYSTEM
(BI)
Special Thanks to Matt
Schwartz
Chapter Overview
• Decision-enabling, problem-solving, and
opportunity-seizing systems
What is Business Intelligence?
Business Intelligence enables the
business to make even more intelligent,
faster decision based on DSS.
Aggregate
Data
Database, Data Mart, Data
Warehouse, ETL Tools,
Integration Tools
Present
Data
Reporting Tools,
Dashboards, Static Reports,
Mobile Reporting, OLAP
Cubes
Enrich
Data
Add Context to Create
Information, Descriptive
Statistics, Benchmarks,
Variance to Plan or LY
Inform a
Decision
Decisions are Fact-based
and Data-driven
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
Artificial Intelligence (AI)
• The ultimate goal of AI is the ability to build a
system that can mimic human intelligence
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
Artificial Intelligence (AI)
• Four most common categories of AI include:
3. Genetic algorithm – an artificial intelligent
system that mimics the evolutionary, survival-ofthe-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
CPU – Content, Performance, Usability
• Content
– The business determines the “what”, BI enables the “how”
• Performance
– Minimize report creation and collection times (near zero)
• Usability
– Delivery Method Push vs Pull
– Medium  Excel, PDF, Dashboard, Cube, Mobile Device
– Enhance Digestion  “A-ha” is readily apparent, fewer clicks
– Tell a Story  Trend, Context, Related Metrics, Multiple Views
How Important is BI?
Top 10 Business and Technology Priorities for 2011:
1. Cloud computing
2. Virtualization
3. Mobile technologies
4. IT Management
5. Business Intelligence
6. Networking, voice and data communications
7. Enterprise applications
8. Collaboration technologies
9. Infrastructure
10. Web 2.0
Source: Gartner’s 2011 CIO Agenda (aka “Reimagining IT: The 2011 CIO Agenda”).
Why is Business Intelligence So Important?
Time
Data
Opinion
(Professional
Judgment)
Making Business
Decisions is a Balance
In the absence of data, business decisions are often made by the HiPPO.
With Business Intelligence, we can get data to you in a timely manner.
The July 2010 Forrester report “Technology
Trends That Retail CIOs Must Tap to Drive
Growth” identified the following technologies
that retail CIOs should be considering as
part of an overall architecture strategy:
Mobile
Social Computing
Cloud
Supply Chain
Micropayments
Business Intelligence/Analytics
Major BI Trends
• Mobile
• Cloud
• Social Media
• Advanced Analytics
Most Important BI technologies
What BI technologies will be the most
important to your organization in the next 3
years?
1. Predictive Analytics
2. Visualization/Dashboards
3. Master Data Management
4. The Cloud
5. Analytic Databases
6. Mobile BI
7. Open Source
8. Text Analytics
BI Today vs Tomorrow
• “BI today is like reading the newspaper”
– BI reporting tool on top of a data warehouse
that loads nightly and produces historical
reporting
• BI tomorrow will focus more on real-time
events and predicting tomorrow’s
headlines
Who does use BI?
only Business firm?
• Essential to the success of companies in a wide range of industries,
and more famously essential to the success of professional sports
teams such as the Boston Red Sox, Oakland A’s and New England
Patriots.
• With an analytical approach, the Patriots managed to win the Super
Bowl three times in four years. The team uses data and analytical
models extensively, both on and off the field. In-depth analytics help
the team select players and stay below the NFL salary cap. Patriots
coaches and players are renowned for their extensive study of
game film and statistics.
• Off the field, the team uses detailed analytics to assess and
improve the "total fan experience." At every home game, for
example, 20 to 25 people have specific assignments to make
quantitative measurements of the stadium food, parking, personnel,
bathroom cleanliness and other factors.
www.cio.com
A Framework for Computerized
Decision Analysis
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.
Highly
structured
Order
entry
Semistructured
Loan approval
Higly
unstructured
Building new plant
Unstructured Text Processing
Facebook
Page
Twitter
Page
Customer Sat
Survey
Comments
Call
Center
Notes,
Voice
Services
Quality
Competitors’
Facebook
Pages
Email
Blogs
32
Cost Friendliness
Public Web Sites,
Discussion Boards,
Product Reviews
Adhoc
Feedback
Alerts,
Real-time
Action
The Scope of Business
Intelligence
Smaller organizations:
Excel spreadsheets
Larger organizations:
Data mining, predictive
analytics, dashboards
Source: Dundas Software, www.dundas.com/ dashboard/online-examples/
screenshots/Marketing-Dashboard.aspx
BI Technologies
•Analytic Databases
DB2
Oracle
SQL Server
Teradata
Netezza
Vertica
Aster Data
Par Accel
Greenplum
Semantic Databases
•BI is a consolidating industry
–
–
–
–
–
–
Oracle: Siebel, Hyperion, Brio, Sun
SAP: Business Objects, Sybase
IBM: Cognos, SPSS, Coremetrics, Unica, Netezza
EMC: Greenplum
HP: Vertica
Teradata: Aster Data
•Independent vendors: MicroStrategy, Informatica, SAS
•Reporting standards determined mainly by Microsoft,
Apple and Adobe
CLOSING QUESTIONS
Revving Up Sales at Harley-Davidson
1. How does Talon help Harley-Davidson
employees improve their decision-making
capabilities?
2. Identify a few key metrics a Harley-Davidson
marketing executive might want to monitor on
a digital dashboard
3. How can Harley-Davidson benefit from using
decision support systems in its business
Appendix – Dash board
Digital Dashboard (example)
Source: MicroStrategy
Digital Dashboard (example)
Source: Dundas Software, www.dundas.com/ dashboard/online-examples/
screenshots/Marketing-Dashboard.aspx
Digital Dashboard Demo
• Informationbuilders
http://www.informationbuilders.com/rfr/qtde
mo/AdvVis_ExecDash/AdvVis_ExecDash.
html
• Open source : Dojo
http://dojotoolkit.org/features/graphics-andcharting
A Bloomberg Terminal
Source: Carlos Osario/Zuma Press
Management Cockpit
Source: The Management Cockpit is a registered trademark of SAP,created by Professor M.Georges
.
Data Visualization Systems
The Power of Visualization
Even though a picture is “worth a thousand
words,” we have to be very careful about
just what we are seeing.