Transcript CHAPTER 10 DATA, KNOWLEDGE, AND DECISION SUPPORT

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Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
CHAPTER 10
DATA, KNOWLEDGE,
AND DECISION SUPPORT
Oleh : Kundang K Juman
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Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
Learning Objectives
 Describe the concepts of managerial decision making and
computerized support decision making
 Understand the life cycle of processing data into information
and knowledge for use in decision support
 Describe the framework for computerized decision support
and the concept of decision support systems
 Describe executive information systems and group support
systems, and analyze their roles in management support
 Describe data presentation methods and explain geographical
information systems as a decision support tool
 Explain the concepts of knowledge management and
organizational databases
 Describe knowledge discovery, online analytical processing,
and data mining
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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Chapter Overview
Management and
Decision Making
• The Manager’s
Job
• Why Managers
Need IT
Support
Data Management
Life Cycle
• The Data Life Cycle Process
• Data Sources and Collection
• Data Quality
• Data Storage and
Management
• Document Management
• Analytical Processing
Enterprise Decision
Support
Decision Support Systems
•
•
•
•
The Decision Support Process
Modeling
A Framework for Computerized DSS
DSS Concepts, Characteristics, and
Capabilities
• Components and Structure of DSS
Data Visualisation Knowledge Management
Technologies
and Organization
Knowledge Bases
•Executive
•Data
•What is knowledge
Information Support Visualization
Management?
•Supporting Idea
•Visual Interactive •IT Support of
Generation and
Decision Making
Knowledge
Creativity
•Geographical
Management Activities
•Group Decision
Information
•Implementing
Support Systems
Systems
Knowledge
(GDSS)
Management
Knowledge Discovery
and Analysis
•The Foundations of
Knowledge
Discovery
•Online Analytical
Processing
•Data Mining for
Decision Support
•Ethical and Legal
Issues
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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Case: Managing Global Business
at 3M Corporation
 The Business Problem
 The company had difficulties responding to
new customers and markets in the global
economy as each business unit kept separate databases and
conducted independent decision support activities
The Solution
 The Company created a global enterprise data warehouse
(GEDW)
The Results
 Distributors and retailers, as well as end-users, now receive
information in minutes instead of weeks or months,
including the delivery of rich multimedia
 Customers can find all their information in one place
 Inventories are lower, and better and quicker inventory
decisions are made, even in globally remote locations
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Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
Case (continued…)
What have we learned from this case??
 The case demonstrates the existence of
vast amounts of important data in
organizations, and the importance of
organizing that data for optimum use
 The case shows the need to share a company’s
data internally and with business partners and
customers, and to make it available in a format
that enables end users to process data quickly
 The case explains the data warehouse, and its
role in supporting managerial decision making
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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Management and
Decision Making
Management
 a process by which certain goals are achieved
through the use of resources
Managers - make decisions in every step of the
process
 interpersonal roles : figurehead, leader, liaison
 informational roles : monitor, disseminator,
spokesperson
 decisional roles : entrepreneur, disturbance
handler, resource allocator, negotiator
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Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
Management and
Decision Making (continued …)
Why Managers Need IT Support
 processing information manually is growing
increasingly difficult
 computerized modeling
 examining numerous alternatives very quickly
 providing a systematic risk analysis
 being integrated with communication systems
and databases
 being used to support group work
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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The Data Management
Life Cycle Process
Data Sources
(databases)
Direct Use
End Users:
Decision Making and other Tasks;
Data Visualization
Data
Organization;
Direct
Storage
Use
Data Warehouse
(storage)
Use
Analytical Processing,
Data Mining
Purchased
Knowledge
Storage
Use of
Knowledge
Use
Generate
Knowledge
Use
Storage
Organizational
Knowledge Bases
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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The Data Management
Life Cycle (continued …)
Data Sources and Collection
 Internal Data - generated by the corporate transaction


processing systems, functional user information systems,
and other functions and individuals
Personal Data - created for IS users or other corporate
employees documenting their own expertise
External Data - generated outside and organization, but
relevant portions of it flow into the organization
 Methods for Collecting Raw Data
 manually or by instruments and sensors
 scanned or transferred electronically
 in the field; other times from within the organization or
from people
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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The Data Management
Life Cycle (continued …)
Data Quality
 an extremely important issue since
quality determines the data’s
usefulness as well as the quality of the
decisions based on these data
 need to be : accurate, secure, relevant,
timely, complete, and consistent
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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The Data Management
Life Cycle (continued …)
Data Storage
 databases or in data warehouse and data marts
Data Management
 difficulties in data management
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
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
exponential increases of data with time
data collected by several methods and devices
various sources of raw data
only small portions are relevant
an ever-increasing amount of external data
different legal requirements relating to data
selecting data management tools - a problem
data security, quality, and integrity
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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The Data Management
Life Cycle (continued …)
Document Management
 Document Management System (DMS)
 automates the control of electronic documents through their
entire life cycle within an organization, from initial creating
to final archiving
 retains an image of an electronic document
 creates an index of key-words
 puts the entire document into computer readable format
 manages (and limits) distribution
 Functions
 document identification, storage, and retrieval; tracking
version control’ workflow management’ and presentation
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Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
The Data Management
Life Cycle (continued …)
Analytical Processing - the activity of
analyzing accumulated data
 work directly with the existing
operational systems, using software
tools and components known as frontend tools
 work with the data warehouse
Introduction to Information Technology
Turban, Rainer and Potter
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Decision Support Systems (DSS)
 The Decision Support Process
REALITY


Examination
Intelligence Phase
Verification
of the Model
Design Phase
Verification, Testing
of Proposed Solution
Choice Phases
SUCCESS
Implementation
of Solution

FAILURE
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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DSS (continued …)
Modeling in DSS
 Iconic (scale) models
 a physical replica of a system, usually based on
a different scale form original
 Analog models
 a physical model, but the shape of the model
differs from that of the actual system
 Mathematical (qualitative) model
 models complex relationships and conducts
experimentations with them
 Mental models
 provide a description of how a person thinks
about a situation
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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DSS (continued …)
A Framework for Computerized Decision Support
 Problem Complexity
 decision making processes fall along a continuum that
ranges from highly structured to highly unstructured
decisions
 Nature of Decisions
 strategic planning - the long-range goals and policies for
resource allocation
 management control - the acquisition and efficient
utilization of resources in the accomplishment of
organizational goals
 operational control - the efficient and effective execution
of specific tasks
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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DSS (continued …)
 Decision Support Framework
Type of
Decision
Type of Control
Managerial
Control
Operational
Control
Structured
Accounts
Receivable
Order entry
Semistructured
Production
scheduling
inventory
control
Unstructured
Selecting a
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cover for a
magazine,
buying software
approving loans
Negotiating,
recruiting and
executive,
buying hardware,
lobbying
Support
Needed
MIS,
MS
MS, DSS, EIS, ES
Strategic
Planning
1 Budget analysis,
2
short-term forecasting,
personnel reports,
make-of-buy analysis
4 Credit evaluation,
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Budget Preparation,
plan layout, project
scheduling, rewarded
systems design
Financial
3
management ,
warehouse location,
distribution systems
Building new plant,
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mergers and acquisitions,
new product planning,
compensation planning,
quality assurance
planning
8 R & D planning, new 9
technology development
social responsibility
planning
EIS, ES,
Neural Networks
Support
Needed
MIS
MS models
F&S
models
DSS
DSS
ES
Neural
Networks
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Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
DSS (continued …)
Computer Support for Structured decision
 support the nine cells, especially to the operational and
managerial control type
 lower-level managers encounter on a regular basis
typically have a high level of structure
Management Science - adopts the view that managers
can follow a fairly systematic process for solving problems
 Define the problem
 Classify the problem into a standard category
 Construct a standard mathematical model
 Find potential solutions
 Choose and recommend a specific solution
Introduction to Information Technology
Turban, Rainer and Potter
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DSS (continued …)
Concepts
 an approach or a philosophy rather than a precise
methodology
Characteristics and Capabilities
 support decision makers at all managerial levels
 support several interdependent and/or sequential decisions
 support all phases of decision making and variety of
decision-making processes and styles
 can be adopted over time to deal with changing conditions
 easy to construct
 utilize models
 integrate systems
 execute sensitivity analysis
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Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
DSS (continued …)
Sensitivity Analysis
 the study of the effect that changes in one
or more parts of a model have on other
parts of the model
What-if Analysis
 checks the impact of a change in the
assumptions or other input data on the
proposed solution
Goal-seeking Analysis
 find the value of the inputs necessary to
achieve a desired level of output
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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DSS (continued …)
Components and Structure of DSS
 Data Management
 includes the database(s), which contains relevant
data for the decision situation
 User Interface
 enables the users to communicate with and
command the DSS
 Model Management
 includes software with financial, statistical,
management science, or other quantitative models
 Knowledge Management
 supports any of the other subsystems or act as an
independent component
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Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
Enterprise Decision Support
Executive Information Support
 Capabilities of EIS
 Drill down
 Critical success factors and key performance indicators
 Status access
 Trend analysis
 Ad hoc analysis
 Exception reporting
 Intelligent EIS
 Integration with DSS
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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Enterprise Decision Support
(continues …)
DSS, EIS, and the Internet
 The DSS/EIS builder can access Web pages
and view data that are related to the DSS
project; thus saving time
 The Web supports interactive DSS-related
queries and ad hoc report generation.
 Users have the capabilities of advanced DSS
application without requiring special software
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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Enterprise Decision Support
(continues …)
Supporting Idea Generation and Creativity
 Generate ideas or be creative in order to
generate alternative solutions for semi
structured and unstructured situations
 Idea-generation software
 stimulates a single user or a group to
produce new ideas, options, and choices
 encourages and pushes, something like a
personal trainer
 increases the flow of ideas to the user
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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Enterprise Decision Support
(continues …)
Group Decision Support Systems (GDSS)
 an interactive computer-based system that facilitates
the solution of semi structured and unstructured
problems by a group of decision makers
 supports face-to-face meetings - decision room
 as well as meetings where members are in different
locations
 to improve the productivity of decision making
meetings, either by speeding up the decision-making
process or by improving the quality of the resulting
decisions, or both
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Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
Data Visualization Technologies
Data Visualization
 presents data by technologies such as digital
images, geographical information systems,
graphical user interfaces, multidimensional
tables, and graphs, virtual reality, threedimensional presentations, and animation
 allows people to spot problems that have
existed for years, undetected by standard
analysis methods
 can be integrated among themselves to create
a variety of presentations
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Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
Data Visualization Technologies
(continued …)
Visual Interactive Decision Making
 Visual interactive modeling (VIM)
 use computer graphic displays to represent the impact of
different management or operational decisions on goals
such as profit or market share
 user can intervene in the decision-making process and
see the results of the intervention
 Visual interactive simulation (VIS)
 the end-user watches the progress of the simulation
model in an animated form using graphics terminals
 users may interact with the simulation and try different
decision strategies
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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Geographical Information
System (GIS)
GIS Categories
Design and
Engineering
Design and
Planning
Function
Surveying and Mapping
Facilities
Management
Spatial Imaging
Function
GIS
Decision Modelling
Function
Database
Management
Function
Strategic
Planning and
Decision Making Transportation and Logistics
Demographic
and Market
Analysis
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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GIS (continued …)
GIS Applications and Decision Making
Company
PepsiCo, Inc.
What the Application Does
Helps select new Taco Bell and Pizza Hut restaurants,
by combining demographic data and traffic patterns
CIGNA (health insurance)
Answers such questions as “How many CIGNA-affiliated
physicians are within an 8-mile radius of a business?”
Western Auto (a subsidiary Creates a detailed demographic profile of store’s
of Sears)
neighborhood to determine the store’s best product mix
Sears, Roebuck & Co.
Supports planning of truck routes
Health maintenance
Tracks cancer rate to determine clinics’ expansion
organizations
strategy and allocation of expensive equipment
Wood Personnel Services
Maps neighborhoods where temporary workers live; used
(employment agency)
for locating marketing and recruiting efforts in cities
Wilkening & Co.
Designs optimal sales territories and routes for their
(consulting services)
clients, reducing travel costs by 15 percent
CellularOne Corp.
Maps its entire cellular network to identify clusters of
call disconnects and to dispatch technician accordingly
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Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
GIS (continued …)
Emerging GIS Applications
 help reengineer the aviation,
transportation, and shipping industries
 enables vehicles or aircraft equipped
with a GPS receiver to pinpoint their
location as they move
 include railroad car tracking and earthmoving equipment tracking
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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Knowledge Management and
Organizational Knowledge Bases
What is Knowledge Management?
 Knowledge assets - regarding markets,
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
products, technologies, and organizations that a
business owns or needs to own
Best practices - collection of the most
successful solutions and/or case studies
Intellectual capital - collection of knowledge
amassed by an organization over the years
Knowledge system - collects knowledge,
stores it in a database, maintains the database,
and disseminates the knowledge to users
competitive intelligence - collection of
competitive information
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Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
IT Support of Knowledge
Management Activities
Knowledge identification - determines what
knowledge (information) is critical to decision making
Knowledge discovery and analysis - using search
engines, databases, and data mining, the proper knowledge
must be found, analyzed, and put into proper context
Establishment of organizational knowledge bases it stores organizational knowledge and best practices
Knowledge distribution and use - target audiences
are defined and technologies are put into place to enable
knowledge delivery when needed
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Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
Implementing Knowledge
Management
Reorganize as knowledge-based organizations
Created a new position, chief knowledge
officer (CKO)
 crating knowledge management infrastructure
 build a knowledge culture
 make it pay off
Facilitate organizational learning
 learn from their experiences in order to survive
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Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
Knowledge Discovery and
Analysis
The Foundations of Knowledge Discovery
 identify valid, novel, potentially useful data,
and understand patterns in data
 supported by : massive data collection,
powerful multiprocessor computers, and data
mining algorithms
 tools : data warehousing and data access,
multidimensionality, data mining, massive
databases, and online analytical processing
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Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
Online Analytical Processing
(OLAP)
Analysis by end users from their desktop, online
Analyze the relationships between many types of
business elements
Involve aggregated data
Compare aggregated data over hierarchical time
period
present data in different perspectives
Involve complex calculations between data elements
Respond quickly to users requests
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Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
Data Mining for Decision
Support
Data Mining searches for valuable
business information in a large database
and “mines a mountain for a vein of
valuable ore”
Two capabilities
 automated prediction of trends and
behaviors
 automated discovery of previously
unknown patterns and relationships
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Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
Data Mining (continues ...)
Data Mining Tools
 Neural computing
 learning approach by which historical data
can be examined for patterns by a computer
 Intelligent agents
 retrieving information from the Internet or
from intranet-based databases
 Association analysis
 using a specialized set of algorithms that sort
through large data sets and expresses
statistical rules among items
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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Data Mining (continues ...)
Ethical Issues
 prohibited valuable data-mined information
 accountability for incorrect decisions
 human judgment
Legal Issues
 discrimination of age or gender for promotions
 data security from external snooping or sabotage
 data ownership
Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
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What’s in IT for Me?
For Accounting
 play major role in the justification of the creation
of a knowledge base and in its auditing
For Finance
 responsible for justifying major investments
 can be helped by most DSS applications in
financial management and analysis
For Marketing
 use the organization’s knowledge base and will
participate in its creation
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Introduction to Information Technology
Turban, Rainer and Potter
Chapter 10 Data, Knowledge, and Decision Support
What’s in IT for Me? (continued …)
For Production/Operations Management
 can get help in scheduling, logistics,
maintenance
For Human Resources Management
 use the knowledge base to find out how past
cases were handled
 resolve the issue of compensating employees
for contributing their knowledge