1. Chapter 11: Data, Knowledge, and Decision Support
Introduction to Information Technology 2nd Edition Turban, Rainer & Potter © 2003 John Wiley & Sons, Inc.
Chapter 11:
Data, Knowledge, and Decision Support
Prepared by:
Roberta M. Roth, Ph.D.
University of Northern Iowa

2. Chapter Preview In this chapter, we will study:
The decision making process and how IT can support it
Various types of decision support, including DSS, EIS, and GDSS
Methods of analyzing and mining stored data
Ways of presenting information through data visualization techniques
Knowledge management and how it can benefit an organization

3. Why Do Managers Need IT Support?
Volume of available information is staggering
Manually processing information quickly is increasingly difficult
Computerized modeling helps manage complexity
examine numerous alternatives very quickly
provide a systematic risk analysis

4. Where do we get the data we need?
Data Sources
Internal Data
Personal Data
External Data
Data Collection Methods
Manually
By instruments and sensors
Scanning or electronic transfer
Internal data – generated by business transactions
Personal data – individual, subjective estimates, projections, opinions, judgements
External data – generated outside organization, but relevant to organization. Economic data, competitive intelligence

5. What is ‘good’ data? Data Quality
quality determines the data’s usefulness as well as the quality of the decisions based on these data
an extremely important issue
characteristics of high quality data: accurate, secure, relevant, timely, complete, and consistent

6. Data Storage and Management
Databases or in data warehouse and data marts
Data Management difficulties
Data volume exponentially increases with time
Many methods and devices used to collect data
Raw data stored many places and ways
only small portions of data are relevant for specific situations
More and more external data
Different legal requirements relating to data
Difficulty selecting data management tools
Data security, quality, and integrity are essential
Need to store and manage data so that it can be transformed into information and knowledge.

7. Document Management Systems
Much data is contained in documents
DMS manage electronic documents
Provide control over and access to documents within organization
Imaging systems, workflow software, and databases are utilized to efficiently capture and control documents
Global systems – systems connecting two or more companies in two or more countries
Electronic data interchange (EDI) – electronic movement of business documents between business partners
Electronic funds transfer (EFT) – transfer of money using telecommunications
Extranets – extended Intranets that link business partners
Shared databases – databases that business partners both have access to
Integrated messaging – delivery of and fax messages through a single communication system.

8. Business Intelligence
Ultimate goal of collecting data is to provide a foundation for business intelligence
All data needed for sound decisions
Data is drawn from data warehouses or data marts
Data analysis tools are applied
Decision makers’ judgment is augmented with facts, analysis, and forecasts
Global systems – systems connecting two or more companies in two or more countries
Electronic data interchange (EDI) – electronic movement of business documents between business partners
Electronic funds transfer (EFT) – transfer of money using telecommunications
Extranets – extended Intranets that link business partners
Shared databases – databases that business partners both have access to
Integrated messaging – delivery of and fax messages through a single communication system.

9. Decision Making Process
Intelligence Phase
Design Phase
Choice Phase
REALITY
Implementation
of Solution 
SUCCESS
FAILURE
Verification, Testing of Proposed Solution
Validation of the Model
Examination
Intelligence:
organizational objectives
Search and scanning procedures
data collection
problem identification
problem classification
problem statement
Design
formulate a model (assumptions)
set criteria for choice
search for alternatives
predict and measure outcomes
Choice
solution to the model
sensitivity analysis
selection of best alternative
plan for implementation
design of control system

10. Decision Making Process (continued)
Decision Support Systems supply computerized support for the decision making process
End-users actively work with the data warehouse
End-users apply models to represent, understand, and simplify the decision situation

14. What do we mean by ‘model’?
Model - simplified representation of reality
Iconic (scale) models
physical replica of a system
Analog models
Behaves like real system; does not look like it
Mathematical (quantitative) model
models complex relationships and conducts experimentations with them
Mental models
how a person thinks about a situation
Iconic model – prototype of building or new airplane
Analog model – topographic map; house blueprint
Mathematical model – weather forecasting and storm prediction
Mental model – beliefs, assumptions, relationships, and work flows. These models determine the information we use the the manner in which people interpret or ignore information.

15. Thinking about decisions…
A Framework for Computerized Decision Support
Problem Structure
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

16. Thinking about decisions…
Structured decisions have long been supported by computers
Classes of structured decisions have been addressed mathematically with Management Science models
Define the problem
Classify the problem into a standard category
Construct a standard mathematical model
Find potential solutions
Choose and recommend a specific solution

17. Decision Support Systems
Needed when decision is not structured
Characteristics and Capabilities
Support decision makers at all managerial levels
Support several interdependent and/or sequential decisions
Support all phases of decision making and a variety of decision-making processes and styles
Can be adapted over time to deal with changing conditions
Easy to construct
Utilizes models and links to data- and knowledge bases
Execute sensitivity analysis

18. DSS (continued) Sensitivity Analysis What-if 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

19. DSS (continued) Components and Structure of DSS Data Management
Includes the database(s) containing 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
Provides knowledge for solution of the problem; supports any of the other subsystems or act as an independent component

21. Enterprise Decision Support
Executive Information Systems
Meet information needs of executives
Need to monitor and identify problematic trends
Need external as well as internal information
Rapid access to data needed by executives
Very easy user interface
Highly graphical
Often connected with online information services (e.g., Dow Jones News Retrieval)

22. Enterprise Decision Support
Executive Information Systems (continued)
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; web accessibility

23. Enterprise Decision Support
Group Decision Support Systems
Facilitate solution of semistructured and unstructured decisions by a group of decision makers
Help the group be productive by mitigating some negative group behaviors
Support the group’s process by encouraging idea generation, improving communication, and applying analytical tools as needed to the problem

24. Enterprise Decision Support
GDSS Implementations
Face-to-face meetings – special ‘decision room’ created with linked computers and GDSS software; use is facilitated by trained leader
Corporate ‘war room’ – information displayed graphically and analyses conducted for all to see
Support for virtual teams – collaborative team tools for geographically dispersed teams; support discussion, calendars, polling, etc.

25. What can we do with the stored data?
Analytical Processing - the activity of analyzing accumulated data
Online analytical processing (OLAP)
An end-user activity
Involve large data sets with complex relationships
Use Decision Support Systems models
Is retrospective

26. Online Analytical Processing (OLAP)
Analysis by end users from their desktop, online, using tools like spreadsheets
Analyze the relationships between many types of business elements
Involve aggregated data
Compare aggregated data over hierarchical time periods (monthly, quarterly, annually)
Present data in different perspectives
Involve complex calculations between data elements
Respond quickly to users requests

27. Data Visualization
Analyzed data can be even more useful if presented using Data Visualization techniques
Visual Interactive Modeling – graphic display of decision consequences
Visual Interactive Simulation – simulation model is animated and can be viewed and modified by decision maker
Geographic Information Systems – display data related to geographic location using digitized maps

28. Chapter Summary
High quality data can be analysed to improve decision making
DSSs help decision makers with semi- or unstructured decisions
Executives can use EISs tailored to their information needs
GDSSs support group decision activities
Data analysis and data mining help in understanding and discovery of new insight
Knowledge is also an organizational resource that can be stored and managed
Global systems – systems connecting two or more companies in two or more countries
Electronic data interchange (EDI) – electronic movement of business documents between business partners
Electronic funds transfer (EFT) – transfer of money using telecommunications
Extranets – extended Intranets that link business partners
Shared databases – databases that business partners both have access to
Integrated messaging – delivery of and fax messages through a single communication system.

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