faculty of arts atkinson college itec 1010 a f 2002 welcome fourteenth lecture for itec 1010 3.0 a...
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Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Welcome
Fourteenth Lecture for ITEC 1010 3.0 A
Professor G.E. Denzel
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Agenda
Point to tutorials on CSS Some last ideas from Chapter 9 on
‘integrated systems’ Material relevant to Chapter 10 in text,
dealing with various Decision Support Systems
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Agenda
A hierarchy of different levels of systems EOQ (straightforward inventory management) MRP (Materials Requirements Planning) MRPII (integrates MRP with Finance, HR, etc) SCM (Supply Chain Management) ERP (Enterprise Resource Planning)
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Integrated Information Systems Reasons for Integration
Existing, functionally oriented information systems are deficient:• cannot give employees all the information they need
• do not let different departments communicate effectively
• crucial sales, inventory, and production data often entered manually into separate computer systems
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Integrated Information Systems How to Integrate Information Systems
Connect existing systems• maximize the use of existing systems and allows the
addition of new applications Using supply chain management software
• Overcomes the isolation of traditional departmental structure by integrating processing across several functional areas
Use Enterprise Resource Planning software• control all major business processes with a single
software architecture in real time
• increased efficiency to improve quality, productivity, and profitability
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
What do Managers do? Make decisions in the process of achieving
goals Interpersonal roles: figurehead, leader, liaison Informational roles: monitor, disseminator,
spokesperson Decisional roles: entrepreneur, disturbance
handler, resource allocator, negotiator
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
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
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Data, Information, and Knowledge
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Data Sources Internal Data Personal Data External Data
Data Collection Methods Manually By instruments and sensors Scanning or electronic transfer
Where do we get the data we need?
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
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
What is ‘good’ data?
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Data Storage 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
Data Storage and Management
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
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
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
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
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Capabilities of a DSS (1)
Supports Problem solving phases Different decision frequencies
Frequencylow high
Merge withanother
company?
How many widgets
should I order?
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Decision Making as a Component of Problem Solving
Intelligence
Design
Choice
Implementation
Monitoring
Problemsolving
Decisionmaking
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Decision Making Process
Intelligence PhaseIntelligence Phase
Design PhaseDesign Phase
Choice PhaseChoice Phase
REALITY
Implementationof Solution
Implementationof Solution
SUCCESS
FAILURE
Verification, Testing of Proposed Solution
Validation of the Model
Examination
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
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
Decision Making Process (continued)
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
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
What do we mean by ‘model’?
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
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
Thinking about decisions…
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Decision Support Framework
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
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
Thinking about decisions…
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Needed when decision is not structuredCharacteristics 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
Decision Support Systems
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
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
DSS (continued)
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
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
DSS (continued)
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
DSS (continued)
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Executive Information Systems Meet information needs of executives
• Very limited time
• Need to monitor and identify problematic trends
• Need external as well as internal information
Rapid access to data needed to executives Very easy user interface Highly graphical Often connected with online information services (e.g., Dow Jones
News Retrieval) Incorporates email
Enterprise Decision Support
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
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
Enterprise Decision Support
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
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
Data Visualization
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
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GIS Examples
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
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
Enterprise Decision Support
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
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.
Enterprise Decision Support
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Analytical Processing - the activity of analyzing accumulated data
Online analytical processing (OLAP) An end-user activity Involves large data sets with complex
relationships Uses Decision Support Systems models Is retrospective
What can we do with the stored data?
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Analysis by end users from their desktop, online, using tools like spreadsheets
Analyze the relationships between many types of business elements
Involve aggregated dataCompare aggregated data over hierarchical time
periods (monthly, quarterly, annually)Present data in different perspectivesInvolve complex calculations between data
elementsRespond quickly to users requests
Online Analytical Processing (OLAP)
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Data mining – intelligent search of data stored in data marts or warehouses Find predictive information Discover unknown patterns
End users perform mining tasks with very powerful tools
Mining tools apply advanced computing techniques (learning, intelligence)
What can we do with the stored data?
Faculty of ArtsAtkinson College
ITEC 1010 A F 2002
Ethical Issues Valuable data-mined information may violate individual
privacy Who is accountable for incorrect decisions that are based
on DSS? Human judgment is fallible Job loss due to automated decision making?
Legal Issues Discrimination based on data mining results Data security from external snooping or sabotage Data ownership of personal data
Data Mining and Analysis Concerns