Faculty of Arts Atkinson 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

Welcome

Fourteenth Lecture for ITEC 1010 3.0 A

Professor G.E. Denzel


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


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)


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


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


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


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


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Data, Information, and Knowledge


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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?


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?


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


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


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


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?


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Decision Making as a Component of Problem Solving

Intelligence

Design

Choice

Implementation

Monitoring

Problemsolving

Decisionmaking


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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


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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)


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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’?


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…


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Decision Support Framework


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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…


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


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)


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)


ITEC 1010 A F 2002

DSS (continued)


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


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



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


ITEC 1010 A F 2002

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GIS Examples


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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



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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.



ITEC 1010 A F 2002


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?


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)


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?


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

Faculty of Arts Atkinson College ITEC 1010 A F 2002 Welcome Fourteenth Lecture for ITEC 1010 3.0 A Professor G.E. Denzel.

Documents

data raw data

data warehouse

production data

good data

data quality quality

data storage databases

oriented information

negotiator slide