E-Business Decision Support -

8/8/2019 E-Business Decision Support -

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E-Business Decision Support

Group members

Anam Ali (03)

Husna Anjum (06)

M Ahsan Nawaz (12)

Abid Hussain (01)


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Trends 1 of 2 New dimensions of competitions added by

E-Business and E-commerce:

Price, Quality and Features comparison bycustomers

New standards in the speed and quality of

delivery, service and after sales service

Time available with managers to takebusiness decisions is shortening.


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Trends 2 of 2 Downsizing or Flattening of Organizations:

Even an employee at lower level is

required to take important decisions whichwere taken at higher levels in the old

economy.

These factors require an efficient

information support to take business

decisions at all levels.


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Levels of Decisions and

Information Characteristics 1 of 3 Strategic decisions: By Board of Directors,

CEO and top Executives. About Overall

organizational goals, strategies, policies,objectives of the company. Strategic

Planning & control.

Characteristics: Unstructured Decisions.

Information required is ad hoc,

summarized, Forward looking, external.


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Information Characteristics 2 of 3 Tactical Management Decisions: Middle-

level management. Short-and mid-term

plans, budgets. Specifying policies,procedures. Involves allocation of

resources and fixing of responsibilities for

execution of plans.

Characteristics:Scheduled, detailed,

historical, internal, narrow focus.


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Information Characteristics 3 of 3 Operational Management Decisions:

Developing short range plans like

production and delivery schedules, Day-to-day operations and solving problems and

bottlenecks in daily activities.

Characteristics: Routine feedback,

detailed, historical, internal with narrowfocus.


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Types of Information Systems

Management Information Systems (MIS)

On Line Analytical Processing (OLAP)

Decision Support Systems (DSS) Geographic Information Systems (GIS)

and Data Visualization Systems (DVS)


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MIS Vs. DSS

Predefined Info Products

for day-to-day decision-

making.

For Operational &

Tactical Managers.

Structured Decisions

Reports : Periodic,

Exception,Demand, Push

Interactive Info support

Initiated, controlled by

decision maker

tailored to suit personal

decision style

Rely on Model bases +

databases, LP , Multiple

regression forecasting,

PV Models


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Tools and Techniques in DSS

1 of 2 What if analysis: Changing variables and

observing change on other

values:Mortgage Loans: Amt, Int rate,

period etc.

Sensitivity Analysis: Value of one variable

is changes repeatedly and change on

other variables is observed.

Goal-Seeking Analysis : Change in

different variables until a goal is achieved.


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Tools and Techniques in DSS

2 of 2 Optimization Analysis : More complex

extension of goal-seeking analysis.Finding

optimum values for one or more variables

within some given constraints.

Data Mining : Discovering knowledge from

an ocean of information. Discovering

patterns, trends and correlations hidden inthe data to get strategic business

advantage.


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On Line Analytical Processing

(OLAP)

Provide fast answers to complex business

queries.

Managers can interactively manipulate large

amounts of detailed data from manyperspectives.

Involves analyzing complex relationships among

vast data to discover patterns, trends Analytical Operations: Consolidation, Drill Down,

Slicing & Dicing


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Executive Information Systems

(EIS) Combines features of MIS and DSS

Focus: Meet strategic info needs of top

management

Info about firms critical success factors.

Report formats are tailored to suit executives

preferences.

Extensive use of graphical user interface andgraphic displays.

Exception reporting, Drilled down info.


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Enterprise Info or Knowledge

Portals Portals for every one in the company.

Knowledge sharing

Critical info support to staff all over theworld ( Refer to Real World Case 1)

Knowledge Management (KM): Creating,

Sharing and disseminating knowledge insupport of Business Decision Making.


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Artificial Intelligence

Technologies in Business

Section II


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Artificial Intelligence (AI)

A field of science and Technology based

on disciplines such as computer science,

biology, psychology, linguistics,

mathematics and engineering.

Tries to develop computer functions

normally associated with human

intelligence such as reasoning, learningand problem solving.


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Major Application Areas of AI

1 of 3 Cognitive Science Applications :

Expert systems

Learning Systems

Fuzzy Logic

Genetic Algorithms

Neural networks

Intelligent Agents


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2 of 3 Robotics Applications

Visual perceptions

Tactility Dexterity

Locomotion

Navigation


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3 of 3 Natural Interface Application

Natural languages Interface

Speech recognition Multisensory Interfaces

Virtual Reality


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Components of Expert Systems

Knowledge base

Software Resources: Inference Engine

and User Interface Programs Refer to Fig 6.29 on page 232


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Expert Systems Applications Loan Portfolio Analysis

Investment Decisions Insurance

Underwriting (Risk

Analysis)

Medical Diagnosis

Machine Control Inventory Control

Chemical Testing etc

etc.


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Limitations of Expert Systems

Limited focus

Inability to learn

Prohibitive development/maintenance Costs

Can solve specific problems in a limited domain

of knowledge.

Fail miserably in solving problems requiring

broad knowledge base and subjective problemsolving (e.g. Assessment of Political Situation)


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Summary

Decision Support in E-Business E-Business Decision Support

MIS, OAP, DSS,

Using Decision Support System

Executive Information System

Enterprise Portals & Decision Support

Artificial Intelligence Technologies inBusiness

E-Business Decision Support -

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