CHAPTER 14: DSS & KNOWLEDGE MANAGEMENT

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LEARNING OBJECTIVES

Understanding of DSS for MIS design

Types of DSS

Operational Research Models

Knowledge and Knowledge management

Knowledge building process

Tacit and explicit knowledge

Knowledge based expert system.

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DSS:Concets and philosophy

DSS are an application of Herbert Simon model(intelligence,design and choice)

It is help the information system to identify problem and then provide solution

Helps in decision making process for management

Provide effectiveness so that performance evaluation take place using DSS

It generally focused on class of system

Using dss decision can be classified in 2 ways programmable and nonprogrammable decisions

Programmable decisions are those which has particular structure and follow certain rules and regulation

Non programmable decisions are assumed decision which is unstructured and can not follow any rules.

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Types OF DSS

Status inquiry systems:

in this systems decisions comes on basic of status if the status is known the decision is automatic

• Data Analysis Systems:

These decision systems are based on corporative analysis, this processes are not structured and therefore it is vary. the use of simple data processing tools and business rules are required to develop this system.

• Information and Analysis Systems:

in this system data is analyzed and information reports are generated. The reports might be having exception as feature. the decision maker use this reports for assessment of situation.

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Types OF DSS

Accounting Systems:

These systems are not necessarily for decision making but they are desirable to keep track of the major aspects of the business or functions. It is based on data processing systems. This system is specially related with accounting application like cash, inventory etc

• Model Based Systems:

These systems are simulations models or optimizations models for decision making.

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Types OF DSS

In order to illustrate these DSS let us take example of material management functions and the variety of decision and type of systems are used to support and evaluate the decision

Decision Types of Systems requied

Finding and selection of vendor Inquiry system

Procurement Performance analysis system

Pricing Data analysis

Selection of vendor based on price and quality performance

Information analysis system

Selection of order quantity Model based system

Inventory rationalization Valuation of inventory and accounting system

Management of inventory within various financial and stocking constraints

Inventory optimization model

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DSS

Facts OF DSS

- The dss are developed by users and system analyst jointly.

- The dss uses the principles of economics, science and engineering and tools of management

- The data uses in dss is drawn from the information systems developed from company

- It is isolated from independenent system of MIS

- The most common uses of dss is to test the decision alternatives and also test the sensitivity of the result to change in the system assumptions.

- The data and information for the dss are used as internal sources such as database and conventional files

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DSS Models

The DSS uses three approaches which are as given

DSS

Behavior Models

ManagementScience model

OR Models

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DSS: Models

Behavior Models:

- These models are useful in understanding the behavior amongst the business variables

- The decision maker can make decisions giving regards to such behavior relationships.

- The trend analysis, forecasting and the stastical analysis models are example of this model

- A trend analysis indicates how different variables behave in trend setting in the past and hence in the future.

- The regression model is example of stastical approaches and generally it is used to count correlation between one or more variables

- These types of models are largerly used in process control, marketing etc.

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DSS: Models

Management science models:

- These models are developed on the business management accounting and economics.

- These are some management which can be converted into for dss models

- For examples the cost accounting systems, the system of capital budgeting for better return on investment.

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DSS: Models

Operational Research (OR) models:

- It is mathematical model

- These models represent a real life problem situation in terms of variables, constants and parameters expressed in algebraic equations.

- It is generally used to compare 2 variables and f aspects.ind conclusion from this

- OR models generally try to find a solution which maximizes certain aspects of business under conditions of constraints

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GROUP DECISION SUPPORT SYSTEMS(GDSS)

It is part of DSS

Main difference is in GDSS there are number of people involve compare to DSS

Same characteristics of DSS like database,query,olap,stastical analysis and others which a group of people need to take decisions

The main objective is to take decision with take suggestions from all the members of group and implement this suggestions into decisions.

In GDSS group members intrect,debate,communicate and conclude using different tool and technique.

GDSS is process that can be run online to conclude important decisions.

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GROUP DECISION SUPPORT SYSTEMS(GDSS)

The group members have some configuration which are as mention beloved:

1)Group members in one room operating on network with common display screen to share display for all members.GDSS process is transparent

2)Group members sit in their respective locations and use their desktop and LAN to interact with other members.GDSS process is not as transparent as ‘1’

3)Group members are in different cities and they come together threw teleconferencing or video conferencing with prior planning

4)Group members are at remote locations may be in different countries and they come together through long distance telecommunication network.

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GROUP DECISION SUPPORT SYSTEMS(GDSS)

In all 4 configurations,GDSS support software is available on server for members to use. there are some common activities which are as mention beloved:

- Sending and receiving information in all forms, type across the network

- Display of notes,graphic,drawings,pictures

- Sharing's ideas choice and indicating preferences

- Participate in decision making process with input, help and so on.

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Artificial intelligence system(AI)

Intelligence supports knowledge and reasoning ability of persons it becomes artificial intelligence

When some AI is picked into a database as a system, then we have AI system

AI System fall three basic category which are:

- Expert systems(Knowledge based)

- Natural language(Native languages)

- Perception systems(vision,speech,touch)

• AI is a software technique which applied on the non numerical data expressed in terms of symbols, statements and patterns

• Ai uses in analysis,planning,training and forecasting.

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Artificial intelligence system(AI)

AI do not replace people

The best example of Ai is knowledge based expert systems

Combinative science application uses knowledge and human information processing capabilities to produce major application as expert systems.

Natural interface application uses AI to build natural,realistic,multi sensory human computer interface.

Generally AI systems is related with virtual world in short it is related with real world.

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DSS Application in E-enterprise

DSS is data driven and model driven.

They are used for solving problem requiring a systematic approach.

The decision is applied on supply chain management

It is depend on structural decision are:

- Deciding number of warehouses, service centres,manufacturing units etc

Use of mechanized and automated material handling system in warehouse

Use of inventory models to decide decisions.

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DSS Application in E-enterprise

The application areas of AI

AI Application

HR InformationProcessing Capability

Computer Uses forproduction

ComputerUses forinterfacing

AI ApplicatinsRobotics application

Natural interfaceApplication

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Knowledge management

Knowledge is the ability of a person to understand the situation and act effectively

Knowledgeable persons should have ability to abstract, understand, speculate and act of subject.

Knowledge is a set of information which provides capability to understand different situations , enables to anticipate implications and judge their effects, suggest ways or clues to handle situations

Knowledge is provide a complete platform to handle complex situation and it has capability to provide complete solution to decision maker.

Knowledge is best illustrated and applicable to resolve complex problem situations.

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Structure and Architecture of Knowledge

Customer IntelligenceDatabase

KnowledgeDatabase

InformationDatabase

DSS Software Solutions

Model based System

Business Forcasting

Business planning

Stastical Analysis ROI Systems

Data DrivenSystems

Pay offAnalysis

DecisionTree

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Knowledge Management

It is the systematic and explicit management of knowledge related activities.

KM is comprehensive towards focusing on three perspectives of business operational, tactical and strategic

KM dispels some myths which must be mentioned for correction

- KM initiatives and activities lead to more work. Instead improved knowledge and usage.

- KM initiatives and activities is an additional function. Instead it is an extension to existing technology driven information management function.

- People are often afraid to share their knowledge.

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Knowledge Management

KM has following processes

- Define,capture,manipulate,store and develop

- Develop information systems for knowledge creation

- Design applications for improving organization’s effectiveness

- Create knowledge set for example intellectual capital to increase economics.

- Keep IC continuously on upgrade to use it is a central resource

- Distribute and share to concerned

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Knowledge Management- Driving forces

Driving Force

External Internal

Competitors Analysis

Customization

Continuous evaluation

Business partnerAnalysis

Effectiveness

Behavior analysis

Knowledge intensivework

Intelligence

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Knowledge Management Systems

Some facts about knowledge management

Facts Comments

Km leads more additional work Reduce problem solving time in routine and non-routine situation

Km is an additional function and a high overhead

Though it is additional function but not provide any benefit

Requires investment in hardware and software

Operational and tacit knowledge doesn’t need any investment

People doesn’t like to share knowledge Yes, But it is managed

Knowledge is kept secret No today’s knowledge is a general knowledge of tomorrow

Km is a static system No it is dynamic

Knowledge is an analytical information, processed for specific goal

Yes it is provide a perfect problem solving mechanism

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Knowledge Management Systems architecture

KMS

Identification

Definition

Survey

Build Structure

KnowledgeGeneration

Process

Manipulate

Create DB

Knowledge Delivery

Access Control

ApplicationMethod

Storage &Security

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Knowledge Management Systems architecture

Identification:

in this phase the knowledge definition, scope and category has been defined then surveys and knowledge structure has been build.

• Knowledge generation:

In this step the knowledge manipulation, process and knowledge database has been generated.

• Knowledge delivery:

this step involves knowledge sharing with proper access control with authorization and authentication process.

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Knowledge management

Tools of KM:

- Database management tools

- DW,Data mining and Data mart

- Process modeling and management tools

- Workflow management tools

- Search engine tools

- Web based tools

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Knowledge based expert system(KBES)

KBES is one kind of problem solving mechanism which generally deals with uncertain conditions

It is helpful in open decision making process where the situation is full of uncertainty.

It deals with applicable constriants,examines all possible alternatives and selects one from this which is near from its goal.

This system is work as source of knowledge

It is developed by experts so this system has ability deal with any kind of uncertain condition

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Knowledge based expert system(KBES)

KBES MODEL

USER CONTROLMECHANISM

KNOWLEDGE BASE

INTERFACE MECHANISM

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Knowledge based expert system(KBES)

Knowledge base:

It is a database of knowledge consisting of the theoretical foundation, facts, rules, formulas and experience. It is a structural storage with facilities of easy access.

• Interface mechanism:

It is a tool to intercept the knowledge available and to perform logical deductions in a given situations.

• User Control Mechanism:

it is a tool applied to the inference mechanism to select, interpret and deduct or intert.this mechanism uses knowledge base in guiding the inference process.

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The benefits of DSS

Ability to deal with data, information in different dimensions and sensing the problem, trend, pattern threw different views

Ability to understand business performance threw evaluations

Ability to identify problem and understand its impact on business.

Ability identify negative Areas of business where the impact starts from.

Ability view a complex scenarios

Ability to make better decisions due to quick analysis,modeling,developing alternatives and testing for selections

Ability to control risk exposure in decisions.