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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.
