Page 2LEARNING 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.
Page 3DSS:Concets and philosophy DSS are an application of Herbert Simon model(intelligence,design andchoice) It is help the information system to identify problem and then providesolution Helps in decision making process for management Provide effectiveness so that performance evaluation take place usingDSS It generally focused on class of system Using dss decision can be classified in 2 ways programmable andnonprogrammable decisions Programmable decisions are those which has particular structure andfollow certain rules and regulation Non programmable decisions are assumed decision which is unstructuredand can not follow any rules.
Page 4Types OF DSS Status inquiry systems:in this systems decisions comes on basic of status if the status isknown the decision is automatic• Data Analysis Systems:These decision systems are based on corporative analysis, thisprocesses are not structured and therefore it is vary. the use of simpledata processing tools and business rules are required to develop thissystem.• Information and Analysis Systems:in this system data is analyzed and information reports aregenerated. The reports might be having exception as feature. the decisionmaker use this reports for assessment of situation.
Page 5Types OF DSS Accounting Systems:These systems are not necessarily for decision making but they aredesirable to keep track of the major aspects of the business or functions.It is based on data processing systems. This system is specially relatedwith accounting application like cash, inventory etc• Model Based Systems:These systems are simulations models or optimizations models fordecision making.
Page 6Types OF DSS In order to illustrate these DSS let us take example of materialmanagement functions and the variety of decision and type of systemsare used to support and evaluate the decisionDecision Types of Systems requiedFinding and selection of vendor Inquiry systemProcurement Performance analysis systemPricing Data analysisSelection of vendor based on price andquality performanceInformation analysis systemSelection of order quantity Model based systemInventory rationalization Valuation of inventory and accountingsystemManagement of inventory within variousfinancial and stocking constraintsInventory optimization model
Page 7DSS Facts OF DSS- The dss are developed by users and system analyst jointly.- The dss uses the principles of economics, science and engineering andtools of management- The data uses in dss is drawn from the information systems developedfrom company- It is isolated from independenent system of MIS- The most common uses of dss is to test the decision alternatives and alsotest the sensitivity of the result to change in the system assumptions.- The data and information for the dss are used as internal sources such asdatabase and conventional files
Page 8DSS Models The DSS uses three approaches which are as givenDSSBehaviorModelsManagementScience modelOR Models
Page 9DSS: Models Behavior Models:- These models are useful in understanding the behavior amongst thebusiness variables- The decision maker can make decisions giving regards to such behaviorrelationships.- The trend analysis, forecasting and the stastical analysis models areexample of this model- A trend analysis indicates how different variables behave in trend settingin the past and hence in the future.- The regression model is example of stastical approaches and generally itis used to count correlation between one or more variables- These types of models are largerly used in process control, marketing etc.
Page 10DSS: Models Management science models:- These models are developed on the business management accountingand economics.- These are some management which can be converted into for dssmodels- For examples the cost accounting systems, the system of capitalbudgeting for better return on investment.
Page 11DSS: 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 conclusionfrom this- OR models generally try to find a solution which maximizes certainaspects of business under conditions of constraints
Page 12GROUP DECISION SUPPORT SYSTEMS(GDSS) It is part of DSS Main difference is in GDSS there are number of people involve compareto DSS Same characteristics of DSS like database,query,olap,stastical analysisand others which a group of people need to take decisions The main objective is to take decision with take suggestions from all themembers of group and implement this suggestions into decisions. In GDSS group members intrect,debate,communicate and conclude usingdifferent tool and technique. GDSS is process that can be run online to conclude important decisions.
Page 13GROUP DECISION SUPPORT SYSTEMS(GDSS) The group members have some configuration which are as mentionbeloved:1)Group members in one room operating on network with common displayscreen to share display for all members.GDSS process is transparent2)Group members sit in their respective locations and use their desktopand LAN to interact with other members.GDSS process is not astransparent as ‘1’3)Group members are in different cities and they come together threwteleconferencing or video conferencing with prior planning4)Group members are at remote locations may be in different countries andthey come together through long distance telecommunication network.
Page 14GROUP DECISION SUPPORT SYSTEMS(GDSS) In all 4 configurations,GDSS support software is available on server formembers to use. there are some common activities which are as mentionbeloved:- Sending and receiving information in all forms, type across the network- Display of notes,graphic,drawings,pictures- Sharings ideas choice and indicating preferences- Participate in decision making process with input, help and so on.
Page 15Artificial intelligence system(AI) Intelligence supports knowledge and reasoning ability of persons itbecomes artificial intelligence When some AI is picked into a database as a system, then we have AIsystem 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 dataexpressed in terms of symbols, statements and patterns• Ai uses in analysis,planning,training and forecasting.
Page 16Artificial 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 informationprocessing capabilities to produce major application as expert systems. Natural interface application uses AI to build natural,realistic,multi sensoryhuman computer interface. Generally AI systems is related with virtual world in short it is related withreal world.
Page 17DSS 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 etcUse of mechanized and automated material handling system in warehouseUse of inventory models to decide decisions.
Page 18DSS Application in E-enterprise The application areas of AIAI ApplicationHR InformationProcessingCapabilityComputerUses forproductionComputerUses forinterfacingAI ApplicatinsRoboticsapplicationNatural interfaceApplication
Page 19Knowledge management Knowledge is the ability of a person to understand the situation and acteffectively Knowledgeable persons should have ability to abstract, understand,speculate and act of subject. Knowledge is a set of information which provides capability to understanddifferent situations , enables to anticipate implications and judge theireffects, suggest ways or clues to handle situations Knowledge is provide a complete platform to handle complex situationand it has capability to provide complete solution to decision maker. Knowledge is best illustrated and applicable to resolve complex problemsituations.
Page 20Structure and Architecture of KnowledgeCustomerIntelligenceDatabaseKnowledgeDatabaseInformationDatabaseDSS Software SolutionsModel based SystemBusiness ForcastingBusiness planningStastical Analysis ROISystemsData DrivenSystemsPay offAnalysisDecisionTree
Page 21Knowledge Management It is the systematic and explicit management of knowledge relatedactivities. KM is comprehensive towards focusing on three perspectives of businessoperational, tactical and strategic KM dispels some myths which must be mentioned for correction- KM initiatives and activities lead to more work. Instead improvedknowledge and usage.- KM initiatives and activities is an additional function. Instead it is anextension to existing technology driven information management function.- People are often afraid to share their knowledge.
Page 22Knowledge 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 increaseeconomics.- Keep IC continuously on upgrade to use it is a central resource- Distribute and share to concerned
Page 24Knowledge Management Systems Some facts about knowledge managementFacts CommentsKm leads more additional work Reduce problem solving time in routineand non-routine situationKm is an additional function and a highoverheadThough it is additional function but notprovide any benefitRequires investment in hardware andsoftwareOperational and tacit knowledgedoesn’t need any investmentPeople doesn’t like to share knowledge Yes, But it is managedKnowledge is kept secret No today’s knowledge is a generalknowledge of tomorrowKm is a static system No it is dynamicKnowledge is an analytical information,processed for specific goalYes it is provide a perfect problemsolving mechanism
Page 25Knowledge Management Systems architectureKMSIdentificationDefinitionSurveyBuild StructureKnowledgeGenerationProcessManipulateCreate DBKnowledgeDeliveryAccessControlApplicationMethodStorage &Security
Page 26Knowledge Management Systems architecture Identification:in this phase the knowledge definition, scope and category hasbeen defined then surveys and knowledge structure has been build.• Knowledge generation:In this step the knowledge manipulation, process and knowledgedatabase has been generated.• Knowledge delivery:this step involves knowledge sharing with proper access controlwith authorization and authentication process.
Page 27Knowledge 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
Page 28Knowledge based expert system(KBES) KBES is one kind of problem solving mechanism which generally dealswith uncertain conditions It is helpful in open decision making process where the situation is full ofuncertainty. It deals with applicable constriants,examines all possible alternatives andselects 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 ofuncertain condition
Page 29Knowledge based expert system(KBES) KBES MODELUSER CONTROLMECHANISMKNOWLEDGEBASEINTERFACEMECHANISM
Page 30Knowledge based expert system(KBES) Knowledge base:It is a database of knowledge consisting of the theoreticalfoundation, facts, rules, formulas and experience. It is a structural storagewith facilities of easy access.• Interface mechanism:It is a tool to intercept the knowledge available and to performlogical deductions in a given situations.• User Control Mechanism:it is a tool applied to the inference mechanism to select, interpretand deduct or intert.this mechanism uses knowledge base in guiding theinference process.
Page 31The benefits of DSS Ability to deal with data, information in different dimensions and sensingthe 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 quickanalysis,modeling,developing alternatives and testing for selections Ability to control risk exposure in decisions.