Book 2 chapter-14 dss

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Management Information System
Chapter-14 (dss)

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  • 1. Decision Support System
    • Decision Making :
    • Information is used to make decisions. Decision making is not a single
    • activity that takes place all at one. The process consists of several different activities
    • that take place at different times. The decision maker has to identify and understand
    • problems. Once perceived, solutions must be designed; once solutions are designed,
    • choices have to be made about a particular solution; finally, the solution has to be
    • carried out and implemented. Four different stages in decision making are intelligence,
    • design, choice and implementation.
    • The model has four phases / stages:
      • Intelligence
      • Design
      • Choice
      • Implement
  • 2. Decision Support System
    • The design support system basically helps the information system in the intelligence
    • phase to identify the problem and then go to the design phase for solution. The
    • choice of selection criteria varies from problem to problem. It is required to go
    • through these phase again and again till the satisfactory solution is found.
  • 3. Decision Support System
  • 4. Decision Support System
    • A decision-support system is an integrated set of computer tool that allows a decision- maker to interact directly with computers to create information and it useful in making semi-structured and unstructured decisions.
    • The software components for decision-support systems are a language system which enables the user to interact with the decision-support system, a problem-processing system.
    • Decision Support System (DSS) is a computer-based information system that
    • supports business and organizational decision-making activities.
    • A properly designed DSS is an interactive software-based system planned to
    • help decision makers and to identify and solve problems and make decisions.
    • Decision support system helps in making a decision.
  • 5. Decision Support System
    • DSS serve the management, operations, and planning levels of an organization
    • and help to make decisions, which may be rapidly changing and not easily
    • specified in advance.
    • Decision Support System is a general term for any computer application that
    • increases a person or group’s ability to make decisions.
    • Decision Support Systems are used to collect data, analyze and shape the data
    • that is collected, and make sound decisions or construct strategies from analysis
    • whether computers, databases, or people are involved generally it does not matter.
    • The nature of the decision is such that the decision makers need a variety of
    • information.
    • The reason for changing the demands is also because the methods of decision
    • making a change from time to time.
    • The model has four phases / stages:
      • Intelligence
      • Design
      • Choice
      • Implement
  • 6. Decision Support System Types of decisions :
    • Structured / Programmed Decisions :
      • Schedule decisions
      • Organization develops specific process for handling
      • Rules of decision making system are predetermined
  • 7. Decision Support System
    • Unstructured / Non-programmed Decisions :
      • Repetitive decisions
      • Handled by general problem solving process
      • Decision taken by Decision Support Systems
      • Rules of decision making system are not fixed or predetermined
      • It requires every time the user has to go through the decision-making cycle.
      • Decision support systems can be built in case of programmable decision situation.
    Types of decisions :
  • 8. Decision Support System
    • Types of Decision Support System:
      • Communication-based DSS
      • Data-based DSS
        • Access data systems (Information analysis systems)
        • Data analysis systems
      • Document-based DSS
      • Knowledge-based DSS
      • Model-based DSS
        • Accounting models
        • Representation models
        • Suggestion models
    • Communication-based DSS :
      • Main purpose are to help conduct a meeting and collaboration between two or more people (i.e. group of users to collaborate).
      • The examples are chatting, instant messaging software and online collaboration and net-meeting systems.
  • 9. Decision Support System
    • Data-based DSS :
      • It is mostly used by managers, staff and also product / service suppliers. It is used to query a database or data warehouse – (a database designed to store data in such a way that to allow for its querying and analysis by users) to seek specific answers for specific purposes.
      • Examples: computer-based databases that have a query system to check including the corporation of data to add value to existing database.
      • Information Analysis System :
        • That provide access to a sequence of decision-oriented databases.
        • Information from several files, tables are combined.
        • The information from one file, table can be combined with information from other files to answer a specific query.
  • 10. Decision Support System
    • Data Analysis System :
        • That support the manipulation of data by computerized tools
        • customized to a specific task.
        • Allow data to manipulate capabilities.
  • 11. Decision Support System
    • Document-based DSS :
      • This is the most common type of DSS and targeted at a broad support of users. It is useful when search web pages and find documents on a specific keywords.
      • A Document Driven DSS model uses a variety of documents such as text documents and database records to come up with decisions as well as further manipulate the information to improve the strategies.
      • The three primary forms of data used in document driven DSS are:
        • Oral (i.e. orally conversations)
        • Written (i.e. reports, memos, e-mail and other correspondence)
        • Video (i.e. TV commercials and news reports)
      • Examples of document-driven tools can be found in Internet search engines, designed to separate through vast numbers of unsorted data through the use of keyword searches.
  • 12. Decision Support System
    • Knowledge-based DSS :
      • Knowledge-driven DSS or 'knowledgebase' category covering a broad range of systems, covering users within the organization.
      • for example, consumers of a business. It is essentially used to provide management advise or to choose products / services.
    • Model-based DSS :
      • Model-based support systems incorporate the ability to manipulate data to generate statistical and financial reports, as well as simulation models, to aid decision-makers. Model-based decision support systems can be extremely useful in forecasting the effects of changes in business processes, as they can use past data.
      • Accounting Models :
        • Use Accounting data
        • Provide accounting models capacity
        • Can not handle uncertainty
        • That calculate the consequences (effect) of possible actions.
        • Use Bill of Material
          • Make pricing decisions
          • Calculate Cost
  • 13. Decision Support System
      • Representation Models :
        • To solve decision problem using forecast (estimate).
        • Used to expand the capabilities of Accounting Models.
        • Use the demand data to forecast next years demand.
        • That estimate the consequences of actions on the basis of models.
  • 14. Decision Support System
      • Suggestion Models :
        • Use the system to recommend the decision.
        • That performs to a specific suggested decision for a fairly structured or well-understood task.
        • For eg: Applicant applies for a personal loan.
  • 15. Decision Support System
    • Types of Decision Support System Models / Tools:
      • Behavioural Models
      • Management Science Models
      • Operation Research Models
    Types of Tools / Models
      • Behavioural Models :
        • The decision maker can make the decisions for such behavioral relationships.
        • For eg. :The trend (development) analysis, forecasting and statistical analysis
        • models.
        • The trend analysis indicates how different variables behave in trend setting
        • in the past and hence in future.
    Behavioural Models Management Science Models Operation Research Models DSS
  • 16. Decision Support System
        • A regression model shows the correlation between one or more variables. It helps in identifying the variables. (for forecasting )
        • For eg. : 1) The sale of two wheelers can be forecasted with the use of
        • regression model.
        • 2) bodyweight can be estimated with the help of food in-take.
        • i.e. Y = C + R . X
        • Where,
        • C is a constant;
        • R is a regression coefficient
        • X is a extra cost
        • Y = 600 + 0.6X
        • In Market Research method, they can forecast or judge the behavior of the
        • customers buying decisions. (i.e. The questionnaire are designed and
        • computerized to evaluate customer’s buying behavioral).
  • 17. Decision Support System
      • Management Science Models :
        • These models are developed on the principles of the business management,
        • accounting and economics.
        • For eg. : the budgetary systems, cost accounting system, inventory
        • management system.
        • In the budgetary system, budgets are used for planning and control.
        • In all the organization, budgets are prepared with the use of graphical representation in the form of line charts or bar charts.
        • For eg. : Sales Budget, Production Budget.
      • Operation Research Models :
        • The Operation Research models are the mathematical models which gives
        • the feasible solutions by satisfying the constraints .
        • For eg. : Linear Programming
  • 18. Decision Support System
      • Benefits of Decision Support System :
        • Ability to view data / information and sensing the problem through the
        • different view.
        • Ability to understand and evaluate the business performance.
        • Ability to understand the problem and its result, and ability to judge the
        • impact on business.
        • Ability to evaluate the impact of any change in the business performance and
        • enabling to focus on the areas where impact is negative.
        • Ability to view the complex scenario or problem and to analyze it and develop alternatives to solve the problem.
        • Ability to make a better decisions due to quick analysis.
        • Ability to control the risk exposure in decisions.
      • All these abilities together make a decision maker, a capable person to handle any complex business scenario or problem. Manager through DSS, builds capability to execute the decision-making process ‘Intelligent – Design – Choice – Implement ’ built by Herbert Simon.
  • 19. Group Decision Support System
    • Information technology supports decision-making where there is a group
    • participation. Such decision support system is called as Group Decision Support
    • Systems (GDSS).
    • There are four configurations of group members are possible.
      • Group members in one room operating on network with common display
      • screen to share the display for all members.
      • Group members sit at their respective locations and use their desktop to
      • interact with other members.
      • Group members are in different cities and they come together through
      • teleconferencing or video conferencing with prior planning GDSS
      • operations.
      • Group members are at remote locations may be in different countries and
      • they come together through long distance telecommunication network.
      • In all four configurations, GDSS support software is available on server for members to use. In all the configuration models, the group members work together in a collaborative manner.
  • 20. Knowledge
    • Knowledge is something that comes from information (to bring a clarity in data)
    • processed by using data (things that can be evaluated). It includes experience and
    • related information and helps in evaluation, integration of new experiences.
    • Knowledge is useful by knowledge workers who are involved in a particular job or
    • task. People use their knowledge in making decisions as well as many other actions.
    • Knowledge is the ability of a person to understand the situation and act effectively.
    • Philosophers, thinkers, scientists are considered to process a knowledge because of
    • their ability, understand and consideration. Besides the knowledge, these people
    • have several other skills namely use of principles and theory, problem solving
    • capability and decision-making skill.
    • Knowledge is not easily measured (evaluated) or audited (reviewed), so
    • organizations must manage knowledge effectively in order to take full advantage of
    • the skills and experience in their systems.
    • Knowledge will be a powerful tool to enhance productivity and reduce cost behind the
    • successful business.
  • 21. Knowledge
    • There are two types of knowledge
      • Tacit knowledge
      • Explicit knowledge
        • In Tacit knowledge  is what people carry in their minds, it is very difficult to find out. We are not ourselves aware of the knowledge for many times. we hold the knowledge and also how valuable, it can turn out to be if shared with others. The transfer of tacit knowledge mainly happens through personal contact and trust but this is considered to be very valuable. Many times this is not shared, primarily because we are unable to communicate all, we know.
          • Tacit knowledge is knowledge based on experience and observation.
          • Tacit knowledge is the knowing of things without knowing how you know.
          • For example, most people can speak grammatically without being able to explain the rules of grammar. This is Tacit knowledge.
  • 22. Knowledge
        • In Explicit knowledge  is what is documented or codifies and can be transferred easily to others. The processes, procedures, journals, manuals, drawings or any such artifacts come under Explicit knowledge. knowledge that can be quantified (measured). It can be written down and clearly communicated to another human being. It's tangible (like material) . There is no need to gain experience. It's something that has been converted to a rule. (standard)
        • Explicit knowledge is the type of knowledge conveyed through articles, books, seminars, and video presentations. There is no need to have direct experience with something to have explicit knowledge about it. This is one of the criticisms of college students who are just graduating. They have a lot of "book knowledge" (explicit knowledge) but lack real world experience (tacit knowledge).
        • explicit knowledge is the knowing of things that you can explain.
  • 23. Knowledge
          • For example, stating to someone that  Tooting is in London  is a piece of explicit knowledge that can be written down and understood.
          • Knowledge that is easy to communicate is called explicit knowledge.
    • Keywords:
        • Data : Data are specific, objective facts or observations. (i.e. it can be illustrated as a fact, which has not been structured and data are collection of facts, measurements, and statistics.
        • Information : Information is a relevant, structured and meaningful data. (i.e. data endowed (capability) with relevance and purpose and it is organized or processed data that are timely, accurate)
        • Knowledge : Knowledge is something that comes from information processed by using data. (i.e. Knowledge is applied by knowledge workers who are involved in a particular job or task. People use their knowledge in making decisions as well as many other actions and Knowledge is information that is contextual, relevant, and actionable)
    • Another important term in context of knowledge management is IC, intellectual
    • capital components.
    • ‘ Knowledge and IC‘ is a set made of information, ability, experience which gives
    • the organization very competitive and expertise.
  • 24. Knowledge In simpler terms, Knowledge Management seeks to make the best use of the knowledge that is available to an organization, creating new knowledge in the process. Input Human Response / understanding Signal Indication of something Data Some measure of this indication (i.e. measurement of data or things can be evaluated) Information Measure in context of some other thing adding focus and clarity (to bring clarity in data) Expertise Information developed on the basis of principles for problem solving. Knowledge Developing capabilities for effective behaviour. IC Set of knowledge uniquely took by the person.
  • 25.
    • Knowledge Management System (KM System) refers to a (generally IT based) system for managing knowledge in organizations for supporting creation, capture, storage and distribution of information.
    Knowledge Management System
    • Create : Knowledge must be created either within or outside the organization.
    • This is typically comprised of iterative tacit and explicit loops until the
    • knowledge is ready for distribution for those outside the creating group.
    Knowledge Life Cycle
  • 26. Knowledge Management System
    • Store : Knowledge can be stored somewhere, either tacitly or explicitly so that it
    • is accessible for others to find and use.
    • Find : Those who need the specific knowledge must then find out where it is,
    • when they need it, by searching in the right places and / or asking the right
    • people.
    • Acquire : Once the knowledge source is found, the user will then go through the
    • act of actually acquiring it. This will involve gaining personal
    • knowledge from other humans or documented sources.
    • Use : Once acquired, the knowledge can be put to use towards some productive
    • purpose.
    • Learn : Having been used, perhaps repeatedly, the user will learn what worked
    • well and not so well as a result of applying the knowledge gained. This
    • can then be taken as significant input into further iterations of the
    • knowledge creation and distribution process.
  • 27. Knowledge Management System
    • Knowledge Management System Architecture :
      • KMS architecture deals with knowledge identification, generation and delivery for application in business.
    KMS Architecture KMS Manipulation of knowledge Surveying and locating Definition of Knowledge Knowledge Holding Knowledge Generation Identification of Knowledge Creation of KDB Build knowledge Structure Application Methods Access Control Knowledge Delivery Storage and security
    • Identification of Knowledge :
        • Knowledge needs to be identified and defined for processing. The next step is to survey for locating the source for knowledge in the organization. On locating the valid source, it is necessary to put into a structure for understanding and application.
  • 28. Knowledge Management System
    • Knowledge Generation:
        • After identifying, define and structuring the knowledge, the knowledge process must set for Acquisition of knowledge (i.e. knowledge holding).
        • On acquisition, knowledge needs to be manipulated for understanding, presentation and usage. Next step is to integrate knowledge sets to build knowledge databases for access and distribution.
    • Knowledge Delivery:
        • Once create a knowledge and it in place knowledge database. Database is secured and protected and also made available to users for viewing, manipulating the application.
        • The system for access control, authorization and authentication of knowledge for the purpose of update, alter, delete etc. are necessary.
    • Tools for Knowledge Management :
      • Database management tools :
        • For data management and look for knowledge through SQL queries.
      • Data warehousing, Data mining tools
        • For business information creation and data mining tool.
      • Search engine tool
        • For locating specific information through search algorithm.
  • 29. Knowledge Management System
      • Document management tools
        • These tools are known as database management tools for documents.
      • Web based tools
        • View and visualize Different websites.
    • Approaches to Develop a Knowledge Management System:
    Knowledge Information Action Result Data
      • Moving a knowledge from data is a conventional approach to KM defining knowledge as just in case requirement, but untested.
      • Moving from results backward to knowledge is a refined (improved) approach, which has passed the test of utility.
  • 30. Knowledge based Expert System
    • Decision-making or problem solving is a unique situation with uncertainty and complexity. In such cases, flexible systems (open systems) are required to solve the problems. Most of the situations, termed as the unstructured situations, adopt two methods of problem solving,
        • Generalized method
        • Knowledge based expert system (KBES) method
    • Generalized method :
        • The generalized problem solving approach considers the generally related (appropriate) constraints, examines all possible alternatives and selects one by trial and error method with reference to a goal.
        • All the alternatives are considered and the resolution of the problem is by trial and error, with no guarantee, whether it is the best or the optimum.
        • The generalized approach is dominated by a procedure or method.
    • Knowledge based expert system method :
        • The knowledge based problem solving approach considers the specific (particular, standard) constraints within an organization.
        • KBES examines the limited problem alternatives within a knowledge domain and selects the one with knowledge based reasoning with reference to a goal.
        • In the KBES, only limited alternatives are considered and resolution is made by a logical reasoning with guarantee for the optimum.
        • The knowledge based approach is dominated by the reasoning process based on the knowledge.
  • 31. Knowledge based Expert System
    • The KBES considers knowledge as a base, the question arises whose knowledge is to be considered as a basis. It is generally agreed that an expert has knowledge and therefore, he/she becomes the source of knowledge.
    • Knowledge is with experienced people and experience, is broad and distributed. Hence, a system is required which will hold the knowledge of experienced people and provide an application path to solve the problem.
    • To build a knowledge-based system, certain prerequisites are required.
        • The first prerequisite is that a person with the ability to solve the problem.
        • The second prerequisite is that such an expert should be able to clear with the knowledge specific problem.
  • 32. Knowledge based Expert System
    • KBES Model :
    • The KBES has three basic components which are necessary to build the system.
    User Control Mechanism Knowledge Base Inference Mechanism KBES Model
    • Knowledge Base :
        • It is a database of knowledge consisting of the theoretical basis, facts, judgment, rules, formulae, intuition and experience.
        • Expert’s knowledge is to be considered in knowledge base.
        • contains lots of problem solving knowledge.
  • 33. Knowledge based Expert System
    • Inference Mechanism :
        • It is a tool to understand the knowledge. Having created a knowledge database, it is necessary to create the inference mechanism. The mechanism is based on the principle of reasoning.
        • There are two types of strategy.
          • Forward Chaining
          • Backward Chaining
        • Backward chaining is a goal-based strategy and Forward chaining is a data-based strategy.
        • For example, if there is a breakdown in the plant, then looking backward for the symptoms (indication, warning sign) and causes, based on the knowledge database. It is called as backward chaining. However, if the data which is being collected in the process of plant operations are understand with the knowledge base, it can be predicated whether the plan will stop or work at low efficiency. The data is used to understand the performance of the plant. It is called forward chaining.
        • The choice between backward or forward chaining depends on the kind of situation. To resolve the problem after the event, one has to go from goal (breakdown, stoppage) to data (i.e. backward chaining). But if the question is of preventing (stop, avoid) a breakdown, then data is directing near to goal (breakdown, stoppage) (i.e. forward chaining)
  • 34. Knowledge based Expert System
    • User Control Mechanism :
        • It is a tool applied to the inference mechanism to select and understand. The user control mechanism uses the knowledge base in guiding the inference process.
        • In the KBES, three components are independent of each other. This helps in modifying the system without affecting all the components.
        • In the database application, where the data is independent of its application.
        • In KBES, knowledge is independent from application.
        • The KBES database, stores the data.
        • For Example: the knowledge base Health Care would have a knowledge such as “ obesity leads to high blood pressure ” , “ there are 60 percent chances that smokers may suffer from cancer ” . The KBES stores and uses the knowledge, accept judgments, questions intelligently, provides explanation with reasons.
        • In the KBES, the knowledge database uses certain methods of knowledge representation. This methods are
            • Semantic Networks
            • Frames
            • Rules
  • 35. Knowledge based Expert System
      • Semantic Networks:
          • Knowledge is represented on the principle of predicate functions and the symbolic data structures which have a meaning built into it are known as semantic.
          • A semantic network is a network of nodes and arcs connecting the nodes.
          • The nodes represents an entity and the arc represents association with a true and false meaning built into it. The association and meaning uses the principle of inheritance.
          • For Example : All animals with four legs have a tail and a dog has four legs, hence the dog has a tail. The system inherits from the fact that the dog has four legs, hence the dog is an animal and therefore a dog has a tail or not.
      • Frames:
          • The second method of representing the knowledge is putting into the frame. The concept of frame is to put the related knowledge in one area called as frame. The frame can be related to other frames.
          • A frame consists of the slots representing a part of the knowledge. Each slot has a value which is expressed in the form of data, information, process and rules.
  • 36. Knowledge based Expert System
      • c) Rules:
          • The third method of representing the knowledge is ruled based. A rule is a conditional statement of an action that is supposed to take place, under certain conditions.
          • Some rules can be constructed in the form of ‘ If Then ’ statements.
    SLOT : Symptoms Value (Temperature more than 80 degrees) (Water Boiling) (Speed Hold up) FRAME Engine Over Heating SLOT :Inspection Value (Check Water Value) (Check Oil in Engine) (Check Carburetor) SLOT : Treatment Value (Stop Engine and Drain Water) (Start Engine) (Increase Oil Level) (Adjust Carburetor)