Chapter - 14

1. Chapter - 14 Decision Support Systems And Knowledge Management

2. DSS : Concept and Philosophy • App. of Herbert Simon Model. • Helps the info. sys. In the intelligence phase. • Objective is to identify the problem and then go to the design phase for solution. • DSS helps in making decision and also in its performance evaluation. • Used to validate the decision by performing sensitivity analysis on various parameters of the problem. • DSS can be built around the rule in case of programmable decision situation. • In non-programmable decisions the rules are not fixed, and requires every time the user to go through the decision making cycle as in model.

3. Types of Decision Support system. • Status Inquiry System • Based on one or two aspects of a decision making situation. • Does not call for any elaborate computations, analysis choice, etc for decision making • Status and solution is unique relation. • Data Analysis System • Based on comparative analysis, Use of a formula and an algorithm. • Eg. Cash flow analysis, the inventory analysis, • Information Analysis System • Data is analysed and information reports are generated • Eg. Sales analysis, account receivables analysis, market research analysis

4. Cont… • Accounting System • Not necessarily for decision making but they are desirable to keep track of the major aspects of the business or a function. • Account items such as cash, inventory, personnel etc. and relate it to a norm or norms developed by the management, for control and decision. • Model Based System • Simulation models or optimisation models for decision making. • One time and infrequent and provide general guidelines for operation and management. • Eg.: Product mix decision, job scheduling rules, resource planning sys. etc.

5. Examples of Material Management function

6. Facts about DSS Are: • Developed by the users and the System Analysts jointly. • Uses the principals of economics, science, and engineering. Also the tools and techniques of management. • Data used in DSS are drawn from the info. sys. Developed in the company. They are from internal sources such as the database, the conventional files and from the external sources. • Developed in isolation and form an independent system subset of the MIS • Used to test the decision alternatives and also to test the sensitivity of the result to the change in the system and assumptions.

7. Advantages of DSS • Sensitising the decisions and assessing its implications on the results or business performance. • Used in focusing on the critical issues in business. • Provides higher management ability to delegate decision making to the lower level once the tools and models are tested.

8. DSS Models DSS Behavioural Model Management Science Model Operations Research Model

9. Behavioural Model • Useful in understanding the behaviour amongst the business variables. • Eg. Trend Analysis, forecasting and the statistical analysis model. • Helps in identifying the influence of one variable on the other. • Used in process control, manufacturing, agricultural sciences, medicines, psychology and marketing. • Behavioural analysis can be used to set the points for alert, alarm and action for the decision maker.

10. Examples of Behavoiural Model • Forecasting : Regression Model:Sale of two wheeler: y = 600 + 0.6x y = sale of two wheelers x = Surplus disposable income • Forecasting : Time Series Analysis and Exponential um Smoothing Exponential average is used, where more weight is given to the latest period and less weight to the older period. Sales for period t+1 = St + 1 St+1 = aDt + (1-a) aDt-1 + (1-a)2 aDt-2 + (1-a)3 aDt-3 Where a = Weight, D = Demand at period t.

11. Market Research Methods • Forecast or judge the behaviour of the consumers in respect of their buying decisions. • Do questionnaires, survey on the advertising campaigns to find the influencing factors in the buying decisions. Ratio Analysis for Financial Assessment • Ratio analysis is a standard method of accessing the financial status of the organisation. • There are dozen of ratios prescribed by the financial institutions to judge the financial conditions of the organisation. • They are current ratio, quick ratio, assets to liabilities and the inventory turnover etc…

12. Management Science Models • Developed on the principles of business management, accounting and econometrics. • Management systems can be converted into the DSS models. • Eg. Material Mgmt. - Budgetary sys., cost accounting sys., capital budgeting for better ROI, ABC analysis • Production Mgmt. – Prod. planning and contro and scheduling and loading systems. • Personal Mgmt. – Manpower planning and forecasting

13. Ex. of Management Science Model • Budgeting Models • Break-even Analysis Model • Return on Investment Analysis • Cash Budgeting • Procedural Models • Project Planning and Control Model • Management Considerations of PERT/CPM • Network Drawing and PERT/CPM Statistics • Estimating Activity Time • Drawing the PERT Network • Probability of Completing the Project • Activity Crashing for control of Time • Cost Accounting System • Job Order Cost System • Process Cost System • Period Cost System

14. Real World Problem Mathematical System Model Abstraction Mathematical Argument (Solution) Interpretation Business Results Operations Research Models • Mathematical Programming Technique • Linear Programming Model (LP) • This model is applicable where the decision variables assume the values which are non-zero, and the relationship among the various variables is linear. • Solution provides a variety of management information through sensitivity analysis

15. Cont… Typical Mathematical programming problems which can be solved by applying the optimisation techniques are • Design of aircraft and aerospace structures for minimum weight • Design of water resources systems for max. benefit • Shortest route of travel • Optimum product mix. • Minimisation of cost by raw material mix. • Assigning jobs to workers • Selection of site for an industry • Inventory Control Models • A-B-C Analysis – Based on the capital blocked in the um inventory • Material Requirement Planning System

16. Applications of DSS • Supply chain management • A supply chain is the collection of steps that a company takes to transform raw components into the final product •  supply chain managements comprised of five stages: plan, source, make, deliver, and return • Supply chain management flows can be divided into three main flows: • The product flow - The product flow includes the movement of goods from a supplier to a customer, as well as any customer returns or service needs • The information flow - The information flow involves transmitting orders and updating the status of delivery • The finances flow - The financial flow consists of credit terms, payment schedules, and consignment and title ownership arrangements

17. Knowledge management • Knowledge in a workplace is the ability of people and organizations to understand and act effectively • intellectual capital is a Collective knowledge of the individuals in an organization or society. This knowledge can be used to produce wealth, multiply output of physical assets, gain competitive advantage, and/or to enhance value of other types of capital • Knowledge and IC (intellectual capital components) is a set made of information, ability, experience, wisdom which gives the organization an advantage.

18. Knowledge management • Knowledge management is the name of a concept in which an enterprise consciously and comprehensively gathers, organizes, shares, and analyzes its knowledge in terms of resources, documents, and people skills • Knowledge management processes • Define, capture, manipulate, store and develop • Develop information system for knowledge creation • Design applications • Create knowledge set • Imp. term in context with KM is IC – intellectual capital components. IC could be defined as a body of knowledge, it is in text and numeric form and has commercial and economic values significance to the person organisation. • Knowledge and IC is a set made of information, ability, experience and wisdom which gives the organisation a competitive advantage and expertise.

19. Knowledge building model Outside organization Business Operations (Work place) Information exchange from external world Internal Operation judging learning Extracts Inputs Extracts Inputs Innovating improving design storing Create knowledge and IC Patent and license technology Learning System Intelligent organization KDB

20. Knowledge management cycle Create knowledge Capture knowledge Refine knowledge Store knowledge Manage knowledge Deliver knowledge

21. Knowledge management system

22. Knowledge management system • Two types of knowledge: 1.Tacit knowledge • Tacit knowledge is knowledge that is difficult to transfer to another person by means of writing it down or verbalising it • Tacit knowledge is not easily shared. It involves learning and skill, but not in a way that can be written down • Tacit knowledge possessed only by an individual and difficult to communicate to others via words and symbols • Examples • The ability to speak a language • The ability to ride a bicycle

23. 2. Explicit knowledge • Explicit knowledge is knowledge that has been or can be articulated, codified, and stored in certain media. It can be readily transmitted to others • Explicit knowledge is easy to communicate, store, and distribute • example  • Knowledge in books, on the web, and other visual means.

24. Knowledge management system architecture KMS Identification of knowledge Knowledge generation Knowledge delivery Processing for acquisition Access control Definition and categorization Application methods Surveying and locating Manipulating and modeling Storage and security Build knowledge structure Creation of KDB

25. Tools for knowledge management • Database management tools • Data warehousing , data mining tools • Process modeling and management tools • Work flow management tools • Search engine tools • Document management tools

26. Approaches to Develop KM Systems Knowledge Conventional: Data to Knowledge (Untested) Refined: : Result to Knowledge (tested) Data Information Action Result Fig : 14.21 Role of KMS

27. Barriers in the KM System Implementation • People in the organization • Resistance to change • Lack of motivation to learn • Turnover of people • Resistance to share knowledge • Management of the organization • Ego problem • Los of power of possession • Fear of loosing to competition • Organization structure • Complex, distributed, based on different principles of structuring, problems in storage, sharing and security • Knowledge Itself

28. Categories of AI Systems AI System Natural Language Expert Perception Uses Knowledge Applies Human-Like Reasoning

29. Knowledge Based Expert System (KBES) • Two methods of problem solving are: • Generalised • KBES • Knowledge based problem solving approach considers the specific constraints within a domain, examines the limited problem alternatives within a knowledge domain and selects the one with knowledge based reasoning with reference to goal. • In this approach only limited alternatives are considered and resolution is made by a logical reasoning with the assurance of the local optimum. • To develop knowledge experts are required which is not an easy task so for that a system is required which will hold the knowledge of experienced people and provide an application path to solve the problem

30. User Control Mechanism (3) Knowledge Base (1) Interface Mechanism (2) KBES Model Decision Making or problem solving is a unique situation riddled with uncertainty and complexity, dominated by the resource constraints and a possibility of several goal.

31. 1. Knowledge Base • Database of knowledge consists of the theoretical foundations, facts, judgments, rules, formulae, intuition and experience • Structured storage with facilities of easy access 2. Interface Mechanism • Tool to interpret the knowledge available and to perform logical deduction in a given situation 3. User Control Mechanism • A tool applied to the interface mechanism to select, interpret and deduct or inter. • Uses the knowledge base in guiding the inference process

32. Eg.: The Knowledge base of “Health Care” would have a knowledge base such as “Obesity leads to high blood pressure”, “ 60% chances that smokers may suffer from cancer.” • The KBES , therefore stores and uses knowledge, accepts judgments, questions intelligently, draws inferences, provides explanation with reasons, offers advice and prompts further queries for confirmation

33. Knowledge Database uses certain methods of knowledge representation • Semantic Networks • Knowledge is represented on the principal of predicate functions and the symbolic data structures which have a meaning built into it are known as semantic • Semantic Network is a network of nodes and arcs connecting nodes • Nodes represents entity and arc represents association • Uses the principal of inheritance • Frames • Put the related knowledge in one area called frame • Frame consists of slots representing a part of the knowledge • Slot has a value which is expressed in the form of data, information, process and rules. • Rules • Is a condition statement of an action that is supposed to take place, under certain conditions

34. Inference Mechanism • This mechanism is based on the principle of reasoning • When reasoning is goal driven, it is called Backward Chaining to goal • When reasoning is data driven, it is called Forward Chaining to goal. • KBES uses both the methods of reasoning. • The success of the knowledge based expert system depends on a degree of knowledge, the confidence in the knowledge and the quality of inference mechanism

35. MIS and DSS

36. The Benefits of Decision Support System