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    DECISION MODELS IN

    MANAGEMENT

    PGDM-I TERM III

    by

    PROF. R.N.VENKATESWARAN

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    Reference Books

    An Introduction to Management Science:Quantitative Approaches to Decision Making, by:

    Anderson Sweeney, Williams, Thomson South-

    Western, 10e

    Principles of Operations Research for

    Management (2e) - by Budnick; McLeavey, and

    Mojena AITB,Delhi edition

    Operations Research by Taha, HA (6e), Prenhall Principles of Operations Research with

    applications to Managerial Decisions, (2e), by

    Wagner, Prenhall, India

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    DECISION MODELS

    Various names given to body of knowledge which use

    Quantitative Methods in Decision Making:Management Science (MS)

    Operations Research (OR)

    Decision Science

    Modern management requires executive-generalists

    who are trained and effectively operate in business,

    industry, government, hospitals, armed forces, educational

    institutions, service industries etc., They could coordinate

    the contributions of all of the specialists of an organization.Their task requires the ability to employ structure before

    content in coping with the extreme diversity of information

    produced by the organization.

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    DECISION MODELScontd

    Modern Management differs from Taylors scientific

    management:

    It views efficiency as secondary achievement, which

    should follow adequate planning. Both good and poor

    decisions can be implemented in an efficient way. A

    company can manufacture a high-quality product at a

    minimum cost, but the product itself might not be the bestchoice to meet the companys objectives.

    Modern management attempts to establish relationship

    between organizations objectives and its resources.

    It cuts across traditional areas of management andemphasizes inter-disciplinary approach. People with

    diverse specialties - e.g. mathematicians, engineers,

    behavioural scientists, accountants etc., join together to

    solve an organizational problem

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    Problem Solving & Decision Making

    Problem Solving is the process of identifying a difference

    between the actual and the desired state of affairs and then

    taking action to resolve the difference.

    Decision Making is associated with management process

    of planning, organizing, coordinating, controlling etc.,

    Managementas defined by Websters Dictionary, is thejudicious use of means to accomplish an end.

    Doing and Deciding are both managerial/executive

    functions. Routine operations require doing. Exceptions

    require deciding.

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    Problem Solving & Decision Making Executive is a word derived from a Latin word meaning

    to do; the Oxford Dictionary defines it as the action of

    carrying out or carrying into effect. This does not suggestthat the main responsibility and function of the executive is

    to make decisions.The executive is rewarded and evaluated

    in terms of his success at making decisions while

    managing his function.

    Organization structure is set up to help executives do

    decision making

    Managerial PROBLEM SOLVING would involve both

    doing - with the organization structure and deciding

    using various management tools and techniques. The

    manager has to form a partnership between those who

    perceive they have a problem (users) and those who have

    the specialized knowledge or skills in problem-solving

    techniques (specialists)

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    TAXONOMY OF OR MODELS

    Search Methods

    Classical Methods

    Non-linear Optimization

    GOAL

    Programming

    Transportation& Assignment

    Linear Programming

    Linear Optimization

    Deterministic

    MarkovProcesses

    Queuing

    Models

    DecisionAnalysis

    Stochastic

    Simulation

    InventoryModels

    Dynamic

    Programming

    PERT/CPM

    HYBRID

    ORMODELS

    C S O O S

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    DECISION MODELS

    TOPICS & SESSIONS

    Decision Theory & Modeling 2

    Linear Programming 7

    Multi-Criteria (Goal Programming). 3

    Simulation 3

    Transportation Models 4 Assignment Problems 3

    Game Theory 2

    Queuing (Waiting-line) Models 4

    (with simulation application) Markov Processes 2

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    Evaluation Pedagogy

    End-Term Exam ... 50%

    Attendance ... 5%

    Quizzes ... 20%

    Cases/Problems(2 Sessions)... 25%

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    Decision-Making Process Role of Quantitative Analysis in the Decision-Making

    Process:

    Problem

    ExperienceSubjective

    Analysis

    Quantitative

    AnalysisOpinion

    Decision Inputs

    P bl l i P

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    Need

    Recognition

    Problem

    Formulation

    Model

    Construction

    Modeling

    Real System

    Data

    Collection

    Model

    Solution

    Model

    Validation &

    Sensitivity

    Analysis

    Interpretation

    of Results

    Implement-

    ation &

    Control

    System of

    Interest

    Problem-solving Process

    Schematic

    Diagram ofProblem Solving

    Process

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    Stages of Problem-Solving Process

    Green, Lee and Newsom classify problem-solving process into

    three major stages:

    Pre-modeling function

    Modeling function

    Implementation (Post-modeling)function

    These stages can be further mapped onto an eight-step process:Pre-modeling:

    Recognition of Need

    Problem Formulation

    Systems Approach Controllable & Uncontrollable variables

    Parameters

    Constraints

    Objective Function

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    Objectives,Criteria and Surrogates

    Objective: The ultimate desired goal. In DMM we use the

    term objective function. Surrogates: To say the company has to perform better is a

    qualitative criterion or objective. But it has to be broken

    into measurable surrogates - Market Share; Profit after

    Tax, ROR etc.,

    To say the standard of living of an individual is to be

    improved is a qualitative criterion. It is to be broken to

    surrogates such as: Income; growth in income; amount of

    spending; amount of savings etc.,

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    Stages of Problem-Solving Processcontd.

    Modeling

    Model Construction - Mathematical Models Data Collection - MIS; Databases; Decision-

    Support systems

    Model Solution(Have alternatives)- OR Models

    Model Validation and Sensitivity Analysis(Optimizing/Satisficing)

    Post-Modeling

    Interpretation of Results and Implication- Selling yourideas

    Implementation, and Control - HRD Issues

    Doing

    Decision making

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    MODEL BUILDING A MODEL is a representation of reality intended to

    explain the behaviour of some aspect of it.

    Taxonomy of Models: Normative & Descriptive

    Normative models tend to prescribe what oughtto be:

    Physicians possess a normative model of health

    Civil Engineers possess a normative model of a building

    Philosophers have a code of conduct for ethics

    Descriptive Models describe facts and relationships:

    Physician conducting tests and analyzing the results to determine

    the ailment

    A civil engineer analyzing the soil conditions and other parameters

    to decide on the type of structure

    Constructing a physical scale model to give the projected view

    of the final structure/equipment/device.

    Analyzing what-if situations in a management problem solving.

    In DMM we are concerned with descriptive models.

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    MODEL BUILDING SIMULATION MODELS

    SIMULATION is one of the key techniques of DMM. It

    involves construction of a mathematical model of theproblem; and imitate (simulate) the operation of the

    system.(System modeling & simulation is an elective

    course in VI term)

    E.g: Simulation of an airplane flight in a wind tunnel

    Simulation of the traffic in traffic junction

    Simulation of customer servicing in a service counters

    Simulation of production - in a manufacturing situation.

    Simulation modeling process helps to understand andanalyze the various alternatives, over pre-determined time

    periods, without physically operating or modifying the

    system.(we will learn more about it under simulation)

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    PROBLEM SOLVING FRAMEWORK

    1. Verbal Statement of the Problem

    2. Decisions:

    * Verbal Statement

    * Mathematical Definition

    3. Criteria

    * Verbal Statement

    * Mathematical Definition

    4. Constraining Conditions

    * Verbal Statement

    * Mathematical Definition

    5. Mathematical Model

    6. Model Outcomes

    7. Interpretation of the Results

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    CLASSICAL DETERMINISTIC

    MODELS

    Decision Models for Management

    E f U i P bl S l i F k

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    E.g. of Using Problem Solving FrameworkIn-house Computer -vs.- Service Bureau Decision

    A large poly-clinic has 30 full-time and visiting doctors.Currently all billing is done manually by clerks. Due to

    the heavy volume of billing, the hospital managementwishes to computerise the billing operation. It has 2options: (1) To buy a computer and carry-out the billing byitself (the make/own option). Or (2) To contract with anagency that would do the operations (the buy/lease option)

    Cost Data: The company can lease a small p.c. and therequired software at Rs. 15000 per year. The variable costof doing the billing in this manner is 0.65 paise per bill.

    Alternatively, the company can sub-contract the operation

    to an outside agency, who would charge Rs. 3000 fixedcharges per year and 0.95 paise per bill processed.

    The company would like to know the critical patient volume tomake a decision on make-or buy. (this is also a deterministic

    decision making problem)

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    Mathematical Representation of Relationships

    Assumptions:

    Criteria are used to make decisionsThey are quantifiable and can be represented by

    mathematical functions

    Such mathematical problems are solved by using Algebra,

    Simultaneous Equations; Differential Calculus etc.,Functional Notation: A functionis a mathematical

    relationship for which the value of a particular variable is

    determined from the values of one or more other variables.

    Y = f(x) is a general representationY = 5x is a specific case.

    Similarly Y = f(x1,x2,x3) is general and

    Y = 3x1 + 2x2 + 6x3 is specific.

    A l i h F k

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    Applying the Framework

    1. Verbal Statement of the Problem:

    Determine the number of patient-bills, (contrast with no. ofpatients) beyond which the make option is less costly.

    2. Decisions:

    a. Verbal Statement: Number of patient bills per year

    b. Mathematical Definition: Let x = no. of patient bills/yr.

    3. Criteria: There are no optimizing criteria. Find out thatnumber of patient bills at which the annual costs of makeor buy are equal.

    4. Constraining Conditions:

    The critical point beyond which the lease option is lesscostly is known as break-even pointfor the two options

    A l i h F k

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    Applying the Framework

    a. Verbal Statement: The annual cost of agency equalsannual cost of in-house operation

    b. Mathematical statement: To find a value for x such thatOwn Cost: 15000 + 0.65 x

    Sub-contract: 3000 + 0.95 x

    5. Model: Solve for x, where :

    3000 + 0.95x = 15000 + 0.65x6. Model Outcomes:

    the value of x = 40000

    7. Interpretation of the results:

    If the break-even number of patient bills = 40000. Hence,if the number is expected to be more than 40000, doingbilling on our own is cheaper. If the bills number is lessthan 40000, it is cheaper to sub-contract the operation.

    Are both equal

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    Single Product Pricing Problem (Deterministic

    Problem; Using problem solving framework)

    The Massachusetts Bay Transit Authority (MBTA) wishes

    to smooth its demand for subway services. The system

    operates to full capacity during the early morning and later

    afternoon rush hours. The MBTA wants to stimulate

    greater demand during off-peak hours and to encourage

    riders who do not need to travel during peak hours to travelat other times.

    Currently the normal fares are 75 during normal hours

    and 30 during off-peak hours. The demand function is

    estimated from data gathered with demand at differentfares. p = off-peak fare; q = off-peak demand (000s of

    passengers)

    p = 70 65 60 55 50

    q = 10.0 12.6 14.9 17.4 20.1

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    Single Product Pricing Problem contd

    Initial attempt was to fit a least-squares regression line:

    q = 45 - ()p or p = -2q + 90

    If the objective is to maximize demand for off-peak hours,

    this would suggest eliminating such fares, and demand

    would be 45,000 passengers.

    But if we derive that the revenue is TR = q * p, then

    TR = f(p) = 45p - p2/2

    This would yield maximum revenue when p = 45.

    And the revenue for this is: 1012.5, and substituting this in

    the regression formula:q = 45 - ()45 = 22.5 or 22500 passengers.