Quantitative Techniques

Slides:



Advertisements
Similar presentations
Quantitative Techniques An Introduction
Advertisements

UNIT 1 CONCEPT OF MANAGERIAL ECONOMICS (continue)
UNIT 1 CONCEPT OF MANAGERIAL ECONOMICS (continue)
Introduction to Mathematical Programming
Linear Programming Problem. Introduction Linear Programming was developed by George B Dantzing in 1947 for solving military logistic operations.
Linear Programming. Introduction: Linear Programming deals with the optimization (max. or min.) of a function of variables, known as ‘objective function’,
Linear Programming Problem
Logistics Network Configuration
Session II – Introduction to Linear Programming
INTRODUCTION TO MODELING
Chapter 1 Introduction to Modeling DECISION MODELING WITH MICROSOFT EXCEL Copyright 2001 Prentice Hall.
Chapter 1 Introduction to Modeling DECISION MODELING WITH MICROSOFT EXCEL Copyright 2001 Prentice Hall Publishers and Ardith E. Baker.
Introduction to Management Science. Definition The application of the scientific method to solving managerial decision problems  Usually involves a mathematical.
Operations Management
Model Building and Simulation Chapter 43 Research Methodologies.
Forecasting Meaning: “Forecasting is the systematic attempt to probe the future, so as to recognize problems and opportunities and turn the into plans.
Economics. Contd. Economics is essentially the study of logic, tools and techniques of making optimum use of the available resources to achieve given.
Operational Research & Management By Mohammad Shahid Khan M.Eco., MBA, B.Cs., B.Ed Lecturer in Economics and Business Administration Department of Economics.
Operations Research I Lecture 1-3 Chapter 1
Introduction to Quantitative Techniques
LINEAR PROGRAMMING PROJECT. V.PAVITHRA SUKANYAH.V.K RIZWANA SULTANA SHILPA JAIN V.PAVITHRA.
By Saparila Worokinasih
1 Chapter 1: What is Finance? Copyright © Prentice Hall Inc Author: Nick Bagley, bdellaSoft, Inc. Objective To Define Finance The Value of Finance.
Quantitative Methods of Management
N. Ravichandran February 18, 2007OR: An Introduction Workshop on Operations Research: An Introduction Jointly organized by ORSI Ahmedabad Chapter & Management.
Optimization Techniques Prof. Ajai Jain
Introduction to Operation Research
Industrial Engineering I
So What? Operations Management EMBA Summer TARGET You are, aspire to be, or need to communicate with an executive that does not have direct responsibility.
1-1 Management Science Chapter 1 Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall.
OPERATION RESEARCH MERVE GUL CONTEXT: What is O.R. ? History of Operation Research Necessity of O.R. The Basic Tools Used in O.R. The Seven.
Introduction A GENERAL MODEL OF SYSTEM OPTIMIZATION.
Introduction to Management Science
ECONOMICS IS SCIENCE OF CHOICE.  ECONOMIC AGENTS HAS TO MAKE THE CHOICE : (A) FIRM - PROFIT MAXIMISATION (B) HOUSEHOLD - SATISFACTION MAXIMISATION PROBLEM.
Key terms by Rahul Jain What is Economics? Economics is the social science that studies the production, distribution, and consumption of goods and services.
Quantitative Methods II Operations Research (OR) Management Science (MS) Why? What? How?
Introduction. MS / OR Definition: Management Science (MS) or Operations Research (OR) is the scientific discipline devoted to the analysis and solution.
Prepared by Mrs. Belen Apostol DECISION-MAKING. Decision- Making as a Management Responsibility Decisions invariably involve organizational change and.
Quantitative Techniques. QUANTITATIVE RESEARCH TECHNIQUES Quantitative Research Techniques are used to quantify the size, distribution, and association.
Chapter 1 Introduction n Introduction: Problem Solving and Decision Making n Quantitative Analysis and Decision Making n Quantitative Analysis n Model.
Management Science Helps analyze and solve organizational problems. It uses scientific and quantitative methods to set up models that are based on controllable.
IT Applications for Decision Making. Operations Research Initiated in England during the world war II Make scientifically based decisions regarding the.
1 Optimization Techniques Constrained Optimization by Linear Programming updated NTU SY-521-N SMU EMIS 5300/7300 Systems Analysis Methods Dr.
DEPARTMENT/SEMESTER ME VII Sem COURSE NAME Operation Research Manav Rachna College of Engg.
Introduction to Quantitative Business Methods (Do I REALLY Have to Know This Stuff?)
Research refers to a search for knowledge Research means a scientific and systematic search for pertinent information on a specific topic In fact, research.
LINEAR PROGRAMMING. Linear Programming Linear programming is a mathematical technique. This technique is applied for choosing the best alternative from.
Introduction It had its early roots in World War II and is flourishing in business and industry with the aid of computer.
© 2008 Thomson South-Western. All Rights Reserved Slides by JOHN LOUCKS St. Edward’s University.
Business Management March 2, 2017, Marketing.
Quantitative Methods for Business Studies
Prepared by John Swearingen
Decision Making Reading: pp. 134 – 139.
Operations Research Chapter one.
Introduction to management
Tools for Decision Analysis: Analysis of Risky Decisions
Rough-Cut Capacity Planning in SCM Theories & Concepts
MARKETING REQUIRES MONEY
Linear Programming Dr. T. T. Kachwala.
Introduction to Decision Analysis & Modeling
PURCHASING AND SUPPLY MANAGEMENT
Personal Decision Making
Introduction to operation research
Costing and Finance P R Upadhyay.
Economics for Engineers Economic Decision Making
Concepts and Objectives of Cost Accounting
Course code:- PGPPA2F007T STATISTICAL METHODS AND COMPUTER APPLICATIONS.
MANAGERIAL ECONOMICS INTRODUCTION.
Dr. Arslan Ornek MATHEMATICAL MODELS
Presentation transcript:

Quantitative Techniques

Introduction and Defination :

Quantitative techniques are those statistical and programming techniques, which help decision makers solve many problems, especially those concerning business and industry Quantitative techniques are those techniques that provide the decision makers with systematic and powerful means of analysis, based on quantitative data, for achieving predetermined goals

These techniques involve the use of numbers symbols, mathematical expressions, other elements of quantities, and serve as supplements to the judgment and intuitions of the decision makers

Evolution of Quantitative Techniques :

The utility of quantitative techniques has been realized long ago and the science of mathematics is probably as old as the human society The evolution of industrial engineering, scientific methodologies the were prominent earlier in the natural sciences, were found applicable to management functions-planning, organizing and controlling of operations

19th century, Frederick W. Taylor Proposed an application of a scientific method to an operations management problem- Productivity. Determined that the variable that was significant was the combined weight of the shovel (move) and its load. Henry L. Gantt, devised a chart-to schedule production activities

Classification They can broadly be put under two groups :

1) Statistical Techniques: Which are used in conducting the statistical inquiry concerning a certain phenomenon It includes all the statistical methods beginning from the collection of data till the task of interpretation of the collected data. Collection,Classification,Summarizing, Analyzing , Interpretation of the data .

2) Programming Techniques: Used by many decisions makers in modern times First designed to tackle defense and military problems and are now being used to solve business problems. It includes variety of techniques like linear programming, games theory, simulation, network analysis, queuing theory, and so on

Applications of Programming Techniques: System under consideration are defined in mathematical language: Variable (Factors which are Controlled), Coefficients (Factors which are not controlled). 2) An optimum solutions is determined (Maximizing profit and Minimizing cost) .

Appropriate mathematical expressions are formulated which describes inter-relations of all variables and coefficients. This is known as the formulation of the mathematical model. It describes the technology and the economics of a business through a set of simultaneous equations and inequalities.

Role of Quantitative Techniques :

Quantitative techniques specially operation research techniques have gained increasing importance since world war II in the technology of business administration. These techniques greatly help in tackling the intricate and complex problems of modern business and industry

They provide a tool for scientific analysis They provide solutions for various business problems They enable proper deployment of resources They help in minimizing waiting and servicing cost They enable the management to decide when to buy and how much to buy.

They assist in choosing an optimum strategy They render great help in optimum resource allocation They facilitate the process of decision making Through various quantitative techniques management can know the reaction of integrated business systems

Functions of Quantitative Techniques :

It useful to the production management: selecting the building site for a plant, scheduling and controlling , locating, scheduling and calculating the optimum product-mix It helps the directing authority in optimum allocation of various limited resources viz., men, machines, money, material, time etc…

It equally help the marketing management to determine – distribution points, warehousing should be located, their size, quantity to be stocked choice of customer, optimum allocation of sales budget to direct selling and promotion expenses with consumer preferences

It useful to the personnel management: optimum manpower planning, the number of persons to be maintained on the permanent or full time role, kept in a work pool intended for meeting the absenteeism. It is very useful to the financial management – finding long range capital, determining optimum replacement polices, workout profit plan, estimating credit and investment risk.

Limitations of Quantitative Techniques :

The inherent limitation concerning mathematical expressions High costs are involved in the use of quantitative techniques Quantitative techniques do not take into consideration the intangible factors ie non-measurable human factors. Quantitative techniques are just the tools of analysis and not the complete decision making process

THANK YOU