INTRODUCTION
▪What
is management science
▪Historical development of management science
▪Characteristics of management science
▪Tools of management science
▪Managerial decision making
▪Areas of application
MANAGEMENT SCIENCE
Management science is the
application of scientific method,
techniques, tools to problems
involving the operations of systems
so as to provide those in control of
operation with optimum solution to
problems
MANAGEMENT SCIENCE
Application of the scientific
method to analysis and
solution of managerial
decision making problems
CHARACTERISTICS OF MANAGEMENT SCIENCE
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Focus on managerial decision making
Application of the scientific approach to
managerial decision making
Examination of decision situation from a
broad perspective
Interdisciplinary methods and knowledge
Reliance on mathematical and quantitative
models
Extensive use of computers
Problems and decisions are viewed from
system perspective
HISTORICAL DEVELOPMENT OF MANAGEMENT SCIENCE
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Scientific Management by F. W. Taylor in
late 19th century
Use of math models
Cross fertilization in science
Wartime use to industry
Public sector decision making
Operational efficiency
THE ROLE OF MANAGEMENT SCIENCE
Prognosis
Diagnosis
Solution
Management
Scientist as
Consultants/Staff
Assistant
THE TOOLS OF MANAGEMENT SCIENCE
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Standard tools for recurring decision
Linear programming, Integer
programming, dynamic programming
Borrowed tools
Statistical tools, forecasting, financial,
marketing, econometrics
Special tools for unique problems
Simulation
BENEFITS OF MANAGEMENT
SCIENCE
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Systematic approach to decision making
Promote communication through experts
Permits thorough analysis of a large number of
alternative options
Evaluates situations with risk
Increase effectiveness in decision making
Quick and inexpensive explanation of alternatives
Allow simulate the practical environment
AREAS OF APPLICATION OF MANAGEMENT SCIENCE
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Inventory control
Facility design
Product mix determination
Portfolio analysis
Scheduling and sequencing
Merger-growth analysis
Transportation planning
Design of information systems
Allocation of scare resources
Project planning and control
Pricing decisions
Credit policy analysis
Management Science Process
Management Scientist
Manager
Real Life
Problem
1. Definition of
the Problem
2. Classification
and
Conceptualization
of the Problem
3. Formulation and
construction of the
mathematical model
6.
Implementation
Y
N
Evaluation:
Is solution
implementable
5. Sensitivity
Analysis
4. Solution of
the model
Management Science Process
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Identification of the problem
Classification and conceptualization of the problem
Model Formulation
Solution of the model
Sensitivity Analysis
Implementation of the model
Step 1
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Symptom VS causes
Collection od data
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Time
Subjective approach-OPM
Future condition
Step 2
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Programed and non-programmed
Deterministic and Probabilistic problem
State of certainty and uncertainty
Step 3
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Types of model-Iconic, Analog, Mathematical, Static
and dynamic model.
Model formulation
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Component of the model
The result variable/Dependent variables
Decision Variables (manipulable and controllable
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Analytical and numerical model
Analytical model for direct result
Numerical model –trial and error, step by step improvement
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Mathematical relationship-objectives and constraint
Validity of the model
Step 4
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Choice of a solution-optimization and sub-optimization
Select alternatives
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Generate alternatives
Predict outcome of each alternatives
Relate outcome to goal
Compare the alternatives
Select the best alternatives
Classification of solutions
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Feasible and infeasible
Optimum and non-optimum
Unique and multiple
Step 5
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Change the variables’ parameter to see the new
result
Step 6
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Evaluation and Implementation