ADM 2302: Introduction to Business Decision Models

1
ADM 2302 Introduction to Business Decision
Models

• Management Science (MS)
  Operations Research (OR)
• Quantitative Methods Quantitative
  Analysis (QA)
• Decision Science
• Decision Modeling

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What is Decision Modeling?

• It is the application of a scientific approach to
  solving management problems, in order to help
  managers make better decisions
• Seeks the determination of the best (optimum)
  course of action of a decision problem under the
  restriction of limited resources

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Introduction to Decision Modeling

• Definition of the Problem
• Decision Modeling Approach
• Model Building
• Decision Modeling Techniques
• Origin of Decision Modeling

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Definition of the Problem

• Problems communicated in a vague, imprecise way
• Perform a detailed analysis of the problem ?
  Present recommendation to management
• Determine the appropriate objectives
• Example you have a manufacturing company and you
  want to introduce a new product in the market
• Objective
• constraints

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The Decision Modeling Approach
Defining the Problem
Developing a Model
Acquiring Input Data
Developing a Solution
Testing the Solution
Analyzing the Results
Implementing the Results
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Model Building

• Pick out the Factors available that are important
  for the decision maker
• Decision variables
• Exogenous variables
• Policies and Constraints
• Criteria and Performance measures
• Model Set of relationships

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Model Building (contd)
Performance Measures
Inputs
Output
Variables
Model
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Model Building (contd)

• If you have a decision Problem
• Is Decision Modeling advantageous to solve your
  decision problem?
• If yes
• Choose suitable mathematical techniques
• Choose best parameter in such a way you can get
  the best solution of this method

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Decision Modeling Techniques

• 1. Linear mathematical Programming
• week 1 week 9
• Linear Programming Models
• Graphical Analysis
• Simplex Method
• Minimization Models
• Sensitivity Analysis
• Transportation and Assignment
• Integer Linear Programming
• Binary Integer Programming
• Goal Linear Programming
• Deterministic Techniques

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Decision Modeling Techniques (contd)

• 2. Probabilistic Techniques (week 10 11)
• Probability (Statistics)
• Decision Analysis (ADM2302)
• Game Theory
• Markov Analysis
• Queuing (ADM 3305)
• Simulation (ADM 3305)
• Forecasting (ADM3301/ADM 3307)
• Statistical Quality Control (ADM3301)

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Decision Modeling Techniques (contd)

• 3. Inventory Techniques (ADM3301)
• Certain demand
• Uncertain demand
• 4. Network Techniques (week 12 13)
• Network Flow
• CPM/PERT (Project Scheduling techniques)

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Decision Modeling Techniques (contd)

• 5. Other linear and nonlinear techniques
• Dynamic Programming
• Break-Even Analysis
• Calculus-Based Solution Techniques

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Brief History

• 1916 Gantt Charts (Henry Gantt)
• 1917 Inventory Control (F.W. Harris)
• 1924 Quality Control (Walter Shewhart)
• 1934 Sampling Techniques (L.H.C. Tippet)
• 1947 Linear Programming (Dantzig)
• 1950-1960 Simulation, Queueing Theory (early
  research work in 1909 by Erlang), Decision
  Theory, goal programming, Mathematical
  Programming, Program Evaluation and Review
  Technique (PERT), Critical Path Method (CPM),
  Materials Requirements Planning (MRP)
• 1970 Information System
• 1980 Decision support systems
• 1990 Expert systems, artificial intelligence
• 2000 Smart systems

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Comments

• Decision Modeling techniques can be applied to
  solve problems in a variety of different types of
  organizations
• Government, military, business, health care
• Decision Modeling consists of more than just
  collection of mathematical techniques.
• Involves the philosophy of approaching a problem
  in a logical manner