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Spreadsheet Modeling
& Decision Analysis
A Practical Introduction to
Management Science
5th
edition
Cliff T. Ragsdale
Introduction to Modeling
& Problem Solving
Chapter 1
Introduction
 We face numerous decisions in life &
business.
 We can use computers to analyze the
potential outcomes of ...
What is Management Science?
 A field of study that uses computers,
statistics, and mathematics to solve
business problems...
Home Runs
in Management Science
 Motorola
– Procurement of goods and services
account for 50% of its costs
– Developed an...
Home Runs
in Management Science
 Waste Management
– Leading waste collection company in North
America
– 26,000 vehicles s...
Home Runs
in Management Science
 Hong Kong International Terminals
– Busiest container terminal in the world
– 122 yard c...
Home Runs in
Management Science
 John Deere Company
– 2500 dealers sell lawn equipment &
tractors with support of 5 wareh...
What is a “Computer Model”?
 A set of mathematical relationships and
logical assumptions implemented in a
computer as an ...
The Modeling Approach
to Decision Making
 Everyone uses models to make
decisions.
 Types of models:
– Mental (arranging ...
Characteristics of Models
 Models are usually simplified versions of
the things they represent
 A valid model accurately...
Benefits of Modeling
 Economy - It is often less costly to
analyze decision problems using
models.
 Timeliness - Models ...
Example of a Mathematical Model
Profit = Revenue - Expenses
or
Profit = f(Revenue, Expenses)
or
Y = f(X1, X2)
A Generic Mathematical Model
Y = f(X1, X2, …, Xn)
Y = dependent variable
(aka bottom-line performance measure)
Xi = indepe...
Mathematical Models & Spreadsheets
 Most spreadsheet models are very similar
to our generic mathematical model:
Y = f(X1,...
Categories of Mathematical Models
Prescriptive known, known or under LP, Networks, IP,
well-defined decision maker’s CPM, ...
The Problem Solving Process
Identify
Problem
Formulate &
Implement
Model
Analyze
Model
Test
Results
Implement
Solution
uns...
The Psychology of Decision Making
 Models can be used for structurable
aspects of decision problems.
 Other aspects cann...
Anchoring Effects
 Arise when trivial factors influence initial
thinking about a problem.
 Decision-makers usually under...
Framing Effects
 Refers to how decision-makers view a
problem from a win-loss perspective.
 The way a problem is framed ...
Framing Effects (Example)
 Now suppose you’ve been given $2000
and must choose between:
– A. Give back $500 immediately
–...
A Decision Tree for Both Examples
Initial state
$1,500
Heads (50%)
Tails (50%)
$2,000
$1,000
Alternative A
Alternative B
(...
Good Decisions vs. Good Outcomes
 Good decisions do not always lead to good
outcomes...
 A structured, modeling approach...
End of Chapter 1
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Introduction to Decision Science

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Introduction to Decision Science

  1. 1. Spreadsheet Modeling & Decision Analysis A Practical Introduction to Management Science 5th edition Cliff T. Ragsdale
  2. 2. Introduction to Modeling & Problem Solving Chapter 1
  3. 3. Introduction  We face numerous decisions in life & business.  We can use computers to analyze the potential outcomes of decision alternatives.  Spreadsheets are the tool of choice for today’s managers.
  4. 4. What is Management Science?  A field of study that uses computers, statistics, and mathematics to solve business problems.  Also known as: – Operations research – Decision science
  5. 5. Home Runs in Management Science  Motorola – Procurement of goods and services account for 50% of its costs – Developed an Internet-based auction system for negotiations with suppliers – The system optimized multi-product, multi- vendor contract awards – Benefits: $600 million in savings
  6. 6. Home Runs in Management Science  Waste Management – Leading waste collection company in North America – 26,000 vehicles service 20 million residential & 2 million commercial customers – Developed vehicle routing optimization system – Benefits: Eliminated 1,000 routes Annual savings of $44 million
  7. 7. Home Runs in Management Science  Hong Kong International Terminals – Busiest container terminal in the world – 122 yard cranes serve 125 ships per week – Thousands of trucks move containers in & out of storage yard – Used DSS to optimize operational decisions involving trucks, cranes & storage locations – Benefits: 35% reduction in container handling costs 50% increase in throughput 30% improvement in vessel turnaround time
  8. 8. Home Runs in Management Science  John Deere Company – 2500 dealers sell lawn equipment & tractors with support of 5 warehouses – Each dealer stocks 100 products, creating 250,000 product-stocking locations – Demand is highly seasonal and erratic – Developed inventory system to optimize stocking levels over a 26-week horizon – Benefits:  $1 billion in reduced inventory  Improved customer-service levels
  9. 9. What is a “Computer Model”?  A set of mathematical relationships and logical assumptions implemented in a computer as an abstract representation of a real-world object of phenomenon.  Spreadsheets provide the most convenient way for business people to build computer models.
  10. 10. The Modeling Approach to Decision Making  Everyone uses models to make decisions.  Types of models: – Mental (arranging furniture) – Visual (blueprints, road maps) – Physical/Scale (aerodynamics, buildings) – Mathematical (what we’ll be studying)
  11. 11. Characteristics of Models  Models are usually simplified versions of the things they represent  A valid model accurately represents the relevant characteristics of the object or decision being studied
  12. 12. Benefits of Modeling  Economy - It is often less costly to analyze decision problems using models.  Timeliness - Models often deliver needed information more quickly than their real-world counterparts.  Feasibility - Models can be used to do things that would be impossible.  Models give us insight & understanding that improves decision making.
  13. 13. Example of a Mathematical Model Profit = Revenue - Expenses or Profit = f(Revenue, Expenses) or Y = f(X1, X2)
  14. 14. A Generic Mathematical Model Y = f(X1, X2, …, Xn) Y = dependent variable (aka bottom-line performance measure) Xi = independent variables (inputs having an impact on Y) f(.) = function defining the relationship between the Xi & Y Where:
  15. 15. Mathematical Models & Spreadsheets  Most spreadsheet models are very similar to our generic mathematical model: Y = f(X1, X2, …, Xn)  Most spreadsheets have input cells (representing Xi) to which mathematical functions ( f(. )) are applied to compute a bottom-line performance measure (or Y).
  16. 16. Categories of Mathematical Models Prescriptive known, known or under LP, Networks, IP, well-defined decision maker’s CPM, EOQ, NLP, control GP, MOLP Predictive unknown, known or under Regression Analysis, ill-defined decision maker’s Time Series Analysis, control Discriminant Analysis Descriptive known, unknown or Simulation, PERT, well-defined uncertain Queueing, Inventory Models Model Independent OR/MS Category Form of f(.) Variables Techniques
  17. 17. The Problem Solving Process Identify Problem Formulate & Implement Model Analyze Model Test Results Implement Solution unsatisfactory results
  18. 18. The Psychology of Decision Making  Models can be used for structurable aspects of decision problems.  Other aspects cannot be structured easily, requiring intuition and judgment.  Caution: Human judgment and intuition is not always rational!
  19. 19. Anchoring Effects  Arise when trivial factors influence initial thinking about a problem.  Decision-makers usually under-adjust from their initial “anchor”.  Example: – What is 1x2x3x4x5x6x7x8 ? – What is 8x7x6x5x4x3x2x1 ?
  20. 20. Framing Effects  Refers to how decision-makers view a problem from a win-loss perspective.  The way a problem is framed often influences choices in irrational ways…  Suppose you’ve been given $1000 and must choose between: – A. Receive $500 more immediately – B. Flip a coin and receive $1000 more if heads occurs or $0 more if tails occurs
  21. 21. Framing Effects (Example)  Now suppose you’ve been given $2000 and must choose between: – A. Give back $500 immediately – B. Flip a coin and give back $0 if heads occurs or give back $1000 if tails occurs
  22. 22. A Decision Tree for Both Examples Initial state $1,500 Heads (50%) Tails (50%) $2,000 $1,000 Alternative A Alternative B (Flip coin) Payoffs
  23. 23. Good Decisions vs. Good Outcomes  Good decisions do not always lead to good outcomes...  A structured, modeling approach to decision making helps us make good decisions, but can’t guarantee good outcomes.
  24. 24. End of Chapter 1

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