Introduction to Decision Science
- 1. Spreadsheet Modeling & Decision Analysis A Practical Introduction to Management Science 5th edition Cliff T. Ragsdale
- 2. Introduction to Modeling & Problem Solving Chapter 1
- 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. Example of a Mathematical Model Profit = Revenue - Expenses or Profit = f(Revenue, Expenses) or Y = f(X1, X2)
- 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. 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. 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. The Problem Solving Process Identify Problem Formulate & Implement Model Analyze Model Test Results Implement Solution unsatisfactory results
- 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. 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. 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. 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. 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. 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. End of Chapter 1