PPT-Session 9b Decision Models -- Prof. Juran

2 Overview Finance Simulation Models Securities Pricing BlackScholes Electricity Option Miscellaneous Monte Carlo vs Latin Hypercube Review of Binomial Decision Models Prof Juran. Decision Models -- Prof. Juran. 2. Overview. Monte Carlo Simulation. Basic concepts and history. Excel Tricks. RAND(), IF, Boolean. Crystal Ball. Probability Distributions . Normal, Gamma, Uniform, Triangular. Decision Models -- Prof. Juran. 2. Overview. Finance Simulation Models. Forecasting. Retirement Planning. Butterfly Strategy. Risk Management. Introduction to . VaR. Currency Risk. Using . Historical Data in Simulations. Decision Models -- Prof. Juran. 2. Overview. Multiple Objective Optimization. Two Dimensions. More than Two Dimensions. Finance and HR Examples. Efficient Frontier. Pre-emptive Goal Programming. Intro to Decision Analysis. Decision Models -- Prof. Juran. 2. Overview. Sensitivity Analysis. Goal Seek and Data Table. Marketing and Finance examples. Call Center LP. More Sensitivity Analysis. SolverTable. Decision Models -- Prof. Juran. Decision Models -- Prof. Juran. 2. Overview. More Sensitivity Analysis. Solver Sensitivity Report. More Malcolm. Multi-period Models. Distillery Example. Project Funding Example. Decision Models -- Prof. Juran. Decision Models -- Prof. Juran. 2. Overview. More Network Flow Models . Assignment Model. Traveling Salesman Model. Decision Models -- Prof. Juran. 3. Professor Scheduling Example. Three professors must be assigned to teach six sections of finance. . Decision Models -- Prof. Juran. 2. Overview. Multiperiod Models. Data Processing at the IRS . Arbitrage with Bonds. Transportation Models. Gribbin Brewing . Decision Models -- Prof. Juran. 3. IRS Example. Decision Models -- Prof. Juran. 2. Overview. Portfolio Optimization. Parametric Approach. Array Functions. Scenario Approach. Put Options. Shorting. Decision Models -- Prof. Juran. 3. 4 Basic Matrix Operations. Decision Models -- Prof. Juran. 2. Example: Preventive Maintenance. At the beginning of each week, a machine is in one of four conditions: 1 = excellent; 2 = good; 3 = average; 4 = bad. . The weekly revenue earned by a machine in state 1, 2, 3, or 4 is $100, $90, $50, or $10, respectively. . Decision Models -- Prof. Juran. 2. Overview. Forecasting Methods . Exponential Smoothing. Simple. Trend (Holt’s Method). Seasonality (Winters’ Method). Regression. Trend. Seasonality. Lagged Variables. Decision Models -- Prof. Juran. 2. Overview. Evolutionary Solver. (Genetic Algorithm). Advertising Example. Product Design Example. Conjoint Analysis. Decision Models -- Prof. Juran. 3. Nonlinear Problems. 2. Overview. Sensitivity Analysis. Goal Seek and Data Table. Marketing and Finance examples. Call Center LP. More Sensitivity Analysis. SolverTable. Decision Models -- Prof. Juran. 3. Sensitivity Analysis. 2. Overview. Monte Carlo Simulation. Basic concepts and history. Excel Tricks. RAND(), IF, Boolean. Crystal Ball. Probability Distributions . Normal, Gamma, Uniform, Triangular. Assumption and Forecast cells. Session 10b Decision Models -- Prof. Juran 2 Overview Marketing Simulation Models New Product Development Decision Uncertainty about competitor behavior Uncertainty about customer behavior Market Shares