MGMT 333 Lecture Notes - Lecture 3: Yield Management, Standard Deviation
19 Oct 2016
School
Department
Course
Professor
Document Summary
You use mad, mse, mape, then find best combination. Look how demand falls and then in period 5 demand went up! High alpha reacts, small alpha reduces response rate. Markets that would use a high alpha volatile. With linear regression you can forecast over more periods, you can forecast half of your data out into the future. *seasonal index: the ability to pick up on seasonality, so you can adjust your forecast. The average demand over time then compare periods to. Identify average demand over time: find the percentage of average demand that your satisfying each month, use index to plot a linear trend, (need more than one year of sales) You must manually do this or you lose product and sales! *tracking signal: tells you if forecast is still relevant. If it is unbiased it will be around the center line. The idea is balance; how much we have vs. how much we make.
