Demand Planning Class Notes

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  • Topic: Time series analysis, Time series, Moving average
  • Pages : 3 (603 words )
  • Download(s) : 1239
  • Published : April 12, 2013
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Nicole-line breaks mean new slide

important questions
Forecasts are needed to predict demand
all different teams within the company need the forecast
different users have different time requirements and detail reqts you might have to collect more data if you don't have enough cost depends on the scope of the project
need to engage the users, so have to provide a feedback system

The top chart appears to be a ore difficult to forecast but they just narrowed the y axiz

2nd chart down slope is almost random Us treasure bills

Sales of product c chart is probably affected by seasonality

Subjective judgmental approach relies on your personal experience Very biased because it is based on your personal experience and also bc humans have a strong reaction to recent events aggregate-looking at something from a larger picture. Ie not the I phone but all apple products, or not this month but the whole yaet -salespeople bias bc they will predict less sales so that they can meet and exceed the #

Relational approach-you believe there is a reason for things happening, so you look for a causal relationship between demand and the generative factor -factors drive demand
-regression technique -regress causal relationships to several causal factors to I'd relationships or correlation -Downside-need real world data which may be hard to find
hard to find the relationship in real world data

experimental approach

time series approach
-look for patterns in data
-pattern vs noise, and noise is random and has zero average ideally -in real world. Noise is random but probably not with zero mean -time series usually decomposed into different affects (seasonality, tend, noise, etc) d(t) =(L+

back fit your data to see if you have a good forecast

what would you do
1. Plot the data in excel
forecast approaches were in order with charts

moving average-look at last few periods and update each new period with the new data (ie in March use...
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