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Demand Forecasting, Time Series Model, Moving Average and Weighted Moving Average
What is a demand forecast?
the estimate of expected demand during specified future period of time
What are the 4 features common to ALL forecasts?
Forecasts closer to accuracy in groups rather than individual items
Forecasts tend to be less accurate the further the date is out
Forecasts tend not to be perfect, make room for inaccuracies
forecasting techniques assume that was has happened in the past will continue to exist in the future
What is the defnition of a “Time Series”?
A Time Series is a timed ordered sequence of observations taken at regular intervals over a period of time.
In demand forecasting, what are the 6 time series models ? describe each?
level - consistent
trend - upward or downward movement
seasonality - weather and holidays/halloween
cycles - trends that come and go (can last a year for example)
irregular variation - one time situation that doesn’t happen regularly - covid/earthquake
random variation - when all other things are accounted for, the remaining (noise)
What are the 3 key factors to take into consideration for forcasting?
cost - how much will it cost
accuracy - more accurate the more costly it will be
time horizon - is there historical data available? how reliable is it?
Why are averaging methods used?
are used when historical data typically contain a certain amount of random variation that tends to obscure systematic movements in the data.
The Averaging techniques smooth fluctuations in a time series because the individual highs and lows in the data offset each other when they are combined into an average = create more clarity.
Moving Average definition
technique that averages a number of recent actual values as forecast for the current period. It is updated as new values become available
Weighed moving average
a variation of moving average where more recent values in the time series are given larger weight in calculating a forecast