Q.5 What should L.L.Bean do to improve its forecasting process?
L.L. Bean should follow method of forecasting which is decided according to the type of products they have and they should since the catalogue is seasonal based they could go for seasonality indices as a method
Seasonality Coefficient method:
When there are seasonal patterns in the data, they can be addressed by forecasting methods that use seasonal factors.
The seasonal factor for any period of a year (a quarter, a month, etc.) measures how that period compares to the overall average for an entire year.
Seasonal factor = (Average for the period) / (Overall average)
It is easier to analyze data and detect new trends if the data are first adjusted to remove the seasonal patterns.
Seasonally adjusted data = (Actual call volume) / (Seasonal factor)
Instead of ranking the items which are required they could also go for exponential method of forecasting.
The exponential smoothing with trend forecasting method uses the recent values in the time series to estimate any current upward or downward trend in these values.
Trend = Average change from one time-series value to the next
The formula for forecasting the next value in the time series adds the estimated trend.
Forecast = a (Last value) + (1 – a) (Last forecast) + Estimated trend, a is the smoothing constant between 0 and 1.
Exponential smoothing also is used to obtain and update the estimated trend.
Estimated trend = b (Latest trend) + (1 – b) (Last estimate of trend), b is the trend smoothing constant.
The formula for forecasting n periods from now is
Forecast = a (Last value) + (1 – a) (Last forecast) + n (Estimated trend)
They could compare methods like average, moving average, exponential with MAD and MSE method.
In here average method is suitable for those l.l.bean items where in the the demand is stable and certain like the regular items which they have. And...