Many services and products experience seasonal fluctuations. Adjusting uniform demand by a seasonal index ratio ean help forecasters to replicate historical fluctuations. By following the seasonal forecasting steps below, you can create a seasonal forecast. Steps $1$ and $2$ have already been calculated in Table $3.$ Complete steps $3,4,$ and $5$ by filling in the last three columns of Table $3.$

Seasonal forecasting steps

Calculate each seasonal average.

Calculate the overall average for the time horizon.

Calculate each seasonal index ratio by dividing the seasonal average $($#$1)$ by the overall average $($#$2).$

Estimate next horizon's total demand. Divide next horizon's total demand by the number of seasons per horizon $($uniform forecast$).$

Calculate the seasonal forecast by multiplying the uniform forecast $($#$4)$ by the seasonal index $($#$3)$ for each season.

For a creamery, fill in the last three columns of Table $3$ if the estimate for ice cream cakes in the next horizon $($Year $3)$ is $500$ ice cream cakes.

NOTE: If you are unable to select any of the cells toward the right$-$hand side of the table, please click on a cell within the same row on the left$-$hand side of the table and use the 'Tab' key to tab over to the cell you would like to edit.

Table $3.$ Sales for ice cream cakes

$\backslash$table$[[$Quarter$,$Year $1$ Sales,Year $2$ Sales,$\backslash$table$[[$Quarterly$],[$Average$]],\backslash$table$[[$Overall$],[$Average$]],\backslash$table$[[$Seasonal Indices$],[($one decimal place$)]],\backslash$table$[[$Uniform Forecast$],[($whole number$)]]],[$Spring$,60,140,100,100,,],[$Summer$,140,220,180,100,,],[$Fall$,60,100,80,100,,],[$Winter$,40,40,40,100,,],[$Total$,300,500,400,,,]]$