Seasonal factors measure the average ratio of monthly data to the corresponding underlying trend value. They are important in the following areas:
- Adjustment of historical data before the fitting of trend models
- Calculation of monthly forecasts corresponding to projected trend values
- Re-phasing of existing monthly forecasts
Seasonal factors may be maintained by
- Using statistical analysis of historical actual demand data
- Manual editing via Edit Seasonal Factors
Seasonal factor codes may be created for any combination of items at any level of detail.
- From IFP Home select Forecasting > Seasonal Factors Estimation
- Select the actual demand data that you wish to use for calculation of seasonal factors. This should include at least two years.
- Select Item Type 01 (Sales), seasonal factors estimation should not include the effects of sample movements or free goods
- You are advised to set the Level of Detail to the variable that best defines each product (normally product group/brand) as products belonging to the same brand tend to have similar seasonal patterns.
- The Seasonal Factors Estimation dashboard will then open.
Editing a Set of Seasonal Factors
- Select the item that you wish to update. You may edit the default code if you wish.
- Set the required Estimation Method.
- Select the period to be used.
- Click Re-Estimate. This will then update the seasonal factors based on the new selections made.
- Seasonal factors can then be manually edited using the Seasonal Factors Editor. Note that:
- Calculated factors may be edited to reflect expert opinion
- The average seasonal factor over the year must be 1.0
- Months with higher than average demand have a factor greater than 1
- Seasonal factors are also translated into an equivalent index and as a % of overall total annual demand.
Note: If changes are made to more than one item then click Re-Estimate All and Save All.