Summary
The life cycle settings tab in Forecast Manager allows you to configure what Life Cycle you might want to use for an item. As with forecast, algorithm, seasonality, and other settings, these settings can be inherited throughout your forecast hierarchy.
Life Cycles can be particularly useful for short-lived items, and also when introducing brand new items to create an initial forecast. See the Life Cycle topic.
Settings
Settings for the life cycle are similar to what you see in the Default Life Cycle Settings screen:
Life Cycle Type- Determines the default life cycle type to use.
- None - By default, this is typically "None", meaning no life cycle logic is being applied
- Use Hierarchy Level - Enables life cycles, and allows you to select from whatever auto-generated cycle you wish to use that is between your "Highest" and "Lowest" levels selected in your Global Life Cycle Settings
- Custom - Enables life cycles and allows you to select from one of your custom life cycle profiles.
Life Cycle Start - What trigger should StockIQ use for starting the life cycle?
- Use Algorithm Start Setting - this refers back to whatever forecast start setting is in your Forecast Settings
- From First Sale - Start the life cycle at the first sale.
- From Creation Date - Start the life cycle based on the item's date created in the ERP data feed
- From Product Launch Date - Start the life cycle based on a product launch date you configure (a box will appear to enter the start date)
- From Date First Stocked - Start the life cycle based on the date first stocked for this item-site based on the date in the ERP data feed.
Peak Period Usage - What is your expected peak volume of sales for this item. This is used to set the scale of your life cycle shape, e.g. will it curve up and sell a peak of 10 per month, or 1,000? This sets the start point for your life cycle-generated forecast. If this life cycle is being set at an aggregate level, that peak period usage value will be prorated based on fair share weights down to child items below.
You can leave this field blank if you wish. The peak period usage from your selected life cycle will be used instead if you really have NO idea what your peak period usage is, but this is generally not recommended.
Auto Update Peak Usage From Actuals?- When initially configuring an item to use a life cycle in the Life Cycle Settings tab, one key input is the expected peak usage. After a product has been introduced, StockIQ can compare actual performance on the life cycle curve to expected performance (based on the curve and the peak value), and auto-adjust the peak value to compensate. When enabled, you can then enter after how many periods you want StockIQ to evaluate this. This is particularly helpful on short life cycle items, where you don't have long to forecast the item before it may expire.
Auto-Revert to Stat Model?- Similarly to possibly adjusting the peak usage from actual sales, StockIQ can begin to evaluate accuracy of the life cycle generated forecast versus the statistical model, and when the stat model accuracy is higher than the life cycle model, it will revert to a standard statistical forecast, and disable use of the life cycle for that product. If you enable this option, you can enter after how many periods StockIQ should begin this analysis. This is particularly useful on long life items where you may need the life cycle assistance for the first 3-6 months of a product's life, but afterward, it can be forecasted accurately from demand history.
At End of Life Cycle 'action' - Determines what StockIQ should do at the end of the life cycle. For a long-lived item, you likely want to revert to the standard statistical model. For a short life cycle item, you likely want the StockIQ life-cycle generated forecast to drop to zero by marking it Obsolete, ensuring you will not get further purchase signals for an item that is likely end-of-life.