The Forecasting function in Toolio's Item Planning module streamlines the sales projection process at the item level. Forecasting is primarily used for creating a demand plan for core / existing products.
Please see below for a walkthrough of using the forecasting feature in Item Plan.
Navigate to your
Toolio - In-Season Planningview in Item Plan. This view will be preconfigured out of the box in your Item Planning module and is designed to help visualize your forecasted sales and inventory values.
2. Using the filter, group, and sort functions, you can easily configure the view to display the products you are interested in forecasting. You will typically want to select your Core / Continuity products at this step.
3. By clicking on any of the checkboxes, you can select the item(s) you would like to forecast. You can then right click and select the Forecast feature which will take you to the Forecast menu.
Please note that you can select and forecast multiple items at once. This may be particularly useful if you want to forecast all products matching a specific attribute in bulk.
4. Now that the Forecast menu is open, you will see that there are 2 distinct sections; Source on the left and Target on the right. On the left hand side, the Source selections is where you will define the Seasonality curve you want your forecast to follow, as well as the Volume input for sales units you would like to feed into the forecast.
Please see a full breakdown of each selectable field below:
This is where you will define the sales curve of your forecast. If you have a Merchandise Plan that accurately projects how you are planning to grow a particular part of the business, you will want to select Merchandise Plan as the Seasonality Method.
The source of your seasonality curve
The time frame you are sourcing from
Same as Target
The scenario from your seasonality method
This is where you can specify attributes to define the scope of your seasonality curve. If you choose to leave attributes blank, your forecast will follow the highest level sales curve from your source.
As an example, if you were to add the Women's division as an attribute, Toolio will then specifically model the forecast at the Women's Division level from the Seasonality source defined in the previous step. You can choose to add as many or as little attributes as you see fit, depending on the granularity you want the Seasonality curve to match.
Now that we have your Seasonality curve fully defined, this is where we will define the input in terms of sales volume for your forecast. This dropdown allows you to select what time frame the sales performance is sourced from. If you are selecting a multiple week period, the average of those weeks will be the Volume input of your forecast.
You can either select the trailing few weeks, or you can select a Customer Time Frame that is best representative for the group of products you are forecasting.
The time frame for which you are building the forecast
Wk1 - Wk52, 2021
The scenario you are outputting the forecast
5. Once you have configured the above steps, you can simply press Forecast and your sales projections (including Sales Cost, Sales Retail, Sales Units and Allowances, i.e. Discount & Markdown) will be generated accordingly. You can always edit these values further and fine tune your forecast as you see fit.
Flow On Order to Receipt
Use Case: Primarily be used for non-replenishment, i.e. seasonal items, and is relevant only if you select `Constrain sales by inventory` as well.
Check this box, if you want to assume on order items as the receipts plan, so that on order will be put into consideration while forecasting sales.
Constrain sales by inventory
Use Case: Primarily be used for non-replenishment, i.e. seasonal items.
This option will suppress your sales forecast based on the inventory and receipts plan.
Toolio provides multiple options for forecasting returns. Below are the options:
Independent: This projects returns independently of the sales, based on the returns seasonality and the recent return data. For core products, this is the ideal selection.
Return Rate: This projects returns as a percentage of sales, based on the return rate data coming in from your merchandise plan.
Forecasting Algorithm leverages 2 core concepts, Volume & Seasonality. The approach looks at the % of TTL each group contributed to in the Time Frame selected in the Volume section, and uses the Seasonality Curve that is coming from the Seasonality selection.
Below is a quick visualization of how the algorithm works