Forecasting in Item Plan

Overview

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. Here is a breakdown of this article.

• Walkthrough

  • Navigate to Forecast Menu

  • Select Seasonality Method

  • Select Choose Seasonality Groups

  • Select Volume

• Advanced Selections

  • Flow On Order to Receipt

  • Constrain Sales by Inventory

  • Returns Calculations

• Forecasting Algorithms

  • Merchandise Plan Method

  • Sales History Method

  • Sales History - Rolling Weeks Method

Walkthrough

Please see below for a walkthrough of using the forecasting feature in Item Plan.

Navigate to Forecast Menu

1. Navigate to your Toolio - In-Season Planning view 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 your products bulk.

4. Now that the Forecast menu is open, you will see the number of items selected, the time frame selected to forecast and the scenario to forecast to Below that the Forecast Profile can be set to Use Defaults or Override Defaults. Please read more about Forecast Profiles here.

5. Let’s click on the Override Defaults to expose the full menu.

Please see a full breakdown of each selectable field below:

Seasonality Method

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.

• Choosing Sales History will generate a forecast based on the historical trends of the Seasonality Groups you select. This is the preferred method when forecasting core items.

Please see below for more information on the forecasting algorithm for both of these methods.

Choosing Merchandise Plan as your Seasonality Method:

Choosing Sales History as your Seasonality Method:

Seasonality Group

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 Division as an attribute, Toolio will then specifically model the forecast at the Division level from the Seasonality source defined in the previous step. You can choose to add as many or as few attributes as you see fit, depending on the granularity you want the Seasonality curve to match.

When you have selected Merchandise Plan for your Seasonality Method the Seasonality Groups will list any attributes you plan in the Merchandise Plan module.

When you have selected Sales History for your Seasonality Method the Seasonality Groups will list every attribute assigned to your item from Division to SKU.

Volume

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 Custom Time Frame that is best representative for the group of products you are forecasting.

6. 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.

Advanced Selections

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.

Returns Calculations

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 Algorithms

Forecasting Algorithm - Merchandise Plan Method

The forecasting algorithm for Merchandise Plan Method leverages two core concepts, Volume & Seasonality. This approach looks at the penetration of the items you are forecasting to the Seasonality Groups you selected based on your forward plan in your Merchandise Plan module.

For Example:

Forecasting Algorithm - Sales History Method

This approach looks at the penetration of the items you are forecasting to the Seasonality Groups you selected and how they performed in the historical time frame you selected.

For Example:

Forecasting Algorithm - Sales History - Rolling Weeks Method

This approach looks at the penetration of the items you are forecasting to the Seasonality Groups you selected and how they performed in the historical time frame you selected. Historical performance is assessed by looking at a Rolling Average for the time frame, using the trailing X weeks for each weekly forecast in order to smooth out any spikes or dips that may have occurred.

For Example:

Related Articles

Forecast Profiles

Item Plan Reporting

Generating Receipts in Item Plan