First Allocation - Comparable

A Comparable is a reference used to forecast another reference for buying or for first allocation.

In order to have the most accurate first allocation, a forecast is needed, but in most cases there is no historical sales data as they are new references, so we need to find other references that will help us guess future sales and stock needs of the new reference.

The "quality" of these comparable items is very important, and therefore, they must be revised and adjusted to improve the forecast that will be calculated.

Criteria to assign comparables

The comparable proposal is made with data criteria (colour, price, name, etc.) that, together with the buyer’s knowledge, will improve the result and the forecast. Following, we will detail how an automatic proposal is made by Nextail’s algorithm:

1. Definition of product features: Name, style, price (range), family, gender and season are considered standard features by Nextail but other categories from the product master could be used.
2. Creation of comparability matrix: the algorithm assigns values for all products that present those similar features.
3. Calculation of comparability coefficients:  the comparability coefficient of each product is based on the features it shares with the product to be assigned as its comparable. The more features they share between them, the higher the coefficient will be.
4. Creation of comparable categories: every product will be assigned a comparable category containing the products with the highest comparability coefficients made in the previous step. The number of items assigned to every comparable category is customizable and ranges from 0 to 100.

The forecast will be calculated whether by the first X weeks of sales (of comparables) or by the 3 best weeks of sales (of comparables).