Solita developed a data science method in the N4S-program that helps the sale of different magazines increase by nearly a third.
IT company Solita, specialized in data analytics, developed a method where the magazine sales are forecasted based on other similar magazines in similar magazine sales points. With this method, it is also possible to predict the sales numbers for a new magazine if it were added to the assortment.
Selecting the product assortment for sales outlets is challenging work. Traditionally, the purchase decision is based on experience and categorization of the products according to their expected target audiences. However, it is nearly impossible to know in advance how many copies of a certain product will be sold. This is particularly difficult when the assortment consists of periodical products, such as magazines. Should there be one or a hundred copies of some particular magazine? Is it a good idea to sell another particular magazine at all?
If there are 1,500 items in the product assortment for the supply chain, what should be selected if there is only space for 250 products? Using Solita’s method, it is possible to predict the future sales of the magazine.
“The method can predict new products for the assortment with moderate success. Preliminarily it would seem like the magazines found with this method should be added to the assortment. If, simultaneously, the same magazine is removed from a poorly selling sales outlet and the sales are compared, the sales increase by 29 %. The assortments are already highly optimized. Our approach serves as a good addition, as the model is completely different from the current ones,” states Senior Software Designer Timo Lehtonen, developer of the method. Read the rest of Timo Lehtonen’s interview here: http://n4s.dimecc.com/2015magazine/article16/