The rate at which fashion designers and clothing retailers adopt new styles picks up every year, so much so that it can cause inventory problems for stores. Merely splitting clothing seasons up into Fall and Winter and Spring and Summer is a thing of the past as practices from fast fashion stores such as H&M, Zara and Forever 21 shake up the traditional model. Forbes noted fast fashion retailers not only sell their clothing for bargain prices, they also have a continuous stream of new offerings going out to stores meaning the supply chain continues to quicken.
In order to stay relevant and in vogue, apparel companies need the assistance of predictive modeling software to anticipate demand and minimize inventory problems.
"Predictive analytics make inventory problems non-issues."
Taking stock of your stock
With trends coming and going out of style at an even faster clip, it's difficult for clothing retailers to get ahead of the curve, according to Apparel. How does a company identify a clothing fad like capes or even which colors will be most popular? On top of that, clothing stores must then rush the orders out for the upcoming trends and get them in store before the designs become passé. This means shops must strike a balance between being out of stock on popular items and being overstocked with a fad that waned.
Predictive modeling tools can make inventory problems non-issues. By analyzing many different sets of data, these solutions give store managers real-time results regarding customer demand and the kinds of styles customers in the shop's region favor. Not only that, predictive analytics also takes shelf space and store layout into account. Forbes noted forecasting solutions can cut down on the amount of unsold items by predicting how much of a particular garment to manufacture so it meets the full demand without going over.
Making for a better and smarter store
Predicative analytics not only gives clothing retailers greater control over their stock, it can also indicate where best to allocate merchandise by determining which garments sell best and where. The software is also able to detect consumer patterns, giving stores the ability to sell customers on complementary items or suggesting they spend more.
Using these software solutions, a retailer may also keep its bottom line from tanking, since stores usually have to take take a loss on overstock.