HS.Forecast

Thanks to state-of-the-art Machine Learning Algorithms, HS.Forecast web platform is specialized in predictive and forecast analytics for the fashion industry. All for the unparalleled optimization of your business processes.

A reliable guide to optimize purchasing, distribution and restocking

HS.Forecast is a web platform that exploits cutting edge Artificial Intelligence (AI) algorithms for predictive analytics, tailored for the fashion industry.

Using HS.Forecast, fashion companies can reliably optimize their production, distribution and restocking processes. This is possible thanks to accurate predictions of demand patterns, enabling efficient resource allocation and minimizing inventory waste. The platform leverages historical data and market trends to generate precise forecasts, empowering companies to make informed decisions and stay one step ahead of the competition.

The platform is designed in three separate modules, each one specialized in managing a different business process. For this reason, each module can also be installed separately.

MODULE Production / Purchasing / Demand Forecasting

This module deals with long-term (6 months/1 year) forecasting (AI forecasting) for the production or purchase of items. In this section of the platform, AI can be queried to make long-term sales forecasts on both continuous items and seasonal items. In addition to making the sales forecast, the AI already proposes a possible sales breakdown by category, color, size and store. At this stage, AI can also point out any anomalies (low coverage) and suggest order proposals.

MODULE Distribution / First Planting / Delivery Forecasting

The Delivery module deals with forecasting (AI forecasting) to distribute references to stores and carry out initial implantation. The process can be managed through optimization logics that operate at both the store and individual SKU level. In the first case: given a store, the AI proposes how to plant all selected items on that store. In the second case: given a SKU, the AI proposes how to implant that single SKU (by color/size) on all selected stores.

MODULE Reassortments / Rebalancing / Replenishment Forecasting.

The replenishment module deals with short-term (1 week) forecasting (AI forecasting). In this case, artificial intelligence analyzes stock availability for each individual reference and calculates the exact quantities to be restocked for each store and each size based on sales forecasts in the following weeks. In addition, this module can handle rebalancing of merchandise between stores, taking advantage of sales forecasts on individual stores.

Case study

Doppelgänger

Doppelgänger is a fashion brand that was founded in 1996, carefully follows the production chain and makes men's clothing collections.

Problem: Being able to make business processes more efficient to cope with the increase in outlets (more than 100 throughout Italy plus e-commerce) and customer demands
Solution: HS.Forecast, integrated with corporate ERP for purchasing, plant, and replenishment management, enabled implementation along the entire AI in supply chain

Efficiency: most of the work is done automatically by the AI, which communicates with ERP and company management
Accuracy: forecast error reduced by 60% compared to traditional supply chain logic