• Fast fashion with short time-to-market
  • Forecast before pre-orders
  • Budget and top/flop curve based
  • User panel ranks the collection
  • Combines statistics with expert knowledge
  • Cleanup of the collection
  • Improves early forecast accuracy up to 50%


  • Collections contain new seasonal items
  • No sales yet on new style/colors, statistical algorithms do not work
  • Unique A3-algorithm using actual buying behavior
  • Accurate forecast during sell-in
  • Evaluates returning, new and lost customers
  • Ability to forecast different account types and channels

Core collection

  • Uses historic sales data: wholesale orders or POS
  • Automatic recognition of sales pattern and seasonality
  • Suggests 'best fit' algorithm and possibility for 'what-if' review
  • Management by exception for large assortments
  • Forecast in multiple dimensions: units, value, volume or weight
  • Supports new product forecasting and expiring products
  • Seasonality recognition ensures optimal availability throughout the year

size split

  • Per style/color
  • Separate size split of pre-order, re-order and total-order
  • Rolling analysis of demand per SKU
  • Optimal size split per article group
  • Easy assignment of size split for new products
  • Different size splits for different channels

Buying &

  • Automatic integration of all relevant data: forecast, stock, purchases, sales and deliveries
  • Dynamic safety stock based on forecast accuracy, service level and replenishment time
  • Automatic purchase advise takes into account supplier, lead time and logistic constraints
  • Optimal product availability on size level against lowest cost
  • More service + less stock = more profit