Q1. Why is a liquidation clean-up required?
IRIS aims to improve the Full Price Sell Thru of brands by betting higher on the products that sell at lower discounts and reducing the contribution of the styles that sell well only on discount.
Q2. Will IRIS provide intelligence for categories, attribute groups, etc which does not have any historical data?
No, IRIS won’t be able to provide intelligence for new categories without any historical Sales/Inventory data.
However, for the new attribute groups, IRIS can predict the ideal size set and do the distribution (allocation/replenishment) based on the historical performance of similar products
Q3. How does IRIS calculate the true rate of sale?
By removing the days with stock out/ highly broken inventory for every Store + Style combination, IRIS identifies the actual live days and calculates the true rate of sale that can be compared across Styles.
Q4. Can IRIS predict the actual Revenue/ Sales quantity?
No. IRIS currently takes the revenue targets at Store level as input from the Brand/ Retailer and breaks it down into an ideal inventory mix across Attribute Groups for each Store.
Q5. Can IRIS predict buy separately for our A+, A, B & C grade stores?
IRIS does not work on the grouping of stores. It predicts the assortment and buys by treating each store separately. Brands can then further group the stores on their own to look at the buy at whichever level they wish to.