Target Brands, Inc.

Saibal Bhattacharya

Luyen Le

Zeynep Erkin Baz

Tikhon Jelvis

Sayon Majumdar

James Gaynor

Elif Tokar-Erdemir

Brian Wongchaowart

Duane Sizemore

Hamidreza Badri

Adam Riggall

Peter Kim

Xiao Pu

Omar N Jabri

Yang Liu

Methods and systems for forecasting demand for items across multiple channels are disclosed. In some implementations, multi-channel demand forecasting may be performed on a per-item, per-location basis, by selectively generating item-location forecasts for each item and location within a supply chain for each channel, or disaggregating a chain level forecast on a per-item basis to each location. Particular selection of an appropriate model, and selective training of models, allows for efficient computation of such forecasts across a large supply chain with thousands of locations and hundreds of thousands, or millions, of items for which forecasts are generated.

Multi-channel demand planning for inventory planning and control

Methods and systems are described for optimizing markdown schedules for clearance items at physical retail stores. For example, price sensitivity of a current inventory item at a physical retail store may be modeled using techniques that account for differences in operating behavior and data availability at physical stores versus online channels for selling items. When the current item is placed on clearance at the physical retail store, a request for a markdown schedule, including goals for the clearance, may be received. The forecasted price sensitivity of the current item may be adjusted based on actual price sensitivity of one or more past clearance items (e.g., based on actual clearance sales data) determined to match the current item. An optimal markdown schedule for the item may then be determined based, at least in part, on the adjusted price sensitivity of the item and clearance goals.

Optimization of markdown schedules for clearance items at physical retail stores

Methods and systems for generating an optimal clearance schedule for inventory items in a retail enterprise. A method includes accessing historical sales data for a plurality of inventory items in a department of a retailer. A selection of an item is received and a set of possible discount schedules for the item are generated. Each schedule includes a set of prices and a price duration. A forecasting tool provides a sales performance of the item based on the historical sales data. An optimal clearance schedule is selected from the possible discount schedules.

Method and system for managing clearance items

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San Mateo, CA, United States of America

Saibal Bhattacharya