o9 Digital Brain for Softlines

Canadian retail leader operating across automotive, hardware, sports, and leisure.

This retailer needed to reliably predict consumer demand and distribute inventory across the network to effectively and efficiently fulfill that demand.

Sustainability Impact

Improved forecast with reduction in inventory and efficient capacity utilization

Business Scope Challenges

Drivers of Demand

They were lacking the ability to incorporate various external demand drivers spanning weather, demographics, pricing, promotions, product assortment, location etc. to predictably and reliably forecast fashion and seasonal merchandise.


With o9, the company can bring in and model various demand constraints under one platform to drive enhanced AI/ML based forecast for half a million SKUs across 220 brick and mortar stores, as well as E-commerce channels.

Allocation Process

The allocation process was highly manual and based on backward looking information without considering tailored allocations to stores.


With o9, the allocation process is automated and managed by exception resulting in huge productivity gains, freeing up time for business to focus on strategies, analysis and inventory policies. The process leverages ML based forecasts, inventory strategies and store specific size profiles ensuring that the right items are replenished to the stores.

Story Capacity Management

Their stores were running over capacity without leveraging intelligence to assist in prioritizing sending the right new and profitable styles.


With o9, they can manage capacity at stores by having full visibility into projected capacity utilization and by applying auto-correction. Auto- correction is applied by prioritizing and flowing profitable styles to stores and mitigating inventory issues.

Value Delivery

Key Functionalities Implemented

The company is using the o9 Enterprise Knowledge Graph for Forecasting, Allocation and Replenishment. Key capabilities include enhanced AI/ML based forecasting, omni-channel planning, regular and cross-dock allocation to stores, demand driven replenishment, inclusion of store capacities into inventory planning and visibility to supply chain operations and store network.

Systems Replaced

Blue Yonder.

Customer Benefits

Success Factors — 3 reasons why o9 was selected

  1. Open architecture AI platform with advanced machine learning capabilities for next generation omni- channel planning.
  2. Thought leadership.
  3. Speed to value.

KPI Impacted

  1. Improved forecast.
  2. Increased in-stocks.
  3. Improved planner productivity.

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