o9 Digital Brain for Softlines

An American clothing and home decor retailer, which specializes in casual clothing, luggage, and home furnishings.

This customer had highly manual and Excel-driven planning processes across functions and Time horizons leading to suboptimal decision, inventory, and service level challenges.

Sustainability Impact

A reduction of logistics expedites and the avoidance of transfers between the distribution centers.

Business Scope Challenges

Planning in Silos

Key planning processes (demand planning, replenishment planning) were all executed in silos without the ability to connect the dots.


With o9, the company will get the unique capability of connecting all planning processes for basic and seasonal product lines across all channels (Retail, Uniform, Catalogue, Online/ Marketplace) and regions on a single integrated cloud-native platform.

Demand Planning

The company did not have a statistical demand forecast in place. Moreover, planners created forecasts based only on sell-out at an item level and spent a large amount of time disaggregating the forecast to a size level, not having the time to focus on the actual analysis.


With o9, the company has access to sophisticated, collaborative and ML-driven forecasts. This will take away the grunt work by enabling data-driven exception workflows.

Replenishment Planning

There were challenges to accurately perform replenishment planning, which was due to a high level of required manual interventions and processes not supported by analytics.


With o9, the company will be able to better manage the replenishment plan for stores and the procurement plan for DCs, at various grains and horizons for all regions. The use of o9’s advanced forecasting and safety stock-driven replenishment plans leads to a more balanced inventory in the stores.

Value Delivery

Key Functionalities Implemented

The Enterprise Knowledge Graph is used to create demand and replenishment knowledge models. Some of the demand planning capabilities leveraged to increase efficiency and accuracy are: lost sales correction,outlier cleansing, characteristics- based item mapping for new product introduction, ML forecasting, planner enrichment models to accommodate causal factors and size scaling functionality.

Systems Replaced

Oracle and Excel.

Customer Benefits

Success Factors — 3 reasons why o9 was selected

  1. The sophistication and flexibility of a single, cloud-native platform for integrated forecasting and replenishment.
  2. Dedication of the o9 team to deliver value, rather than just executing the project.
  3. Deep industry knowledge in the retail industry, allowing for faster time to value.

KPI Impacted

  1. Hours saved on manual planning and inventory management.
  2. Reduction in inventory and expedite costs.
  3. Improvement of instock/fill rate.

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