On Shelf Availability Solution | Built by Databricks & Tredence

Databricks and Tredence Solve for Retail On-Shelf Availability

Reclaim missed sales with AI and out-of-stock modeling

Tredence partnered with Databricks and co-developed a joint on-shelf availability solution (OSA) accelerator which is a robust foundation of best-practices, quick-start guides, and notebooks for a full Out of Stock or Supply Chain solution.

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Out-of-stock is never an option in retail

Shoppers encounter an out-of-stock (OOS) as often as once in three shopping trips, according to IHL Group research. On-shelf availability (OSA) is the single biggest challenge in Retail. Retailers are missing out on nearly $1 trillion in global sales because they do not have on-hand what customers want to buy in their stores. According to ECR, a 2% improvement in on-shelf availability is worth 1% in increased sales for retailers. The impact of OOS is not limited to just loss of revenue, but also a loss of loyalty and share.

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Challenges:
Why hasn’t technology solved out-of-stocks yet?

Modeling
Challenges

False positives and false negatives driven by inaccurate models erode user confidence in OOS models

Data Processing
Challenges

Large amounts of data mean that the ML models can’t be processed fast enough to provide timely insights

Alerting
Challenges

Lack of prioritized OOS alerts sent directly to store personnel mean that OOS insights can’t get into the hands of the people that can act on them

Tredence co-created the On-Shelf Availability (OSA) Solution Accelerator in Partnership with Databricks

Tredence and Databricks jointly built the On-Shelf Availability Solution (OSA) accelerator to help retailers and manufacturers reclaim missed sales. The accelerator is a robust foundation of best-practices, quick-start guides and notebooks for a full Out of Stock or Supply Chain solution.

The accelerator covers

End to end approach to identify historical out of stocks, predict potential future out of stock risks, and create automated out of stock alerts for field personnel
Highly accurate models to alert you to the presence of out of stocks
Quantification of the business value of improving on-shelf availability and prioritizing action
Robust training to help increase your knowledge of Databricks best practices and advanced ML modeling techniques

Why Tredence and Databricks to Improve On-Shelf Availability?

Tredence, a leading data science and AI Engineering Company focused on solving the last mile problem in analytics works with the largest retailers on the planet to understand the nuances of modeling out-of-stock (OOS).

Databricks provides a unified analytics platform powered by Apache Spark for data science teams to collaborate with data engineering and business.

The combination of Tredence’s advanced data science capabilities and Databricks’s data processing provides a winning combination. Only the partnership of Tredence and Databricks can help you confidently solve the trillion-dollar problem of Retail Out of Stocks.