Using demand forecasts for optimum stock availability

With its predictive applications, Blue Yonder makes sound business decisions possible to ensure optimum stock availability in traditional trade and e-commerce. The company does this by combining the intelligence of its software with the analytical strengths of EXASOL.

For us to continually provide reliable analyses, a database with high scalability is imperative.

Jan Karstens, CTO Blue Yonder

  • About Blue Yonder

    About Blue Yonder GmbH

    In traditional trade and e-commerce, retailers tend to tread a fine line between increased out-of-stock risk and no purchases because margins are too high. And knowing the optimum stored quantity of a product not only means that shelves are always filled with the correct amount. It also reduces subsequent storage or logistics costs.

    To make such important forecasts, retailers need reliable and accurate analyses to make over-stocking and under-stocking things of the past. With its predictive applications, Blue Yonder makes sound business decisions possible. The company does this by combining the intelligence of its software with the analytical strengths of EXASOL.

    Industry:Analytics as a Service
    Application:Fraud detection, Scoring, Managing Returns
    Database:MySQL, Oracle DB, Teradata
    BI tool:Own application
    ETL tool:LUA Scripts
  • Challenge


    • Generate billions of sales forecasts and assess hundreds of millions of data records a week
    • Calculate precise forecasts of product needs
    • Lower administrative costs
  • Solution

    Why EXASOL?

    • Database engineered and architected to deliver lightning-fast analytic performance with no data limits
    • Linear scalability through a combination of in-memory technology, columnar compression and storage, and massively parallel processing
  • Benefit

    Benefits for Blue Yonder

    • Free scalability and quick and flexible adjustments to growing amounts of data
    • Demand forecasts that are exact to the day, hour, or even minute
    • Reduced administrative costs with efficient compression algorithms and self-tuning capabilities