CUSTOMER SPOTLIGHT
Global manufacturer identified ways
to reduce the impact of late shipments
by more than 4M yearly in 17 days
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Company Profile

A global leader in manufacturing and distribution of specialized equipment

Industry

Manufacturing

Region

US

Challenge

Surface patterns around why certain shipments are late, and mitigate loss by prioritizing which shipments to expedite or take remedial action on.

Solution

Initial data preparation, data cleansing, and data analysis was delivered within 5 days. Based on business user feedback, the use case was strategically adjusted to incorporate critical business segmentations. Within 7 days, Aible provided updated analysis on the use case that was reviewed and accepted by the business team. Numerous next steps were identified.

Outcome

Aible helped identify ways to reduce the impact of late shipments by over $4M yearly, with serverless AI in 17 days.

"Aible showed us how to unlock actionable insights in our data. The speed to insight was way faster than we expected, and the insights found would likely never have been uncovered using traditional analytics.”

–VP of Marketing & Analytics

Use Case & Project Details

  • Use Case

    Late shipment prediction and expedite optimization

  • Potential Project Results

    $4M+ cost reduction

  • Time from data provision to project completion:

    17 days

  • Elapsed time from start of model training to completion of over 2600 models on serverless infrastructure:

    Over 10 iterations in less than 10 minutes each

17_Days_Reduced_Late_Shipments

Global manufacturer identified ways to reduce the impact of late shipments by more than 4M yearly in 17 days

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