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Case study

How AI/ML rapidly improves your forecast accuracy

  • Read our use cases and understand how industry leaders achieved more accuracy in planning.

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PepsiCo
Kone
Westrock
Philips
T-Mobile
Starbucks
Samsung SDS
Lands’ End
PepsiCo
Kone
Westrock
Philips
T-Mobile
Starbucks
Samsung SDS
Lands’ End
Trusted by leaders across industry verticals

Why AI/ML?

Why AI/ML?

What are your challenges when connecting leading indicators of demand with your internal enterprise data?

Is your current forecasting process on a weekly/monthly cycle and only supported with lagging indicators driving statistical forecasts?

Are your forecast accuracy issues causing friction between Finance, Sales and Supply Chain?

How do you know if you have the right data to use AI/ML Forecasting?

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Learn how o9’s AI powered platform has improved major companies’ forecasting capabilities

Discrete manufacturing

How the use of ML algorithms improve the OEM forecast of a major global automotive supplier by 10 percentage points.

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Life sciences

How forecast accuracy at a global consumer health company improved by 10 percentage points when using leading indicators of demand.

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Consumer Products

How o9 improved forecast accuracy by 5-8 percentage points for a major global food producer.

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3

Retail

How over 230+ demand drivers were used to improve forecast accuracy leveraging ML algorithms for one of the largest Canadian retailers.

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Find out how leading organizations overcame challenges through AI/ML forecasting

Read our use cases and understand how industry leaders achieved more accuracy in planning.

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Resources

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