What challenges did o9 Solutions face before AI implementation?

CPG and retail companies face challenges with inaccurate demand forecasts, leading to lost sales, stock-outs, excess inventory, and inefficient supply chains. Traditional forecasting methods relying on historical sales and gut feeling often fail to capture complex demand patterns or account for new products without historical data.

What was the impact of the AI solution?

Achieved 30-50% reduction in forecast errors. Enabled 5-10% reduction in logistics costs. Decreased supply chain administration costs by 25-40%. Reduced overall inventory levels by 10-30%. Improved demand fulfillment, decreased lost sales, and strengthened financial outcomes and brand loyalty.

Source

GCPExpandedEvidence: Medium50/100

o9 Solutions integrates Google Cloud Vertex AI Forecast for enhanced CPG and retail demand forecasting

Use case typeDemand forecastingUpdated Jun 13, 2026

o9 Solutions integrates Google Cloud Vertex AI Forecast within its Digital Brain platform to improve demand forecasting accuracy for Consumer Packaged Goods (CPG) and retail companies. The solution leverages Vertex AI Forecast's multivariate data analysis and hierarchical modeling to generate accurate, scenario-based demand predictions using both internal and external data, including for cold start products without historical data. This integration targets key challenges of reducing lost sales from stock-outs, optimizing inventory levels, and improving supply chain efficiency to directly boost financial performance and brand loyalty.

Organization: o9 Solutions
Industry: Retail
Location: New Zealand
Published: January 2022

Reported outcomes

30-50%

accuracyQuality & accuracy

5-10%cost25-40%cost10-30%quantified impact

Strategic outcomes

New product / capabilityAdded AI-powered demand forecastingNew product / capabilityEnabled cold-start product forecastingBetter decisions & insightImproved scenario-based demand predictionsCustomer experience & trustReduced lost sales and stock-outs

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Accuracy: 30-50% decrease

o9 Solutions WebsiteJan 20, 2022News articleInferred claimMedium evidence strength

Achieved 30-50% reduction in forecast errors.

Normalized claim

Cost: 5-10% decrease

o9 Solutions WebsiteJan 20, 2022News articleInferred claimMedium evidence strength

Enabled 5-10% reduction in logistics costs.

Normalized claim

Cost: 25-40% decrease

o9 Solutions WebsiteJan 20, 2022News articleInferred claimMedium evidence strength

Decreased supply chain administration costs by 25-40%.

Normalized claim

Quantified impact: 10-30% decrease

o9 Solutions WebsiteJan 20, 2022News articleInferred claimMedium evidence strength

Reduced overall inventory levels by 10-30%.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: o9 Solutions
Provider: GCP
Maturity: Unknown
Linked source: o9 Solutions Website

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 2 of 2

1Demand Forecasting
2Inventory Optimization

CPG and retail companies face challenges with inaccurate demand forecasts, leading to lost sales, stock-outs, excess inventory, and inefficient supply chains.
Traditional forecasting methods relying on historical sales and gut feeling often fail to capture complex demand patterns or account for new products without historical data.

o9 Solutions integrated Google Cloud Vertex AI Forecast into its Digital Brain platform for advanced demand forecasting.
The solution uses machine learning-powered hierarchical modeling and multivariate data analysis to improve forecast accuracy and model complex demand scenarios.
It enhances forecasting for new products with no demand history (cold start items) and provides explainability and scenario planning capabilities.
The platform runs on Google Cloud, leveraging its flexibility and scalability.

Technologies

Google Cloud Vertex AI Forecast Google Cloud

Achieved 30-50% reduction in forecast errors.
Enabled 5-10% reduction in logistics costs.
Decreased supply chain administration costs by 25-40%.
Reduced overall inventory levels by 10-30%.
Improved demand fulfillment, decreased lost sales, and strengthened financial outcomes and brand loyalty.

Architecture

Integration of Google Cloud Vertex AI Forecast with o9 Solutions Digital Brain platform using ML-powered hierarchical demand forecasting models to produce scenario-based demand predictions from multivariate data.

Sources & evidence1

Evidence: Medium50/100Evidence strength

Customer explicitly identified
Independent source available
Quantified outcome available
Technical implementation details available

ExpandedExpanded

The same organization appears in newer AI deployment evidence.

Same organization re-documented as recently as 2024.

Measures whether this deployment's public evidence persists — not whether the system is still in production.

Type: News ArticlePublished: Jan 20, 2022Publisher: o9 Solutions WebsiteEvidence: SecondaryConfidence: Low

Primary source

AI-generated summary. Verify important details with the linked sources before relying on this case.

o9 Solutions integrates Google Cloud Vertex AI Forecast for enhanced CPG and retail demand forecasting

Use case focus

Challenges

Solution

Impact

Comments

Similar cases