Normalized claim
Time: 50% decrease
Monthly planning job completion time was reduced by 50%.
Orica case study | Google Cloud
Use case typeInventory planningUpdated Jun 13, 2026
Orica modernized its SAP and analytics environment on Google Cloud to improve performance, resilience, and data-driven planning across its global operations. The company migrated SAP workloads with Google Cloud Professional Services Organization support, used BigQuery and Cortex Framework for data transformation, and used Vertex AI for proprietary machine-learning-based demand planning and sales forecasting. Orica reported faster SAP response times, shorter backup windows, and improved monthly planning and forecast accuracy.
- Organization
- Orica
- Industry
- Energy & Utilities
- Location
- Australia
- Published
- May 2026
Reported outcomes
+18.5%
timeTime & speed
−50%time+10%revenue−4.5%time6 hourstime17 minutestime
Strategic outcomes
New product / capabilityModernized SAP and analytics environmentBetter decisions & insightImproved demand planning and forecastingSpeed & agilityFaster SAP response and backup processes
Catalog median for time & speed deployments: +60% across 143 reported metrics. Compare benchmarks →
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Revenue: 10% increase
North America sales forecast accuracy improved by about 10% in the demand planning pilot.
Normalized claim
Time: 18.5% increase
SAP Fiori response times were 18.5% faster and SAP HANA response times were 4.5% quicker.
Normalized claim
Time: 4.5% decrease
SAP Fiori response times were 18.5% faster and SAP HANA response times were 4.5% quicker.
Normalized claim
Time: 6 hours decrease
Backup times were reduced from about 6 hours to 17 minutes.
Normalized claim
Time: 17 minutes decrease
Backup times were reduced from about 6 hours to 17 minutes.
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Orica
- Provider
- GCP
- Maturity
- Pilot
- Linked source
- Google Cloud Customer Story
North America sales forecast accuracy improved by about 10% in the demand planning pilot
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 3
- 1Predictive Analytics
- 2Demand Forecasting
- 3ERP Modernization
- Modernize core SAP workloads while improving performance, availability, resilience, and migration risk controls.
- Enable data and AI-driven efficiencies for demand planning and sales forecasting.
- Support global operations with a scalable platform for business-critical enterprise planning.
- Migrated SAP environments to Google Cloud with Google Cloud Professional Services Organization support.
- Used Compute Engine, Network Connectivity Center, Backup and Disaster Recovery Service, BigQuery, Cortex Framework, Looker, and Vertex AI.
- Adapted Cortex Framework workflows into BigQuery and ran proprietary machine learning models for demand planning and sales forecasting.
- Monthly planning job completion time was reduced by 50%.
- North America sales forecast accuracy improved by about 10% in the demand planning pilot.
- SAP Fiori response times were 18.5% faster and SAP HANA response times were 4.5% quicker.
- Backup times were reduced from about 6 hours to 17 minutes.
Architecture
Orica migrated SAP workloads to Google Cloud with PSO support. The architecture includes Compute Engine for SAP applications, Network Connectivity Center for connectivity, Cortex Framework and BigQuery for data flows and analytics, Looker for reporting, Vertex AI for ML use cases, and Backup and Disaster Recovery Service for backup resilience.
Sources & evidence1
Evidence: Medium65/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Customer StoryPublished: May 25, 2026Publisher: Google CloudEvidence: PrimaryConfidence: High
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