What challenges did Dow Chemical face before AI implementation?

High costs and inefficiencies in logistics and supply chain management. Complex freight invoicing handling thousands of shipments daily. Demand forecasting inaccuracies leading to waste and cost inefficiencies. Inefficient shipment planning and customer service. Managing returns and procurement processes effectively.

What was the impact of the AI solution?

SPAR Austria achieved more than 90% accuracy in demand forecasting, resulting in a 15% reduction in costs due to minimized waste. Dow Chemical automated freight invoice processing improving spend management efficiency. Decathlon reduced calls needing live agent intervention by 20%, enhancing service efficiency and customer satisfaction. The solution supports scalable, intelligent, and secure multimodal logistics management and analytics from edge to cloud.

Source

Microsoft

Microsoft AI and Agentic AI Transform Logistics and Supply Chain for Major Companies Including Dow Chemical and Decathlon

Use case typeSupply chain forecastingUpdated Jun 13, 2026

Microsoft and its partners have transformed the logistics and supply chain operations for companies including Dow Chemical, Decathlon, and SPAR Austria by leveraging Azure cloud and AI technologies. The companies faced challenges such as high costs, inefficiencies, complexities in freight invoicing, demand forecasting, shipment planning, customer service, and returns management. Microsoft implemented an adaptive cloud platform combined with AI and agentic AI for end-to-end logistics optimization. This included AI-powered demand forecasting, invoice processing automation with Microsoft Copilot Studio, AI-enhanced customer service automation, and AI-driven procurement and pricing. Specific achievements include SPAR Austria reaching over 90% demand forecast accuracy leading to 15% cost reduction, Dow Chemical automating freight invoice processing to reduce spend, and Decathlon improving customer service efficiency by reducing calls forwarded to live agents by 20%.

Organization: Dow Chemical
Industry: Logistics
Location: Austria
Published: March 2025

Reported outcomes

−90%

costCost savings

−15%cost−20%productivity

Strategic outcomes

Better decisions & insightImproved demand forecasting accuracyCost efficiencyReduced logistics costs and wasteCost efficiencyAutomated freight invoice processingCustomer experience & trustReduced live-agent customer support calls

Catalog median for cost savings deployments: −44.5% across 344 reported metrics. Compare benchmarks →

Primary read

Use case focus

Showing 3 of 4

1Demand forecasting
2Invoice automation
3Customer service automation

High costs and inefficiencies in logistics and supply chain management.
Complex freight invoicing handling thousands of shipments daily.
Demand forecasting inaccuracies leading to waste and cost inefficiencies.
Inefficient shipment planning and customer service.
Managing returns and procurement processes effectively.

Implementation of Microsoft Azure Adaptive Cloud for a unified logistics platform.
Use of Azure OpenAI Service, Microsoft Dynamics 365 Supply Chain Management with AI-powered Copilot, Microsoft Copilot Studio for invoice automation, and additional Azure services like API Management, Event Grid, Event Hubs, and App Service.
Deployment of AI and agentic AI solutions for demand forecasting, invoicing automation, customer service, procurement, pricing, and shipment planning.
Partnerships with Paiqo and Parloa to enhance AI-powered customer service and automation.

Technologies

Azure OpenAI Service Microsoft Dynamics 365 Supply Chain Management Microsoft Copilot Studio Azure API Management Azure Event Grid Azure Event Hubs Azure App Service Microsoft 365 Copilot

SPAR Austria achieved more than 90% accuracy in demand forecasting, resulting in a 15% reduction in costs due to minimized waste.
Dow Chemical automated freight invoice processing improving spend management efficiency.
Decathlon reduced calls needing live agent intervention by 20%, enhancing service efficiency and customer satisfaction.
The solution supports scalable, intelligent, and secure multimodal logistics management and analytics from edge to cloud.

Architecture

The solution uses Microsoft Azure Adaptive Cloud to unify distributed logistics operations across cloud and edge environments, combined with Dynamics 365 Supply Chain Management enhanced by AI-powered Copilot and custom AI agents created with Microsoft Copilot Studio. It integrates data streams via Azure Event Grid and Event Hubs, exposes APIs through Azure API Management, and supports scalable deployment with Azure App Service.

Implementation partners2

paiqo Parloa

Sources & evidence1

Groundedness: 4/5

Primary source

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

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Customer evidence