MicrosoftExpandedProductionEvidence: Medium65/100

Unilever boosts operations and sustainability through digital twins and data-driven insights

Unilever, a global leader in consumer goods and manufacturing, undertook a deep digital transformation to empower employees and meet evolving consumer demand. Shifting from a project-based mindset to a platform strategy, Unilever used Microsoft Azure as an architectural backbone, enabling real-time data democratization and agility across its supply chain. The company implemented Azure IoT-based digital twins in its factories, enabling automated data collection, advanced analytics, and machine learning for operational improvements such as controlling moisture levels and optimizing production batch processing. Power BI allowed Unilever's employees to create their own reports and reduce false alerts in production lines, leading to increased productivity and reduced manual effort. By introducing Power Apps, employees built and deployed quality assurance tools, which replaced paper-based processes, streamlined factory operations, and contributed to sustainability by saving energy and materials. Microsoft Teams and Microsoft 365 strengthened global connectivity and knowledge sharing among Unilever’s 155,000 employees, further enhancing productivity and rapid decision-making. The digital strategy, developed in partnership with The Marsden Group, delivered 90% fewer actionable production alerts, significant energy savings in factories, and built a data-intelligent organizational culture to support future growth. Unilever democratized access to insights for non-technical staff, built strong collaboration communities for sharing best practices, and created the technological foundation to expand digital twins to dozens of global plants, accelerating value realization.

Organization
Unilever
Published
July 2019

Reported outcomes

−90%

timeTime & speed

Strategic outcomes

New product / capabilityDeployed digital twins for factory optimizationCustomer experience & trustImproved employee access to real-time insightsSustainability & ESGReduced energy and material use in factoriesEcosystem & partnershipsBuilt global collaboration and knowledge sharing

Catalog median for time & speed deployments: −50% across 312 reported metrics. Compare benchmarks →

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

Normalized claim

Time: 90% decrease

news.microsoft.comJul 15, 2019News articleInferred claimMedium evidence strength

90% reduction in actionable production alerts per day, increasing uptime.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
Customer
Unilever
Provider
Microsoft
Maturity
Production
Linked source
news.microsoft.com

The company implemented Azure IoT-based digital twins in its factories, enabling automated data collection, advanced analytics, and machine learning for operational improvements such as controlling moisture levels and optimizing production batch processing

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 4

  • 1Digital twin-enabled predictive maintenance and process optimization
  • 2Automated quality assurance using employee-built low-code apps
  • 3Democratization of data-driven insights for manufacturing
  • Needed to increase efficiency and responsiveness across global manufacturing operations.
  • Wanted to democratize data insights for employees at all levels, reducing reliance on technical support.
  • Struggled with excessive manual interventions in quality assurance and batch processing.
  • Required tools to improve quality control and sustainability performance (energy/waste).
  • Faced high volume (3,000+/day) of production alerts, disrupting operator productivity.
  • Needed to connect a globally distributed workforce for easier knowledge sharing.
  • Shifted to a platform-based approach using Microsoft Azure as cloud backbone.
  • Deployed Azure IoT-powered digital twins to optimize multiple factory processes.
  • Used advanced analytics and Azure ML algorithms for predictive operational management.
  • Empowered employees to build custom apps for quality assurance using Power Apps.
  • Adopted Power BI for democratized real-time data visualization and alert reduction.
  • Rolled out Microsoft Teams and Microsoft 365 for global collaboration and productivity.
  • 90% reduction in actionable production alerts per day, increasing uptime.
  • Increased employee empowerment through custom app development and broader access to data.
  • Significant reduction in energy and paper use across factories, supporting sustainability goals.
  • Faster batch processing and optimized asset utilization through data-driven insights.
  • Improved communication and productivity for 155,000 global staff via Teams.
Architecture

Unilever’s architecture is built on Microsoft Azure as the central cloud backbone. Azure IoT collects machine and process data into digital twins hosted on Azure, which are utilized for real-time analytics and machine learning using Azure ML. Employees access insights and build custom apps through Power BI and Power Apps, integrated fully within Microsoft Teams and Microsoft 365, enabling secure global collaboration and data sharing. The Marsden Group supported the custom development and implementation of the digital twin solution.

Sources & evidence1
Evidence: Medium65/100Evidence strength
  • Customer explicitly identified
  • Deployment status explicitly supported
  • 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 2025.

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

Type: News ArticlePublished: Jul 15, 2019Publisher: news.microsoft.comEvidence: SecondaryConfidence: Low

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

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