Our Asana setup delivers a lean way to collaborate by enabling stakeholders to stay informed at a completely new level of transparency and efficiency.”

Winner: 2026 Industry Transformation Award, EMEA

This award recognized REWE Markt GmbH for redefining logistics governance by building a digital twin of its national infrastructure. By professionalizing its data structure and layering AI-driven synthesis and validation, REWE has established a blueprint for retail organizations to move from reactive firefighting to proactive, data-driven execution.

Use case 1: Strategic intelligence and portfolio governance

Previously, program managers were trapped in a cycle of manual data retrieval, losing nearly a full workday every week to the burden of compiling reports. REWE solved this by implementing an AI-powered reporting engine that acts as a strategic filter for the national portfolio. This new workflow scans hundreds of projects to extract actionable signals from the noise, ensuring that rollout delays are surfaced instantly for executive review.

• Standardized intake: Every new initiative is submitted via Forms and automatically converted into a project based on its strategic pillar.

• AI-powered synthesis: AI Studio scans projects to focus specifically on milestone shifts and financial anomalies, ignoring subtask minutiae to extract high-impact variances.

• Strategic One-Pagers: The system automatically drafts prioritized newsletters that summarize risks and wins, moving portfolio updates from a 6-hour task to 5 minutes of review. Without this capability, program managers wouldn’t have the capacity for reporting at this scale.

• Strategic pillar alignment: Every task is mapped to core values like logistics costs or customer impact, ensuring growth remains aligned with company goals.

We used AI Studio to embed a custom-engineered prompt into Smart Status, which allowed us to move beyond simple summaries to a strategic filter that audits 300+ projects. This transforms thousands of data points into a prioritized, executive-ready one-pager in minutes.”

Use case 2: Automated facility operations across 16 centers

Previously, facility management used siloed tooling with rigid functionality that didn’t meet business needs, leaving headquarters with zero visibility into the health of regional infrastructure. REWE replaced this with an automated hub-and-spoke architecture that routes 740+ maintenance tickets with 100% cost transparency. By standardizing the intake process, the organization has eliminated administrative friction and ensured that critical repairs are addressed before they threaten the food supply chain.

• Automated regional routing: Rules use branching logic to instantly dispatch tickets from a central

  Forms intake to one of 16 regional projects based on location.

• Multihoming for transparency: Local warehouse tickets exist simultaneously in regional boards and the national oversight portfolio, allowing technicians and headquarters to work from the same live data.

• Lifecycle oversight: Custom fields track tickets through phases like Offer Pending and Approval, providing a documented history of direct costs and repair durations.

• Strategic dashboards: Real-time reporting aggregates regional data, providing 100% visibility into maintenance spend across the national network.

The single most impactful mechanism is the Automated Regional Routing & Multihoming Architecture. By using branching logic to instantly dispatch tickets, we eliminated manual coordination and created a real-time bridge between local repairs and national oversight.”

Use case 3: Intelligent validation with AI Teammates

As an early adopter of Asana AI Teammates, REWE focused on testing and designing strategic use cases to establish an operational framework for future scale. Rather than deploying tools directly into live production, the creative team used an experimental environment to prototype an intelligent review layer at the intake stage, identifying exactly how automated agents can remove administrative friction before work begins.

• Verified use cases to scale: By treating early adoption as a discovery phase, the organization built a library of verified use cases to streamline deployment at scale.

• Autonomous review: AI handles the review layer by reading linked brief content to flag missing event descriptions, empty fields, or placeholder text before resources are allocated.

• Connected automation pipelines: Once AI Teammates validates a project brief for accuracy and completeness, it triggers AI Studio to generate and route downstream scoping subtasks.

• Human-in-the-loop oversight: Humans remain the final gatekeepers, reviewing AI findings and adding strategic nuance before finalizing project updates.

We moved to an AI-driven synthesis model that reduces administrative overhead by 98%. Anchoring our Asana AI Teammates experimentation to our strategic playbooks has turned Asana into a scalable business engine that identifies missing details before work begins.”

Conclusion

Before this transformation, REWE relied on manual reconciliation and subjective communication to advance complex infrastructure and portfolio initiatives. By building a scalable, AI-powered system in Asana, the organization has shifted from administrative chasing to proactive leadership. As REWE continues to expand its national fulfillment network and move toward agentic fleet auditing, its AI-augmented operating model ensures that every operational task is visible, standardized, and mission-aligned.