Case Study: Uber achieves over $10 million in annual savings with Shibumi

How Shibumi Helped Uber Scale Intelligent Automation to Drive >$10 Million in Annual Savings

Uber's Intelligent Automation Center of Excellence (COE) faced challenges in scaling its automation initiatives across the business. As they expanded from RPA into AI and other solutions, using disparate tools like Google Docs and Forms to manage the intake pipeline became messy and inefficient. This lack of a single source of truth made it difficult to organize and scale their impact, hindering their goal of becoming an automation-first enterprise. They turned to Shibumi and its Automation Accelerator for a solution.

By implementing Shibumi, Uber gained a robust system to track and manage automation opportunities from ideation to deployment. The platform provided essential visualizations to prioritize projects and, through an integration, enabled real-time savings tracking. This allowed Uber's team to secure executive buy-in by clearly demonstrating intelligent automation's value. The results were substantial, including over $10 million in annual savings and 200,000 hours of manual effort saved. The team credited Shibumi as being critical to achieving this scale.

Uber

Chad Aronson

Global Head of Intelligent Automation COE