By implementing Shibumi’s Automation Accelerator, Uber gained a robust tracking mechanism to help manage their pipeline and monitor potential opportunities from ideation to deployment and production.

“Before Shibumi, we were using Google Docs and Forms to manage our intake process,” said Chad Aronson, Global Head of Uber’s Intelligent Automation COE. “It was messy, cumbersome, and inefficient. Now, there’s no more searching for files or problems finding data. We can quickly pivot and, with the click of a button, have our pipeline sliced and diced by various statuses, such as ‘in progress,’ ‘on hold,’ ‘in assessment,’ and even ‘canceled.’”

With Shibumi, Uber is able to systematically capture key fields and generate visualizations in order to prioritize automations. For example, one visualization the team often refers to shows estimated annual savings on one axis and automation complexity on the other. “Since we of course like to have higher value with lower complexity, this is useful for helping us figure out how to switch gears,” Aronson said.

Through an integration with Kibana, Shibumi also enables Uber to track savings and exceptions. Previously, this would have required significant manual work, but now it can be done with the click of a button to inform real-time decision making.

Aronson’s team has also rolled out a dashboard built for upper management and leadership teams to provide visibility and insights into key metrics, such as transaction volumes, estimated time savings, actual savings, and headcount. These can be filtered by program and line of business.