With its global workforce of about 20,000 employees, Uber is re-imagining the way the world moves. The company has brought together a collection of optimists and doers to tackle some of the most challenging problems of our time. Uber’s people vision is to build the highest performing diverse workforce and to anticipate and meet the needs of its diverse customers, thus leading the global marketplace.
“A key early decision was to use Visier as a business tool, not just an internal HR tool. While HR needs to have it, our key stakeholders are the managers and leaders running the business. Visier enables everyone to ask and answer questions themselves using data.”— RJ Milnor, Global Head of People Analytics at Uber
Uber’s fast global expansion created the need for a people analytics solution to support its culture of data-based decision-making. There was limited ability for Uber’s People function or business leaders to quickly conduct analysis on their workforce, particularly across the entire organization.
Disparate sources of data
The company’s people data was housed in disparate systems and often categorized in different ways. “There were different taxonomies and very few of them were connected,” says RJ Milnor, Global Head of People Analytics at Uber.
Sometimes questions as apparently simple as, “What is my current headcount?,” couldn’t be answered in efficient, repeatable ways. In a business where fast data-based decision making is expected, including within its People function, this status quo was not good enough.
Speed to value
Uber was faced with choosing whether to assign internal user experience and engineering resources to build a customized people analytics solution or to select a vendor’s solution that could deliver to their requirements. Additionally, Uber’s business leaders needed, and expected, all this comprehensive information on their people to be delivered through an attractive and intuitive interface. Lastly, time to value was an important factor for determining their approach to a people analytics solution.
Uber was driven by a principle of enabling all business leaders, not just HR leaders, with data and analytics. The organization pursued a self-service model that empowers users, rather than the having a large analytics team doing customized analyses with specialized tools and raw data. Uber’s decision to buy Visier was based on its intuitive user interface, its robust and people focused data model, and the power and speed of its implementation partnership approach.
“With our team working in close partnership with Visier, the speed and quality of developing a live solution was truly stunning,” says RJ.
By choosing Visier as an alternative to building a customized solution, Uber was also able to avoid the time and cost of building a data model and metric definitions for its people data.
“Visier’s robust data model and metric definitions enabled us to avoid spending time ‘reinventing the wheel’ where there was already a good solution, and instead focus our effort on the requirements that were truly differentiated for our business and our users. The value of Visier is seeing everything on one pane of glass–rather than having to go to five different dashboards to figure something out.”— RJ Milnor, Global Head of People Analytics at Uber
Uber’s focus on helping business leaders answer questions about their people ultimately drove the decisions about solution selection, design, and enablement.
First initiative: Fast track go live
In order to meet Uber’s short time to value requirements, Visier and Uber executed a tightly defined onboarding, configuration and feedback approach to the project. The solution was brought to a go-live stage in a matter of weeks–not months. Here’s how this was achieved:
After vendor selection was finalized, the onboarding and development approach was based on Uber’s “Test and Learn” product development approach. This approach draws on the lean concept of Minimum Viable Product (MVP).
“We want to deliver value as quickly as possible, full stop,” says RJ. “So our approach is to create a beta or Minimal Viable Product quickly, then continue to iterate and get more value based on feedback from users.”
To start, an “Uber People Dashboard” based on a previously used design was developed in the Visier solution and tested with a group of users. The approach was to fast-track the go-live of an 80% solution, then iterate to get to a 95% solution by co-developing improvements with Visier.
Feedback was gathered from users weekly and converted into lists of changes and enhancements to data and configurations. One learning from this process was that different user groups had very different needs. The solution needed to enable local configuration changes without having to develop multiple customized versions.
For example, leaders with small teams didn’t value analysis of headcount or past attrition as much as leaders with 200-300 employees. However, both types of leaders were interested in predictive analytics.
“Instead of saying ‘We’re the people analytics experts’ and taking an expert-driven approach, we took a user-centric approach and said ‘Please tell us the problem that you’re trying to solve and what you need to be successful.’ We want to orient around that,” RJ explains.
Uber’s people analytics team
Also important to the speed of implementation was the organization of Uber’s People Analytics team, which comprises over 20 solutions, product, and engineering resources. These resources were responsible for developing and executing the rollout and deployment plan, training and coaching users, and managing the development roadmap.
One of the issues that needed close attention by these resources was security.
“With Visier, our analytics team can very carefully curate analyses and use Visier’s security to ensure that only the right people see the right things and that data privacy is rigorously respected.”— RJ Milnor, Global Head of People Analytics at Uber
Crucial to implementation was having a senior business executive as an executive sponsor, along with the Chief People Officer. With the sponsor’s involvement, the direction of the project became one of enabling leaders to directly use people analytics in their everyday decision-making, rather than HR using the platform to support leaders.
The project was also guided by a decision team composed of key stakeholders from user groups.
“Visier is fantastic! For a talent decision, I used to have to go to an HR business partner, wait two weeks, and by then, the decision window was gone. Now I can have the current data, interrogate it, then meet with my HR business partner to discuss solutions.”— A senior leader at Uber
Supporting business decisions
Business users began to see more value in the solution as more use cases were enabled during roll out. Uber leaders use Visier to answer questions about attrition, diversity, workforce structure, labor cost, and more.
“One example of how we are using Visier to support our business priorities is our commitment to create greater equity, specifically increasing representation at Uber. Leaders see their team’s diversity data in Visier and can analyze from various angles to assess our organizational health. We’re actively making decisions on our plans using Visier and measuring ourselves against the data to hold ourselves accountable,” RJ explains.
Uber rolled out its new people analytics solution to a broad group of business and HR users in a few quarters. Among business and HR users, over 50% are actively using the solution.
Business leaders now answer questions themselves using Visier. For example, the C-Suite can ask and answer questions in Visier to identify and frame problems and solutions. Further, there has also been a substantial upskilling of Uber’s People function using self-guided and instructor-assisted training provided during the rollout process. The People team is now empowered to go beyond reading dashboards to conducting analyses.
Today, Uber’s People team is actively growing, and analytics use will soon be available to over 1,000 users. The analytics team and Visier continue to support Uber’s growth and success by providing solutions that support decision-making by business leaders and strengthen the data literacy of the People function.