Welcome to the first in a multi-part series about data at Rover! To kick it off, I’ll talk about our culture of data self-service, what that means to us, and why we think it’s so important. Later on, I’ll go in depth on how we cultivate our data practice, specific challenges we face, and tactics we use.
Data makes our world go ‘round
At Rover, data is central to how we understand every aspect of our business. We use data to measure our progress, plan for the future, and make decisions. In order to stay nimble while we grow rapidly, we can’t rely on a centralized reporting authority and the cumbersome, restrictive data governance that goes along with it. Instead, we expect a base level of data literacy from everyone who manages a team or business function.
Data literacy empowers everyone
Our colleagues in every department want to take ownership of their work and push the boundaries of their skills. When a program manager has to wait on an analyst to fetch data for them, it disempowers both the manager and the analyst. Neither party has autonomy over both the data and the decisions it’s driving and overall speed of decision-making is hindered. It’s a no-win situation.
On the other hand, when business users are their own analysts, or have embedded analysts on their teams, it increases their accountability, autonomy, and empowerment. Users who do their own reporting produce superior analyses than those who rely on reports from a BI department. They have the tools and skills they need to explore the questions on their mind and the business domain knowledge needed to interpret their results. As a result, they can immediately dive as deeply as they want to when answers inevitably lead to more questions. The only things holding anyone back are their own imaginations and skillsets.
This is the environment we’ve created at Rover. Because our users can access and interpret their own data, our marketplace analyst team is free to focus on the truly high value-add areas of predictive and prescriptive analytics. This would not be possible if they were additionally burdened by having to perform the rote descriptive and diagnostic analytics for all the other teams.
How to avoid data literacy growing pains
While our organization grows ever larger, one of the Data Engineering team’s main priorities is propagating this culture that’s steeped in data literacy. That means that we’ve been training up more and more people with a basic analytics skill set, which includes:
- Knowledge of basic data and statistical methods
- Writing SQL queries
- Using spreadsheets and reporting tools to make pivot tables and charts
- Using data to tell a story
Together with our Marketplace Analyst team, our goal is to develop Rover employees into confident, curious, self-directed learners. We want self-directed learners because they are resilient, and will try things on their own before they ask for help. Just how do we go about accomplishing our goal? All will be revealed in our next installment of The Dog People Dig Data.
Sarah Johnson is a data engineer at Rover. Prior to joining Rover, she was a high school math teacher, actuary and business intelligence analyst at a leading pet insurance company. 📈📇🐶🤓✨