Geotab - DataOps Generative Research

Discovering pain-points and communicating results to key stakeholders

User Research | Service Design
June - November 2021

Background & Challenge

The DataOps team had a vision to create product that would unify all data processes together, and solve for any challenges from data stewards. I joined the DataOps team and as a first step, I wanted to understand what different data stewards did, and what challenges they faced at the company.

Results

There were many pain-points that were uncovered through the survey, however what we found over and over again was that there were some important organizational problems that must be solved first before product should be added on.

7/9 interviewees and 30% survey participants had challenges
with data discovery

“I was really surprised that nobody uses the Big Data tables [on my team]. Those tables are built for DNA, used by DNA and not used outside the department. And the only reason why is because there is no good documentation.”

5/9 interviewees and 34% survey participants had challenges
with data quality

“Sometimes we realize that we don’t have a good dataset in terms of quality, or coverage and was not ready to be used for customers. It needed more work.”

3/9 interviewees and 8% survey participants had challenges
with permission control

“It’s annoying to start a project only to not be able to do it until my [permissions] gets updated - and that’s not right away.”

Outcome

Results were presented to engineering and business stakeholders at the company, which resulted in key organizational changes. Instead of just one “DataOps” team, there is now:

• Data Enablement Team which will focus on Data Community and ensuring all data practitioners can come together and learn

• Data Management and Governance Team which will focus on permission control

• Data Observability Team which will focus on ensuring data quality and health

• A specific Data Platform team so everyone who is working on product will work together

Research Process

Hypotheses

The Product Manager had some hypotheses that we wanted to validated.

These included:

• Certain teams may focus on different data tasks than others

• Data quality is perceived to be poor

• Data practitioners have a hard time understanding the data which others created

• Data practitioners have difficulties finding or getting access to what they need

• How long someone at the company is negatively correlated w/ challenges they have

Survey

I created a survey and sent them out to anyone who uses and works with Data across Geotab. This survey consisted of multiple select questions that asked employees what they did at Geotab, and what they had challenges with.

We got a 35% response rate with 71/233 responses.

Hypotheses that were validated / unvalidated:

• Certain teams may focus on different data tasks than others - Validated

• Data quality is perceived to be poor - Validated

• Data practitioners have a hard time understanding the data which others created - Validated

• Data practitioners have difficulties finding or getting access to what they need - Validated

• How long someone at the company is negatively correlated w/ challenges they have - Not Validated

Interviews

I spoke to 9 people to really understand what they do and what they’re struggling with. This resulted in types of information that came out, which I mapped.

I built out a user journey map which showed a generally very negative path, and realized that pulled out quotes that highlighted not being able to meet business goals.