Mars Petcare
The Global Petcare Data and Analytics team at Mars Petcare is on a mission to democratise access to data for the business to make smarter decisions and to improve pets' lives.
Data Unleashed
It’s 2022. The data is the power. At Mars Petcare, the amount of data the analysts have to interact with is growing at an incredible pace. Not only is there more data, but it is coming from more sources. As a result, the experience of interacting with the data is slow and complex.
My Role
I was part of the Product team in the Global Data and Analytics division. Our team took it upon itself to understand the intricate world of data analysts and empathised with their day-to-day pain points. I took the lead in planning, strategising, and conducting user research. I reported directly to and worked closely with Kaylin, the Product Director. I led a small team of UX designers and data visualisers.
The challenge
‘It’s complicated….’
To fully understand the complexity of what our users do. Dealing with a highly technical data analytics environment was a learning curve for my team and me. I had to understand and consider different users’ needs depending on their role in the process.
The Approach
Step into their world
Strategy and Vision
The strategy and vision I had were for the team to focus on the users’ problems and how to solve them, understand the business needs, and create a bridge between those two. Second, I wanted the team to focus on the goals we wanted to achieve. I directed the team towards outcomes rather than outputs,
Human-Centred Design Approach
I worked with stakeholders to understand overarching business objectives and desired outcomes and get answers to questions such as 'what do we want to achieve?' or 'what does success look like?’ I shared my vision and methods with the stakeholders, which helped me build strong relationships with them from the start.
Empathy
I conducted remote interviews with the data analysts. Focusing on the current as-is scenarios and problems the users face allowed me to gain a deeper understanding of the context of use. I invited product managers, designers and developers to be present during the interviews - so the whole team understood the problems we were trying to solve.
Digging deeper
For a more holistic understanding of the broader challenges the analysts faced, I spent much time reading the studies produced by them to understand better the final product of their work and how they approach and analyse the data they interact with. I also listened in on their collaborative sessions, where I could gather a deeper context of their challenges.
The discovery
Themes and Patterns
After gathering the information in the discovery phase, I observed common themes and patterns; I identified the user needs and challenges that were consistent across the board:
In data, we trust
Researchers’ work revolves around the data. But data is nothing when it’s not usable for the end user. They want to understand the data, know where it comes from and, trust it, be able to work with different sets of data simultaneously.
Scale it up
A massive scale of data will allow users to have statistically robust data sets that have not been available before, ensuring rapid scientific development, never possible before, via individual studies.
Quality, quality, quality
If the data is complete and consistent, data scientists can save time fixing it to make it usable. Unfortunately, this takes time away from other activities and means it takes longer for them to produce and report the insights the data uncovered.
Diversity and collaboration
Users need more access to a broader community where ideas and challenges can be shared across different fields. I understood that there are strong connections between the groups, their use cases and the data sets required;
Outcomes
Tangible Results
Data product used in published research that improved care provided to dogs by vets when neutered/spayed, enabling dogs to get back to pre-surgery level activity more quickly.
Improved digital advertising data products, resulting in $4.7 million in media savings and a 200% increase in the usage of 1st party data annually.
Lessons learned
If I could turn back time…
Setting specific goals
One thing that I didn’t spend enough time on is setting specific goals for the team so that we can easily navigate them. We sometimes lost track of what we were trying to achieve and had to take a step back and refocus. If I could do it again, I would focus more on setting specific goals, so the team is not lost along the way.
People don’t like change.
Instead of revolutionising how users work, I should have focused more on gradually improving their experience. I found users reluctant towards provided solutions simply because they varied too much from what they were already comfortable with. We had to compromise.