How to Collaborate with Your Company’s Data Team
How to build internal partnerships when you’re not (yet) on the data team
If you’re interested in working in data, but you’re not yet on the data team, how can you get visibility and a positive reputation that could possibly pay off with a pivot to the data team in the future?
The good news is that you don’t need a job title with “data” in it to start collaborating and using data. You can build experience with basic skills and curiosity, and use your domain knowledge and business acumen to identify projects that can add value.
Read on for ways to start building trust and visibility with your company’s data team - and hopefully gain experience working with data.
Lead with curiosity, not requests
When you’re reaching out to someone on the data team, don’t just make a request. Lead with curiosity and context.
“Can you pull some data on usage of onboarding materials?”
No context. No opportunity for collaboration. It turns the data team into order takers, not collaborators.
“We’ve been getting negative feedback about our onboarding materials. I’d love to understand how that shows up in the data - do you have any reports or past projects exploring that?”
This signals that you’re not just making a demand - you’re genuinely interested in using data to solve a problem. It shows respect for their expertise, which is the foundation for a good working relationship. It can also lead to more conversations about potential projects - and opportunities to collaborate.
Offer to work together, not just dump more work on them
Most data teams have a long list of projects and requests from various teams. I’ve never been on a team that has the bandwidth to tackle everything in our backlog.
Meaning they might be receptive to sharing the work if you’re willing to collaborate. Especially if you can bring your business knowledge.
Is there a project that touches your part of the business? Maybe you can offer to help with tasks like data cleaning and exploratory data analysis and visualization.
For example, if you’re on the sales team, you could reach out and say:
“I’m interested in getting involved in the customer churn project as I know it will help my team better understand why our customers are leaving. I’d be happy to offer an extra set of hands for data cleaning and exploration.”
Combine your business knowledge with their analytical expertise
Furthering the idea above, the magic happens when domain knowledge and business acumen meet quantitative data and analysis skills.
Data scientists often know what users are doing, but not why.
Business pros often know why users behave a certain way, but not how many people share that behavior or what other measurable patterns or relationships exist.
When you collaborate, you can answer both. For example:
Use behavioral data to validate patterns from your part of the business.
Compare qualitative pain points with event data or churn logs.
Review user anecdotes from UX interviews and feedback surveys to supplement friction data to tell a holistic story of the user experience.
Compare sales text transcripts and marketing data to understand the end-to-end customer journey.
When you can connect the dots between what users say and what they actually do, especially if you can tie it to outcomes like revenue, your work doesn’t just tell a story; it can lead to decision making and business impact.
Additionally, both teams win. You gain exposure to new data tools and a deeper understanding of how metrics tie to user experience.
The data team gains a fresh lens for interpreting data, access to the commercial side of the business and a domain expert, and extra bandwidth for analysis or visualization.
Start small, but be consistent
You don’t need an open role or a formal rotation to start collaborating or even using data. Sometimes it’s one project, one question, one shared document.
Start with what you have access to - dig into the dashboards you can access with a list of questions you have that are relevant to your role or team. Bring any interesting patterns or insights to the data team, perhaps for a collaborative project or a project you own, but they can provide oversight and guidance for analytics methods.
Final Thoughts
If your goal is to pivot into a data analytics role but you’re frustrated that you’re on the outside in a different part of the business, realize that you have important business skills and domain knowledge that a lot of technical folks lack.
If you can bridge the gap between business and data, between qualitative stories and quantitative evidence, you’ll quickly build a positive reputation for helping drive good decisions.
So reach out. Be curious. Offer help. Bring what you know to the table and use collaboration to learn the rest along the way.
What do you think? Have you made a pivot from an unrelated fucntion into the data team? Are you trying to make such a pivot? Tell us about it in the comments.
Great post! Those are some similar methods I used before I had "data" in my title. Build your skills and reputation for doing data in the role you have, and you'll gain experience in no time.