The PM and data team relationship

6 tips on how to create a great working relationship with your BI/Data Science team

Apr 20

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☕ Happy Wednesday morning folks — I hope you’re all having a happy, fun, and productive week so far.

This weeks edition is all about working with the data science team.

Data has such an important role to play at all the different stages of the product life cycle — from pulling info based on your historical data during research, to finding insights from analytics post-release.

The technical skills that PMs have around getting answers from data falls on a pretty wide spectrum — from being fully self-sufficient, to relying heavily on someone from the BI/data team for help even with simple questions. Regardless of where you fall though, you will still work closely with the BI team — just because you're skilled with data doesn't mean you're performing their function.

I definitely started in the camp of PMs who know less. And with that, spent a lot of time working with the BI team, getting feedback, and figuring out what a good working relationship looks like.

So, this week — I’ll focus specifically on answering the following question:

How do you foster a good working relationship with your BI/Data Science team — and what does a good, collaborative one look like?

So, let’s jump into some answers around how you can best collaborate with BI, and how not annoy them.

1. Treat them as a partner.

Like the recent advice given around working with engineers and designers — treat your data science team like partners — it's the most important aspect towards a healthy and collaborative working relationship. Don't just Slack them a request to run a query that you can't, and await delivery. That's the same as treating a designer like a pixel-monkey.

The BI team are very smart and creative people who enjoy thinking about how data can solve problems, plus they are the experts (regardless of how skilled you are). So as the PM, focus on context and goals! Share what you are trying to achieve and why, not just the queries you need run. This gives them room to think in a more holistic solution-space rather than a requirements-space, and the more and better you do this – the more new ideas and novel insights they will come back with.

Plus, the more they will enjoy working with you!

2. Prioritize your asks.

On a weekly basis, I get a look at our BI teams roadmap and have a meeting with our Senior BI Analyst who manages it. And man, do they get a ton of requests. From finance, leadership, marketing, content, me, and the other PMs — everyone has data requests. From the “quick question!" to new dashboards, reports, and larger analyses — people want and need data — and most people want it from them “Now!”.

It's super important to bare that in mind because it shows an understanding of what's on their plate. And while the BI team manage their own roadmap and don't need your help to triage or prioritize their overall TODOs, what is helpful and your responsibility is to be very clear about prioritizing your new and existing asks with them.

This can happen through Slack, but I also find a recurring 1:1 with someone on the BI team where an agenda item is to review the roadmap and your asks together works nicely.

3. Know how the answer will help you.

One of the best takeaways I got from my first experience working with an actual BI team, is that not all questions are worth asking.

I recall talking through one of my requests, and I was asked, “What will you do with the answer when you have it?”. That's a fantastic question, because it gets you thinking about whether the things you want to know are actually going to change anything — which they often won't, and thus are not worth looking into.

Ask yourself this before going to the BI team, and make sure you have a clear and precise answer for how the answer you get is going to be actionable.

4. Develop your own data skills.

This starts with an honest take at your current skillset around working with data. You don't have to be a wiz by any means, but the more you “get” what they do, and the more you can answer your own “easier” questions without adding to their TODOs — the better.

There are many very affordable resources out there to help you level up your data skills, and it's definitely a technical skills worth investing in for yourself and career. If you have someone on the data team you can ask for advice on the best stuff to focus on learning, definitely do that.

4. Share and document the findings.

When you get the answers to your data questions and insights are discovered — share and document them!

Even a quick Slack to a team/channel letting people know what was found, and what you're going to do about it, is a great practice that people notice and appreciate.

Further to sharing info, document it somewhere. For our team, I setup a doc in Notion called “Ongoing Insights”, where one of the sections is “Data Insights”. This is a handy wiki where myself and others can jot down and tag insights and findings. This, along with the other sections in the document: customer/macro(market)/competitive insights — is a goldmine for when reviewing strategy and working on the roadmap planning.

When sharing and documenting insights — be sure to put whoever helped in the spotlight. Whether that's giving them a shoutout for their work, tagging them as a contributor in documentation, or better yet – getting them to actually present and share it to the team. This helps them be seen and appreciated for what they did -- by you, and by others.

5. Find a balance.

Data should be directional, not perfect. This was one of the most helpful things I learned from my manager, and unless you're working on a product that sends people to space or saves lives — it's advice I strongly suggest you take.

By and large, you're just trying to figure out the best direction to steer the ship as quick as possible. This means you want data that is “accurate enough", and where it's just going to be one of the inputs you bring to the decision making table.

This balance between being data-informed rather than totally data-driven not only helps you move faster and make quicker decisions — but it helps you and your BI team to better scope and time-box the asks.

You can always keep working with them to perfect – trying to be more accurate or precise. This is a rabbit hole that can suck away both your time, and some of the BI people you work with may need extra shepherding away from perfection.

6. Ask them what is helpful.

Last but not least – ask them!

Getting feedback from the people you work with is the best insight into knowing how you can make that relationship great.

You might find out how they specifically like data requests laid out, or what level of involvement they want/expect from you with stuff like dashboards, etc.

A simple conversation can uncover a lot, as well as show you're vested in the relationship and being the best PM you can for them.

If you have any additional advice to add to this, I’d love to hear in the comments below! 🤔

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