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🪿 Talk to me Goose.

I’ve been AWOL a little over April and May.

I was visiting family at home in Australia for Easter as well as a celebrating milestone birthday (I’m not saying which one) and dropped the ball on the newsletter.

However, one very cool thing that did happened was this👇🏻

For my birthday I was gifted a joy flight in a fighter jet. (I posted about it here)

Now that bucket list item is ticked, on with this week’s newsletter!! 🪣✅

Strengthening Collaboration Between Data Teams and the Wider Business

I’ve worked in environments where collaboration with data teams was low and relationships were fragile.

Specifically, I can recall working in a product org where product managers would come to my data team and ask about a new feature they’ve just launched, wanting to know “how’s it doing?” when they never even told us they were launching it in the first place!

We didn’t know what the feature was, what metrics they were interested in, what KPIs it was aligned to, and there would almost certainly be no tagging in place.

This was a symptom of a fractured and poor relationship with that business unit, where collaboration was unfortunately very low.

It made us feel like our team was working in isolation.

How you ever felt that? It looks like this:

Requests come in last minute, decisions are made without data input, and your team is seen more as a service desk than a strategic partner. Yep, that old chestnut.

It leads to better decisions, faster delivery, more relevant insights, and greater appreciation for the value your team brings. When collaboration clicks, data becomes a shared asset, not just a specialist function that no one else gets.

Unfortunately, without intentional effort, collaboration stays surface-level. Misunderstandings build, trust erodes, and the business continues to see data as something they use after decisions are made - not ideal!!

This week’s poll question:

Always the last to know

When data teams are on the periphery, and collaboration is low, success is hard to come by.

Here are some of the key impacts this dynamic cultivates:

🤷‍♂️ Data is treated as an afterthought

When collaboration is weak, the business doesn't bring in data early enough. Your team is stuck validating decisions instead of shaping them.

😬 Misaligned expectations and rework

Without shared understanding, requests lack context, deliverables miss the mark, and your team wastes time chasing unclear goals.

🤬 Frustration builds on both sides

The business feels the data team is slow or unhelpful. The data team feels overwhelmed, under appreciated, and misunderstood.

😑 Low impact, low influence

If collaboration stays transactional, your team won't get visibility or influence, limiting your ability to drive real business value.

The good news? You don’t need a reorg or new tooling to fix this. A few strategic shifts can change the dynamic entirely. Let’s take a look at how👇🏻

🛠️ How to improve cross function collabs

Establishing strong collaboration with other functions is a key step in the data leadership journey. Collaboration isn’t about working harder, it’s about working smarter together.

Here’s how to build stronger, more productive relationships across the business:

1. Embed data roles in cross-functional teams

Rather than sitting around waiting for requests, have data people sit alongside product, marketing, or ops teams. Proximity builds trust and gives data a voice earlier in decision-making.

It doesn’t need to be a formal decentralised team structure. This can still be achieved within a centralised model, providing sufficient guardrails are in place.

2. Co-create goals, not just outputs

Start projects by aligning on what success looks like, not just what data is needed. This encourages shared ownership and reduces confusion. It also exposes the data team to a wider variety of business nuance and challenges.

3. Improve your intake process

If everything comes through as a ‘data request’, rethink how the business engages with your team. Use forms, triage meetings, or office hours to clarify needs early and reduce back-and-forth. I recently wrote about how to do this here. 

4. Teach teams how to work with data

Run simple training sessions to help non-data folks understand what’s possible, what’s not, and how to ask better questions. This empowers them and saves your team time.

5. Celebrate shared wins

When collaboration leads to impacts like increased conversions or smoother operations, shout about it. Acknowledge both the business and the data team’s role in the outcome.

Karma works in business as well. Publicly recognise great work done by other teams and you’ll see that good will come back to you in droves.

When you make collaboration a priority, your team stops feeling like a reporting function and starts acting (and being treated) like a true strategic partner.

⌛️ Taking new clients for June

I work with data professionals like you looking to supercharge their careers and grow into influential and unstoppable data leaders.

If you’re curious or you’ve been thinking about working with me, make sure you book in your free 1:1 intro call right now. Availability for starting in June is limited.

To book in your free 1:1 intro session click here - availability limited!

Tristan Burns

Find me on LinkedIn or Book a 1:1 call