What I Actually Did When I Became a BI Leader

When I stepped into the BI Manager role at the start of 2024, one thing became clear within the first few weeks: being good at data wasn't going to be enough. Not for my team, and not for the value we needed to create.

The landscape was shifting too fast. AI was beginning to do things that used to define a BI analyst's day. And the organisations we served weren't looking for more reports — they were looking for answers to questions they hadn't fully formed yet.

So instead of waiting to see how things played out, I made a decision: we were going to change how we worked before the market forced us to.

The first thing I introduced was something simple but deliberately uncomfortable — bi-weekly data storytelling sessions.

Every two weeks, someone on the team brings a piece of data or a visualisation they found interesting. Not a finished report. Not a polished deck. Just something that caught their attention — and they have to present it as a story.

The rule is this: the data alone is not enough. You have to tell me what it means for a real business, a real client, a real market situation. You have to make me feel the so-what.

It sounds straightforward. In practice it's surprisingly hard — and that's exactly the point. We're building a muscle that most BI teams never develop: the ability to translate raw information into a narrative that compels someone to act.

Because that's where I see the future of BI heading. Not in the technical complexity of the analysis — AI is rapidly commoditising that. But in what happens after the insight exists. Who can take it somewhere? Who can make it land?

Beyond the storytelling sessions, I've been pushing the team to develop four capabilities deliberately:

1. Bridge data and business reality

Understanding a number is not the same as understanding what it means in the context of a client's competitive pressure, a market shift, or an internal tension nobody's talking about yet. We train for that gap.

2. Deepen business acumen

A BI team that only understands data will always be one step behind the conversation. A BI team that understands how the business actually works — commercially, operationally, strategically — gets invited into the room earlier.

3. Master persuasion and narrative

The most sophisticated analysis in the world is worthless if it doesn't move someone to a decision. We work on this explicitly — not just what we say, but how we frame it for different stakeholders.

4. Embrace AI — deliberately, not reluctantly

This one is non-negotiable. Staying current with AI tools and understanding how to direct them effectively is no longer optional for anyone in data. I make this part of our team's regular learning, not an afterthought.

The goal of all of this is a shift in identity — from a team that produces reports to a team that guides decisions. From data operators to strategic partners.

We're not fully there yet. But we're moving — and moving with intention.

If you're leading a BI or analytics team — or trying to make the case internally for why this kind of evolution matters — I'd genuinely like to compare notes. This is one of the things I think about most in my current role, and one of the reasons I started writing here on Beyond the Dots.