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If business isn’t your thing, I’m sorry to say, but maybe data isn’t either…

I’ve definitely been there myself and learnt things the hard way. Early in my data leadership career, I focused myself and my team around a data strategy that had nothing to do with the overarching business strategy.

If anything, it was a list of bullsh*t: Deploy this tool by this date. Close all tickets in 24 hours. Create a suite of dashboards. Run n experiments in Q2. The list went on like that and I thought I was doing a great job. I’d update with exec proudly with ever milestone I hit.

But the entire plan/roadmap for my data function, the things we would get up every morning to work on, was 100% a list of activities to complete, and we thought we were kicking ass 🤦🏼‍♂️

None of it, I repeat none of it, had any correlation to what the business wanted to accomplish and did SFA in helping us get there.

I know what you’re thinking: “he’s about to tell us to align everything we do with the business strategy”. And yes, alignment is the real lesson here. But there's a step before that you don’t wanna miss. And it's the one that’s caught me out in the past too.

I’ve often assumed there was a solid business strategy sitting above me to align to. But so often there isn’t. Just as with my own “data strategy” it too was its own list of ambitions and targets with no real choices behind it, the exec version of my dashboard checklist. Aligning to it perfectly would still have left me also building on sand…

So the real starting point comes earlier than alignment. Before you point your data work at the business strategy, you have to work out whether it's a real strategy at all. Don’t blindly follow an “org strategy”. You have to pressure-test it first.

Let’s look at how 👇🏻

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👋 If you’re new here: I’m the former Global Head of Data & Analytics for Pizza Hut’s Digital Business and have working data roles in investment banking, multibillion dollar oil & gas projects and tech start ups. Four years ago, I went out on my own as a coach and advisor to data leaders at some of the world’s most well known organisations. I’m currently writing my first published book on data leadership and strategy due out in 2027. I’m super active on LinkedIn and Instagram. I help data leaders and data entrepreneurs succeed and I can help you too. Grab time with me.

This is what I missed back then and what I see many data leaders missing today. When a business strategy lands on your desk, the instinct is to get moving and shape a data roadmap that is aligned and responsive. That instinct is where a lot of data leaders get stuck, thinking they are doing the right thing. But a roadmap built on a strategy that is packed with holes inherits the gaps in that strategy, and you end up building the wrong things regardless.

1️⃣ Your data roadmap literally makes no sense. If you don’t correctly know what the business is building towards, how can you know what to do in data.

2️⃣ You’re saying yes to the wrong things and of course no to the right things. That’s a sucky position to be in.

3️⃣ Your metrics tend to measure activity rather than progress, because nobody defined what winning looks like, or it has been defined poorly

4️⃣ Bad business strategies tend to change quickly as they inevitably fail. The effort that you’ve poured into what you thought was the right thing is wasted and you’re back at square one.

5️⃣ You carry the reputational cost of a failure that was not really yours.

The good news is that this is a skill you can apply the moment the next so-called “strategy” doc arrives. The tests below borrow from Good Strategy Bad Strategy by Richard Rumelt and Playing to Win by Lafley and Martin. If you want the fuller picture of what a strong strategy should contain, I covered that here.

1. Look for a diagnosis, not just ambitions. Ask what core problem the strategy exists to overcome. No clear answer means there is nothing underneath the ambition for you to support with your data initiatives.

2. Find the hard choices. Ask what the organisation has chosen not to pursue, and who it has chosen not to serve. If everything is a priority, nothing is and tradeoffs must be made if we hope to succeed.

3. Check that "how we win" is made really clear. There should be a specific, defensible advantage named. If it is missing, or could describe any competitor, the strategy has a hole in it.

4. Turn it into a prioritisation decision. Take a live request you’d typically receive and ask whether the strategy tells you to do it or not. This should become a filter for the vast majority of your work.

If the business strategy holds up, build with confidence and point to the specific choices your work supports. If it does not, take the gaps back upstream to your exec teams and ask better questions before you commit your team to supporting it.

Most data leaders were never trained to read a strategy this way, which is exactly why it is worth getting good at. It is one of the things I spend most of my time on with the Heads of Data I coach and it is absolutely essential for future data leaders who hope to have an impact. If that is where you are stuck, let's talk it through.

Free resources:
Data Leadership Playbook · Data Career Compass · Data Leader Assessment

Tristan Burns
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