Aim Higher
Why scope-setting matters in data/business partnerships
Good data/business partnerships can still fail to deliver results.
I’ve seen a particular pattern of failure in analytics that deserves some airing out. It’s the kind of mistake that many of us have made at least once in our careers, until we learn to avoid it. It usually goes like this:
Imagine that your business is getting ready to announce an exciting new product. Leading up to the launch, a marketing manager reaches out to the data team to prepare. You, a marketing analyst, work together with that marketer to get all of the data and reporting in order.
On the surface it’s an excellent partnership, and everyone thinks they’re doing the right thing. You ask the smart question: “What’s the business problem you’re trying to solve?” Together, you dutifully gather requirements for the instrumentation, the datasets, and the dashboard updates. You execute. By the time the launch arrives, you’re feeling pretty good about the situation.
And then, on launch day, it’s a disaster.
The requirements only covered the narrow slice of the business that the marketing manager cared about, and that you, as the analyst, knew best. That slice happened to be organic marketing. Paid marketing never entered the conversation.
You didn’t realize that there was a sizable paid marketing budget tied to the launch. Because the paid marketers’ requirements weren’t considered, they were flying blind. Once the issue surfaced, everyone scrambled to fill the gaps. But by then, the business had already missed a critical window of opportunity to reach a new audience.
“Make sure this never happens again,” marketing leaders said.
What went wrong? Everyone was so prepared and diligent. The problem is that we tend to reward analysts for being responsive to their immediate stakeholders, not accountable for outcomes across the business. If analysts are trained to keep their scope neatly in check, who is responsible for seeing the bigger picture?
In situations like this, it might help to consider who the most senior leader is who would notice or care if this work went well or failed miserably.
If the answer is the CMO, then the scope of the work can’t stop with the one stakeholder who reached out. It needs to extend across that leader’s full charter, even if that means venturing into areas that you don’t normally consider.
I get why you might not like to hear this. Expanding scope can slow things down. Analysts are already stretched thin, and this can make it seem like you’re being asked to do someone else’s job.
However, keeping the boundaries too narrow has consequences. It doesn’t matter how good that one data/business partnership is if you wind up failing to address the most pressing needs of the business.
This doesn’t mean you should broaden scope on every single project. I would encourage you to be selective. For large or strategically important initiatives, it’s worth taking a pause in the beginning to ask whether you’re aiming high enough.
There are definitely tradeoffs. For both data folks and business stakeholders, keeping scope contained feels safe and familiar. Looking farther afield might introduce ambiguity and debates. Still, if you stay too narrow, it could be an expensive mistake.
Here’s what we can learn from this kind of story:
Individuals need to aim higher than their immediate comfort zone. If you just deliver what your nearest neighbor asks for, you could miss the opportunity to support the outcome that the business actually cares about.
Organizations, meanwhile, need to make it possible for people to see higher at all. When teams are only weakly connected to one another, you’re bound to have blind spots. This shouldn’t come back to individuals as evidence of personal failure.
Strong data/business partnerships only work if they’re paired with the right scope.