From the course: Problem Identification and Solution Design for Data Scientists

Looking at the project from the sponsor's point of view

From the course: Problem Identification and Solution Design for Data Scientists

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Looking at the project from the sponsor's point of view

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- Your time with a project sponsor is precious. You'll both be busy, so you won't have unlimited access to each other. Let's pause and think about the project from their point of view. As a data scientist, you may or may not have a boss that is also a data scientist. But your project sponsor almost certainly is not a data scientist. They're most likely to be a manager or director of a particular part of the business, like marketing, operations, or customer service. It's conceivable that your contact is a data leader that has been asked to lead the project and that you only have indirect access to the project sponsor. If so, ask to meet with them directly. Now, they probably have a certain curiosity about data science, machine learning, predictive analytics and AI. They might even be curious about you, especially if you're external. If you let it go there, your conversations could be a speculative chitchat about whether or not you think you'll use XGBoost or deep learning. Two or three minutes of that might establish a bond, but I wouldn't squander much of your time together that way. The one topic that your project sponsor is an absolute expert on, more so than anyone else, is the problem from their point of view. So they'll know the numbers and the dollars associated with that problem. That's what you want to spend your time together talking about. Now, they might be surprised that you will be so curious about that, but you should be trying to understand their KPIs. I'm sometimes quite blunt about it, with questions like: "How will the success of the project be judged? Do you specifically have KPIs that you have to monitor, and what are the current values and targets for those KPIs?" Now, I spend a lot of time in the LinkedIn Library watching data science and machine learning courses. That's probably not surprising. What might be more surprising is that I'll frequently watch courses on marketing, finance, supply chain, and sales. Why? Because I'll watch them to prepare to meet with a project sponsor that works in those specialties. There's a good chance that some recent event triggered the project. I've had projects over the years where the triggering event was dramatic enough that it was in the newspaper. It's common enough that I'll ask. I frequently hear some kind of story in response. I also ask if there is a future event coming up that might have inspired the urgency. End of quarter or year, maybe a board meeting, promotion, new boss, new or altered KPIs, maybe even a missed target? Now let's revisit the technology and solution side of things. The project sponsor might mention a technology or solution that they have in mind. I always listen and listen carefully, but I'm always a bit skeptical and I want to know the source. It could be a recent conference presentation, a suggestion a vendor made, or maybe even a single sentence in a social media post. Make note, remember the suggestion, thank them about it, but draw out this information about the source. In other words, listen, but be skeptical. Concentrate on what they know better than anyone else: the problem.

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