Your project sponsor is the best person to add to your data science team. The biggest obstacles you'll face with this gold user are perceptual.
In over 20 years of consulting, my all-time favorite client was Linda. She reminded me of a Civil War general like Grant, Jackson, or Lee. Instead of hanging out in headquarters from 9 to 5, Linda was deep in the trenches with me -- often into the late hours of the night and sometimes on weekends. She was a manager by title and profession, so she didn't have to get her hands dirty; however, she knew a lot and didn't have a problem applying all her talents and skills to the issues at hand.
Linda's what I call a gold user, and they're the best kind of users to have on a data science project because they're worth their weight in gold. So, when building analytic solutions, develop gold users who can actually practice data science.
Staying in the know
Gold users are primary stakeholders in the business who have a need and the skills to contribute to the solution. On a data science effort, you'll have many stakeholders across different functions in the organization, but the primary stakeholder (i.e., the project sponsor) is the one paying for everything.
All too often, the sponsor acts solely as a high-level decision maker and funding source, even though they're the only ones who are entitled to the value you're creating. The issue with this model is in the inherent lack of context the sponsor has around the solution's development. Data science is a process that involves solving and discovery. So, if the sponsor is not plugged into the discovery, they quickly lose touch with the context and consequently the real issues as they shift over time.
The best way for gold users to stay current with the issues is to put them to work -- this may sound extreme, but it's quite practical. Once you get past the perceptual issues of who's supposed to do what, you'll realize that your sponsor is the best person to work on the project. First, they are very clear on the opportunity and how analytics can solve the problem. Furthermore, they are highly motivated to get this solution in place.
There may be an issue with availability, but that's a matter of priorities. If it's important enough to contribute money, then it should be important enough to contribute time.
That just leaves competency -- do they know enough about data science to make a valuable contribution to the solution? That's up to you.
Helping the hired help
It's easy to get sponsors in a position to contribute; the real obstacles are more perceptual in nature: why is a VP writing formulas or code? Isn't this why we have data scientists? Yes, but that shouldn't preclude your executive from joining the effort when there's real money at stake. This is what I loved about Linda -- she didn't care about how things looked, she just cared about getting things done.
Also remember, you're not trying to teach your sponsor how to be a data scientist -- you're just trying to get them to a place where they can add value to the solution. Your data science team will surround them, so if you structure it properly, they can't do much harm. Since data science is a multi-disciplinary capability, there's a pretty good chance that your sponsor has already developed some ability in one or two areas. Sure, they may not have a PhD in Mathematics, but maybe they have programming skills or maybe they have an eye for data visualizations. Build on their strengths rather than trying to teach them a brand new skill from scratch.
Finally, you should develop a learning and development culture and competency within your team. It's not only about solving problems -- it's also about teaching, mentoring, and finding ways to develop each other. With this infrastructure in place, it's easy for a sponsor to plug in. Your data scientists should be sensitive to the fact that your sponsor doesn't have the same background and experience that they do, and they should welcome the opportunity show your sponsor the ropes.
It's good for a project sponsor to approve a solution, but it's better for them to get into the trenches with the data scientists. This means overcoming the perception that: sponsors shouldn't work, sponsors can't be data scientists, and sponsors don't have time to focus on the hard stuff.
In truth, your project sponsor is the best person to have working on your team, so take some time today to bring your new gold user into the fold. It's time to dust off that college text on Probability and Statistics and put them to work.