There’s a temptation to put air quotes around the words mentor and program, because very few mentor programs are more than a list of people who may or may not stop by once or twice a year. Perhaps the proper thing is to segment mentor programs to make it possible to identify how they use mentors – and how they reward them.
What does it take to be part of your program?
Predicting the future is a hard business, so focus on performance instead of selection. Pay close attention to how often your mentors show up and how they do with the startups. If they do well, keep them.
If you’re just starting your program, don’t sweat mentor selection. Know that rules and pre-requisites can be a poor way to pick mentors. They may make it easier to make the list of potential candidates smaller, but you should be looking for effective mentors – and they come in many sizes. Recommendations work well as do instincts.
How do you manage your mentors?
You shouldn’t have to think about this one. The results matter more than the tools you use. What you’re looking for here is clarity. How active are your mentors? Who is meeting with whom? What is everyone getting out of it? If you want to do it with index cards instead of an app, be my guest, but make sure you’re capturing the data.
What is your churn?
Mentors come and mentors go. Sometimes they’re active and sometimes they’re not. How do you measure their activity? How do you segment them?
Do you keep inactive mentors on your list to make the list look pretty? Do you have a plan for activating inactive mentors? Do you strike them off if they haven’t been coming to your events or meeting with your startups?
What is your mentor cost of acquisition? What is your mentor ROI? How many hours of mentoring does your program provide your startups? Can you answer these types of questions or are there different rules for you and the startups you advise?
Why do the numbers matter?
Your mentors can add absurd amounts of value if used properly. Gathered and used properly, your data can tell you a lot about your program. Does it make a difference to star mentor retention whether your startups visit the mentor’s office or your mentors have to come to you? Ask your numbers.
Your data can show which mentors are good at making introductions and which are good at making teams work better together. It can show your investors how much value the mentor network you built has created. The numbers can prove or disprove your assumptions. And as long as it’s effective, it doesn’t matter whether the data is collected on index cards or an app.
Assumptions vs. Facts
Most of you have assumptions about these questions, but no formal data. You have assumptions about how to attract and keep the best mentors. You’re not alone. Most mentor programs prioritize differently from the startups they work with because no one demands they do what their startups do: test their assumptions. Ask yourself whether that makes sense.