How to measure a successful mentoring program

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What comes to mind when you think about measuring a successful mentoring program? If you're considering a digital solution, you might think of web-based questionnaires with lackluster response rates. Or if you're like most schools, you consider positive career outcomes an indicator of a successful mentoring program.

Evaluation and measurement tools should do two things. First, they should make it easy to document student outcomes. Digital tools should also shed light on potential problems as they unfold in mentoring relationships. Career counselors need data in the early stages of a mentoring relationship to intervene when there’s still time to right the ship.

According to a study by the CTS Journal, many universities use student outcomes alone as key performance indicators.  But a successful mentoring program is only as strong as the meaningful connections it fosters. A mentoring relationship is not a succulent - it needs nurturing to flourish.

 

Photo courtesy Charles Deluvio.

The PeopleGrove mentorship platform includes customizable dashboards. These dashboards are useful for tracking many mentoring relationships at the same time. This big-picture perspective makes PeopleGrove a key partner for small staffs. There will always be more students than staff and a mentorship platform makes a scalable mentoring program possible. Also, having metrics on the progress of mentoring relationships, help prove a program's value.
 

STANFORD'S  STORY

In addition to the significant trends, you can watch specific mentor-mentee relationships. Stanford University’s Career Catalyst team started using PeopleGrovein 2015 to create a successful mentoring program. The program was not broken - Stanford graduates have never struggled with finding good jobs. But, that does not mean the career catalyst program was as effective as it could've been.

The traditional six-month single-mentor relationships that Stanford used often left students confused and disappointed. The career catalyst team found that their initial model did not appeal to a generation accustomed to constant connection.

PeopleGrove's analytics features helped Stanford's team understand how students connect with mentors. They found out that students often got stuck at the ‘choosing a mentor’ stage. The ability to see these hurdles in real time empowered the team to intervene before it was too late. They began offering students more training to address outreach and communication issues. PeopleGrove's 'User funnels' helped them track the status of mentoring relationships.

 

Photo courtesy Nirzar Pangarkar.

PEOPLEGROVE ANALYTICS APPLIED

 Imagine this. Hannah, an engineering student, makes a university career center appointment. Hannah indicated she had been trying to find an alumni mentor without success.

As PeopleGrove admins, career counselors can diagnose Hannah's problem before the appointment. Admins can drill down to the user-level view to see how many times Hannah has initiated outreach (e.g., the number of times she clicked "Let's connect"). Career counselors, armed with PeopleGrove analytics, see that Hannah has clicked to connect with 26 different potential mentors.

Right away, it is clear that when Hannah says "she tried to find an alumni mentor," she means that she tried to connect with everyone. What is more telling is that Hannah took no further action to make a meaningful connection. Before Hannah’s appointment, the career counselor can prepare the appropriate materials. Often all it takes is a little push in the right direction at the right time to make a more successful mentoring program.