How to Match Mentors and Mentees Using Matching Software

Effective mentor matching plays a vital role in the success of a mentoring program. It sets the foundation for a productive mentoring relationship within your organisation. Companies around the world have seen the need for mentorship programs. LinkedIn Learning has identified mentoring among the top three focus areas for Learning and Development in 2024. In another survey, 9 out of 10 workers reported feeling happy in their jobs with a mentor in place. 

Because of its importance, it is up to you (as the program administrator) to carefully assess how to match mentors and mentees. But how do you make the best matches? And can you guarantee that these potential matches will be a success?

Factors to Consider When Pairing Mentors and Mentees

Organisations with mentoring programs had 18% better than average profits compared to those without one. Because of the benefits that organisations get from mentoring, most organisations now have mentoring programs. If you are manually pairing mentors and mentees, here are some of the things you need to consider to create successful matches:

• Should you match candidates from similar or different roles (ideally you ask people what they want; don’t make assumptions)? Does the mentor need to have a longer tenure in their position compared to the mentee?
• Do the candidates have similar objectives for joining the mentorship program? 
• How different are their personalities? Do they need to have the same values?  
• What are their long-term goals in their careers? 
• Do they need to have the same available hours? Or do they need to be from the same location? 

You need to consider these factors when manually pairing mentors and mentees. By establishing clear matching criteria, you’ll be able to increase your chances of a successful match with your organisation’s mentoring program. 

The Problem With Manual Matching

Unfortunately, manual mentor matching can often be influenced by unconscious bias and unhelpful assumptions. Mismatched mentor-mentee pairings are among the most common mistakes that program administrators make when they choose to pair candidates manually. The mismatch can often lead to unproductive relationships and frustrated participants – resulting in the mentoring program having a poor reputation. 

As the program administrator, you need to stop playing matchmaker and pairing mentors and mentees because you think they will be a good fit. Making assumptions that a mentor will be a good fit for someone because they are more experienced and in the Department doesn’t help – what if that mentee wants a mentor in a different Department because they want to explore other career opportunities? You shouldn’t make pairings based on any assumptions or unconscious bias. You also need to importantly consider personality and values when matching. These are some of the biggest predictors of mentoring program success. 

Another issue with manual matching is the time taken to effectively pair mentees and mentors. It is manageable to manually pair 10 or 20 people if you have to, but anything beyond that becomes incredibly time-consuming. Before using Brancher, some of our customers disclosed it took them a full week to conduct mentee-mentor pairing with 6 senior staff in a room reviewing and approving matches. 

The best way you can remove these dilemmas and maximise your chance of achieving >90% average matching satisfaction is through a mentor-mentee matching software like Brancher. 

How to Match Mentors and Mentees Using Mentor Matching Software 

Brancher’s mentoring software has a proven science-based AI matching algorithm that can minimise unconscious bias in mentor matching. Brancher is the only mentoring software worldwide to match based on personality and values – the biggest predictors of mentoring success. Brancher also considers skills, goals and other customisable options.

Brancher offers three mentor matching options that you can choose from: 

• Admin-Driven: Allows administrators to match users based on suggestions from our unique science-based AI algorithm.
• User-Driven: Allows users to select a mentor by presenting them with their recommended mentors (and highlighting the top 3). The recommendations are fuelled by the science-based AI algorithm.
• Hybrid: Users are allowed to self-match for a set period of time. The administrator then steps in and ensures that everyone is matched by a certain date. 

Brancher’s mentor-matching software makes it easy to run an effective mentoring program. Our mentor matching app allows you to match and manage small or large numbers of participants without sacrificing quality and resorting to any biases. 

We can’t guarantee a 100% perfect match every time, but we can guarantee you will have the most evidence-based matching approach worldwide. We are the only platform using the latest research from the behavioural sciences to inform our mentee-matching algorithm and as a result, we create matches that matter.

Our average matching satisfaction is over 90%, with some customers at 100%, thanks to our mentor matching software. Call us today to book a demo and see the best mentoring software in action. 

Resources:

1. LinkedIn Learning. (2024). Workplace Learning Report 2024. https://learning.linkedin.com/resources/workplace-learning-report.

2. Wronski, Laura, Cohen Jon. (2019, July 16). Nine in 10 workers who have a career mentor say they are happy in their jobs. CNBC, SurveyMonkey. https://www.cnbc.com/2019/07/16/nine-in-10-workers-who-have-a-mentor-say-they-are-happy-in-their-jobs.html.

3. Cantalupo, Gracey. (2022, May 19). Does Mentoring Still Matter For Fortune 500 Companies? Forbes. https://www.forbes.com/sites/forbescommunicationscouncil/2022/05/19/does-mentoring-still-matter-for-fortune-500-companies/?sh=446eb40b5d8c.