How to match Mentors and Mentees? Step-by-Step guide to matching in mentoring programs

One of the most important aspects of any mentoring program is matching mentors with mentees. The participants’ subsequent satisfaction, the regularity of meetings, and the actual results of the mentoring depend to a large extent on the quality of this process. This is confirmed by research that you can find in the latest report we’ve prepared.

You can have highly qualified mentors, well-developed program communication, and an extensive resource library. However, if the mentoring pair isn’t a good match, even the best-designed program may not yield the expected results. It’s no coincidence that organizations are increasingly asking not only: How do we launch a mentoring program?, but also: How do we effectively match people?

Why is matching so important?

A mentoring relationship is based primarily on trust, openness, and mutual understanding. A mentor is not a trainer, and a mentee is not a passive recipient of knowledge. Both individuals must feel that their collaboration is meaningful and provides an opportunity for honest conversation.

A good match doesn’t mean finding two people with identical profiles.

In practice, the following turn out to be more important:

• areas for the mentee’s development,
• the mentor’s experience,
• mentoring goals,
• work style and communication style,
• expectations regarding the process,
• the participants’ time and availability.

Only by combining these elements can we build a relationship that will last for months to come. At Mentiway, we have repeatedly observed that carefully matched pairs are one of the most important factors in the success of a mentoring program.

What happens when matching isn’t well thought out?

Many organizations start by manually matching participants. At first, this seems like a good solution. HR knows the participants, talks to them, and tries to find the best matches. The problem arises, however, when the program begins to grow. With a dozen or so pairs, this is still possible. With several dozen or several hundred, it becomes very difficult. In practice, typical problems then arise.

Some people are selected exceptionally often, while other mentors remain unused. Some decisions are made intuitively. It is also more difficult to ensure that participants feel the entire process is transparent. As a result, the organization cannot be certain that it has actually created the best possible mentoring pairs.

The Three Most Popular Models for Matching Mentors and Mentees

There is no single, universal method of matching. Depending on the organizational culture and the nature of the program, different approaches can be used.

1. Recommendations for Mentees

This model strikes a very good balance between participants’ autonomy and the organization’s control. Based on data regarding experience, competencies, and development goals, the system suggests several of the best-matched mentors to the mentee. The participant then selects the person with whom they would like to have an introductory meeting. This gives the mentee a sense of control over the process, while at the same time sparing them the need to review dozens of profiles on their own.

This approach increases participant engagement right from the very first stage of the program.

2. Mentor Directory

In this model, the mentee is given access to a complete list of mentors and independently chooses the person with whom they want to work. The advantage is the participants’ high degree of autonomy. However, a challenge arises when some mentors become very popular, while others receive no requests. Additionally, participants often base their decisions on first impressions or the mentor’s position rather than on how well the mentor actually aligns with their development needs.

3. Organization-Side Matching

This solution is particularly popular in large mentoring programs. The algorithm analyzes participant data and suggests the optimal set of pairs, and the program organizer can approve or modify the recommendations.

This approach allows us to view the program as a whole and ensure not only that individual matches are made, but also that the workload among mentors is balanced and the quality of the entire process is maintained.

What really makes for a good fit?

Just a few years ago, matching was often based primarily on the position or department in which participants worked. Today we know that this is definitely not enough.

A good match takes many factors into account simultaneously. First and foremost, the mentoring goals and the mentee’s areas for development are analyzed. The mentor’s experience, competencies, and area of expertise are also important. Communication style and preferences regarding collaboration are also playing an increasingly important role. Two people may have excellent competencies but completely different styles of conducting conversations and working on development.

Modern mentoring programs also use artificial intelligence and advanced scoring algorithms that analyze participants’ responses and their qualitative descriptions. As a result, the matching process is not based solely on intuition.

How does the matching process work at Mentiway?

At Mentiway, we consider the matching of mentors and mentees to be one of the most important stages of the entire mentoring program. The process begins as early as the participant recruitment stage.

Each person provides information regarding:

• work experience,
• competencies,
• areas of specialization,
• development goals,
• interests,
• preferences regarding cooperation.

The algorithm then analyzes all the data and generates suggestions for the best-matched pairs.

Depending on the program model, an organization may:

• approve the match on their own,
• allow mentees to choose from among recommended mentors,
• make the mentor directory available,
• combine several methods at the same time.

Importantly, the system doesn’t just optimize individual pairings. It takes the entire schedule into account, making the matching process fairer and more effective.

Matching is more than just technology

Even the best algorithm cannot replace a well-designed mentoring process. Therefore, effective matching should be supported by:

• clearly defined program objectives,
• well-trained mentors,
• a well-thought-out onboarding process for participants,
• monitoring the activity of pairs,
• regular evaluation of the program’s results.

It is precisely this combination of technology and the right methodology that makes mentoring both scalable and highly personalized. Learn more about this at how to measure mentoring effectiveness, in this article.

Summary: Good mentoring starts with a good match

You could say that matching is the moment when a mentoring program really begins. It determines whether participants will want to meet regularly, whether they will build a relationship based on trust, and whether they will achieve their development goals. That is why it’s worth moving away from random or purely intuitive pairings of participants.

Modern mentoring is based on data, transparent rules, and a process that takes into account the needs of both parties in the relationship. Well-designed matching is one of the best investments in the success of the entire program.

Want to see how matching works in practice?

We have prepared a presentation showing:

• The 3 most popular models for matching mentors and mentees,
• the advantages and limitations of each,
• an example matching process,
• ways to use AI and scoring in mentoring programs,
• Solutions used by organizations that use Mentiway.

Schedule a demo or contact us—we’ll show you how to choose the right matching model for your mentoring program.

FAQ – Matching Mentors and Mentees

How to Match a Mentor with a Mentee?

It is best to take into account the participants’ development goals, the mentor’s experience, competencies, work style, and preferences. The more data the matching process takes into account, the greater the chance of a successful mentoring relationship.

Should a mentee have a say in choosing a mentor?

Yes. Many organizations use a recommendation model in which the mentee chooses from among several mentors who are the best fit. This increases engagement and a sense of influence over the process.

Can matching be done manually?

Yes, but as the number of participants grows, this becomes increasingly difficult. That is why many organizations use mentoring platforms to support the matching process.

What data should be considered during matching?

First and foremost, career goals, professional experience, skills, areas of expertise, interests, and preferences regarding collaboration.

Can AI help match mentors with mentees?

Yes. Algorithms can analyze both numerical data and qualitative descriptions of participants, making the matching process more accurate and objective.