How to Match Mentors and Mentees in Mentoring Programs: Matching Strategies and Free Matching Simulator

We hear a common refrain from talent development and HR leaders who attend our annual Virtual MentorCom and monthly Mentoring Spotlight events: How do I match mentors and mentees? While matching participants at scale is one of the core features of MentorcliQ’s tool, mentor matching is not always straightforward. That’s because you can match mentors and mentees in various ways. The matching option you ultimately land on can vary by program and could even change between cycles for the same program.

There are multiple matching strategies that can be effective under different circumstances, including:

• Manual matching (relies on spreadsheets and manual surveys)
• Admin matching (software-based)
• Self-matching (software-based)
• Suggested matching (software-based)
• SMART Match (automated and software-based)

Any of these can work, although you will likely find far more benefit with matching scalability, speed, and accuracy using a software-based matching strategy. In this post, we’ll walk through all of the matching options commonly used by experienced program administrators and help you determine which is best for your needs. As a bonus, we’ve also created a free matching algorithm simulator to help you understand the potential results you’d get using mentoring software.

What Mentor Matching Options Are Available?

All great mentoring relationships start with a strong match. Within the platform, program admins have four potential options for matching participants:

• Manual Matching: The traditional matching approach that relies on hand-matching participants using intuition or through survey-based data coordinated within spreadsheets.
• SMART Match: The overarching matching technology that can be combined with other matching styles that can automatically assign mentors and mentees into relationships.
• Suggested Match: Allows participants to recommend a match they’d like to have the program admin make on their behalf.
• Self Match: Allows mentees or mentors to pick independently.
• Admin Match: Allows the admin to choose who to match together from the entire list of participants.

It’s important to note right out of the gate: No one matching option is superior to any other matching option. It all comes down to your program design, population size, preferences, and other program needs. That’s why multiple matching options exist for you on the platform. Different options help give you the flexibility you need when you’re building out your program architecture.

Let’s break down each of these in a bit more detail.

Manual Matching

Manual matching is the traditional strategy used by mentoring program admins for decades. Most people are familiar with the core concept of manually matching mentoring participants:

• Create a list of mentors and mentees
• Create profiles of all participants (or ask participants to create their own profiles)
• Review profiles and, based on profiles and personal engagement with participants, match mentors and mentees together.

This strategy was the most common approach for years because it was the only approach. Spreadsheets like Excel made this process a bit easier, as they allowed for the organization of information in a more structured format.

However, matching manually has always been a nightmare. I’ve even heard stories of program administrators sitting on the floor in the middle of the night, with printed-out profiles in front of them, struggling to figure out which mentors should be paired with mentees.

Manually matching participants is the most limited and riskiest way to run a mentoring program.

• Manual matching limits program size
• Manual matching increases time investment required to launch and manage programs
• Manual matching introduces bias into the matching process

Manual matching in the wild

If you need an example of why manual matching is more trouble than it’s worth, this Stack Overflow post offers a great example of why.

The poster came to Stack Overflow for help as they were attempting to match participants manually. As they stated in the post:

Unsurprisingly, they got few answers, primarily because manual matching is always guesswork. And as the one person who did respond noted:

“What happens if there are say 5 mentors and 7 mentees in the same program?
What happens if there are programs that have mentees but not mentors?
It’s difficult to see how you could program a definitive solution, but you can get Excel to group things for you to use your judgment to complete the process.”

Their biggest hurdle was that there’s no formula that will bear good results when trying to match mentors and mentees. They needed an algorithm, instead.

To break it down:

• A formula tells you the relationship between two things, or what to calculate. Formulas can get very advanced, but they won’t solve a complex matching problem.
• An algorithm tells you how to perform a calculation or solve a problem, often by applying one or more formulas in a specific order.

In layman’s terms here, formulas do the calculation, but algorithms explain how to do the calculation. Matching without algorithms is like driving a car with no steering wheel. It’ll run if you turn it on, and it’ll move, but you can’t steer it in the direction you want it to go.

This is the reality that exists for small organizations or for admins struggling to get internal support for programs. If you can start small with a manual program and prove why it’s valuable, you may be able to get internal support for a software-based approach.

SMART Match

SMART Match simplifies the matching process and produces the highest quality match for ALL your participants. MentorcliQ’s SMART Match is built using the scientific framework established in the Nobel Prize-winning Gale-Shapley algorithm. It delivers a great match to your participants, no matter when they enroll or request a match.

Most mentoring platforms offer “Bulk Matching” which matches all participants in the program at the
same time. With this basic approach, you lose out on match quality for your participants because the further they are down the list, the lower their match quality.

Alternatively, MentorcliQ’s SMART Match calculates match scores for every relationship combination while also factoring in matching rules, suggested matches, and other program-configurable variables. The algorithm then looks at the matching landscape to find an optimal set of matches across the entire population of participants.

In addition, each time you run SMART Matching, you have a control board of adjustments that can be applied to the matching algorithm so you can control the process.

Suggested Match

Suggested Match utilizes the same technology as SMART Match, but with some caveats. Instead of automating who gets matched or letting participants pick their own match (as with Self Match), participants can see a list of matches with the match score provided. They can request to be paired with different individuals based on their own preferences. The admin can then reject or deny that match. This method gives program admins and program participants much more flexibility and collaboration in the matching process.

Self Match

Self-directed matching in a mentoring program means that either A) the mentee finds and picks a mentor, or B) the mentor finds and picks a mentee. This is an exceptionally common matching option as it fits well with most mentoring programs.

Admin Match

Admin matching is when the administrator(s) of the program make the match for each mentor and mentee. They may do this in consultation with the participants, with other administrators, with other managers and leaders, etc.

This matching option is leveraged by the SMART Matching technology, so program admins can visibly see the matching scores before matching participants. Of course, you can match participants in any way you want through Admin Match. In this matching style, the scores will help give you critical intelligence into the chance that the relationship will be effective.

Aglorithm-Based Matching Simulator

The Gale-Shapley algorithm is the core framework for all matching software (including ours). The differentiator for all matching software is how it’s refined. The key to matching algorithms is unbiased matching at scale.

Use our free tool to determine if your current program size and matching criteria are ideal for successful matches, and what you might need to get the type of successful matches you want.

Which Matching Option Should I Choose?

When designing your mentoring program, one of the biggest factors you will need to determine is how you want mentors matched with mentees.

There are legitimate and even research-supported reasons for choosing either automated matching options, such as SMART Match, or one of the technology-supported matching options with more independent control (Admin Match, Suggested Match, and Self Match). Which one you ultimately land on—and whether you choose to do both within the same program—will depend on a critical review of your organizational needs, program structure, program size, and the needs of your mentoring program participants.

Here are some potential scenarios to consider:

In this scenario, you would likely opt for Admin matching if your incoming new hire cohort is a manageable size. However, if you’re onboarding dozens or even hundreds of new hires at the same time, you’ll get far better results and reduce your calorie burn if you use SMART Match.

MentorcliQ even has an extension of this called Intelligent Match that allows you to completely automate the matching process based on the preset criteria.

In this scenario, you’d likely want to choose a Suggested Match option. This would allow participants to choose their own mentor, but present them with the match scores so that they’re guided toward selecting the best-fit match for their mentoring relationship.

Explore Mentor Matching Options During the Planning Stage

How you plan to have your mentees and mentors matched within the program is a planning stage decision. You won’t be able to effectively roll out your program if you don’t determine which matching method will work best for your organizational needs.

Some criteria that will impact your mentor matching strategy will be:

• The size of your program
• How you will gather data about mentors and mentees to make matches (such as HRIS integration and personality surveys)
• Minimum requirements for program participation (both mentors and mentees)
• How participants would prefer to be matched
• Program administrator bandwidth
• The type of mentoring matches

This list is not exhaustive but should give you the right idea.

Considering what your organization and participants need out of the matching format should be a central part of the planning phase and come well before the program starts enrolling participants. Mentee and mentoring matching will flourish when you’ve effectively structured the matching process in a way that maximizes the success rate of matches and the subsequent mentoring relationships.

With that in mind, though, we’d like to give some additional attention to Self Matching and Admin Matching. Program admins getting their feet wet in running mentoring programs often opt for these two strategies.

The ins and outs of Self-Matching

There are several reasons why you may want to use self-directed matching. This type of matching option can be easily implemented with mentoring software and benefits strongly from the SMART Matching technology.

Mentees and mentors feel a sense of ownership for the match when they choose for themselves. Adults tend to want to have control over their development and learning (i.e., andragogy). Program administrators have limited time, making administrator matching inefficient. Your organization needs to reduce onboarding costs, which can exceed $3,000 per employee.

Many companies come to MentorcliQ because they want to use mentoring software to ease administrative burdens and allow mentees and mentors to find their own mentoring partners. The self-directed mentor matching option that MentorcliQ offers can be configured in many different ways, which not only helps administrators ensure quality matches are made but also helps mentees and mentors take an active role in deciding who they connect with for mentoring.

The matching profile guides the show

Successful matches with mentoring software start with a comprehensive mentoring participant profile. Administrators can configure these profiles so that participants input specific information—such as location, job function, or experiences—that is then taken into consideration when our matching algorithm works behind the scenes. 

You may have a variety of mentoring programs, but let’s take onboarding as an example again.

Perhaps you are running an onboarding program and want to ensure that mentees find mentors who work in the same business unit/job function as the mentee. The algorithm can be configured and weighted so that potential mentor matches must meet that particular condition. This lets you control the program criteria to the degree you need as the administrator, while allowing the participants to have the final say about who they partner with. 

Leveraging an algorithm in mentor matching is a scientifically-based approach that’s also utilized by some of the most popular dating services in the world. (And no, mentoring is certainly not a dating service, but it shares many of the same concepts regarding finding two individuals with similar personalities and interests.)

When should you NOT use self-directed mentor matching?

While I wouldn’t call them negative necessarily, there are some considerations to keep in mind that may make you decide that self-directed is not right for your program.

• Your program structure needs to have certain mentors assigned to certain mentees.
• Your organizational culture includes many introverts who may not feel comfortable asking someone to be their mentor
• You want to maintain oversight over the matches made  

If any of these three factors is true, you may want to consider Admin Matching over Self Matching.

Digging into the details of Admin Matching

Some reasons why you may choose administrator matching as the right fit for your program include:

• Your program structure needs specific mentors assigned to specific mentees
• Your organizational culture includes many introverts who may not feel comfortable asking someone to be their mentor
• You want to maintain tight control over the matches made

Sounds familiar, right? That’s because these are the very reasons why you wouldn’t want to choose Self Matching.

Admin matching isn’t necessarily always about oversight or even about reducing the stress of introverts (both of which can be incredibly important). Deploying admin matching could make far more sense when the program is distinctly skills-based and aligns with certain organizational goals.

For example, since as many as 1 in 5 workers feel personally discriminated against because of their background (according to a 2021 Deloitte survey), your DEI goals may include a reverse mentoring strategy intended to pair executives with employees from historically marginalized populations. 

Technology significantly reduces the time investment for Admin Matching

Placing the matching responsibility in the hands of program administrators has come a long way in the past decade. Administrators now have options like MentorcliQ’s mentoring software to help them deal with the administrative burden of matching participants. Administrators no longer have to suffer through tedious and time-consuming spreadsheets to pair people up. 

Even if you are running multiple programs at once and each needs varying degrees of control, you can configure MentorcliQ to fit each unique program. This means you can actually run a highly controlled succession planning program, for example, in which you make the matches as an administrator while also running an onboarding program that uses self-directed matching. The software is just that versatile.

When should you NOT choose admin mentor matching?

I read an interesting perspective on mentor matching recently. It was part of a story about a business roundtable discussion on mentoring, and in it, Kelly Rich of Amazon Music described being paired with a mentor as she transitioned into her new job with the company.

And therein lies the potential downside of using Admin Matching. Many mentoring participants want to have control over who they connect with and work with as a mentee or mentor, so you risk diminishing their relationship if you force the match.

Still, sometimes it’s just more practical to do an Admin Match. If you do, you should strongly take into account the participant’s match score and only match mentors and mentees who have high match scores.

You may want to avoid admin matching if:

• Your workplace culture values independence and choice for employees
• You have no critical need to maintain control over the matches made

If either of these is true, Suggested Matching and Self Matching may be the best fit for your program.

Still, I’ll reiterate here: MentorcliQ’s mentoring software still uses the matching algorithm in every mentor matching option available to you. Even with administrator-level mentor matching, the administrator can see a best-fit percentage for potential mentor/mentee pairs, which makes the process much easier. 

Create a Strategic Mentoring Program with MentorcliQ

We know that each mentoring format is unique, so we spend time with our clients, guiding them through program design consultations and strategic program planning. What we’ve seen over the years is that most organizations use a combination of matching styles. With one matching option being right in some circumstances, while the other option makes better sense in other situations.

One of the most highly valued and utilized features in the MentorcliQ platform is our SMART Match option. SMART Match looks at every possible combination of every available participant and generates the best possible outcome for all parties involved. It saves admins hours of time that they would have spent on hand-matching people. 

FAQs on Matching Mentors and Mentees