7 min read

The keys to avoid mentoring matches hell

storm is coming - innovation copilots
storm is coming – innovation copilots

So you’ve started a mentoring programme, and managed to create some mentor-mentee pairs… After a few months you notice that some pairs are ok, some others or even many others are not seeing each other regularly, or even haven’t gone passed the first meeting. It may be a sign that the match is not a good fit, but it may not only be due to conflicting personalities, your matching process may be the problem.

After nearly ten years of designing and auditing mentoring programmes, I have seen my share of mentoring matches, mismatches, unethical pairings, and downright foolish matching processes. In this article, I’m focusing on the three key criteria of a matching process and explore how they are impacted by the various forms of matching such as random, speed-matching, manual, semi-autonomous and pro-active.

Strategic Focus

As mentioned in our latest white paper on strategic mentoring, when designing a programme it is key to connect it to the company strategy otherwise you take the risk of having just another “nice to have” “good for the people” HR initiative which has no real impact on the business and soon disappears through lack of funds, interest or value. Even the matching process has to be connected to the strategy or at least be coherent with the overall purpose of the programme: for an intrapreneurial mentoring programme we match mentees with external entrepreneurs as mentors, for  internationalisation focus we match cross cultures, for women’s careers we encourage proactive matching and networking.

Pro-active matching is when the mentee goes to find his/her own mentor within the organisation. This practice stimulates networking but also encourages mentees to go out of their comfort zone and be very engaged in their own development. The downside being that mentees might still limit their search to their immediate network, hence reducing the potential for diversity of mentoring experiences.

When matching manually or pre-matching pairs, the coordinating team can keep control of the matching criteria and ensure that the pairs are created following some pre-determined criteria such as cross-BU because we want to encourage innovation, give a wider perspective to mentees (as well as mentors) on the business, and eventually stimulate mobility and knowledge sharing.

One of the worst practices I’ve encountered, meaning with the least (well non existent) strategic focus, was random matching. Mentors were attributed to mentees randomly – with no criteria at all – which led to some lucky matches (as would happen with informal mentoring), many “nice” relationships with no real impact for the mentee or the business and some very disappointed participants who wasted their time.

To keep a good strategic focus within the programme and specifically in the matching process:

  • Avoid random matching;
  • Match or pre-match manually with some very clear criteria linked to strategy;
  • If using more autonomous types of matching, ensure the internal communication is clear on the aim of the programme and give participants strong guidelines.

Involvement and Transparency

The level of involvement of the participants in the matching process is very favorable for a higher degree of engagement in the mentoring programme. Since it has to be a mutual choice, keeping a high level of involvement whilst still effectively creating pairs is no easy task, it is not only a numbers game (getting a critical mass) but a diversity game too – ensuring a wide variety of mentor profiles to cater for the various needs and personalities of mentees. In this regards, autonomous matching is like a dating experience, many might go home single at the end of the day.

However a lower level of involvement can be counter-balanced by a high level of transparency on the matching criteria and decisions.  In many programmes the manual pre-matching process has been a good compromise on that front as it also allows to keep our first criteria (strategic focus) fulfilled.

Manual pre-matching is often used in mentoring pilot programmes. A team of coordinators attributes mentors to mentees according to several strategic criteria (cross-BU, cross-nations, cross generations, etc.) and according to the mentors and mentees’ profiles. The mentoring matches are suggested and submitted to the pairs’ mutual acceptance. Although a time consuming task, a knowledgeable team can ensure that mentees’ needs can be matched to mentors’ experiences, whilst keeping the strategic focus. This practice is limited by the number of participants, with more than 30 mentees to pair it becomes impossible and overly time-consuming.

When the results of the manual pre-matching are announced to participants, the big question that always arises is: “why this mentor?” or “why this mentee?” as the matching criteria might not appear that obvious at first. This is why who-ever is coordinating the matching has to be able to clearly answer this question with for example: “knowing this mentor personally and his experience and evolution as an expert and reading your profile and specifically your needs in terms of understanding the evolution of experts, we thought it would be a good fit”.

So to avoid a low engagement early on in the mentoring relationship, your matching process must :

  • Ensure the participants (mentors and mentees) have a say or some involvement in the pairing choice ;
  • Make the matching criteria transparent and avoid the “black box” effect which may disengage or even create mistrust.

Critical Mass

In a pilot mentoring programme, the voluntarily reduced number of participants allows for more control and testing of various parts of the programme to learn how to adapt to the culture and context of the company. For pilot programmes, the usual number of participants varies between 15 (5 mentees and 10 mentors – to ensure some choice of pairing) to 60 participants (to create about 20 to 30 pairs). These low numbers allow for many possibilities in terms of matching: pro-active, manual matching or pre-matching, but also other practices such as what I call “beauty contests” and “speed-matching”. Low numbers are manageable for a team to manually match and are manageable for a matching event.

“Beauty contest” matching is a good practice for entrepreneurial mentoring programme as pitching in front of a crowd is already a good exercice for future or new entrepreneurs. The idea here is to pitch in front of potential mentors (experienced entrepreneurs) who can then propose to mentor an entrepreneur based on the pitch they have seen and some networking they might have done during the event. This ensures the informed engagement of the mentor.

The problem with small numbers is often the lack of diversity of profiles or just the lack of choice as finding mentoring matches is partly about the professional fit (mentee’s needs fitting to mentor’s experiences) but in a big part about the personal / human fit. For that kind of fit the more choice the better. Also whether you are using beauty contest, speed-matching or other similar practices, several issues emerge: mentees who do not pitch well, are shy, or not comfortable yet with networking events may not be chosen by mentors, some mentors with a strong personality may appear scary to mentees, some people may choose each other for the “wrong reasons” (gaining access to a powerful person in the company)… Many may end up disappointed at the end of the day.

“Speed-matching” is inspired by speed-dating practices and allows mentees to meet quickly several mentors. At the end of the event, a mutual choice will allow for a mentoring pairing.

This is why for a pilot programme in a corporation in order to keep a good strategic focus I would recommend manual pre-matching or pro-active matching with strategic guidance. When using speed-matching or beauty context matching, it is important to ensure that the form is in line with the strategy of the programme:

  • Pitching for entrepreneurs is an opportunity to practice and get feedback;
  • Developing networks and networking practices is part of the company strategy to break silos;
  • Presenting yourself in front of an audience is one of the objectives of the talent programme.

With a successful pilot comes the will to deploy to a larger scale. The pilot might indeed have created a buzz and the context and strategy of the company might call for a large scale mentoring initiative. With more volume comes some great mentoring opportunities: more variety of profiles, more diversity in pairing and wider impact for the business… and more mentoring challenges in terms of matching.

First, trying to match or pre-match manually more and 30 pairs becomes very cumbersome. But beyond the weight of the task is that the matching team may not be sufficiently knowledgeable to be able to create good mentoring matches… Match-making is actually a real job for some people! Like head hunters and dating agencies. This is why some mentoring programmes use automatic matching to deal with high numbers of participants with multi-factor matching issues: algorithmes do the job. So the matching robot will give a percentage of fit between a mentor and a mentee based on information participants will have inputted onto a profile or platform. Of course the factors the algorithmes are using are mostly limited to professional ones.

Looking at research on cognitive biases, allocating a random “percentage of fit” figure to a match is as efficient as a real one. Say a computer tells me that I fit 89% with someone I do not know, I will start the relationship and my brain will interpret or only perceive informations that confirms the positive assumption I made based on  the calculations of  a “trusted, neutral, unbiased” party, even if the figure is wrong. So it will probably end up being a fit.

In order to avoid the automatic matching which may not always be very well perceived by participants (lack of transparency and involvement) and in order to deal with the increased number of people involved, I recommend to go for what I call a semi-autonomous matching.

Semi-autonomous matching allows for a large pool of mentors and mentees (a critical mass of about a hundred is necessary) to find each other via a tool or platform on which their profiles are detailed: their background, experiences, their ambitions, as well as their needs or expectations and for mentors the areas or domains they feel they can be of value to mentees. Usually the mentees browse through mentors’ profiles and select around 3 potential mentors who then can accept or not. Other mechanics can be designed but the key points being the transparency of the process and the possibility to accept or not the pairing requests.

Usually, using this type of matching allows for about 60% of participants being matched via a tool or platform. For the remaining participants, a coordination team suggests some matches just like they might have done for a pilot programme when numbers were limited.

For rolling programmes which do not have a start and end date, a matching team is not necessary, as participants will visit the platform later in the year to see if new mentors could match or if the mentor of their choice becomes available.

So, mentoring matches made in hell or…

It is not reasonable to think that you would get 100% success on the mentoring matches. It is first and foremost a human relationship with its lot of unpredictability. Saying that, the role of a mentoring programme coordination team is to create the best possible conditions for adequate pairings. And when I say “adequate”, it is not just about two people getting along nicely, it is about creating useful, developmental relationships which can strengthen the company’s informal networks to sustain the chosen strategy be it innovation, internationalisation, attracting talent for growth etc.

And remember: to push the matter further, you can grab our free whitepaper on mentoring right here.