Peers Crowdsourced: The ultimate solution to recruitment and training

What if you can crowdsource your peers’ knowledge of you to help your recruitment process, the training that your employer provides to you and your personal progress?

A successful crowdsourcing effort requires the active participation of a set of people who will together create value that will otherwise not be created. As we spend most of our days with our classmates, colleagues, clients, professors, etc., they all accumulate invaluable information about us – whether it is useful feedback information for our own progress or evaluation information that can benefit an employer or any institution that we decide to join/create. Leveraging this inside information into a database together forms a very powerful tool of information that creates invaluable value.

Crowdsourcing talent currently exists in another form, whereby platforms bring together a set of recruiters that will each recommend the best-fit talent and the employer will get a pool of say 10 talent recommenders by different recruiters; please see Reflik and Visage[1]. Contests to reward peer-recommendation is also another way that employers are using crowds to find the right candidate; please see The Job Stack[2]. However, what those recruiters don’t have is inside a good 360 inside information into the talent. Why would this crowdsourced data be important?

  • Firstly, it reduces the risk for both the new employer and the candidate to ensure that there is a right fit in terms of expectations, culture, team, etc.
  • Secondly, the employee could use the crowd-sourced data to track his or her progress – as he/she aims to improve. If the employee elects to share this data with his/her current employer, the employer could also help with the adequate training and progress tracking.

The value creation thus happens at both the personal level and at the organizational level. However, how does one capture value?

Employers– as clients to the platform – would pay to access data (with permission of the candidate) that will help them dis-intermediate recruiters. A successful candidate – as he or she becomes an employee – could then elect to share the progress/training data with the employers, as they work together for personalized training. For more advanced information and analysis, the employees could also opt-in to pay a subscription fee for access and for data collection i.e. crowd participation. If the employee elects to have this fee fully waived or partly waived, he or she could participate in turn by earning credit as he/she provides information about their peers, colleagues, classmates on the platform.

The crowd participation will thus happen partly by the incentive of reciprocation. Nonetheless, for those that participate more, gamification and further rewards could be used to incentivizing them. They could thus capture some of the value create and earn cashable credit. I also believe that peer-pressure could also push participation as asking your colleague to provide information on the platform can sometimes be enough to have someone engage in it – especially if reciprocation could be at play.

Now comes the question as to why I believe this model is better than the current system? I strongly believe that pooling crowds around you to provide information creates value that otherwise would neither be created nor captured. All this information creates a better picture of the applicant’s true personality, skills, strengths, weaknesses – allowing for better/more accurate recruiting and training, whilst significantly reducing cost and risk. Opportunities for personal progress and organizational cohesion would be endless, and companies would be able to better build and manage culture. What I believe over the long-term we could achieve with such a platform is happier employees with a longer-term employment within an organization, and better managed organizations with lower churn.

*Disclaimer: This idea has been thought of for this assignment and further thought, analysis and test need to be put in place for this model to be called superior to current solutions. As the question didn’t ask for flaws/risks, I am happy to cover that separately, answer any questions. I also would love to have your feedback – criticism and other ideas.

[1] https://www.reflik.com/employers

https://www.visage.jobs/

[2] https://thejobstack.com/

 

Previous:

Quantopian – Crowdsourcing the Alpha!

Next:

Crowdsourcing for Cash – Cryptocurrency Mining

Student comments on Peers Crowdsourced: The ultimate solution to recruitment and training

  1. Hi, love the idea! Would definitely have used it if it were available when I was recruiting! One question I had was do you worry it might become a popularity contest? In other words, if someone has a lot of friends, whom they could ask or even pressure into writing recommendations for them, is there a risk that the recommendations won’t be fully trustworthy? How would you insure the integrity of the process?

  2. Hi Pasha,
    I believe that there are 3 important elements to ensure the integrity of the process:
    1. Your friend cannot write a recommendation for you. It would have to be a colleague of yours that you have worked with directly i.e. a member of your team or who you interact for work e.g. your counterpart within the organization or outside of the organization. It is like reviews on Amazon or some travel platform that make sure that you bought product or used the service prior to commenting. So unless you are friends with all people you interact with in your professional life, then you can’t rig it. You can skew it if you are friends with everyone and everyone likes you, but that usually means you are a likable person and companies would love that. Also assuming that the participant in providing the information on you is also someone you and other people are going to provide information on, it is likely the feedback will be honest, as this tool is not only for recruiting but also as importantly for training.
    2. There needs to be at least 10 counterpart, and the interesting part in the data and the value of the data is the aggregation of all the information from all the participants. It is the crowdsourcing part that creates the value.
    3. Those recommendations need to be anonymous – to ensure integrity. But that doesn’t mean that such information can’t be updated nor challenged.
    Hope that helps. Would be happy to hear more about what you think about those suggestions?

Leave a comment