Imagine that you graduated from HBS and started your new job. You are working hard every day to make a difference in the world. As you take on more stretch opportunities, you encounter various challenges – managing time, striking the right work-life balance, or maybe even finding purpose at your work. But you no longer have your section mates or your LPA friends that you can ask for advice nearby. So you attend a learning event provided by your firm, but it is not tailored for your specific needs…
Meet BetterUp. BetterUp provides a personalized learning and 1:1 coaching opportunities for professionals, empowered by their AI and analytics. For instance, they can identify the needs of organizations and individuals based on the demographic data and behavioral patterns. They will then match you with a perfect coach based on 150 unique variables with 97% accuracy. (i.e., % of employees satisfied with their original coach) In addition, their analytics will aggregate the data from those coaching sessions to identify company’s stated culture and behavioral gaps. Their customers include Airbnb, Linkedin, and Lyft, and they have increased 45% in employee productivity, a 63% in retention, a 35% in organizational agility, and a 29% in employee engagement. 
While I was intrigued by their comprehensive services as well as the integration of algorithm and behavioral science, two questions came to my mind.
- Coaching: how do they ensure the quality and how does their matching algorithm actually work?
I was curious how they ensure the quality of coaches given that they have 1600+ coaches in their directory, and how they are actually matching those coaches with clients. Since they don’t disclose much information publicly, I tried to find some research papers from their scientific advisory board and data science team, in vain. Therefore, as a last resort, I applied to become BetterUp’s coach to find out. (I happened to take 100+ hour coaching training last year and I am now in certification program, so I qualified for application…)
Quality of coaches is ensured by its rigorous selection process (8% acceptance rate) as well as continuous learning opportunities. Coaches are selected based on a) credentials (e.g., ICF certified = minimum of 60 hours of accredited training and 100 hours of coaching) and b) familiarity with BetterUp’s behavioral science approach to coaching. In terms of b), once a coach passes the initial resume review and written interviews, they will receive 5-6 hours of BetterUp’s training, and then conduct a demo session. After they join, they have access to various resources in BetterUp Coach Community.
In terms of matching, based on the questionnaire they asked, I would assume that they will be using demographic data (e.g., years of experiences, industry, areas for expertise, name of training institute to identify the types of coaching) as well as behavioral data from written and demo session. In addition, I think they might be using data from their Coach Community and conduct analyses (similar to ment.io) to identify coaches with similar approach to improve their matching in the future.
- Overuse of algorithm?
Their comprehensive use of algorithm is impressive, but I think it could be overused. For instance, if you let the algorithm decide your development areas, would that hinder the opportunity for you to ask feedback from your team members directly? If the employees know that the company is collecting data from your coaching sessions, would they feel less inclined to use the service? As in any cases we’ve learned, I believe it is crucial for the companies to be thoughtful about how to integrate these tools, instead of using the algorithm to all possible cases.