Why Talentpad Shutdown? [Lessons Learned]September 30, 2015 2015-09-30 10:25
Why Talentpad Shutdown? [Lessons Learned]
Why Talentpad Shutdown? [Lessons Learned]
Talentpad which raised funding from Helion shutdown a few months back. Founder, Mayank Jain in the spirit of ‘paying it forward’ shares great insights behind the story. These insights are immensely useful not just for founders in recruitment space, but for the ones doing B2B businesses as well.
Our inability to figure out a scalable solution, which addresses a large enough market in India.
To begin with, let me start by defining our target market, we were targeting the white-collar private sector permanent job market in India. Out of the total working population of ~600mn, our TG was 1%+ of that, around 7mn. I know this might sound surprising, but it’s true. The rest of the workers are either blue or grey collar workers, or working in either public sector, or in agriculture.
So, the total recruitment market (defined above) is ~$1bn, out of which the share of the recruiters / consultants is ~$600mn, and the share of job-boards is ~$125mn, Naukri being the leader with ~$60mn in revenues. We had intended to take some market share away from both of the above, so our TAM was ~$725mn.
So, when we started we started with the premise that existing marketplaces (like Naukri, TimesJobs etc.) are fairly inefficient, in my mind they’re a directory, directory of CVs, directory of jobs. And today no one wants a directory, neither the candidate nor the employers, everybody wants a customised and highly relevant list, which is also small in size.
We said, let’s take a segment of the market, which is large enough, but let’s serve it well, instead of just being a directory. When I say serve well, one thing we wanted to do was improve the ‘MATCHING‘, as we believed there is no perfect candidate or job, it’s all about marrying the right candidate with the right opportunity / company. We had intended to do that using data science, technology, by capturing organised data sets on both sides i.e. CV and job, and using data science / rules to do the matching, which’ll of course improve with time as more data gets fed into the machine.
Learnings as we went along
However on our journey, as we got to understand the market better, following is what we realized.
The consultant’s $600mn market is further a sum of three sub-markets:
1. Senior Management (~$100mn): this sub-market works on trust, relationships, confidentiality, basically lack of transparency. And over 90% market share in this segment belongs to the exec. search firms. Couldn’t figure a way to fix this using tech.
2. Junior / Mid Management (<$300mn): what we realized is that the key thing employers look for in this sub-market, while making a hire, was the probability of the hire turning out to be a good manager. Because this is the point where an individual is transitioning from an individual contributor role to a managerial one, thus probability of being a good manager was the key. And domain knowledge becomes a hygiene rather than an acceptance parameter. While there are a couple of psychometric assessment companies out there to solve this problem, but they’ve their own type 1 and type 2 errors.
Also, what we understood was that presently, an interviewer largely tries to de-construct a person’s past work experience, basically CV, and understands that in more detail, asks him examples of specific instances where he showed certain traits, in an in-person meeting to gauge whether he or she’ll be a good manager or not. This is largely intuition along with some supporting facts. Again, we thought if we could try capturing the details asked in an in-person interview and build into the person’s CV, we could solve this problem to some extent, maybe reduce the duration of the interview, or reduce the number of interviews.
But this seemed to be a very very hard problem to solve, and this would require to be done for each role, sub-role and skill, not to mention that the sub-market size is less.
3. Junior / Entry Level (>$200mn): In this sub-market, what we figured was that the one-thing required to crack this was figuring a scalable way to up-skill talent, then assess talent and then finally place him/her. Roughly 50% of this sub-market comes from three industries i.e. IT/ITeS, BFSI and Retail, and that’s how it works with them, they largely work with recruiters / consultants, in some case provide the training material to these consultants, for them to find people, train them over a period which can range from 3 to 6 months, post which assess them, post which the good ones get hired by the employers. In IT/ITeS the training part happens in-house owing to the mismatch of supply and demand. Over 1mn engineers graduate every year, while the industry hires ~0.2mn every year in this segment, 90% of which happens on-campus. The demand supply gap because ~25% of these graduates are deemed employable, not talking about quality hires.
Coming on to the ‘Assessing’ part, while there is a scalable way to assess tech. skills, and HackerRank is the leader in this, but for non-tech skills this is a very hard problem, one that has not been solved with accuracy globally. We tried hard to solve this part, but couldn’t figure out a scalable solution to assess most of non-tech skills, while we could for some.
Plus, in my mind this is a different and an independent business altogether (B2B SaaS), than what we were doing, which does not mean we couldn’t get into this, but our inability to figure for most non-tech skills led us to take this decision, not to mention the part to scale up-skilling / training, which is also a complete business in itself (which is why I think LinkedIn made a huge bet on Lynda).
So, in my mind the above three sub-markets are completely different to each others, and practically need three different businesses to serve these well, except that individually size of each sub-market is less. Coupled with our inability to figure out a scalable solution, we decided to discontinue.
Of course there are generic solutions, which will apply for all the above three sub-markets, like providing access to the directory, where Naukri etc. are playing, and it’s hard to disrupt them unless you’ve a solid differentiation, which we could not figure out. We could have taken the path of a tech-enabled recruiter and scaled the business to a $25-30mn revenue business over the next 5 years, however that did not match with our aspirations, and we decided to take the hard call rather than dragging on. Also, when I say aspirations, it’s more to do with our unwillingness to run a service business.
Then we tried to figure out an adjacent market in recruitment space that we could possibly attack like temp. placement market, part time job market, freelance, intern, contract hire, up-skilling market and so on. While temp. placement market by definition asset-heavy and hard to scale using tech., the size of the part time, intern, contract hire market was very small in India (<$50mn), on the other hand the freelance market was overcrowded, and in some ways a different market altogether with different dynamics, which is when we decided to not limit ourselves to above and explore other ideas / markets as well.
As a summary, my view is the following:
- Extremely hard to replace horizontal marketplaces, like Naukri / LinkedIn, unless there is a solid value prop. which is defensible (which we could not find for a large enough market)
- With vertical marketplaces like IIMJobs, HasGeek etc. , there is a market size issue in India, so will have to expand globally to build a large business
- Opportunity to build an assessment business, for non-tech skills, if you can figure a scalable way to do so. Can address the blue collar market too if you figure that.
However, that being said, in many ways we succeeded, we did figure out a scalable solution to address a segment of the market i.e. skill workers. We scaled the business to $1mn+ in revenues, with 1500+ clients signed up, 60,000+ tech. candidates signed up, built a stellar team, a team I’m really proud of, a team who believed in us in spite of this failure, team that decided to work together for our present venture.
We also got a chance to learn from marquee investors like Helion, made a great friend i.e. Ritesh who was on our board, all of this in 18 months. We succeeded in a lot of aspects pertaining to execution, in areas like marketing, sales, client management, product, hiring great folks etc.
Now we’ve started our next journey (like we promised), have come out wiser and stronger, and in takes me great pride to announce our next venture i.e. Trevo, it’s a venture in the intra-city bus-pooling space, more details soon in a blog post.
[You can email Mayank at