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New Success Stories - Asia
CEO Interviews - Exclusive for HR Digital Today with market leading HR Tech pioneers -TalentDataLabs
Stefan van Tulder, Co-FOUNDER of Talent Data Labs



It is common to hear about people making hiring decision based on “gut”. But how does one define “gut”?


In essence, it is a condensation of one’s past experience which lead to a certain behaviour and decision making mode.


Unfortunately, “gut” isn’t highly accurate nor replicable.


Talent Data Lab aims to use data to reduce process friction, biases and human errors in HR, enable data-driven decision making, and establish clear relationships between personality, skills, culture, preferences and performance.


We speak with Co-Founder Stefan to learn more:


1. Please share with us briefly what you do.


Presently, I run Talent Data Labs (TDL), a Singapore-based startup, which works on creating the most accurate prediction and recommendation system for "career fit".


We have a tremendous database with years of research on talent and what makes them successfully perform in various kinds of environments. Over time we have built and validated some tools such as "cultural matching” (currently launched under the brand name of that assesses the work style of an individual and compares that with the organizational environments this individual could end up in.


We believe that through mapping attributes such as culture, skills, and preferences we can recommend people to organisations and vice versa. Moreover, using those attributes is relatively free from bias and makes our recommendations more objective.


2. What were you doing before this?


Before Talent Data Labs I was privately consulting some organisations on how to create value through data and how to make the transition towards data driven decision making. A few of those organizations worked on talent identification and analytics, which inspired our work at TDL


3. In one sentence, how would you describe what your product does?


Our product predicts performance-related outcomes such as sales performance, promotions, tenure, engagement, absenteeism, and recommendations based on people data, such as skills and capabilities, personality and cultural tendencies, and career preferences.


4. How did the idea for your business come about?


After years of working on similar data projects we found a clear gap in psychometrics.


The current landscape is very good at measuring intelligence and personality but it remains incredibly hard to find good solutions that measure a company’s culture.


Moreover, most of the existing tools refrain from providing actionable recommendations.


With the data and insights that we have amassed from previous work, we were able to build experimental models that provided statistically reliable measurements of culture-fit.


5. How does it work?


In technical terms our product is "quasi-ipsative", meaning that users have to make trade-off decisions between a predefined selection of attributes and give us an indication of how much they like a certain cultural trait over another.


Some might find the most important aspect of a company culture be the atmosphere or spirit of the staff, where others are more motivated by learning and development opportunities.


Cultural Matching uses some smart decision-making logic to figure out what is most important to the individual.


6. What are the key benefits that your product brings?


On the entry level of our product you will get a fully automated ranking of the candidates that fit your culture best. This can be based on team, department, office or company level.


One level above that you can see how well you are strategically aligned with other departments or versus your competitors. The third level brings in actionable advice, which gives you access to our data dashboard.


This is a continuously updated personal space where you can view trend lines in your data and appropriate recommendations to deal with any fluctuations. 


Once you are set up as an organization and you source the necessary data through easy-to-use forms or alternative channels, you can instantly understand, which teams and departments would work together best or which candidates would fit into a team better than others.


It also allows you to target people that may be attracted to some of the cultural aspects you are performing strongly on but they do not necessarily relate to you.


7. Who are your closest competitors?


Depending on our product we compete with different entities. Our primary focus is on being an end-to-end people data analytics solution suite, making us competitors to Workday, Lever, Taleo and others.


However, instead of focusing on building a platform for data storage and processing we focus on data extraction, collection and structuring through intelligent algorithms (crawlers, parsers, and other).


These algorithms can supplement your data files, dig out some really unstructured data, and dump all of it into a centralised location. Because of the data extraction focus we ultimately position ourselves as a Palantir for HR.


Last but not least our cultural assessment tool is one of the few tools out there that can prove a substantial degree of predictive validity, pushing me towards believing we live in the same ecosystem as psychometrical testing providers like Gardner and Hogan but also compete with the more hands-on approaches of the MBTI consultancy branch (Myers & Briggs foundation).


8. Who is your first customer and how did that happen?


A small Swedish company called "Nova" asked us to develop an applied model for cultural fit and therewith became our first client.


Previously we have been building event matching algorithms for them and a scoring model that would help t identify whether a candidate would be more or less likely to outperform the others.


9. What were they using before this, and why did they switch?


Before this they were using people to interview candidates, then make educated guesses about the degree of cultural fit and then made recommendations based on their beliefs.


10. How do you price your product?


Our tier 1 product: the cultural matching score is priced at S$3 per candidate. The comparative report is priced at S$10.000 and the more tailored data solutions are priced on a per project basis.


You will get access to our data dashboards to continuously monitor your progress for only S$99 a month.


11. What’s your business focus for this year?


By the end of the year we are aiming for 100 paying clients and having ran 100.000 tests.


Secondly, we are developing an applicant tracking system that allows candidates to integrate other assessments such as interviews, skills assessments, and open/multiple-choice questions into the process.


12. What is your favourite failure (and what did you learn from it)?


I guess that always comes down to over-engineering and making your business too "opinion driven".


When you make product decision based on what you think is the best possible solution and take too many opinions into account you risk building something so complicated that by the time it arrives people have grown so restless and tired of waiting that they will most definitely be disappointed with the end result.


These days I always deliver the basics as fast as possible (within 3 months) so that we can evaluate a future course of action based on validation and not on further opinions.


Especially in data science we risk alienation through complexity a lot. A solution is only as good as people's willingness to use it.


13. What’s one productivity hack you would recommend to everyone?


Plan your week with some blocks of three-four hours where you can be hyper-focus on one task at hand, this way you can reach a state of "flow".


To achieve that it is imperative that you remain uninterrupted. Besides that, it is very easy to reduce time spent on internal meetings and email reminders.


Firstly, always have a clear agenda for your meetings so that everyone can prepare their answers and you do not miss out on any topics.


Secondly, your email reminders are typically 90% similar, so one could just use boomerang or similar software to automate the reminder process.


14. Where can people find out more about your product offerings and you online? would be a good start but anyone can find me on LinkedIn under as well.


More about Stefan:


Born: 08-November-1988 in Amsterdam

Marital status: Unmarried

School: ESADE Business School

First job: I had a paper route when I was 13

Favourite book: A Short History of Nearly Everything by Bill Bryson

Favourite Film: The Hitchhiker's guide to the galaxy

Favourite Music: Coldplay

Favourite Gadget: Cozmo by Anki

Last holiday: Langkawi, Malaysia