Stefan van Tulder is Founder & CEO of Talent Data Labs.
Talent Data Labs is a talent analytics company based in Singapore.
Full Podcast Transcript
Sidney: Welcome to the "SalesNative" podcast, where tech founders share their most valuable sales lessons. I'm Sidney from Sydney, founder of SalesNative. And today's guest is Stefan van Tulder, founder of Talent Data Labs based in Singapore. Stefan, welcome to the show.
Stefan: Thank you so much for having me, Sidney. I really appreciate you inviting me.
Sidney: It's great to have you here. So, Talent Data Labs is a talent analytics company. I'd love to learn about the business, but first, I wanna know why did you start this business?
Stefan: Yeah, that's a very good question. And we have been dabbling around in the talent business for quite a while, but my personal background is really in looking at data and trying to make consumers, let's say, buy more or help them better...give them better advice, recommendation systems. The funny thing is that there was a big HR conglomerate, a founder in Sweden, who once picked me up off the streets literally and said, "Can you do the same for people?" And people, being the workforce. I told him, "Probably." And I just gave it a try. So, as I got into this business of looking at how people moved through workflow or through their jobs, through their careers, you find that data has a lot of similarities to its customer data and with insurance data.
What was interesting though was that in this business, I talked to a substantial amount of clients of this Swedish conglomerate, and the interesting thing that I found is that most of them don't really have much material that they can bring to the table for a board meeting or at a management meeting about their influence on the P and L. So, what we realized is really that, while we're helping this one specific company, we're never really addressing a market problem. And it's that we're not doing something that's really scalable and really, I would say, interesting for the society at large. So, we decided to found a business called Talent Data Labs that would really focus on talent analytics and all talent data to ultimately help society at large.
Sidney: That's a really good ardent story, I think, for our listeners. Again, those that are thinking about, "What business should I get into? What grand idea can I be working on?" The best is to work on real customer problems. And I think you can take a skill set that you've applied in a particular industry or category and look for similarities and opportunities in another industry that's not as developed or emerged because systems haven't traditionally been there or data hasn't been as much available, just like Stefan did. And thinking about we're not looking for the one-hit wonder and a bit of a consulting work, but something that can scale and something that can have impact and value at large. I love those words that you used there, Stefan.
So, tell me about Talent Data Labs. What do you do? Who do you do it for? And how are you moving the needle via target customer?
Stefan: Yeah, thanks for the question. That's actually one of the things that is most interesting for us, right, so to actually move the needle for the customer because now our customer is specifically an entity and an organization that's often been underappreciated a little bit as a force to be reckoned with, and they're mostly even considered a cost center. But as we move more and more towards a future where everyone is incorporating some really awesome data tools like Workday is doing a great job there, and Taleo and Lever are all, you know, facilitating these processes quite excellently. We really feel that there's a shift there, and that shift is really something we want to facilitate to an extent where we can all be proud of.
So, those managers, those HR managers specifically, can be proud of the achievements they've made and can show it, can put the numbers to it, and that we can be proud of the influence we've had on that process at large. Now, the way we do that is actually quite simple. What we do is we try to gather as much data as possible available from the industry at large. We have some partners that provide us with a lot of preference data and personality data and skills data in the market. We have a special army of robots that scavenge the internet to define all the data that the public itself, so people like you and me, put on the internet, and we put all of that together, and what we then do, and that's, I think, that's one of the key things we've accomplished as a company, as Talent Data Labs, is we compare that to the data sets we have been amassing by working with clients in Sweden, in Spain, in the Netherlands, in England, in the U.S., quite closely, and have found patrons in.
So, to clarify that a little bit because I guess that's quite abstract, is we have been working quite closely with clients where we've overhauled their entire data practices, where we've looked at, "Okay. So what is it that drives the success of your employees in your company? And what are the main factors?" And there's four things that are insurmountably important. In every piece of literature, you'll find some back...and one of them is obviously mental aptitude, which is sort of IQ, or some call G factor. One of them is personality, which is, do they...one of the things that a lot of people see as an acronym of four letters from Myers-Briggs, you might be familiar with that. That is not personality in a statistical sense, that's personality in a social sense.
The third one would actually be skills. And skills is something that's...and I think one of the most interesting things here as well that we do is we don't look at skills as a binary thing. So, predominantly, and especially in computer science or in more exact ways of looking at things, you look at skills as something you either have or you do not have. Now, we're pretending to be more savvy than that by saying, "Well, skill can also be something that you almost have. You can have a so-called approximation, a closeness, to a skill that you might be able to develop towards."
So, when you say, for example, we're going to hire an army of data scientists. The typical way that you look for people with either a mathematical or statistical or a neuroscience background to figure out how you can give them the right amount of software training to become a data scientist. Whereas I truly believe that software training can be acted upon by pretty much anyone, barring that they have the right logical capacities. So what you would do, you dissect what it takes to become a statistician or a mathematician. It doesn't really matter.
And we find that the components in that are more, like, analytical skills, logical skills, computational efficacy. So you dissect it and you put that all together and you put it on one big map. Imagine the biggest spatial map that you can find, and you start grouping things. And if you do that, you could draw lines basically between, "Okay. So what does it take to be a data scientist? And what kind of skills do you have? And how far is all that away from each other?" And if you research that well, you can assign probability scores, which is what we have done, of someone able and eligible to move into such industry or move into such a task.
So, we don't really look anymore at, "Hey. Can you do it? Yes or no?" We look at, "How much effort is it going to take to make you be able to do it?" And I think that's a really phenomenal perspective because it gives us the ability to tell users of our data systems, you know, basically, A, "What do you want to do in life?" And we'd say, "Okay, it's not very probable that with your background right now, you're going to succeed in that. So, try this first. Try this little thing first, and it's a lot closer to where you are right now and it's well on your way to where you want to be. See how that goes for you." And so, we try to take the steps in between to allow people to grow slowly but surely because as human beings, we only like a maximum amount of stress. Our attention span is too short to dive into some material that's so disconnected from us that we won't be able to correct a single part of it.
And the last one, and that's, I think, one of the most unique ones we do as well is we look at culture, we look at cultural fit. Cultural fit is studied into the deepest depths, and it's something that has never really been incorporated well in an applied model. And when I say an applied model, I mean something that you can use, that you can apply now to people who work for you or working with you and predict, accurately predict, whether they're gonna stay long, whether they're going to be happy, whether they're going to fit in well. And because we have so much data, we were able to, sort of, facilitate that process of building a tool there as well.
So, we move the needle by introducing our own data, but looking at their data and, you know, really understanding, "What are the factors that are key in the industry. What are you doing that makes no sense whatsoever in this industry? What kind of products are you building? What kind of teams are you having to gather, and how does that all work together?" Typically, when we see a company, they have only the skill component and the binary skill component in place. And they look at, you know, "Are people staying long enough? Do we have enough succession planning? Do we have high profile talents at these kinds of things?" Regression models to how much that impacts, isolating things that matter. We barely see that.
So, what we give them all of a sudden is the tools to really understand what matters and therewith also what doesn't matter, and what doesn't matter is usually tremendously expensive for a company. So, imagine if you're hiring everyone from, let's say, Harvard Business School all the time because you think that those are your top performers. And maybe they are your top performers but is it because they went to Harvard Business School or is there something else in their profile that we could easily dissect in a data segment that determines whether they should be part of that. That's sort of how we try to influence our clients.
Sidney: That makes a lot of sense. People are an organization's greatest asset, and yet we haven't applied anywhere near the sophistication of data analytics to the way we hire, enable, engage, onboard, upskill people as much as we've used that to try to sell more things to people. So, I think, we're using data analytics for good here rather than for not good. So, fascinating story.
So, now I wanna turn our attention to sales at Talent Data Labs. Stefan, tell me about your most interesting sale.
Stefan: Yeah, that's a tough one. That's probably our first sale, where we...We as a company, we think in very mathematical ways and we're all educated in heavily quantitative subjects, while at the same time, that's the only staff we have that's trying to sell or to convince clients. So, I would say one of the key things that our sales processes always teach us, and it's a sort of humbling experience as well, is to educate yourself extremely well into the daily grind of your client, the specific person buying from you.
So, as I said, previously, we were dealing with a lot of HR managers, with a lot of people...analytics teams. And what we learned quite quickly is that they have a subset of problems that they're confronted with on a day-to-day that isn't very well aligned with what we're trying to achieve because we're trying to achieve things on a high level, on a statistical level, whereas most of these people are trying to focus on things on a granular level, on a day-to-day, "Hey, this is my headcount. These are the amount of people I need to hire," type of ways.
So, when I introduce, you know, "We're gonna grab all your data and we're gonna throw it through our algorithms, and at the end of the day, we'll roll out this fantastic report, how you're better or worse or more specific in a certain field than other companies and how we recommend you to improve, but you're still stuck with a file of resumes that you have to read through." So, one of the most fundamental things in our journey, I think, was that we needed to first find an internal partner, stakeholders, so people that felt that this topic is something I can put on my roadmap, my personal agenda, and work towards and achieve and accomplish things in.
Most of the companies that we work with are just hiring a head of people analytics, and their roadmap is usually a roll-out workday or introduced more similar systems across. So, even they have different priorities. So, for us, the most challenging thing has always been finding the person that you can, sort of, live this journey with, that will find it a rewarding journey for themselves and will, therefore, be most invested in helping you. That's never in the same position.
So, one of our first clients we had basically...she's full on a regional recruitment manager, and she's just been confronted with a lot of hires not working out, and by being in that cycle time after time after time. And effectively so, her pain was really not really hiring anymore, it was just trying to find the people that will succeed or will bring this business forward. And from meeting to meeting, the next meeting, with a different person, we would have exactly the same role and exactly the same functionality, where they would say something completely different again, they would have success in the hiring, so they wouldn't care about finding the right people that much, they would just care about getting through their resumes faster.
So, I guess, what I'm alluding towards is our journey taught us one thing, and that's, learn from your client really, really fast what drives them and see if your product problem or solution fits in there because if it doesn't, it's going to be an uphill battle from there on and it would take months to close a deal. We have the biggest problem with basically trying to identify the right targets, so what you may want to do, and it's sort of our hack we do, our growth hack is you wanna be very...you wanna approach someone in your organization, maybe even someone you know that's on a lower level of things, and you wanna offer something for free, a small nugget of data or maybe a small sample of your test, and then you want to ask that person quite specifically who in the company is working on project-related to, in our case, optimizing your workforce and are introducing the talent on the P and L.
So, we target completely the wrong person deliberately at start or...never actually the wrong person, at least not the person that's going to buy anything, to get quicker response rates. these people are usually very young, very enthusiastic, and they all point you in the right direction. That eliminates, I would say, effectively months of chasing the wrong horse, if that's an expression in English.
Sidney: So, I wanna call out a bunch of things that you've shared with us that's valuable, I think, for our listeners. Firstly, when you started you said, "All of our team is made of effectively technical, mathematical, data science-type guys and girls. So, we had to take the responsibility of sales on ourselves, which meant we had to educate ourselves on how to take complex concepts and simplify it in order to explain, we'll talk in layman's terms because the target audience we're helping think of it in a traditional way to manage people, but yet we're bringing complex and sophisticated modern data analytics approach."
So, I think, it's the first thing where, you know, in terms of one of the values and of the foundations of SalesNative is, as tech founders, you need to own sales, right? And eventually, you're gonna bring salespeople on the board or eventually you're gonna have marketing and growth hack people, but in your early days, especially as you try to navigate through your first 10 to 20 customers, it's so important as the founding team, you're involved and you're upskilling yourself and your technical team to be able to conduct sales. So, awesome that you're sharing that.
The second real nugget was you said, "We had to educate ourselves in the daily grind of our customer." I don't think we do enough of that. All of us could do a better job of understanding the daily grind. So, it's not just, "Hey, I've got something I wanna sell you and just be done with it, but, truly, I wanna walk in your shoes to understand what drives you, what makes you happy, what makes you sad, what motivates you, what deflates you. And how can I then align what I'm doing to help you win in the objectives you have in the environment, in the political arena, that you're working in inside of corporate." And so, I think, walk in the daily grind of your customers is very important.
The little tidbit around finding an internal champion who will set the goal to make whatever it is that you're working on jointly, so important. You know, we as tech service providers into organizations can only do so much, someone internally needs to own and run with this, so identifying that person. And I think there's a lesson here or two more lessons here.
One was, look out for the false positives. Because you spoke about, we go into a certain organization, we understand the role that they have and the title that they carry and the problems and the objectives that they're interested in, yet we walk into another organization, and the person with the same title and the same role will have a different priority and a different problem, which means we need to adjust our sales approach and sales language. And this is where solution selling kicks in, right? So, we're not just trying to just offload again what we have on the back of the truck, but rather we're going in to understand problems, objectives, goals, timing and align our sales process to that.
And finally, the little hack you spoke about, awesome to share with our listeners. So, you're targeting a decision-maker in an organization, they might often be hard to reach. How about you look at who in the organization is one or two levels below, go in with some value. So, Stefan's example was, give some samples or some nuggets of value, then get their guidance and their advice to help them...sorry, to help you navigate the organization. And that has proven to save a lot of time for Stefan and his organization.
Lots of awesome wisdom there, Stefan. Thank you. I think continuing with the great wisdom you've been departing, now I wanna turn our question into, "What should first-time tech founders know when it comes to sales?" Or in other words, "What sales advice would you be giving yourself if you were starting over?"
Stefan: Yeah. That's one of the most interesting questions. And it's, how do you take this experience and translate it? The key to everything is honesty, right, being genuine and specifically not being salesy because people will sniff that up. Yesterday evening I was at the event, and there's just this salesy person coming to me, complimenting on my hair, or whatever. It's not a very desirable start of a conversation. So, honesty is key, but the question is, can you create honesty by imposing that on telling someone, "Hey, sell more like this or sell more like that." I think it's imperative that you create a learning journey there. So, you would need to have your staff to understand things through their own eyes and through their own perspectives. And if you want them to grow and be good at this, then they will need to learn it the hard way, meaning by failing, specifically by failing.
So, what I would do specifically is I would probably create more role-playing. And role-playing, it's not commonly done in any of my professional experiences, nobody really wanted to do that, nobody really likes doing it, but it's so effective. It's such a brilliant way of activating your team to understand what you've already understood. What you want to do is you want to take all the elements that you've been exposed to and use them in a role play with your sales staff or with your co-founders, especially in the first couple of days, just lock yourself in a room, just do that. And even though it sounds undesirable, spend two days pretending to be the client. Ask them to so send you emails, don't reply to the emails. Have people exposed to the problem hands-on and let them discover with the right rhetoric and with the right questions how to circumvent that so that it becomes genuine.
Sidney: Got it. So, key takeaways here, be authentic, or as Stefan said, be genuine, be honest. And the key message there is, within that same frame is, don't be salesy, people can sniff that out from a mile away. Although I must a admit, if someone complimented me on my hair, I'd appreciate that. There's obvious reasons for that, those who know me will know that hair is not one of my strengths, at least of my head. So, that's all good.
Secondly, think about allowing the failures and learning from them. So, being open to failures both for yourself and your team. And then, thirdly, in order to pass on some of that knowledge from an experiential way, think about role-playing. And I think that's a really good bit of advice, I don't think any of the other founders have shared that on this podcast. So, I think that's gonna go down as a strong one here for you, Stefan.
So, Stefan, sales aside, as a tech founder, what's your biggest struggle and how are you overcoming it?
Stefan: Oh, that's a no-brainer. That's growing. Unsustainable growth. I have the biggest issues in life to trust that the quality of whatever we've been delivering, especially when you do these heavily statistical analyses, and most of them are automated, but we tweak little bit for different clients and everything, and then the presentation. So, I'm always afraid that the quality is subpar when I remove my hands from it, which I think it's probably one of the dumbest things I do in life. And I don't know why. I just always assume that the way it's invented is probably the way, how it should be. And when these new people come on board and do things differently, I get a little bit afraid of, "What if the clients don't like it?" And as soon as I hear the slightest hint from saying, "Hey, I'm not so sure if this is what we wanted it to be," I sort of panic and want to step it.
Now, this happened as well very recently. We were delivering a new product. I held my hands tight sort of, so I didn't do anything. First phase, initial sort of pre-delivery, they produced a nice report and the client came back saying, "I don't really understand this." So, I started panicking. Now, to not drift off and extend it so much, the conclusion of that is I let them go and they delivered something in the end infinitely better than I did, and the client now loves them, ignores me entirely, doesn't believe I exist anymore. But what is so hard is to let your baby be taken care of by other people, that you might set standards to your team and to your next hires that are just surrealistic. You might not be patient enough, you might not want to wait for them to mature and develop themselves into it long enough, you might want to take too many things over, especially, you know, having that environment, it's always easy to say, "Okay, nevermind, we're going to do it like this."
It's just a huge inhibitor, and I've lost an employee on that already, where you're just...it's not necessarily micromanaging, but it's the fact that you think you know it better, whereas that's the opposite of what a startup should be, right? So, you're a startup, you're trying to figure it out, that nobody knows it better and that's why you exist. You're trying, you're just trying to get there building up the knowledge, and the only way to effectively do that is to find the staff that you could trust, and to find the staff that you can let go. And that mostly isn't a problem with the availability of talent, it's mostly a problem with how well you allow them to mature and how much patience you have.
Sidney: Brilliant. So, speaking of authenticity, thank you for being so vulnerable and being authentic in answering that question. I think it's a big person who's able to say, you know, "I've made mistakes and people have left of the way I've previously behaved." But you've had an aha moment, and that is, as founders, we can absolutely the single point of failure of a company. And I've said this before on this podcast, you're never gonna be the single point of success, but you absolutely will become the single point of failure, especially if we've not learnt to trust, delegate, and allow for failures, just like we said in the sales process, we should allow people to make some mistakes. I think in our delivery process, it's no different.
And Stefan's learning has been to demonstrate more patience and allow for people to develop their own maturity. And guess what? Some people might be better than us, and that's a good thing, we should be hiring people better than us. And it's not the lack of availability of people when we're thinking about expanding our team, but it's our own mindset and our own processes that allow them to onboard, figure the state of play in our environment, and then for them to shine if we allow them to. Otherwise, we're creating a coin-operated environment both in our delivery and in our sales environment. So, good wisdom to be sharing with Stefan.
Okay. So, thank you very much for being on the show, Stefan. I wish you and Talent Data Labs all the best and I look forward to hearing more about your progress.
Stefan: Yeah. I thank you highly for your questions. Looking forward to meeting you here in Singapore next time...
Sidney: Perfect. See you soon, buddy.
Stefan: See you.
Sidney: There you have it, folks. Valuable insights from a fellow founder. Remember, as a tech founder, to succeed, you need to sell. And sales is not a dirty word, it's a value exchange. Meaning, you need to create and capture value. Here at SalesNative, our calling is to provide sales inspiration, training and coaching to tech founders wherever you may be in the world, enabling you to reach your potential, to make your impact and to leave your legacy. If this is you, then I invite you to head over to salesnative.com and sign up for my free talk, "The 10 Sales Essentials for First Time Tech Founders."
From one founder to another, I wish you success. And remember, you're just one sale away.
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