Ani sits down with Jerry Hu, the Senior Manager for Regional Talent Acquisition for Doctor Anywhere. With his business and human resource experience, Jerry shares on how data and analytics can help organisations in their talent acquisition and talent management processes. Jerry speaks on what talent intelligence looks like, how Alibaba utilised talent intelligence in their Digital Media & Entertainment Group, and where to start when an organisation wants to leverage analytics for their talent acquisition process.
You’re listening to A Daffodil for Your Thoughts, a show where we speak to leaders across multiple industries to gather their views and advice on prominent themes and topics within the workplace.
Anirudh Arvind 0:18
Good evening, Jerry, it’s a pleasure to have you on Single Steps. Thank you very much for making the time.
To all of our listeners, today we’ve got the very, very charismatic Jerry Hu, senior manager of talent acquisition of Doctor Anywhere, with us today. But before I carry on, Jerry, congratulations to you. I know it’s a new role that you’ve taken up. Would be great to hear a bit more about you and the role. And maybe if you could even share a little more about what Doctor Anywhere is doing at this point.
Jerry Hu 0:44
Yeah, sounds good. Thank you so much Ani for inviting me to this podcast. I’ve been a sincere fan all along.
And so, in terms of kind of my change, really, I joined the Doctor Anywhere like, this is my first week. And I can say only so much.
So, we founded in 2017. Our founder’s name is Wai Mun. And then hopefully, you can find all his talkings and podcasts online. And you will be able to really- if you cannot, then just follow my LinkedIn page. I did a lot of posting in there.
So, what we were trying to do as one our vision is to become kind of the largest health tech provider across Southeast Asia. And- and in order to do that, our mission is to kind of through, you know, very innovative technologies, but also solutions as well. When you look at that health care system, sometimes they, you know, there are old-fashioned ways of doing it. And it’s not very convenient, I think, across the globe. And when we think about insurance, when we think about “I want to see a doctor,” there’s tons of like, paperworks. There are tons of, you know, troublesome things you have to go through. Basically, we want to be able to, you know, give power back to our patients and users. Really, you know, make it more easy, more accessible. And then, you know, in some countries in Southeast Asia, it’s also not very cheap, right? It’s expensive for high quality health care. We wanna making sure that, you know, we’re able to utilize a platform to be able to provide everybody, you know, when it’s necessary, right?
Anirudh Arvind 2:37
Yeah. Awesome. I mean, I think it’s, it’s really nice to see how you’re obsessing around patient care and trying to really kind of ensure that it’s the seamless experience for these individuals to access some of this healthcare, which could some points, you know, be difficult to do so. So I think the purpose behind the organization is really fantastic. And kudos to you for starting on and kind of helping them grow across the region.
Jerry, if there’s anything you’ve got a reputation for, it’s really for kind of, you know, adopting talent intelligence and leveraging analytics within the world of talent acquisition. And you’ve done so, you’ve done that very successfully across multiple organizations you’ve been in. You know, be it multinationals, be it start-ups, early age organizations. But you know, what exactly is talent intelligence? What is- what does that actually mean?
Jerry Hu 3:24
Yes, thank you, Ani. That’s a really great question. So, you know, if we come down to what talent intelligence is, right? I think it’s threefolds I always talk about. It’s, it’s really I think, we know, since the start of LinkedIn Talent Insights, the space itself has been quite hot. However, you know, many people are still not familiar. Sometimes, you know, in Southeast Asia region, it’s still quite nascent. Or people just have different understandings, right. And I think that’s totally relevant and true because it should be a very customized approach to different organizations and challenges. There’s no set in stone to say this is the right way to do talent intelligence. Some people thinks it’s related to executive sourcing. Some people think it’s more related to the systems. Some people think it’s related to people analytics. I think it’s really, again, we drill down to what kind of business challenges you’re trying to solve, okay?
So the threefolds kind of, from my experiences, is that number one is really to be able to utilize the data, internal and external across. So internally, you know, we will be connecting, you know, kind of the entire employee journey right from the beginning: when we are getting them; you know, all the way how they’re performing; all the way you know, when are they leaving, are they happy; something like that, right. So there’s a lot of data points around that.
External wise, these days there are many, many tools you will be able to easily find out like, where are people working at, what are their migration patterns. You know, what is the some of the competition insights around your competitors. So a lot of the external people data, it’s also has been out there. So the first step, right, the first fold for talent intelligence is really to be able to aggregate and synthesize all those information. And then from there, you know, you will be able to draw out some of the insights that’s truly kind of relevant to you, and really, you know, able to provide actionable insights. I think that’s also a challenge. Sometimes it’s on the surface, you can see descriptive data, but not necessarily coming down to, you know, actionable insights that we could leverage.
Then the second fold is really, you know, I think, with those kinds of very useful tools and with those knowledge that we will be able to influence our hiring managers in a different way. So, you know, changing kind of the recruiting mindset from very reactive, meaning like, you know, there’s a job rack, I post jobs, I download resumes, and then you screen to a very proactive mode. Meaning like, sometimes there is no role. But I know our competition is hiring this role out there. Should we be thinking about doing the same thing? Or I know, there’s some constant organizational changes in our organization. I know COVID has a hit on the talent trends. Should we be planning ahead in terms of in our talent strategies? How are we always thinking about it? So the second fold is really, you know, I think that entire shift up there. You know, mindset towards talent. Is that, you know, it’s rather than hiring managers telling you, “You know, these are our target companies, you just map it out, that will do it.” We are going to tell you that, “Okay, if you’re looking at this market in Vietnam, these are, you know, the size of your software engineer. What are they good at? Where do they like to go? And where have they been to and they failed? What can, what some sort of the lessons can we learn from that?”
So the third piece is, I think the circle is really I think, you know, from all that, we will be able to kind of create a culture of recruiting ideally. Because, you know, we always say that, that not and not just recruiting, right, every job of HR, every function, is not just a HR’s job. Ultimately, you know, we are enabler. We give you the tools, you know, as a business partner, we’re partnering with you to making sure that you can use, utilize some of those management tools, some of those, you know, people strategies to better engage your own team. And in ultimately, the driving productivity and performance. And then, you know, ultimately, obviously, improve the company performance in that sense.
Yes. So these are the three folds kind of coming from my practices and my experiences. Yeah.
Anirudh Arvind 8:18
Right. No, that’s really interesting how you say that, because I think a lot of it, like you say, is is also a mindset, right. Leveraging the technology, the insights, but also at the same point, working very closely with business leaders and functional leaders to kind of say, “Hey, this is what we’re seeing in the market, do you think you should be thinking of a particular role or a particular strategy, or maybe even taking advantage of, you know, a particular direction one of our competitors are going into?” But I guess at this point, there’s a lot of opportunity to kind of relook at the existing talent pools that we want to start, you know, we’re actually not relevant to our organization in the past. Is there a particular point when you adopt this type of intelligence that you can kind of expand the talent pool and, you know, advise hiring managers to kind of look above and beyond the common three to four organizations that they may want to poach from? Or would that also be an avenue on in terms of adopting some of this intelligence?
Jerry Hu 9:19
Yes, totally. And I’ll share with one of the kind of the examples that we did, so I’ll just give you a more concrete, you know, taste of it.
It’s that- so I was with Alibaba for five years. And my last phase, I think I was with the Digital Media Group. So the Digital Media Group, some of you know Alibaba for the e-commerce piece. But it’s it’s these days it’s much more than that. There’s like a hundred twenty thousand people. It’s more like a Amazon. And then one arm of it is that really a little bit like Amazon Prime. You know, we have the videos, we have, we have music, we have something like TikTok, the sports—all that. So altogether that Digital Media Group, you know, has 13 different businesses all around the entertainment area. And that was really the direct, you know, request from our CEO, was that we’ve been constantly facing these challenges, even though Alibaba, you know, every year there are 4 million applications. He just said, “You know, I don’t think they’re suitable. Actually, we are not really able to, you know, help us get to where we’re going.” And then you know, the talents, you know, even though the applications are there, but the readiness of the talent, the maturity is not there, or the potential is not there, right.
So, so that’s very interesting if you’re thinking about, you know, the start-up recruiting, sometimes you don’t get applications. For the big ones, you think, “Oh, you got a name. You got so many people apply.” But actually you got different type of challenges because I think the big ones, you know, they always want to disrupt in the new territories. But sometimes those talents are not there simply. It’s not there in the, you know, in the, inside the border, right? So we need to really go beyond the border to do that, right?
So when we, our team back then, when we took out like such an assignment, we actually took two folds, two steps to do it. One is that we really wanted to look at internally again, right. What is his- problem statement really? That, you know, actually we don’t want them, they cannot, you know. So because when we look at some of the internal data we realize, actually, the previous people that we hire, we have very high turnover and attrition is very high. And also when we looked at some of the qualitative aspect of it, it’s that they’re simply not happy.
So they, meaning you know, those content people we actually use to full time employee is a movie directors, actors. That’s you know, if you think about it’s a complete different types of- types of species, right, compared to the geeky software engineers, which, you know, is definitely the majority of any tech companies. So, so both sides actually, they cannot really work together, and they’re not happy. And especially for the creative people, later on, you know, if you find out and then if you have ever had experience working with them is that- so number one is that, you know, creative people, they are very much in need of freedom. So they don’t like to come to work. They don’t want to be strangled by like a physical space. Or like a nine to five. They like to wake up at 3 am and start writing, or, start you know, thinking about their creative projects. Now, number two, is that they can definitely not obey your OKR (Objectives & Key Results) or maybe your performance things. It doesn’t mean anything to them.
Yeah. So so but overall, you know, Alibaba is known for this kind of very aggressive performance management, right, this type of culture. And then you know, the long hours and stuff and so on. So so how are we able to really, you know, harmonize, right, these two groups in that sense? So that’s number one: our findings, right. And then basically then the second thing we thought you know, further deep into is that actually do we really need them, you know? Because coming back to the root of the question is that you know, we wanted to build up this business because we saw the success of Netflix. And we were thinking kind of the Netflix culture, to say, you know because Netflix has such a good culture and it’s so successful in the content space right? It should be kind of you know, see it as a model.
So the second project we did is that we dug very, very deep into you know, the Netflix culture and model itself: the origins of it, the root of it. We even flew to Los Angeles, met with the CEO and founder Reed Hastings.
Anirudh Arvind 14:13
Jerry Hu 14:15
Yeah. And then, so you know, our conclusions we find out is that, so Netflix you know, some of you have read his new book, right, “No Rules Rules.” It’s all these radical things. It’s very much actually cater to founders of his own belief is that he wants to create the best content in entire world right? So his culture is very much cater to the content, creative side of the talent, right. So I’m, you know, I don’t, you know, strangle you with some leave. We always pay top the market. Yeah, just competitive. And so can these things to you know, be able to really work in the in a very tech driven, the majority of engineers kind of companies, right? So that was our question.
Number two is that when we also dig deeper into the content, is that, like, why do they really enjoy and stay at Netflix? Right? So we found out, actually, yes, of course, they’re very attracted to, you know, high salary, you know, the freedom. But ultimately, it’s also connected with their purpose in life. Because for creative people it’s a bit different. It’s that you only need to succeed once in your entire life. And the majority don’t. Only, you know, the 1% comes out. Meaning that you only need one movie, you only need one book, just in making sure you’re in that market. But in order to do that, you need the greatest amount of luck, but also the world class team to be able to carry that out.
So Netflix provided that platform to say that only here, right, you would be able to have a chance to work with the best directors, the actors, that you would have a chance to be able to succeed in your field. Versus, you know, if you stay at Disney today, right, it’s ending, right? Or you know, you’re doing your internal things. So you know, both sides, I think, kind of gave birth to this radical and successful culture at Netflix. So when we really dive deep into it rather than just you know, seeing on the surface, right, our CEO, went back from his trip to Los Angeles. He made also a very immediate decision, he said. I will stop hiring anyone.
It’s been, you know, it’s a constant churn. And then, and then we, his original thought is that we need the best content people to create the best content. That’s how we’re gonna win the war. But the truth is the Alibaba way of doing, you know, this digital media business, ultimately, it’s we want those content people to be able to drive back those traffic to our e-commerce platform. We want to be serving our e-commerce customers more than just a shopping experience, also a lifestyle experience, right?
So the two missions are gigantically different. So once he comes back, he thought that thought through. He said, “I will stop hiring. Instead, I will change the entire model to just outsource it. So I will work with those creative people outside of the company. I will not employ them anymore.” But because those creative people, usually they have their independent studios, one or two of them. So we will just put money in, share IP, intellectual property with them. And we will work with them as a partner. And it turns out to be much, much more successful.
So I think this is a example, I guess, I want to showcase it’s to say that, you know, we started out as a talent acquisition project. The conclusion at the end, is that actually the needs is not there, they’re not positioning correctly. And there I’m, you know, this might be a very interesting kind of example, that when, you know, huge. But I think, you know, if you ask M- every TA (Talent Acquisition) person’s life day-to-day, they will be facing similar questions. Cause a lot of times the hiring managers because, you know, a lot of the needs is coming from inward, right? They think, “I’m lacking this capability, that’s why I what you to do it.” But sometimes the outside market may be very different. So that’s where we really will come in to, help him to shape out, you know, what is the correct positioning of the needs and what’s the realistic position.
Anirudh Arvind 18:41
Yeah. No, but that makes a lot of sense. Because I guess in a lot of these digitally native digitally, I guess, started organizations like Amazon and the rest, they kind of think of the customer has like 1x, and 10x, and 100x, right, which is how they do books, and then Prime, and then you’ve got like your video, and then you’ve got basically everything under the sun. Like you go from software to hardware by selling the Kindle. And I guess if you were to kind of look at the customer from that perspective, you see, “Hey, can we not dabble in that space” and it’s only kind of, I would say from a-from an entrepreneurial spirit, kind of it makes sense to kind of go into that space because you’re increasing the customer lifecycle, which is, I guess, is what they all really want to do. But at the same point, what you’re saying is really interesting, where you’re saying that talent acquisition is looking at the harmonization of these different individuals to bring this to life, in terms of how we need to hire the right type of people, to kind of mesh into who we have in the existing core to ensure that we’re able to bring some of these strategies to life. And the adoption of intelligence then can tell you much more than do you hire or it’s actually even if you’re going to look at you know, hey, maybe this is not the right business idea for us. Maybe we need to look at a different model. And we need to sort of maybe outsource the entire element. Which I guess kind of brings me to a different question, which is, you know, in an organization like in Alibaba or in Amazon, where there’s so much emphasis on data and understanding the consumer, I can only think that in larger ecosystems and more, you know, analog companies that are now going digital, they would also have access to this insane amount of data as well. But what is the starting point for an organization to come to realization on, on how they can leverage data and analytics to support, you know, talent acquisition, or talent management in general? Where do they start?
Jerry Hu 20:40
Yes, thank you Ani. That’s a very good question. And I always get that a lot. So I think not every organization probably would have the luxury of setting up a TI (Talent Intelligence) function. You need the size. And some people always argue that you need that large amount of data to work at, right? This one, I, you know, I hold my thoughts is because I think back to my first point, I always feel like, ultimately it’s a mindset. And then when it comes to external data, it’s actually all over the web. There’s, you know, the LinkedIn. There’s all kinds of social media that we will be able to connecting, and figuring out people’s behaviors. And net- net- Another thing is that sometimes we will always think, you know, when it comes to data analytics, do we really need a lot of algorithms, you know, all those skills are- ready to use, those complicated software to churn out the models and to figure it out. To be honest with you, if you’re asking people in kind of the HR analytic space, in many, many, many, you know, large organizations, if you ask their customers specifically, they will say, “Sometimes I do feel like it’s very relevant.” And they’re like, doing their own analytic things. But it’s not really solving a business problem, which is kind of my challenge, right?
So I think, again, this would come down to kind of the, the ultimate goal here is, I think, whether you know, you use analytics, or you use, you know, the tactical approach— it’s all just a route to an end. Because, ultimately, you know, we’re trying to making sure that, that we- we’re not just, you know, kind of, kind of sitting on the other side of the table anymore, right, versus we are equipped with this type of knowledges that some of our businesses, you know, it’s the first time they’ve seen or they don’t have access to, and then really be able to shape their thinking around not even just people, right. It’s the entire model as well.
So yeah, so I think, you know, kind of, in summary, back to my point, whether I think you are start-up, you know, and then you’re a large corporation, you have big amounts of data to work with, there’s always a different way of doing sort of the analytical approach. And, you know, using metrics to drive performance, I think ultimately, it’s, it’s, that’s also an interesting piece as well, is that your creative way of thinking, you know, the, what’s the most customized, that’s very suitable from the stage of my organization, and then be able to solve some, you know, actionable insights and real problems. Yeah.
Anirudh Arvind 23:46
Right, right. No, I hear you loud and clear. So you’re saying it doesn’t really matter, I guess, you know, if you have copious amounts of data, or if you’re just kind of starting out. It’s a lot around the mindset and the approach to getting the insights and finding actionable insights so you can actually drive home a solution at the end of the day. I guess, you know, there’s a bit of skepticism around, you know, talent intelligence and data analytics as well. Within like talent acquisition, you hear, you know, some horror stories like, Oh, you know, because of a particular AI, you’re losing out, you know, a bunch of relevant or qualified candidates or female candidates are getting missed out because of certain algorithms- algorithms or anything like that. So so when you are kind of investing into, you know, technology and kind of utilizing AI and ML within, you know, talent acquisitions, is there a way you can predict some of these mistakes and even when they do come around, when they are elicited, how do you then kind of deal with that and quickly kind of make the right changes to ensure you’re always getting the right talent at the right time for the organization?
Jerry Hu 24:54
So again, very good questions. I think it’s more around the system side, right? And then I always say, you kind of, you know, the qualitative and quantitative piece should go always go hand in hand. Because, you know, data, when it get there, but if you’re missing sort of the human part. So that’s why the telling is, you know, it’s not about data analytics. It’s, you know, we also talk to the candidates. We understand them from a different perspective. Not necessarily wanting to, you know, acquire them, but truly understand the pool. Right? What are their needs? What are their dislikes? So combining both, right, and then I think that’s always the challenge. And the true, sort of, I think the most difficult, right, part of this is that you need experienced people to be able to distinguish from the noise and extract what is real, what is that truth, you know, that insightful that you can actually draw upon. So I would say, you know, kind of, again, the machine learning, all the tools, the predictions, they are very good. But if they’re living without context, and if they’re not really connecting with a real kind of problem, then it would be something again, called descriptive data. It’s just the, this, you’re just describing a matter. Yeah but not, you know, translating into some of the things we can act upon immediately.
Anirudh Arvind 26:37
Got you, got you. I really thank you, Jerry. I think it’s really good to get such wonderful insights from you and kind of giving us a really good view on how an organization can start this journey, leverage the data, at the same point, the significance of having the right mindset to kind of bring this form of adoption of intelligence to kind of life was really interesting. So I’d really like to thank you for taking the time on a Friday night to speak to us. So I really, really appreciate that.
Jerry Hu 27:09
Thank you so much, Ani. Thank you for having me. And, you know, to the audience there, any of you if you want to know more about me, feel free to connect with me on LinkedIn. And, you know, we are also expanding Doctor Anywhere. We welcome all types of people with who are just interested in about our company. Feel free to reach out to us. Obviously, we welcome applicants and candidates as well. Yeah.
Anirudh Arvind 27:37
Awesome. Thank you very much.
Jerry Hu 27:39
Thank you for listening. We hope this podcast can help in your learning journeys. Check us out on our LinkedIn page, Hatch Asia Consulting. Till next time, keep growing.
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