#09: Chang Wen Lai CEO at Ninja Van

My honor to be here. Happy to help and share whatever I can.

Well, the journey so far, when we first started we knew close to nothing at all. I think we kept a very open mind, learning all kinds of mindsets. So it wasn't about thinking that we could change everything, but learning what the current players are doing and trying to innovate if it makes sense. And many times we realize that it doesn't make sense to innovate because they're doing things the right way. And I think that takes a lot: you cannot have too much pride when you do this and think that you do everything better. Sometimes, over the last 100 years, people have perfected certain things and some things are just not meant to be changed. But understanding what has changed—I think what has really changed is technology. Technology has definitely changed a few things. The way I look at it is that technology is a very good transaction cost leveler. It makes certain things a lot easier, more intelligent. And I think when we take that mindset and we look at how technology isn't just a cost-optimizing this business, but technology is an enabler for services to allow businesses which have evolved in the light of technology for us to serve them better, that really is kind of the base in which we believe we can make an effect change in this industry.

Well, I definitely think so, but perhaps not the way most people think it will be. I think if you think about AI, you think of autonomous bots, autonomous drones, autonomous vehicles moving. I actually don't think that that's too close. I think it's still quite far across the horizon. I don't expect to see a robot delivering my parcel in my apartment building anytime in the next few years. But I think AI has great strides. You look at Siri, look at Cortana, all these. I think AI has the ability to improve the customer experience, not to lower cost. So again, back to technology as more of an enabler for services rather than a cost optimizer. People think that AI will allow us to replace human labor in delivering parcels and lower the cost. I would actually beg to differ. I think the first usage of AI in this business, at least, is how do we use AI to provide fantastic customer service. Instead of calling the call center and waiting, AI takes over, replies on chatbots very fast, answers all your questions. And of course, all this is on the basis that the information is there to be found. If the entire business doesn't run on technology, if you have no idea where your parcel is, it's a lot harder for you to answer these questions. But with AI, I think you can answer: 'Where's my parcel?', 'Can I change the delivery timing?', and then this gets affected and pushed into our logistics systems, which then changes the time windows, for example. So I think AI, in terms of helping both consumers with their delivery experience and helping our shippers in scheduling a pickup slot and changing the details of a certain parcel, all these can be a lot more seamless with AI. I think this is the immediate path for us where we try to improve the both shipper and consumer experience with AI.

I would say it's less AI, it's more NLP. I mean, it's all kind of under the same realm. You look at route optimization: I think the first thing most people forget or take for granted is that the address is accurate. Without accurate addresses, there is no route optimization. The question then is how do you get accurate addresses? And on the back of accurate addresses, how do you build a strong optimization engine which learns from previous routes, from historical routes, which is able to adapt despite inaccurate road networks? So again, a few assumptions: the first assumption is we know exactly where the location is; the second assumption is we know the exact road networks in Southeast Asia. I think both assumptions are not valid. So before we even move into road optimization, we kind of have to solve two problems: how do we use a variety of sources and our own internal databases and our own feedback mechanisms from our drivers through the driver application to provide a very accurate address database, so we know when an address string comes in where the exact address is. The second would then be: given that we know the exact lat-long of an address, how do we know which roads lead to it? You look at Southeast Asia, look at Indonesia for example. It's not surprising to see a one-way road with two-way traffic, a two-way road with one-way traffic, or even more surprising an area with no road but people are still traveling through it. So how accurate are these road networks? Not the most accurate. It is most accurate when you look at the data which is moving—how your actual drivers are solving the problems on the ground—and then building your own virtual network above existing road networks. Because you know that this building, there's no road going through it, but somehow your driver always manages to go to the building, deliver something, and go to the next building which is supposedly a one-kilometer detour on the road. Something's happening on the ground we don't exactly know what, but we are collecting all that data to better understand that building A to building B is not a true one-kilometer detour but a fifty-meter walk under—gosh knows what—a fence, a hole in the fence, jumping over a wall. We don't know, but he does. So by solving the address—and that's where NLP comes in very strongly—and by solving the road network where there's a bit of AI, a lot of algorithms there, we better able to understand where exactly the location is and which roads lead to it. Then the optimization algorithms come in.

Well, with my CTO, we were friends for about five years. He was always helping me fix any tech problems I had, but any business I had before this he figured it wasn't important or challenging enough, and he never wanted to get involved. I think we realized that the last mile could be very complex; he got very excited, although we severely underestimated the complexity of what we had to build. We thought that we could finish everything in two or three years; now, I think we are probably 10% of the way. My COO, he was my badminton doubles partner when I was 10 years old, and we've been in the same school ever since. So I think we have a very strong friendship amongst all three of us. We kind of share the same vision that we want to make an impact in what we're doing. We're not happy just going to work every day and knowing what's the purpose of us, not just for earning money. What keeps us going and makes us work really well—I think it's quite interesting. The mutual trust and respect we have, a rather clear segmentation of responsibilities, allows us to align on high-level objectives. We see the mountain, we see the peak, we know we want to get there, but we don't bug each other with how we should take our own paths up. We chart our own paths up, but we trust that we will always be doing our best, finding the best path, and that we are always going to the same point. So a lot less conflict; we don't try to come to a consensus on everything. Decisions generally fall clearly into someone's camp, and we try not to get overly involved unless our opinions are asked. I think it allows us to run very fast but yet be very aligned.

So we looked at this, we kind of asked ourselves: how did we even get here ourselves in the first place? What was the most important attribute we had? And I think it's quite similar to what I said before: a lot of it is self-awareness. That means I'm going to learn it all; I'm going to learn; I don't know everything but I want to keep learning. Self-awareness is fantastic for people who want to learn because they know that they do not know. The worst people are those who think they know everything. The second worst are those who do not know that they do not know everything. People we like to hire are people who know that they have big gaps in their information, and these are people who keep poking, keep learning, keep trying to improve themselves—whether it's in technical expertise or in management leadership. So these are the kind of people we look for: people who are hungry, people who know that there's a lot to learn and they actively want to learn. And of course, what really helps with this is a very strong logical mind. So a smart person with a logical mind who is hungry to learn, has no ego, and keeps improving himself every day can eventually become great leaders in Ninja Van. This is exactly the kind of people we look for.

Well, the hunger to learn and less ego. Ninja Van appears to be very traditional: hub and spoke network, a bit like a schoolbook almost. It's when you poke them with 'what ifs,' asking them 'could you do things another way?' And when you see a stubbornness or unwillingness to shift their thoughts from the norm into something more open-minded, I think that's where you detect a lot of ego. You detect people who think they know it all and refuse to keep an open mind. So there's no single question; you can never ask someone 'are you open-minded?' or 'are you self-aware?' You can ask, but they're going to say yes. So these are the kind of questions you never ask, but you can tell from conversation very strongly. Someone who's very obstinate, very stubborn, you can immediately tell. Someone who's super confident but no one knows everything, and not everything is black or white; there are many shades of gray. People who are willing to accept that this is a shade of gray which I have an opinion on, you may have a different opinion which is another shade of gray, but we are both not wrong, neither are we both right. But let's explore. And then that ability to explore and distill the fundamentals down to core concepts is something we look for.

Well, I think what it means is you're ready to fail if you try your best. So entrepreneurship isn't about saying 'I always want to be successful'; entrepreneurship is saying 'I want to embark upon a journey where I constantly learn, be it because I'm successful or I failed.' So I didn't have a successful startup before. I failed, but I'm still an entrepreneur because I learned. It's always about what's next and remembering what's behind that makes one an entrepreneur.

Yes, even in a successful company you fail many times, and in many other aspects. Correct. So I think that's a part of life. But sometimes, and I've been in Asia for about 10 years, you have the concept of losing face. So it's something that for an entrepreneur it's almost impossible; you cannot worry about it, which is why maybe the best way to look at it is if you want to be an entrepreneur, you should throw your face away first. Assume you have nothing to start with, that way you have everything to gain anyway.

Well, I think one of the best advice I've gotten was: keep your eye on the prize; don't worry about a lot of small things. That's one. Actually no, I think the best advice I've ever had was that in life there's never a right action, but there's always the right thing to do at the right time. And I think this applies a lot to management philosophy: what is culture or strategy? There's no right culture; there's a right culture at the right time. So be very cognizant of the two extreme ends of the spectrum and figure out which shade of gray you should be at any point in time, and how it's always evolving. So when people are super prescriptive and say 'the way to be a manager' or 'the way to be a leader is to do this,' generally that's nothing one-size-fits-all.

Well, I say I'm a bit OCD, so I like to respond to things very quickly. I believe in being very responsive, and I think that's one of the key attributes which won us the initial vote of confidence from our customers. Essentially, if you text me or send me an email maybe from 3:30 AM to 6:30 AM, chances are you wait 3 hours to get a reply. But any other time, if it's important, you probably get a reply in two minutes. I think that kind of responsiveness is super important in our business because in logistics you're never 100%; you always have failures, you always have edge cases. But it is in handling these failures which you really make a mark. I don't profess to handle 100% of edge cases either; definitely things slip through the cracks. But this culture of 'we know that we can never be perfect, but we try to be perfect at fixing our imperfections'—we try to catch everything which falls through the crack, but we know that there will always be cracks. I think this culture permeates through the entire organization and allows us to be a lot more responsive, a lot more caring, a lot more mindful of what our clients care and need. I think this helped us really grow our client base from one customer to thousands and thousands of them.

But don't get me wrong, I'm not saying that we have perfect customer recovery. But if you look at priorities: if we had limited resources and I'm asked to move my SLA from 99.9% to 99.99%, or move my service recovery from 90% to 99%, I always choose service recovery. Because when people are pissed off, they get really unhappy, and now you have social media, they get really unhappy and really loud. So that's another reality. It's a thankless business: if everything goes well, it should be the case. Five minutes late because of heavy rain, why do I care? But if you get me my parcel exactly when I need it, that's good. Can you share any resources, online websites, courses, anything that you keep yourself updated to learn?

Well, to be honest, I think I'm a bit ashamed to say that, but not really. I think my best source is Facebook. Make friends with people who are useful, not people who just keep taking pictures of themselves. That way you get the best knowledge base. I do unfollow a lot of people who post pointless pictures of themselves, but you realize that your friends or your network is actually the best source of knowledge. They post a lot of very relevant articles and you read them. I use Flipboard as well and subscribe to quite a number of publications, but I find the best filter is my friends. They post an interesting article.

Well, this can seem quite out of the ordinary, but my first advice is: don't get married. It might sound funny, but let me explain. I believe that going to a startup isn't to get you quick bucks or anything; it is really to quicken your learning curve at the expense of your wealth. Chances are you're going to exit a startup poorer than if you worked for an MNC, 99% chance, or your expected value is definitely lower. This means that the only reason why you join a startup is so that you can learn in three years what you would have learned in six. However, to really get a good learning of a startup, it is good that you experience corporate life first. You see a lot of bad habits coming from people who leave university and join a startup: poor email etiquette, poor work habits, sometimes they just don't know how the real world functions. You might have done internship, but it's not the same as working two or three years. So my advice would be: don't get married. Work for two years, but quit after two years. If you're married, you cannot quit; you're scared, you have mortgage to pay, hopefully you don't have a kid, but by then if you have a kid, good luck. You won't quit and you'll do that for the rest of your life. So don't get married. Work in a big corporate for two years, understand and keep your eyes open: why are corporates doing what they're doing? There are good reasons for that. Then leave, join a startup, experience how it is to work in a three-person group, but always remember how it was to work in a 30,000-person group. Along the way, I think this gives you both extremes, and you learn along the way.

In Southeast Asia, it's going to be really hard to get married or buy a house. That's another problem.

They're never going to walk their daughter down the aisle.

No.

Thanks.