The next US President must be able to lead America into the future

For the past three years, we’ve seen divisive identity politics and populism take over America, which has given us an administration that threatens America’s standing in the global order. Much of this comes from economic discontent, driven by the simple fact that making a living is harder than ever for working class Americans.  However, politicians who point fingers at Mexico and start trade wars with China are not solving the root cause of these economic ills; foreigners aren’t taking are jobs, software is.

The idea that “software is eating our world” is nothing new: in 2000, Bill Joy wrote on some of the dangers that new technology brings to the human race (albeit with a more dystopian perspective). The discontent we see today is simply an ugly manifestation of a post-software society, where “many workers in existing industries will be stranded on the wrong side of software-based disruption and may never be able to work in their fields again.” A PwC study shows that 5% of jobs in America could be automated by the early 2020s, which could more than double the unemployment rate. This number rises to 26% by the end of the decade — a decade that will span the next two Presidential terms.

But the future doesn’t have to be a dystopia. In the fictional universe of Star Trek, technology has made poverty obsolete, leaving everyone free to pursue their passions and better humanity without worrying about having a roof over their head. That’s a future I’d like to live in.

Andrew Yang is the Presidential candidate that gets us a step closer to that utopian future. The center of Yang’s campaign is the “Freedom Dividend”: give every adult in America $1000 a month, no questions asked. But what’s more important than this policy idea itself is the thought process and man behind it — I’m supporting Andrew Yang because he’s a leader for the 21st century.

Software disrupting our economy doesn’t have to look like shiny robots doing our bidding, nor does it only affect blue collar jobs. In the early days of commercial aviation, there was a member of the cockpit crew called the Flight Engineer, whose job was to monitor and control the different flight control systems. The advent of computers in the 1980s basically eliminated this job, as the flight control systems became digitized and automated. Many flight engineers either retired along with the older planes they flew, or retrained to become pilots (after all, we didn’t have self-flying planes back then). But in today’s economy, the pace of innovation exceeds the pace at which people retire or retrain — even tech workers have a tough time keeping up with new innovations as programming languages and the devices we use change.

I know a thing or two about automation. I previously worked at Uber, which likely permanently erased a lot of jobs for taxi dispatchers with an algorithm (Uber’s currently working on permanently erasing the job of “driver” entirely). I worked with some engineers who automated the work that highly-paid operations employees did, like calculating how many rider discount codes to send out the next week, or producing analytics reports for management.

Andrew Yang also knows a thing or two. He founded a tech startup in his early days, and worked with a lot of startups through his organization, Venture for America. He understands that what most Americans think of as the “future” is actually just around the corner — and we need to be ready as a nation to address the challenges of a vastly different economy. The Freedom Dividend is part of that — ensuring that we can share the prosperity that technology brings to our society.

This understanding of technology sets Yang apart from the other Democratic party candidates, who have some interesting policy ideas, but too often look backward to the 20th century more than they look forward into the 21st.

Elizabeth Warren’s plan to “break up big tech” only reveals her lack of understanding about tech, while Bernie Sanders thinks that we can just will jobs into existence. And Joe Biden? While an admirable statesman, the strongest argument going for him is that he was Obama’s Vice President — a rather un-progressive thought.

Unwinding the Facebook / Instagram merger sounds great, until you realize mergers are actually the most common exit option for entrepreneurs. A $15 minimum wage sounds great until you realize it just increases the return on automating lower-wage jobs — it’s almost guaranteed that startups like Dishcraft Robotics are going to get a fresh round of funding if that happens. And hoping to create jobs by committing to massive infrastructure projects like we did in FDR’s New Deal ignores the innovations in construction machinery since then, which significantly reduce the amount of workers needed to build things in the first place.

Andrew Yang is a leader for the 21st century, with 21st century solutions.

Getting your rally crowd to chant “PowerPoint” might sound wacky, but it actually makes sense to bring a slide deck into the State of the Union — corporate CEOs have to use PowerPoints during quarterly shareholder calls, so why shouldn’t the CEO of America? And Andrew Yang wants to regulate “big tech” as well, but his policy proposals are focused on the real, 21st century challenges for technology — everything from data privacy to cryptocurrency and AI. While Warren wants to destroy “big tech”, Yang wants to create new tech — in a responsible way.

What inspires me is that Andrew Yang can unite Americans in a shared vision for the future, moving us forward as a country — instead of moving us left or right (or worse, backward). Yang has support from some former Trump voters, demonstrating his ability to reach across the proverbial aisle. His ideas are rooted in a deeper understanding of modern technology than those of the other candidates. This understanding is not only invaluable in solving for our new-found economic ills, but it applies to other American challenges like healthcare or climate change (Andrew Yang wants to invest in geo-engineering technology to roll back the effects of climate change).  

Today, you don’t have to agree with my views on how technology is disrupting America, or my optimism about Andrew Yang. The Democratic primaries are a few months way, and we still haven’t had our first debate. But I do think you should start paying attention to the Asian guy talking about math, and start treating him as a serious contender.

One of the top priorities for Uber in APAC was improving the pickup experience for riders and drivers. In complex and unfamiliar environments, being able to get a ride reliably was paramount to delivering a stress-free transportation experience. No matter if you were in a new city for the first time, or trying to get a car for your morning commute, we wanted you to be able to simply “push a button, get a car.”

Uber’s original pickup experience relied on a rider moving a pin on a map: while this worked great in the US, the experience broke down in Asia where pickups often do not happen on the street — but rather in designated pickup areas embedded in complex, multi-storey urban environments. Simply providing a pin and street address didn’t give drivers enough context to meet their riders — an experience that often resulted in stressful phone calls and missed pickups.

“Venues”

In June 2016, I visited Singapore to help prep the Uber Southeast Asia team for the upcoming launches of uberPOOL in Singapore and Manilla. I was staying at a hotel in the Orchard district in Singapore — a major shopping and commercial district. My hotel’s street address was on Orchard Road; however, the road was a fast-moving, busy thoroughfare where the sidewalk was fenced off for pedestrians, and stopping on the side of the street was illegal for cars.

In fact, the hotel had a designated pickup & dropoff area in front of the lobby; but drivers could only access it from a different street — from a perpendicular road (Scotts Road). And if a driver missed the entrance, he would have to drive around a loop that would add 5-6 minutes to the pickup — costing the driver additional unpaid time, and adding stress for the rider who now has to wait twice as long for his ride.

Uber’s original solution to address complex pickup environments was the addition of “pickup notes” — allowing riders to type a short note to the driver (i.e., “I’m in the hotel lobby; access from Scotts Road”). However, this was far from an ideal solution — riders would have to type a note everytime they requested a ride, and none of this information was passed in to the driver’s navigation. The amount of international travellers relying on Uber made this problem worse as drivers often couldn’t understand the language that their riders were communicating with them in.

When I left Singapore to return to China, I wrote a note to the Singapore team about this experience and suggested a different solution: adapting the tooling Uber had built for airport pickups to urban environments.

Major urban complexes in Asia actually had many similarities to airports: for starters, there were designated pickup points that riders and drivers were obliged to meet at. Further, riders and drivers were both often perplexed as to where they should meet — a rider going to an unfamiliar shopping mall for the first time may not know where to request their ride, and a driver that hasn’t picked up anyone at the complex may find it challenging to navigate to the pickup location.

Uber had built a customised pickup experience for airports specifically, allowing global operations teams to designated pickup zones (i.e., terminals) and pickup points (i.e., door numbers). While this was live globally, it was only used at airports.

Later that year, the Singapore operations team started deploying this feature — internally called “Venues” — across a number of major shopping malls and office complexes.

When the Uber app detected riders were requesting from inside a Venue, the rider would be asked to select a pickup location, which would be passed to the driver. Riders were guided with wayfinding information, and because the pickup location was controlled entirely by Uber, we could ensure that critical information (i.e., “hotel lobby” or “level 2 carpark”) would be correctly translated and integrated into the driver navigation flow.

A quick comparison of marketplace metrics before and after this change revealed double-digit improvements in pickup times and trip completion rate.

“Hacks” and Hotspots

Of course, this solution was not perfect; at Uber, we called these informal product adaptations “hacks” — and for good reason. Venues at times could add friction to the rider request flow, and it was difficult for a rider who may have been erroneously placed into a Venue — for instance, if their GPS location was wrong — to escape out of the flow.

The majority of the efforts in San Francisco still revolved around improving the pickup experience in the US, and continued innovation focused on the curb-side pickup experience that riders in America experienced every day. This ultimately meant that the Asian product experience for Uber riders and drivers was “branched off” from the efforts of the global team.

In early 2017, Uber launched a new rider app (internally codenamed “Helix”). One of the core promises of this new rider app was that riders would not have to manually set their pickup location — Helix was “destination-first” in that riders would only have to tell the app where they were going, and the app would intelligently determine where the rider was and suggest a pickup location.

To help deliver on this user promise, a considerable amount of effort was dedicated to generating machine-learned “Hotspots” — pickup points based on where riders and drivers historically met each other.

The problem was that these Hotspots were generated without contextual labels, and only referenced as latitude & longitude coordinate pairs displayed as a dot on the map for riders, or reverse-geocoded street addresses for drivers. The Venues that we created were entirely incompatible with Hotspots — meaning that the advanced machine-learning algorithms would not benefit the pickup experiences we needed them to help with the most.

Don’t ship your org chart

By mid-2017, I had asked each of my country product leads in Asia to implement Venues across their markets — in markets like Vietnam and Thailand, close to a thousand were created within a matter of days.

However, this clearly wasn’t sustainable; the right answer for Uber was to develop a solution that integrated the contextual information provided by Venues with the machine-learning provided by Hotspots — and eliminate the incompatibility between the two features.

Unfortunately, Venues were owned by a team whose charter was to improve the pickup experience at Airports — and not the shopping malls, office complexes, or large housing estates that dotted Asian cities. The Asia team’s pleas to the Rider team, who largely owned the Pickup Experience, were mired in cross-functional communication frictions and progress was slow until San Francisco proposed to create “pickup zones” for Uber in certain neighbourhoods. A cross-functional effort was kicked off to build a better solution than the existing Venues experience provided, incorporating some of the initial research that my team conducted in Asia a year prior.

The challenge throughout this year-long ordeal for Uber in Asia revolved around the regional focus on our customers, rather than our product and engineering team’s org chart — we were, as a regional team, eyeballs-deep in the needs and wants of our riders and drivers, but often unaware of the complexities of navigating the 100+ tech teams situated in San Francisco — and the challenges of collaborating across teams (who often were re-orged on a quarterly basis).

Ultimately, a quote from a senior leader in our product org resonated with me: “don’t ship your org chart.” As a product leader, your responsibility is to build on behalf of your customers — capturing their needs and wants, and distilling that into innovative and delightful experiences. All of this is irrespective of the artificial boundaries that your org chart puts on your team; reaching out across functions and collaborating — and even toe-stepping (another Uber cultural value) — is critical to delivering the best experience for your users, especially in larger companies where team structure and feature ownership becomes more complex.

Uber’s business in Southeast Asia was sold before a longer-term solution could be built. However, Grab has taken the reins of improving their pickup experience in mirror to our efforts from 2016; I’m excited to see where they take the urban pickup experience.

I spent the past 2.5 years at Uber trying to educate our US-based product and engineering teams about Asia — at first while I led the growth of uberPOOL in China, and later when I led product strategy for the rest of APAC and went on to tackle the tough local nuances across 14 diverse markets. I was fortunate enough to have a front-row seat to Uber’s globalisation efforts, and to have fought alongside some of the most amazing operators who built a thriving transportation business from scratch.

In light of recent events in Southeast Asia, many people are wondering whether American tech companies can win in Asia — especially the group of Uber China alumni who later rejoined Uber APAC, only to be sold a second time. I believe that building product for a vastly different part of the world is always difficult, but not impossible — and that in today’s era of globalisation, it’s crucial that companies understand how to build for local nuances and handle the complexity of diverse customer bases.

While Uber’s original cultural values were criticised after the departure of Travis Kalanick (“TK” as he was affectionately known), I believe that they played a crucial part in the rapid hyper-growth that Uber saw around the world. Two of the ones that always stood out to me were “Celebrate Cities” and “Customer Obsession” — these two ideas were at the heart of how I approached product strategy for the region: think about how a local entrepreneur might build product.

Celebrate Cities

We’re passionate about cities. Everything we do is to make the city a better place. We see what the future of a city can be and celebrate the heroes and heroic efforts that make it a reality. Uber works best when we are woven into the fabric of the city with our mission to serve the people.

Ridesharing is an incredibly localised, nuanced business — it inherently deals with the complexities of urban development and transportation planning. The local cultural and geographic nuances in every city and country where Uber operated applied tremendous pressure on our product, whether it was figuring out how a motorbike driver in Jakarta might accept dispatches safely, or making uberPOOL more efficient in congested cities like Manila.

The latter was especially close to my heart — I was part of the initial launch of uberPOOL in Southeast Asia while I was still leading the China POOL team, and hosted a group of Southeast Asia ops in Chengdu to help them learn more about uberPOOL in May 2016.

At the time, the threshold for launching uberPOOL was that a city needed to be hitting 400,000 trips per week. Only two cities in Southeast Asia fit this criteria at first — Manila and Jakarta — but Singapore tagged along despite being much smaller. When I heard that Headquarters was not superpumped about launching uberPOOL in Singapore, I stepped up to fight for a launch there.

My belief that uberPOOL would work in Singapore, despite lower trip counts, was rooted in my experience with uberPOOL in China. Our primary metrics for measuring the success of uberPOOL in a city revolved around efficiency: how many uberPOOL riders actually got matched with other riders, and how much busier drivers got as a result of taking uberPOOL trips. The main contributor to efficiency was liquidity — the more trips being requested, the more likely it was that we would be able to match two riders together. Our ideal scenario was that two (or three) riders ordering an uberPOOL from the same office building after work, going to the same apartment complex, would share the entire ride home for a lower price but experience no inconvenient detours.

Far before the Southeast Asia operations team paid us a visit, we were struggling to identify why certain uberPOOL cities in China weren’t performing despite high trip counts. In particular, sleepy cities like Hangzhou or Suzhou were outperforming megacities like Guangzhou and Beijing, despite having similar or even lower trip counts.

I was stumped at first — until I compiled a heatmap of request and dropoffs in these cities. The trips in the cities looked something like this:

Visually, it became obvious why these smaller cities were doing better: liquidity was more than just a function of trip count, but a function of the city itself and how it was laid out. Hangzhou was not only compact, but everyone was going to the same part of the city; Guangzhou had multiple centers of economic activity and people were using uberPOOL to go everywhere in the larger city.

I took a look at maps for Jakarta and Singapore and came to the conclusion that despite Singapore having less than 400,000 trips per week, it would outperform Jakarta (which was doing far more trips). I took this hunch to some data scientists on the uberPOOL team, who ran a full simulation on Singapore — and found it would be one of the top performing cities in the world for uberPOOL.

When we launched uberPOOL in Singapore in July 2016, it was a resounding success. Riders loved the low prices, and drivers loved being busier — especially during the peak commuting hours where surge pricing made it so that drivers earned more. We even got a couple of employees later who were only interested in Uber after we launched POOL!

Customer Obsession

When determining what to do, we start with what is best for our customer. That can be hard, but we refuse to settle. Instead, we innovate our way out of the box. Many companies talk about being customer-focused, we’re customer obsessed. We are relentless in figuring out what matters to our customers and then doing everything in our power to deliver it.

The introduction of uberPOOL highlighted another problem in Asia for Uber: picking up riders was dramatically more complicated. The original Uber pickup experience was designed in the US, where most riders met their drivers curb-side — and they even were willing to cross the street if it meant a faster trip.

However, Asian cities looked quite different. For starters, most pickups didn’t happen curbside; rather, they happened in mega-malls or office buildings with complex layouts and multiple, designated pickup locations. Clearly, Uber’s original concept of “drop a pin on a map” wouldn’t work in here. Further, asking a rider to cross the street was a dangerous endeavour: major roads in Asian cities would require people to either cross multiple lanes of fast-moving traffic without a crosswalk or make a multiple-minute detour to find an underground passage or above-ground walkway.

In my presentation to new hires in APAC, I often joked about how our product and engineering teams knew more about the Caltrain station in San Francisco than any major pickup location in Asia. After all, senior execs at Uber would have to deal with getting picked up and dropped off at Caltrain everyday —  but they may have never visited Asia at all.

We tried to solve this problem in APAC by porting over a solution originally built for airport pickups — internally called “Venues.” Venues allowed operations teams to designate special geofences for pickup experience overrides, letting operators designate and label pickup locations. We eventually bastardised this solution to cover hotels and office bulidings with designated pickup points, shopping malls with basement and above-ground pickups, and apartment complexes encompassing multiple buildings and blocks where residents could get picked up. We let loose a team of operators to create these Venues across the APAC region, to the point where over 50% of the world’s Venues were created in APAC — despite us having a much smaller share of the world’s trips.

I later found it heart-warming that Grab added a similar feature into their app — letting riders in Singapore designate a pickup point in many shopping malls.

Can American Tech Companies Win in Asia?

To answer this question, I think we need to look beyond tech companies to the examples of Western companies who have won in Asia — Starbucks, Haagen Daz, and McDonald’s come to mind. I spent some early days of my career at PwC helping Western multinationals expand into Asia — and one of the frameworks we presented to our clients was the globalisation maturity framework.

The globalisation maturity framework highlights a key point for Western companies seeking to do business in Asia, or really, anywhere in the world: you must localise your products. Many tech companies are still stuck in the “export model” phase of their globalisation journey — where a headquarters-led team builds product to ship to the world — rather than living in the “originate model” phase where each individual region and market contributes actively to the global business.

Successful companies in China like Starbucks fully localised their operations somewhere between the regionalise and originate models; Starbucks in China was originally operated by a local Taiwanese company, who was able to quickly adapt to local market needs. However, Uber remained in the “export” phase of globalisation; product and engineering teams lived in San Francisco, and while a portion of the tech teams visited China, none of them actually lived in China long enough to truly internalise the problems that our users faced. Our operations and marketing teams in China were thus stuck with the products built in San Francisco, and had to hack around their limitations.

Going back to my approach to product strategy for a global company — “think about how a local entrepreneur might build product” — I firmly believe that American tech companies stand a chance to win in Asia. However, for them to be successful, they have to realise that there are tremendous differences in consumer culture and behaviour — and localise their product accordingly.