Supriya is a product technology executive who currently is the Chief Product Officer of Rentalcars.com, the largest online car rental company. Supriya has over twenty years of experience in product and engineering executive roles across the west coast of America.
She was with Amazon.com in Seattle for over a decade focusing on the core customer experience on a variety of products including retail, social and Kindle. Her last role at Amazon.com was the technical advisor to the Sr. Vice President of Kindle devices. Prior to that, she worked in a variety of startups including Zynga and pro.com. Supriya has a dual masters degree with a masters in distributed computing from Michigan Technological University and an MBA from Wharton Business School.
Supriya loves product innovation and believes that design thinking is at the core of product disruption. She enjoys talking at conferences that sit at the confluence of product design and technology innovation.
[00:00:01] Hi everyone. How many of you attended my talk this morning on the Strategy piece? Okay, so the first five minutes is going to be a little bit of a repetition, because I'm going to give some context on myself, but then hopefully we'll get better after that. How many of you failed today? How many of you have done something that you contribute as a failure today? Good for you. I mean, there's like, you know, three or four people raise their hands. Kind of goes to say that we don't take failure as a part of our everyday life, right? We want to succeed. We always want to put our best foot forward, and we don't really think about failure as something that is just part of our everyday life, right. You mean, you know, but if I don't floss my teeth in the morning, that's probably a failure, because that's gone a long-term, like you know, impact my teeth, and so we have to kind of be in the mindset about failing fast and what does that mean when you think about rapid product development? Okay so how many of you here are product owners? Please raise your hand. And how many of you are engineers and designers? Fantastic!
[00:01:13] This is me. I started as a chief product officer of Rentalcars in October 2016. This is my dog Scotch, who's the chief product office of my household. His major criteria is to ensure the happiness of my household. He's much more successful as a product owner than I am. I grew up in India. I arrived in the USA 20 years ago, did a whole bunch of work there. Got two master's degrees: one from Wharton, and one from Michigan Tech. I'm basically a geek at heart, and I then went to Amazon, and worked there as an engineer for a long time. I also worked for a number of years at startups in San Francisco, have cofounded three startups. Think like, you know, probably failed in all of them.
[00:02:01] So ten years at Amazon doing product work, and started as an engineer kind of helping Amazon move from 10 million products to 100 million products. Trying to think about how to get sellers on on our platform from from 1 million to 15 million. Trying to think about how do we extend our customer base to get to hundreds of millions of users. Trying to figure it out, as Amazon Web Services was going to be built, how can we do our own dogfooding exercise and kind of learn from first principles how Amazon Web Services worked. And then, the last four years I have been doing a lot of work on Kindle, and Kindle devices, in terms of like really trying to figure to figure out what do these devices, or what does this family of devices, mean for our ecosystem? Okay, and what do they mean for our customers? What does engagement of devices mean? What does loyalty mean? What does it mean for Amazon to be within the house? To have a footprint within the house versus a footprint on on the laptop or on the desktop? Right. So it led to a bunch of proliferation of many many devices in our household, but really trying to figure out how do the customers engage with us differently when we are part of a device family.
[00:03:35] I also worked at a bunch of different startups in San Francisco and Seattle. How many of you have heard about Zynga? It was a Zynga for a while, very early days, kind of helping FarmVille grow from, like, 15 million daily active users to 30 million daily active users, and trying to like you know wonder, like you know, where have the sheep gone? Do we need another lonely cow in the mechanics? So a lot of work in that space. I've also been the founder of microfinance solutions company in India, an online discounted fashion shop, and I run my own product strategy consulting firm for a few years. A lot of people asked me this question, why Rentalcars? And Rentalcars, because I didn't know what I liked more: rainy Seattle, or rainy Manchester, and at some point I was like, "okay, if it's going to be rainy, I might as well switch.".
[00:04:37] But more importantly, the Priceline Group that Rentalcars is managed by, and was acquired by, is the third largest online retailer in the world. It's a sister to booking.com, which a lot of you have heard about. It's a very product-centric company, very, very, open to change. We're continuously iterating, and trying, and failing, and learning from it. It's truly global: 50k different locations, 900 suppliers in 163 different countries, and it has 1400 employees — and that's a cool place to be. That's a sweet-spot in terms of, like, I can still remember people's names, and like feel like I'm contributing to helping cross the proverbial chasm to get us from, like, two billion pounds to a five billion pound company.
[00:05:22] What is product management? Product management, in my opinion, is four basic things like every product owner should kind of learn, internalise, and manage. It's data-centricity: are you able to play around with the numbers? Vision and delivery: are you able to take different business stakeholder options, or create a vision out of nothing? And then one important item are you able to deliver on that vision? If you're great at stakeholder management, but if you cannot deliver anything, that doesn't work, right? Nobody's going to look at you if you cannot deliver. Are you obsessed with the customer? Are you really getting into the customer mindset and really figuring out what the customer wants needs and what does this batch of the blind spot in the customer's life that they cannot that we have to tap into to figured out what customer delight actually means? And the fourth one is an open approach to failure. This is super critical, right, because even if you have one, two, and three, but you don't have four, you're probably not going to learn from it. Super critical, and how do you instill this lack of fear to failure and make it a daily practice?
[00:06:37] Is everyone aware of this model? Right. As a product owner this is what you breathe. You build a hypothesis, then you experiment with the hypothesis. You evaluate, and then you use that evaluation period to take insights, and then build your next hypothesis. And I had hypothesis today that my talk this morning was excellent. That was my hypothesis. I went ahead and gave this 30 minute talk, but at the back of my head I'm like, "oh my god! You're rocking it!" Okay. Then I asked one of my peers from Rentalcars, and another lady who kindly stood up and asked a few questions, and he's like, "Your talk was all fluffy. There was no data. You need to go deeper." So then, there, my hypothesis was totally lost, because it's no longer an excellent talk, because my audience didn't have any data, which you need to kind of capitalize on. I went broad and shallow with fluffy words. I didn't kind of, like, give them a chance to reflect through my personal examples.
[00:07:42] The insight from that is, I can't let that happen in this talk, right? Because if I don't take that insight, and I rebuild my hypothesis, then I come in and say, "this is a fantastic talk." And so it's really kind of important that most people don't realize this insight phase, and they don't internalize it, right? And if that evaluation and insight phases are super-critical, and you really don't have to look far for it. Data is always coming to you, right? You don't really have to, kind of, like do tons of market research, and do a bunch of, like, you know, customer-intent focus groups. Data is always coming to you at all points to help you with your evaluation and insights. So how do we deal with failure, and most of us do really poorly with failure, right?
[00:08:35] When I was 9 years old, my parents sent me for this public speaking competition, and somehow I got picked amongst like, the first, the top five people from a group of, like a thousand kids, to be able to go and speak to the city of, you know, have a speech in front of the city, in front of the mayor of the city. So I go in there, I'm like the fourth person in line, and my mom sitting somewhere out there, and you know your eyes kind of wander, because you're trying to make eye contact. When I look at my mom she starts giggling, but she also hides her face, and what happens if you're a 9 year old kid and you see your mom giggling? You start giggling too. So there I am stage trying to giggle twelve minutes into my 30-minute speech, and because my mom was giggling, I forgot my words, right, and because I forgot my words, I made a fool of myself in front of the mayor of the city. Now I could apply that to myself, and I could say I'm never going to take my mom again to any further speech, or I could train myself that if someone starts laughing, do not, like, you know, let that affect me.
[00:09:40] This process of continuously evaluating, and applying it to yourself, needs to be a part of a daily regime. If you do that, you become comfortable with failure. Does that make sense? Like if you don't do that then you're uncomfortable with failure, right, because you're like either it's you're holding yourself to some crazy standards, or you're looking at public perception, but if you just think about this as a continuous learning mechanism, that you have to apply in your personal life, there is no judgment. There is just this continuous evaluation phase of what could have gone better, but never ever do this with your partner, right.
[00:10:21] You have a partner, and you're like. "Oh wow! If he or she was this way, things would be a lot better." That's like, no goal. You can do to yourself, but you can never do it to your partner. So let's talk a little bit about what failure means in this iteration, innovation, and disruption spectrum. Right? And iteration is like trying to look at incremental improvements to your current process. Innovation is you're trying to figure out a new way to look at the same process, and disruption is you're trying to figure out a whole new process to look at things. When you think of, back to the slide again, when you think of the slide, what we have to lose in the iteration spectrum is not a lot, right, because it's incremental. For example if you're getting a thousand bookings per day, and you run some tests that will give you two or three additional BPD bookings per day, and if you fail, it's perfectly reasonable. On iteration though, does the scope of failure, or your risk tolerance to failure is really low, but then I think of innovation. You think of innovation, your risk tolerance suddenly becomes a little harder, if you put in changes that changes your thousand bookings per day to 2000 bookings per day. Now, you're like, you know, more averse to risk because the return of investment seems a lot harder, right.
[00:11:47] All of this works really well when you think of the disruption spectrum as well. Now thousand bookings per day and you're trying to get to 10,000 bookings per day. Now you're going to be even more risk-averse, right, because the return on investment is higher. So just know that the outcome of a discussion of an offputting thing sometimes changes your internal methodologies of the risk profile that you have.
[00:12:10] All of this seems to work really well, besides the gambling spectrum, right? Because in the gambling spectrum, you don't mind putting ten pounds, ten pounds in, ten pounds in, ten pounds in, hoping for a million pounds in change, but this is something that you as product owners or as co-founders of companies have to always think about, that like, you know, is the return of investment so high that the risk of failure is making me think myopically? And if you don't think that way, you know, you're probably making the wrong decisions in terms of your failure-making criteria.
[00:12:44] So at Amazon, we follow something that is called as the working backwards process. Does anyone know what that is? So the working backwards process is really the hypothesis process, and we do a lot deep learning during the working backwards process, and sometimes we say, "Okay, we want to go to China, or we want to go to India, or we want to launch a new device." A really good example: I wanted to launch a new device that is voice-activated, or I want to launch a new device that is activated just through blinking my eyes, or I want to launch a new device that is sense-activated, right, sensory, through touch.
[00:13:29] And we do this deep analysis — and that analysis can go anywhere from like two weeks to nine months — where we're really trying to internalize and work backwards from what we want from the from the customer, what is the ideal output that we want from the customer? And through this practice of working backwards we inherently figured out like, you know, our appetite for risk would also get a deeper understanding of the customer. This, by itself, is not sufficient. Right. Like you know, if you go work in a silo and say, "okay, this is what it takes for us to get into the Chinese market." You worked for six months. You come up with a document of how you do go into the China market. You go into the Chinese market and you realise, boom! Everything's different, right? So your strategy doesn't necessarily define the way you, kind of, think about your hypothesis, intent-driven approach. You have to keep tweaking that to get the best out of it.
[00:14:29] Here are two common practices that we have, that we use even at Rentalcars: pretotyping was prototyping, and pretotyping is a new concept developed by this really cool leader at Google or Alberto Savoia, and he's saying, "pretotyping is basically prototyping with skin in the game," right, and so what can you do as a product owner, or as an engineer, or as a co-founder that shows skin in the game; that I am committed to this, right, and a really good example that he gives is for Elon Musk, when he launches first model of of Tesla, that he, you know, made sure that everyone got a deposit. Everyone paid a thousand pound deposit even before the card was made right, and that shows the customers showing skin in the game, right.
[00:15:14] For us within Rentalcars, if we are trying to reduce the spectrum of how painful it is to pick up a car, just testing the intent of how painful it is, but also how much customers are willing to pay for that effort, to reduce that pick up time, is really critical from a pretotyping perspective. So we kind of deal with both of these. Pretotyping seems to take a while for product owners to kind of establish, but once they do, they feel they have skin in the game, and when they have skin in the game, they feel more committed to the outcome of a decision. Very different than building a prototype.
[00:15:52] The second concept that we've kind of used is premortems versus postmortems. Does everyone know what a postmortem is? Okay, for the postmortem is, you failed. Now let's analyze why you failed. Right. Or you succeeded. Let's analyze what what happened, and why you succeed, and let's use that. A premortem is an important concept that we've used a couple of times, and I'm going to give you a few examples of that. A premortem is an assumption of a point in time in future. So assume I'm launching a voice-activated device, a premortem is a discussion that the device launches, two years from now, And is a disaster. Why is it a disaster and what steps could have taken to prevent that disaster is really the premortem analysis.
[00:16:39] So two examples of what we did within Amazon that kind of helped out was, we wanted to we wanted Kindle to be a very social engaged effort, and Amazon doesn't have a lot of foray into social, and so we built what we thought was the product vision for Kindle devices to go social, and then we ran a premortem exercise, and with premortem you bring a bunch of different people with different viewpoints and say, "Give me all the exact reasons why this particular product will not succeed," and you say, "Okay, we launched social within Kindle devices and is going to fail, and it's going to fail." The one recurring theme that we came back over and over and over again is it's going to fail because we do not have the network effects. Amazon inherently isn't what we would consider a social product company, and so to be able to build that social product within the transactional context of Amazon is going to be super, super hard. That reflection, along with other things, led us to, like, actually make an acquisition of a company that was already inherently social. And so we bought Goodreads, and Goodreads is a social community around reading. So, sometimes you can make build-or-buy decisions by running a premortem.
[00:18:05] We ran a premortem just a couple of weeks ago in Rentalcars. Rentalcars has a solution called Rideways, and Rideways is a chauffeur driven service that brings you from point A to point B. So if you land in Amsterdam, and you want to go to your hotel, and you don't want to have to deal with, you know, trying to figure out where you Uber is, or your taxi drivers, or trying to figure out whether they communicate in English, then Rideways is a good solution for you. What Rideways does is they'll have a chauffeur, or a concierge, wait for you right outside your gate, or in a common place saying, "hey, here's your name, Supriya." You go find that person, and they take you where you need to be taken, and that is works really well for travellers who don't want to engage in a foreign environment, also for business travelers that don't necessarily want to wait in a queue, right?
[00:18:58] So we ran a premortem on Rideways, and we're like, "Okay, Rideways is at scale, right now — it's like, you know, it's doing well. We've had this product on for two years." We ran the premortem to say what will prevent Rideways to become 100x its size, okay, and we said, "right, Rideways is 100x its size in two years, but it's a disaster. What are the reasons why it's a disaster?" And we came up with the recurring themes about why it's a disaster, and the common one was that we couldn't figure out how scale worked from a supply standpoint, right? How do we get suppliers to come in? And so now, you know, the managing director of Rideways is making that his number-one focus. And so premortems kind of opens up your world into what is the elephant in the room — but not just the elephant, but also say "oh, it looks like the legs of the elephant is what everyone is worried about, so let's try to focus on those two or three things." So it kind of like is a risk mitigation strategy to help you deal with failure.
[00:20:02] I think the language of failure comes down to two things: risk tolerance versus regret minimization. And risk tolerance is your propensity for risk, right? How risky are you if you're a single individual who's starting a company, founding a company, and you know, you've saved up enough money. Your risk tolerance is quite high. That risk tolerance changes now if you have a family: someone to feed. That risk tolerance changes if you have like 20 employees. And so your risk tolerance changes based on your life stage, but also your propensity for risk, right. That propensity for risk can be adjusted if you increase the horizon of your thinking. The propensity for risking, "Oh, should I take this risk on this particular venture?" Immediately if the answer is no, and you're like, "No I don't want to take the risk." Ask yourself the question, "What is the time horizon for which you're looking at the return of investment?" If the time horizon of your return of investment is a year, or two years, that kind of like you know changes your risk portfolio. So if that risk portfolio, or the risk, the time horizon becomes seven years, or 10 years, you're much more likely to take a risk, right? And so just know, that that is just human behavior. Right. If you're looking for a return of investment really really quickly, I mean I say quickly, it could be three months, six months, a year, then your risk tolerance changes.
[00:21:34] The second one is regret minimization. This is something that Jeff Bezos talks about frequently when asked why he started Amazon.com. He said he tried to apply the regret minimization framework, and it's basically asking the question, "are you going to regret not taking this decision?" Okay, so for me when I decided I was going to like, you know, take me and my family away from Seattle, and move to Manchester, I thought about, "do I really want to do that from a risk tolerance perspective? I'm in this cushy job in Seattle, and this really nice house, and like, you know, have all my friends, and everything set up." The answer was "no, I don't want to take that risk." Okay.
[00:22:20] But when I thought offer from a regret minimization framework. I was like, well, this is an opportunity for an adventure that I may not have again. What will this, what will... Will I regret not taking this opportunity two years, or three years, down the line? Will I regret not coming to the UK, working out here, being able to travel, being closer to my family in Dubai? And the answer was a resounding yes. So if you feel like your risk tolerance is failing you, you do have that to regret minimization framework that you can apply to yourself, right? And so coming back what, coming back to our basic point is like, what does failing fast mean? Failing fast means really the ability to be able to continuously try things, but knowing full well that as a human being your risk tolerance changes based on various criteria, and so if the answer comes a resounding no, I don't want to take that risk, than answer the question, is it an iterative, innovative, or disruptive risk? Is it a risk based on time horizon and maybe that's why I'm not willing to take the risk? Even if through all those answers of that risk tolerance portfolio says no don't take the decision, then look at regret minimisation, and see whether the choice of an adventure is kind of going to lead you elsewhere.