 Hi, everyone. It's amazing to be having these in-person events after such a, such a long time. And just the energy and people taking selfies. So hope everyone is making the most of these connections. I am very, very thrilled to be here. At the same time, I'm pretty nervous doing this in-person after just being virtual behind the computer. And it reminds me of my daughter saying, don't be a robot. So let's see how it goes for today. First of all, I wanted to talk about, you know, Cruise, where I'm right now VP of Product Engineering at Cruise. And Cruise is a self-driving car company in San Francisco. It's a pioneer, and we launched it this year. They've safe, shared, and all electric. And I was talking to some of the colleagues here and some of the other attendees. They were like, is it real? Do we have driverless cars on the San Francisco roads? Yes, it is. And you can take a ride. And if you want to find out more, you can go to getcruise.com and join the world of transforming the future together. Today's topic is very much along the similar themes that you've been listening to in the morning, which is customer-centric and hypothesis-driven innovation. This topic is something that I'm very passionate about and very close to my heart. What is a good product? A good products are researched extensively, and they are tested extensively as well. But what differentiates the best products? And that is where they are built in a culture that values experimentation. It values empowerment and risk-taking. It values the piece around data-driven insights, and last but not the least, customer-driven insights. So with that, there is no one magic formula that's going to transform the organization to get to that end state. And you saw today morning talks. There are so many different examples, and I'm sure each and every one of you is championing it in some way or the other. And today, I want to share some of those experiences and insights that I have seen have helped to transform and bring about this culture change. So with that, today, I'm going to focus on four areas that are touching different product development lifecycle phases. One, being honing the problem and scoping your hypothesis. The second is going to be experimentation and ways to validate the hypothesis in the shortest time. The third is going to be MVP and seamless collaboration with everyone wearing a product hat. And the fourth one, completing the circle, being in the trenches with the customer and how to go about doing customer shadowing. So with that, let's jump into the first one, honing the problem. Not having the clarity of the problem and purpose can result in getting pulled in multiple directions. And I'm sure that's happened to each and every one of us in some way or the other. And then how do you bring back to the guiding principle or to the goalpost? I often tell people, don't tell a solution to an engineer, but rather, take the problem to the engineer. And we all have fallen traps to that. For example, if you tell an engineer, build me a wheel, they will build you one. But if you tell them the problem that you're trying to steer a boat or a sail, they will surprise you with the solution. So with that, how are some of the ways to hone in the problem? I love this golden circle that's described by Simon Sinek in his book, Starting with the why. Every org knows what they are building and how. But very few organizations know why they do what they do. And why is the purpose, the cause, the belief that brings and binds the people together? And this concept of why and the purpose is not just high up at the organization level. It is to be weaved into every aspect of your product, your feature. And this is how you bring in the muscle memory. So let's look at some of the examples of organizations that have defined this purpose or this why. One of them we'll start with is crews. At crews, we've driven to safely connect people with places and things and experiences that they care about. The sense of purpose and mission to save lives and reshape our physical environment and restore freedom is what binds and brings the cruisers together. And that is what we often talk about and have that shared bond. Let's look at some other known examples, Microsoft, to enable people and businesses throughout the world to realize their full potential. Another similar brand name, Apple, to create products that enrich people's lives. So you need to look at what is that why and purpose for you, for your organization, as well as for your product and feature. Let's talk about how to scope the problem and frame your hypothesis. People are familiar with the build, measure, and the learn model. But many times, I see people fall into a trap. They start with the build. But rather, first, start with the learn. What do we need to learn to validate or invalidate the riskiest hypothesis? Then you go into the measure. What data will allow us to measure the learning? And then the third step is when you get into the build, which is what do we build to generate the data that we can measure? And this is really important to be able to answer our questions. There are two common types of hypotheses. One is the value hypothesis, where the metrics that you're optimizing for is around retaining your target audience. The second hypothesis is around growth hypothesis. And the metrics there that you're optimizing for is referral rate, NPS, et cetera. Now when you're trying to hone in all these different hypotheses, you want to ask the questions that's going to help you narrow it down. Do your target audience recognize that this is a problem? And if you build a solution, will they use it, pay for it, and will they use it from you? This is where we all have seen the reverse happen quite often times. I have an example where we were biased by some of the buzzwords and some of the solutions at one of the companies. And we were like, we want to build a community. Well, we all have seen different communities and the flavors of it, so we all know what that end thing looks like. But that's where we were biased and not seeking truth on the problem and how the community would internalize for our customers, for our problem space. And we jumped into solution too quickly. And we had a six to nine month, fully perfect community building going on. And that's when we realized that we were just too invested in it and we were trying to find the problem that would use that as a solution, rather than other way around. One of the ways to help hone this in is by investing in training and learnings and frameworks that can equip the team for templatizing some of these hypothesis and assumptions statements. To wrap this section, what is the impact once we have honed in this purpose and the problem? It inspires and bonds people together. And this bonding is not just at the organizational level. It continues and creates this bonding across partners, across your customers, through your products. This in turn lays out a foundation that becomes the not star to drive the alignment by having everyone draw in the same direction. Let's go into the second section to talk about experimentation and how do we remove the biases and get answers and confidence quickly. Doing big investments without having the conviction leads to self-fulfilling prophecy. I'm sure we all have run into some variation of this. How might we mitigate this group think and biases? Example, we all have biases from our experiences and we all have strong opinions. But without validating, you don't realize how quickly we can get into a black hole. The example I was talking to you about earlier, where we invested in building this community functionality, we realized that we were just bought into it and were hesitant to pull the plug because of the investment we made. And on hindsight, we could have got the answers much more quickly with shorter investment rather than being stuck to know it all attitude. This is where we need to go broad and then to go narrow. Get all the perspectives and cross-function representation to make sure we have a well-represented ideas. First, you need to hear from a diverse set of voices, both in the room and outside the room. At Cruise, we encourage this culture of psychological safety, empowerment, and ideation. You want to have debates. You want to have curious questions. And that is how you create these respectful environments that fosters psychological safety. And you want to have this comfort of people voicing their thoughts, because we all know the strongest ideas could come from anywhere in the room. And at the end, to avoid the group think, how do you agree to disagree and come it forward? This is where when we push beyond our conventional thinking, we discover unique solutions that delight our customers. Now, how do we get to these ideation, right? When we start with the ideas, we all know the first one might not be the right one or might not be the one that makes it. But it is the stretch of ideas that put something together which is beyond and much more greater. And now, how do we narrow these ideas down to know which one we can test to not spread ourselves too thin? So for that, we need to have a well-defined experiment. What is the goal of a good experiment? It is to build confidence that we are on the right track in the quickest way at the same time with the least investment. And what are these ways to define this good experiment? It consists of a really narrowed down hypothesis that we want to validate with quantitative and qualitative data that can give us customer insights to validate or invalidate our assumptions. Now, we all know time is the essence. So how do we get these experiments turned around in the most quickest way? We want to avoid waste, and we want to learn quickly. Here are some of the ways. These are just some of them. I'm sure there are other opportunities and experiments that people have tested that have worked and that can be done in the most fastest way. One, being for cycle sketch. Just doing sketches and validating those. Second one, more visual walkthroughs. Both of these have least investment. At the same time, it gets the point across. And trust me, we all have seen where sometimes we've skipped these steps. It's bringing that discipline. The third one is demand test. Just even putting a button and seeing if the users are clicking it, even if it means the functionality is still to come. But it helps you to demand test that whether the customers are going to be needing this or where they're going to be needing it. The last but not the least, hack to market test. At Cruise, we do a lot of these with our operations workflows where we have used a mix of spreadsheets, collaborative tools, forms, et cetera to simulate these operational ways to automate. We ideate. We are able to quickly adjust those things. And then once we have confidence, we are able to integrate that into our product, into our functionality. And that model is helping us to do least work, as well as least throw away. Now, one of the ways to keep this in mind is to make sure that we are not stuck in one particular aspect and are able to leverage different things based on what's working and what's not working. We know that at Cruise, when we tried out some of these things, our learning time went drastically down. And what does that mean? It's not only that we can cater better products, but it helped motivate our employees because who doesn't love shipping? Who doesn't love learning? Who doesn't like faster iterations? And it was a great motivator. What is the impact from some of this? With the experimentation and speedy hypothesis, we are able to ideate quickly. We are able to rule out the noise and bias with the least investment. More so, it creates this culture of risk-taking. It removes guesswork and know-it-all mindset, and instead fosters a framework for decision-making. Because even if your experiment showed that it's not, the result shows that it's invalidated, it's not a failure. It's a learning that's helping you have more information to equip the next steps in your life cycle. Doing this is significantly helpful and it should just become a way and normalize it and make it a day-to-day thing. Let's go into the third section, which is MVPs and seamless collaboration. As the product matures, it's vital to get end-to-end perspective by honing the product instincts in every role. Why is this important? We all have seen it, whether it is a product that you're just trying to get product market fit, or it's a well-established product that you're enhancing and taking it to the next level. Perfection can be your enemy and bias how you break down the problem or you scope the MVP, because that is really, really critical. Being siloed in role boundaries can result in gaps and end-to-end thinking and flows can be jeopardized. Let's look into how to mitigate some of this. One of the ways to do that is through dog-fooding. I'm sure everyone is well-versed with this term. Don't let your customers be your first testers. One of the ways to validate is understand and walk through the functionality yourself. It forces you to think like a customer and understand what might be the gaps. Getting different perspectives as part of validation is really critical, and this is where, how does everyone put on a product hat? This is where some of the things that have worked is doing dog-fooding and validations, bugbashes together as a team with PM, design, engineer, everyone. And how do we make it a fun activity? Prizes always goes a long way. Small things like gift cards or recognitions of who found the most trickiest situation or who had the most polished bugs or who had the most number of bugs discovered. But this brings about a shared understanding across all of the functions and brings about this product hat for everyone and this ownership of product instincts. There's a fabulous example that I learned the hard way. At Microsoft, I was working on Azure Management Services which used to have all these different compute data security services that people could manage or onboard to. And we used to release every two weeks and our VP at that time would actually, before in the pre-production environment, before it goes live, he would dog-food it and he would catch issues or patterns or extra steps or missteps that can cause into customer friction. This actually helped rein in that culture at every level and across the whole company. And it was very, very powerful, very insightful at the same time. The last one is about metrics and stats sake. How do we make sure that data and metrics is not an afterthought? It's easy to say, but we have fallen, pray to some of this. For example, we had a metrics, we had an experiment and MVP that we launched and after launching, there was confusion around which metric, what is that metric supposed to do? Was it the right metrics? Is the data that can be trusted? And that is too late because now you've missed the boat, you have to now spend the time fixing it and redoing the experiment. So make sure as part of your validation, you are also looking at validating the data and clarifying the ownership across whether it's a data analyst, whether it's the PM, whether it's the engineer and making sure that the definitions and the outcomes are well understood. At the same time, what are the goals that we are looking at for the metrics to hit? Doing these MVPs as well as the seamless workflow and dogfooding helps to have a better ownership. Not only that, it avoids building a Frankenstein product. It is just amazing to see how products and functionality as they evolve, you can make out the organizational boundaries that start surfacing in that and the ways to mitigate that is with this dogfooding and everyone wearing a product hat. It also builds repeatable and continuous MVPs and last but not the least, builds the data-driven decision-making muscle that is so critical in the organization. That brings me to my last section, be a customer. Walk in the customer's shoes to empathize and understand the problem. Why is this important? Teens can't work in a vacuum. They need to hear from the customer's voices that will be everywhere and teams need to strengthen these relationships. Completing the circle, being in the trenches with the customer to celebrate the impact of our work and understand if it's solving the customer problem is key. It is super motivating when you see how your customer is using your technology and how it's saving them time. At the same time, it's humbling when you see them struggling and feeling like dumb of what and how to use this. So how do you learn from it at the same time celebrate? Here are some of the ways to ingrain this customer-centric view through customer shadowing. We regularly integrate user research and data into both the early stages and the later stages of the workflows. When our teams have this data in front of them, it helps to tap down biases and helps drive clear decision-making. At the same time, the second aspect which is a theme over here is the customer shadow also called the Gemba Walk. Gemba is a Japanese term for the real place. And Cruz does this really well and it's a culture that's instilled by our CEO Kyle who actually takes weekly rides in the driverless car and shares the experiences and learnings, both the wins as well as areas of improvement. Now, given today's day and age of remote work, we can't expect everyone to be able to travel and shadow and do everything in the same place. That's where we have made this an explicit and early on investment to bring customer shadowing to our organization in a repeated fashion. We have repeated meetings set up virtually that shows the customer shadowing. Whether it is demoing the actual car rides at the all hands to having repeated meetings that are sharing what our operations are doing to launch our fleet as well as to service it and while keeping safety at the number one step. This is where we have virtual ways for people to see the end to end functionality. At the same time, ask questions and understand where the pain points are. We also encourage in-person, so whenever we have off-site and in-person meetups, we usually have it with a shadowing exercise as well. This is where it makes it easy for everyone to see but also share their observations. One of the things I really am proud of at cruise that it does is we have recently added be a customer as a value to our top six values. And we use the hashtag be a customer to be able to share these experiences and learn from it. And making a connection with the customer and building this relationship means removing just the word persona or customer, giving it a name and making it more real human. It goes a long way. As we wrap up this final section, you can see the profound impact that this Gemba walk has. It builds deeper relationships and empathy for our customers. It helps drive better products that are catering to the customer needs rather than just the buzzwords in the industry. Last but not the least, it helps speedy turnaround on friction. There have been numerous cases where engineers have come back from their shadowing and they've gone and fixed bugs without anyone telling them. Why? Because now they understand how their products and their features are being used. What is the friction that they are having and to course correct and adjust very quickly? This is how we empower people with the information at their fingertips to do their best and make the best decisions. And how do you drive this DNA and build this customer-centric innovation across the company is through these connections with customer and customer shadowing. To close on, hope you start with the why and find the purpose. I love this quote from Antoine. If you want to build a ship, don't drum up the people to gather wood and give orders. Instead, teach the people to yarn for the vast and endless sea. It was a pleasure to be here, to learn from all of you, to connect with this amazing product community and thanks to Product School and have a great rest of the day, everyone. Thank you.