I didn't say that. You were the evil, he threw you in the first. Hi, how are you?  Can you have just to get them open? Has he come in yet or not? I don't think so. I'll just take them with me. Pack the phone. Thanks. Is that a follow-up or no? Is it religious though? Yeah, but I've been going to school for two years. Better than me, don't you think? You've got Jamie. Jamie, can we get somebody to load in? Yeah. Oh, I'm sorry. Do you get a picture of her over here? Who are you? Who are you doing it? Who are you?


Scholastic Audio Presents. My name is not Friday by John Walter, read by Deon Graham. Civil War, Mississippi, Part 1. Heaven, Chapter 1. I know that I'm with God. He's with me in the darkness. He's close to me. Not real close, but close enough I know he's there. Somewhere. I can feel him. So I know he must be. It was him that brought me here. At least I think he did. Only it ain't what I was expecting. I never thought it'd be dark here, but it is. It's real dark. Pitch dark. And it can't be night time cause there's birds singing. There's a blackbird and a sparrow. There's all sorts. And them birds don't sing at night. Except maybe they do in heaven. Maybe they sing here all the time. If I shift my head, it hurts me inside and out. So I don't try to move. I stay as still as I can. It's kind of damp here in the darkness. I got it up inside my nose. A musky smell. Like fur. Like rabbit. Yeah, maybe it's like a rabbit. And there's another smell. A whiff of old shoes. Like when you're wearing for too long after they get wet. But I ain't wearing shoes. I left them in the Sunday box and they ain't no good to me there. Not anymore. I can feel the dust beneath my toes.  A cloth against my cheek. That's the reason I can't see my feet. I got a bag on my head that's been used to carry rabbits. I still don't move a muscle. But in my skin. In my head. In my heart. I panic. I feel like a cornered rat. Scramming up against the wall of a deep dark cellar. Breathing fast enough I could've run a mile. So I say to slow down, Samuel. Slow down now and calm yourself. Take one step at a time. Give yourself the time to think this thing through. I know I'm lying down. I got a sense of me stretched out upon the ground and it feels like I'm lying on twigs and stuff. Yeah, I'm sure I am. I got one sticking at my side and- Sample complete. Ready to continue? Thank you for watching.


Hello, everyone. Thank you for joining me today to talk about product-led growth. This is Sashi and you guys might already be familiar with who I am from the LinkedIn post. So anyway, today we're going to spend some time talking about product-led growth, why this is important for PMs and how some of the successful companies and products that we know of today have used some of the techniques and frameworks I discussed today to drive that growth. We will dive into the core parts of what is a product-led growth strategy and then we'll talk about some of the effective strategies to use to build a good product-led growth. So I'm product director Expedia and I lead the shares at Expedia. Before this, I was at a stock about today to drive growth for my product. I've been doing product management for about 10 years and most of which has been building consumer products. So I've worked on some really successful products like Amazon Alexa as well as Launching Edge. And here are some details. I have my email here as well as the LinkedIn profile link. So feel free to connect, reach out if you have any questions. Let's dive in. So as I said, the on the agenda we have today, spending a minute about product-led growth is growth can mean different things to different people. And so we'll talk about when we say product-led growth, what am I referring to by product-led growth and what does product-led growth actually stand for. We will strategy and then we will look at how to build an effective product-led growth strategy. And as I mentioned, I'll be using Dropbox for our case study to see how some of the concepts that I introduced today earlier in the talk, they have used in building a successful product and a company. Whether you're a growth PM or just a product manager working on any product really, growth is every product manager cares about. You know, you want your product to be used and whether it's about user adoption, whether it's about driving an additional ARPU incremental revenue or just re-engagement from existing set of customers. It is something that all product managers think about. We'll see in the talk today is that a lot of the concepts and techniques that I discuss can be used regardless of whether you're working on a B2B product or a B2C plus don user acquisition or retention. All of the things that I talked about today can be used as a product manager for driving growth. I will talk about my experience, how I use some of these techniques today during my work at Alexa as well as cloud kitchens. Okay, so let's talk about what product-led growth is. Product-led growth essentially is a business strategy where your product is the center focus for driving the company's growth. So in traditional business models, companies rely on marketing and sales to drive product awareness and adoption. Whereas in case of product-led growth, your product itself is the center focus of your growth strategy for the company. And so what does that mean? Really, it starts with building an intuitive, you know, valuable and a user-friendly experience where the product practically sells itself. This is what the essence of a product-led growth is. It's about creating a product that's not just functional, but the one that also creates a really great user experience. This positive user experience becomes the catalyst for growth where a satisfied user naturally starts advocating for your product and thus driving that adoption. At the core of the product-led growth is the idea that a great product leads to growth by fostering customer adoption and loyalty. When users find your product to be useful and they can see that their daily lives or the problems that they have to work with are becoming easier as a result of your product, they are going to become the spokesperson for your product and talk about it to their friends and their colleagues. Think about from your personal experience itself of some of the products that you like and really love to use, whether it's digital products or physical products. Like if you use a product that really solves the problem and it's easy to use, you will then go and talk about it to your friends. And that is really in a nutshell what product-led growth strategy is. It is about building an intuitive product that solves a customer problem, is easy to use and creates sort of this viral loop from your customers which drives organic product growth, hence creating a self-sustaining strategy for growth. Take Dropbox as an example. If you remember when Dropbox came out, it was really solving one problem which was giving you access to your files across different devices. And to get started on Dropbox, it was really easy. You just had to enter your email, the account is created and boom, there you go. You have 2GB or 4GB, whatever model space you got, right? And so think about that intuitive and onboarding experience. It's so easy to get started with. And further in the talk, I'll talk about some of the other strategies that Dropbox used to drive that growth. But that's an example of how from the right from the moment you use the product, the experience is so intuitive and easy to use that you immediately become a sticky customer and then you go and talk about it to your friends and other people, thus driving the growth for the product and generating more users and customers. It is really about creating that mindset shift from, hey, I want to sell this product to identifying that customer problem, solving it in a really intuitive way and creating this great customer experience which then translates into product-led growth. Now let's look at the building blocks of product-led growth strategy. The first one is user-centric approach. User-centric approach is really the heart of product-led growth strategy. It is about understanding your users' pain points and behaviors. If you understand your customer's main problem, then you'll be able to empathize with them and then you can focus on building a product that solves that core problem. And user-centric approach is not just about solving the problem, but also the user experience itself. It's about creating this experience where the customer is able to achieve their goals from the product without having to face any friction. The next one is product adoption and onboarding. Onboarding is another important one. It's really about creating this seamless way for the customer to get started with using the product.  Think about some of the products that you use where you can really get started by giving your email address as an example. Experience and being very careful about getting them to the product experience as soon as possible without front-loading them with all these other things that are really not needed. And so that's one part of it, but there is more than that. In addition to making the onboarding seamless, the first set of screens that they see, the tooltips, the introductory video, the clear instructions, letting them know how they can access tutorials if they have to come back later and check something out. So that's another part of the PLG. Now, once you have figured out the core customer problem to solve and you've built this experience that is less fructive to use and super easy for the customer to get started with using your product, you've laid the foundation at that point. At that point, it is really about getting the data to iterate further on the product. So I'll talk about like an example from my work at Cloud Kitchen. At Cloud Kitchen, my team built analytics products that helped restaurant owners understand how their food delivery business was doing. So it was really about sort of looking at the sales, identifying the trends in the sales, figuring out which menu item was selling the most, which channel was performing the most and so forth. Anyway, it was a bunch of data presented in charts and stuff where the restaurant owner can look at this and have better operational strategy when it came to running their restaurants. And this was a web product. One of the customer discovery sessions that I led, I realized that a lot of our customers were not using our product because their lifestyle made it harder for them to use the product on a regular basis. What I learned was that a lot of these restaurant owners by definition are mobile, meaning they're not sitting in front of their desktop or laptops all the time, you know. Most of the restaurants and owners have one or two restaurants or maybe multiple restaurants and they're going back and forth. They have to deal with their out of potatoes or one of their staff member did not show up and things like that. So by nature, these people are mobile and so expecting them to sit in front of a computer and do this analysis to figure out what is the most operational strategy is really not the right thing to do. What I realized was we are missing the customer sort of daily life, like what their day looked like. Once I sort of understood that, hey, the core problem is that these people are always mobile and they don't have an easy way to access our product. Actually pivoted our strategy from just having a web product to building a mobile app for our restaurant owners. This was me sort of understanding that the core of the problem is not that we are not giving them the charts or the data that they want. It's that we are not meeting the customer where they are. We are building this product on the desktop, whereas the customer is really on the move all the time. Once I had that insight and I was able to empathize with our restaurant owners, I sort of pivoted towards, hey, we should go build a mobile app. That mobile app really focused on one or two problems. Instead of having this gigantic amount of sheets and all the data loaded in mobile, my first version of the mobile app was very much focused on just showing them the sales throughout the day. Not just that, the onboarding to the mobile app was super easy. All they had to do was download the app, enter the email address, and then log in information because they are existing customers and boom, they are on the dashboard which shows them the core data that they look for on a daily basis. Just by doing this, just taking the existing product on web and removing, taking some of the features from the product, not even the entire product, taking some of the features from the product and offering it on a mobile form drastically changed the adoption for our product. We went from having anywhere like 15 to 20 percent of weekly active users slash monthly active users to more than half our customer base were now using our mobile product on a daily basis. That's how impactful that was. We didn't invent new features. We did not invent any new strategy or anything. It was really about sort of understanding that customer problem and building that problem by understanding where they are, what their daily lives look like. Once I had that, I used data that we collected from user interviews, feedbacks, app reviews, and then further iterated on adding new features. So that's what data-driven iteration is. Data-driven iteration is the idea that once you have identified the core problem, you've built a seamless experience for the customers to get onboarded, you then use data to further fine-tune that experience and identifying new problems, new features that needs to be added to bring those customers back into the product. Whether it's about new features, whether it's about sort of improving a certain experience, that's what data-driven iteration is. The next one on the block is using freemium and free tile models. What this is really about is some products, you know, and this could vary from product to product, but some products really creating an experience where user can get started and they get a preview of your product. And, you know, think about Canva as an example, right? Somebody who is looking to actually edit a picture or create a nice, you know, slide deck or stuff, they're most likely not going to go download Canva and start using it or like go for pay for the product right away. But by having a freemium product where you let them edit one image or two images, help them sort of get a taste for the product, which then, you know, you can use to convert them into a paid user. Similarly with free trials, you know, having a free trial for a product, you know, gets your product into people's hand where they use it for certain amount of time, whether it's three days or a week or a month. And once they are used to using this product and they realize that this product actually solves a real problem for them, they are more likely to pay for your product and become a customer, versus if they did not have that free trial or they did not have the opportunity to use the product for free. So that's another effective strategy in sort of using your product to drive growth. The next one is viral loops and network effects. Viral loop is the strategy of giving your existing user or a customer an incentive to talk about your product or share about your product, whether it's social media or word of mouth. Take Dropbox again as an example. Dropbox really did an amazing job with the viral loop. If you remember with Dropbox, once you signed up as a customer, if you brought any of your friends to use the Dropbox, then you got 2GB in additional storage as well as your friend did. Now that is a great loop wherein as a referrer, you get some bonus as well as the new customer who is coming on board is getting a benefit or so. It's like if you're able to create two-sided incentive like that, that's obviously a great loop. But that's just not that. It's also about take Viral, the game that became super popular. Another example of how it got a lot of user adoption was they created this network effect wherein once you played the game, it encouraged you to share how you did on that particular day on Twitter, an example. And people saw that and then other people wanted to come talk about it and brag about like how they got the word right. So that's another example of how you can use now these small strategies like sharing on social media or incentivizing your existing user to talk about your product to drive that organic user adoption and acquisition. Next up is in product marketing and upselling. This is really obvious, but this is this notion of like whether you're doing freemium, whether you're doing a B2B product or a B2C product, having sort of banners in your product that talk about new feature releases or I don't know, like change of certain models or things like that is another way to sort of get people to learn about new features that you're launching or new products that might be coming. You can also use in product messaging to upsell new features. In the Cloud Kitchen's example that I already talked about where the mobile app, where the mobile app is what we use to bring a lot of these customers to use the app on a regular basis. Actually in the mobile app, I would talk about new features that the company was launching. For example, we launched a way for the customers to manage their promotions on Grubhub or Uber Eats. I would talk about that as a banner in the app and that drive the signup for that additional SaaS service through the product. So that's another sort of strategy that you can use that once you have product customers using your product, you can use the in-product messaging whether it's notifications or banners or things like that to upsell them to new features or new revenue streams for that matter. That drives additional revenue from these customers. So I already talked about Cloud Kitchen's and how I used some of the techniques from the last slide to drive adoption and growth for our product. But let me actually just bring all the different pieces together from the previous slide and how I use this, how I use some of the things to drive an end-to-end growth at the company. So as I mentioned, the first step was identifying this user need that they want to be able to actually be connected to the restaurant in terms of what's going on when they are mobile. And so once I had that insight, I said, okay, the desktop product is not where this is going to work. We need to pivot to having using mobile as our strategy to drive growth. Then I built that, identified that mobile. Next up was then sort of designing this onboarding experience. And the first thing that we did was once the customer logged into the app, the homepage was just a dashboard of how each of these different restaurants were doing, what was their sales, total number of orders that we're seeing by taking them directly into the data that they cared about the most that they were looking for quickly, like not additional screens, no additional clicks. As soon as you log in, you give them what they're looking for, that most of them are in problem. On a daily basis, track sales, track orders made that they immediately were able to extract value from the product. The next step was using the data and talking to the customers and identifying that what else are some of the things that they wish the app did for them. And I learned that they would like us to tell them if there is anything that goes wrong with their restaurants at one of these platforms, they would like to actually get real-time notifications. So I built real-time notifications. So it's like you take the first set of users that you have that are really sticky and you ask them, hey, what else are things that you value that you would like to see in the app? And once I had that insight, you add that feature. Once we have a starting app, a set of features you add based on the feedback, I actually started to talk about other sort of SaaS services that my company provided, whether it's subscription to the marketing product, subscription to the labor product as an example. And they would learn about it, about these other subscriptions online in the mobile app, and they would go subscribe to it. They would sign up for these services. And this actually generated more revenue from the existing set of users. Next up in the strategy was like, how do you sort of take this product and bring new customers to the company? And one of the things that I was considering before I moved on was then taking the app and letting anyone sort of go download it and use it. And so really the crux here is sort of like, as you can see, to drive more revenue from existing customers, as well as bringing new customers to the company, how that small shift in using mobile as a hook drove all these different things, which ultimately that in more revenue and more for some of the products and features that the company offered. So going back to sort of like, how do you like take these strategies that I discussed and use that to generate an effective product-led growth? It could really be sort of broken down into maybe at a high level, these three things, freemium and free-tile models, viral loops and network effects in product marketing and upselling. And as you saw from my example at CloudKitchen, I've used all of this in some capacity to drive the incremental customer growth and incremental revenue from existing customers. So let's actually unpack each one of these and see what they mean. Freemium and free-tile models. This is about offering free version of your product so customers can try it before they make a decision on should I pay for it or not. Can wise an example, that does that. The second one is showcasing the value of the product during the trial period. As I said, you know, giving the customers a window to use the product without charging them for it is another way to sort of get your product introduced to the customer, have them get a feel for it and see if it solves their problem. And if it does, then they're most likely to actually become a paying customer. Take ESPN plus, Disney plus, HBO, they all use the strategy right where in you sign them up for one game or like one match. And once they start using it, they realize how easy it is to watch this video on the go or whatever it is. And then they're more likely to actually convert from being a customer for the trial period to an ongoing subscription. Similarly, you know, converting free users to paying customers is really all about once you have this product during a trial or whether it's a free version of it, identifying the new set of features that they would be willing to pay for or identifying what was the most sticky problem that your product is solving for them and then solving it so that these customers will be like, okay, I want to pay for this because this is a problem that this product does a really good job solving for me, right? So that's, that is in a nutshell of free management and free trial models is essentially using a version of your product that you give to your customers to use for free for a limited period or a limited set of features. So the ones they know and are familiar with your product, they're more likely to become a paid customer, whether it's a subscription or whether it's a one time purchase. Second one in an effective strategy is the viral loop and network effects. Again, viral loop, I kind of talked about already is this idea of creating referral programs and incentives. Dropbox did this, you know, if you take it Instagram as an example or TikTok as an example, once they make a video, they're sharing it on the social media platforms, right? And so chasing them on social media platform, you know, organically drives discovery for a new person who watches a TikTok video and they are no more likely to go to download the TikTok video or go make a video, right? So it's using social media, it's using a referral program as a way for people to discover and learn about your product in product marketing and upselling. As I talked about in the, the freemium and free trial models, once you have a customer using the product, you know, using the messaging features or notifications in the app, you can drive upsells to other features, you know, so for example, somebody might come in to edit a picture as an example, but you can limit them to say, hey, you're only limited to three pictures, but if you want to edit more than three pictures, then you have to pay for it, right? So you can always sort of find ways of upselling them to new set of features or unlocking a bunch of other capabilities. Once you have this customer through a freemium or a free trial model, and this essentially leads into this idea of like, you know, maximizing the customer lifetime value, which is unlocking sort of one benefit for them and then using that sort of interaction and the stickiness of the customer to drive incremental value from your product. So let's bring all these concepts together. I think Dropbox is a great example of a product that has used a lot of these strategies that I talked about to build not only a great product, but a great company. You know, if you think about Dropbox, sure, Dropbox makes a lot of other products other than clouds, file storage and sharing, but majority of its revenue actually comes from the from the Dropbox. So this is an example of a company that use product and drove a lot of these, these growth. So let's actually look at each one of these, right? So from, from first one, simple onboarding to instant value creation. What were they trying to do? They were just looking at solving a customer problem of enabling customers to access files across devices. And they created this very seamless way for anyone to get started. Enter email address and boom, there you are. You get two gigabytes of space and you can now sort of move your files and keep your files here. That's like unlocking the value for the customer right away. Now once you have that, they created this viral loop wherein you as a customer can share your referral link. And if a new person joined Dropbox, they would get additional storage, you would get additional storage. So they created this two-sided incentive, which means that they didn't need salespeople to go talk about Dropbox. There are existing customers who talk about it because they benefited from talking about the product. But one thing you know, I remember is that no matter how great of a viral loop you create, the first step is still very important. If the onboarding, the adoption and the usage of the features are not intuitive, then that customer is less likely to actually go and talk about their product. So while it may seem that, hey, throwing free features or throwing free things that customers would enable them to go talk at it, but really sustainable viral growth, you need to make sure that the product itself is a good product. It does its job right and it's easy to use. Then FreeMeme model, they also use this FreeMeme model, right?  And if you want more storage than that, then you have to pay for it, right? So that's another way of like, had they started with like, hey, sign up for Dropbox, pay X amount of dollars and you get X amount of GB space in cloud, less likely for people to buy in that idea. But having them get started with the product, get a hang for it, increase the chances that a customer could come for free and then pay and become a paid customer. So that's another way of sort of driving your revenue growth by using your product, not sales, but driving your revenue growth through your product itself. Again, in product upselling is sort of having these customers, you know, subscribe to the premium plan from the product itself. So it's not that, hey, you have to call our customer care or email us on, we can give you additional storage, but building that feature wherein becoming a premium customer, getting awareness about that premium feature are things that you can learn organically in the product itself. Believe it or not, this seems very intuitive, but it's really not something that you will see with a lot of products. There are definitely a lot of products, not necessarily popular for this reason, because they fail at some of these simple things wherein they will let you use the product. But if you want to add an additional channel or like an additional subscription, they would rather have you email or call their customer care center to add on to that, for that add on. That is not the right way to do it. Like, you know, an easy way to drive your revenue growth from an existing customer is just making sure that it's easier for the customer to sign up for that premium plan or that additional, like upselling is really critical to driving that organic growth internally as well. And then like user experience iteration as well, you know, Dropbox did a great job. They started with launching a service for file storage. But if you think about it, over time, they have really stayed connected with the customers and identified what are the things that the customers want from their product. And they've added things like, you know, editing files directly in the Dropbox, or whether it's about offline sync folder on your desktop or laptop so they can see their files locally or not. These are all sort of, you know, the data driven iteration to drive these new feature sets, right. And so that's, so like that's why I think is a great example of a product and a company that really used its product and used a lot of these techniques to drive, you know, user acquisition, translating those users into more customers, taking those customers, increasing revenue from that existing system set of customers, but either by either making them a paid customer or by selling them to a premium plan and like that ongoing iteration. So yeah, so to conclude the talk essentially, product led growth is at the heart is really about understanding who your customer is, what their pain points are, and then building a product that is solve that core customer problem with a very intuitive customer experience. And it's super easy for the customer to start using it. And once you sort of have figured out the core customer problem, you solve the customer problem and it's easy for the customer to go download and use your product, then using the data on, on iterating the feature set of the product, whether it's about new set of features or other things. And then as I talked about, you know, using the viral loop strategy or creating network effects, you know, the free model, free model are the things that you use to drive that ongoing adoption. So with that, you know, concludes the talk, I hope this was helpful for you guys to understand what a product led growth strategy is. And I hope you guys will actually use some of these frameworks I discussed in your products in, in creating growth that's led by product. Thank you for joining.


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Hi, everybody, we're back. This is Dave Vellante. I'm with wikibond.org and my co-host Paul Gillin and I have been going all day today. We're here at MIT at the Information Quality Symposium. It's a symposium that comprises the root, really, of the event, which was the Chief Data Officer forum that occurred on Tuesday, and a number of information quality practitioners. We're here at the Tank Center at MIT. It's a very intimate event, a lot of one-on-one conversations, a lot of hanging out, a lot of breakout sessions, keynotes and the like in the auditorium. And we've been covering it. This is the Cube. We go out to these events. We extract the signal from the noise. We bring you the best guests. Naim Hashmi is here. He's a chief research officer for information frameworks. He's involved in the MIT Sloan School CIO symposium, does a lot of CIO activity, focuses on analytics and big data, which is something that we're going to be talking about. Naim, welcome to the Cube. Thanks for coming on. Thank you, my pleasure. OK, so tell us, you have your hands and a lot of pies. So tell us a little bit about yourself and what you do. Right. Basically, I'm a nuclear physicist and health physicist. It's a weird combination. But having engaged with a lot in the industry has worked for digital for a long time, and doing a lot of innovative stuff, always been in the area where how we are going to manage information in the future. So looking forward 10 years, 20 years down the road, build the architectures and reference models, and then work with the vendors as well as the IT organizations how to roll out that kind of vision. So I'm sort of a vision type of person. So I started this after living digital. I started this business. And a lot of work has been publications. So I wrote about author four books. I'm working on the fifth book. And this fifth book is really interesting. And it talks about informatics and analytics, design strategies. The way I see it is in the health care today, there is a lot of talk about informatics and analytics. Well, you can define, I don't mean to interrupt you, but define informatics, because that's a word that's been around a long time. I'm not sure many people know what it means. Correct. It's very misleading. In fact, if you think of any kind of analysis in the health care business, it was classified as informatics. But it's really not informatics in that term. It's a lot to do with how if you look up, aside for the informatics world, it's informatics and ICS ticks, like analytics, analysis size, all of something. So anytime you see the informatics, it's informatics about something. So this informatics is, so when I start to write this book, I have to really spend a lot of time doing research. What's the difference between informatics and analytics? So the informatics have some attribute that you are basically discovering the information. You are synthesizing information. Where in the analytics world, you are analyzing the data. In the informatics world, you're also giving sort of a recommendations and the looking of some kind of pattern, especially in the health care world, disease or other area of planning. When you go back to the typical analytics world, there we're talking about very much of a structure data of qualitative and the predictive kind of modeling in that context. So that classifies. Plus also, it's a lot more of a informatics requires very powerful visualization type of piece because it's a very complex information, how you present that information, especially for the doctors. In this book, I also talk about how a clinician thinks and how a physician thinks. It's a very different approach. So where informatics really fit in from the physician perspective, where they're looking up some kind of pattern. So sometimes you're presenting the large information, set of information visually, and they can see certain type of trend is appearing. It was not intended to show that, but they could see this trend is going on. Where clinician, him or herself, they will be looking a lot more of an algorithmic. I need to run this ventilator. What steps I have to go through. So it's very much of a thought process is very different. And then comes up the analytics piece. How you optimize the clinical process?  How you share the benefits? How you optimize this thing? How you, this is very interesting because we've been talking all day about healthcare and most of the conversation has been focused on electronic health records and gathering the data and simply getting the data into a database. You're talking about going beyond that to understand, to derive some greater meaning out of that data. How does that affect the quality of care? I mean, what kinds of analysis do you believe clinicians will be able to perform? As EHR goes mainstream, what kinds of, how will it improve their diagnostic ability, their treatments? There are several ways that actually we're just starting up that area. So it's, I would call it a virgin territory at this point. So a lot ahead of us, we will do a lot of learning, but I'll give you an example. Like just before, till last year, I was working at Forsenius Medical Care. I was their vice president for knowledge management. And when you talk about knowledge management, in this term, in this conference term, there's a lot more to do with exactly like what the CDO they're defining. So I'm responsible for all the data and the Forsenius is the world's largest dialysis company. So we treat about 60,000 patients daily and there are about 2,000 clinics throughout America and about 1,500, 1,600 individual EMR. And the patient moves from clinic to clinic. So how you make sure when the person comes to a clinic A, like sales person is today is getting treatment in Boston, tomorrow they're in New York, how the information have traveled. So we have, we build the architecture, that's I'll talk in the afternoon, use the big data platform to move all of this information from these clinical systems into this central hub and then analytics like the dose adjustment perspective. So we can see the latest result of the person and also look at the longitudinal query and build those analytics that how the dose should be adjusted. So when the clinician or physician comes up to give the treatment, they have the latest information and the recommendation because at night we run the algorithm. So when the patient gets the treatment, so they get the right input that this is the recommended value but up to the physician to really override because that's the decision, that's the regulatory thing. I cannot really automatically change the dosage. Someone have to sign. So what medications I administer, they will go back. So this is just one example. I could see the usage of Watson. Watson as a service. Yeah, I was just gonna say. It's a differential diagnosis because not every IT organization or the healthcare organization will have the capability or the resources to build that kind of knowledge service or the diagnostic service where they are looking up information from all the publication, published material, getting up all the from the practice information and doing variant tests. That will be part of, I will call again, informatics, not analytics, but a lot more do informatics. They are synthesizing the lot of information, giving some recommendation to the decision maker, in this case, physician, and they will decide what benefits and are, which treatment is good and are. So I think those kind of things will start to emerge more and more. And you're familiar with the Kaggle content, the crowd source. So where would you put that kind of activity? Do you know about this, Paul? No. So Kaggle is essentially the crowd source, the crowd source healthcare data and have a contest. I think the move winner actually is lucrative, the million dollars to the winner to develop, do predictive analytics and develop algorithms on which class of patients are gonna be most susceptible. Exactly. I think last year I was also one of the judge for Massachusetts Health Data Palooza. So they were 21 really innovators. They were presenting it. And the winner was one of the young lady from Harvard. The young entrepreneur started the firm and what she was doing was looking at, she took her own depression scenario and converted into the innovation. What they were, she mentioned that because of, she's taking the birth control, it was affecting their, it was causing depression. So she started a firm, take up all the medications data and look, scan through all the social networks, see how people are describing their depression, especially in the women and then map out what kind of medication birth control will be better for them. So to me, these kind of things are really coming around. The major challenge comes up is once you are getting this information from disparate systems, especially the healthcare, how you really make sure the proper context and the content is done properly. Healthcare is such a very specialty oriented. So term are very specific to one, what they call practice. It's the same term on the other one but have very different meaning. So those kind of things, it will require a very much of a semantic and what they call ontology properly, especially in the healthcare perspective. I think those things will be coming more and more and I see in the future, actually in 2003, I published one of the cover story in the Intelligent Enterprise Magazine and that was on the BI on sale, Business Intelligence on sale. And that was the same thing in the future when you're going on, it will be a lot more to do with few powerful services that are available and you subscribe to this part of the clinical process. So the clinical processes themselves have to be more of a customizable. Today's vendors, I don't think their systems are really flexible enough because to me, their systems are nothing more than changing their paper forms to electronic form. I call it forming without reforming. So not understanding how even you automate these things or electronize these things. It's a great point. So how do you make those things together? So essentially they're taking the same business process and they're pushing it to electronics and of course that business process was developed for paper. Right. And it was developed because paper's so inflexible. Correct. So they're taking that process and say, okay, let's make this electronic. Exactly. It's not really only the process level. Also the content, the paper, exactly the same form electronically and now in paper form, you can write and write, there's no validation. It's like when TV came along, right? Well the radio guy said, why would anybody want to watch a bunch of guys doing radio? That's true. That's true. So I think in my experience when I was at Forcinius, we learned that too. When we were implementing the EHRs, the migrating thousands one to the newer systems and it was inflexible. A lot of data quality issues were coming up because there's no validation and verification on this field because those fields are originally designed from the form and you do the same form up there and since there is no control there, what based on the rule is certain value comes up what should be the next one or valid one? So how should we think, I mean thinking of us as patients, how should we think differently about how our health information should be used in the future? As we get out of, as Dave mentioned, it's kind of paving the CalPath approach right now where you're just taking data and putting it into a different form. What you're talking about is it's going to be used differently and what should we expect as patients? I think to me there's a big responsibility on the patients and to me it's a healthcare itself is such a fragmented industry. Pares are fragmented, providers are fragmented and patient have their own ego. So once nobody's trying to work together, so they will be all with that kind of issue comes up. To me, I think patients also have to be open because there is, I think there's a concern for privacy but there's too much concern for privacy. Once that comes up, then this information sharing becomes an issue. But information sharing becomes an issue, you can't have a longitudinal view of the information. So I think some of the healthcare reforms they're coming up, they're going in the right direction. We need to learn a lot through that. I think there's a intent, intent is really right because sometimes when you do the meaningful use, once you know I'm going to the EHR giving incentive, that's a good move but it's still at the early stage to change the culture. Because again, it's not really only the treatment, physicians are taught differently, nurses are taught differently and they're always, they have to live because of regulated industry, they have to live within their own. Well, and it is cultural. Look at the backlash from prison. This is a manifestation of the country's opinion right now but you got one side and the other side with people defending it, people attacking it. And so privacy is one of those touches. We had Scott McNeely on the cube recently about a year ago now. There's no privacy, just get over it, which is kind of what you're saying. Maybe not that much. That's true. In fact, I went to this HEMS conference in New Orleans. I was mentored and also do their award and also the BI and the informatics track. When you enter in their hall, what they call exhibit hall, they have about thousands of vendor, 1,000 plus vendor and you can smell in the room when you open the door, smell of analytics. And everyone, and actually 90% of those analytics are not analytics. I wrote one paper as search for a health IT. I call them arithmetic, not even analytics. Analytics means? What do you call them? Arithmetics. It's analytics or arithmetic. And the CMS meaning for use, the major PQRS and all the way. When you think of, it's nothing more, it's not intelligent, it's not analytics. It's to do with what's the numerator and what's the denominator, give me the ratio. So it's simply arithmetic. I couldn't agree more. Right, it's the basic arithmetic. It's a basic arithmetic. We're going to make it pretty. All right. Not even pretty, just give the number. Not even more. Everybody, every vendor is going on the bench over the bandwagon, we're analytics. So that's why I wrote this series of those analytics. Analytics washing. All right. I call it the snake oil, you know. And actually they are moving more towards future, especially with the like Watson kind of thing. In the book I also will talk about how the translation informatics comes, translation informatics is basically coming from the bioinformatics and medical informatics and all the therapies and things after trial gets into the practice. Now when you go to the practice, because these trials and the effectivity was basically on a controlled trial basis, but not in a practical, when the patient comes, look at a lot of economic factor, a lot of disparities comes along, how a patient behavior come into play. That time the actual, what the translation of research came from the lab is implemented into the clinical practice. It doesn't really give the same results outcome than really what it is. That's what last year healthcare and administration people they have launched CER, Comparative Effective Research Project, meaning that look up how different clinical practices they do the outcome. And that's become also dealing with the social data, taking the feed from there and refining why a certain type of therapy really worked or not with this kind of community, with this area, with this kind of physician, with these kind of comorbid conditions, while the bioinformatics pure science was saying this, but actually it's this. So how you marry those together? And that's where you know some kind of Watson type of area, the technologies. And I know I have talked with few people when they're starting up that area. But on top of the other area, which is my interest these days is called psyche mining. Psyche mining. Psyche mining. Okay, what's that? I published that in 2004. And that psyche mining is how people think, why the things, what influences them, and especially in a cyberspace perspective, different part of the world, people think differently. The concept of reward is differently. The concept of respect is differently. So how you develop distributed autonomous agent technology that becomes like a virus and attaches to the mobile and on and on on both end of the communication or the end of the communication. And also senses, like if I'm making a gesture, because now there's all the mobile devices, it's sophisticated, the cameras and everything. So you're doing the gesture mining as well. You are seeing the object and you're creating some emotion, that brain waves kind of thing. And actually I had four PhD students, they were doing some research, I was advising them, I formed Center for Knowledge Engineering. It's an interesting concept, but I see that a lot into, especially when you're moving more towards the behavioral and mental health, that will be really key. And right now I'm working with six Harvard professors. They're launching a company called I Hope. And that will be the behavior and health therapy perspective. So developing those kind of technologies. Do you know Jeff Hammabarker? Jeff Hammabarker is one of the, he's a work at Facebook, he's one of the founders of Cloud. Oh yeah, sure, sure. So he has a famous statement in the big data world, this is the best minds in my generation are trying to figure out how to get people to click on ads. Sure, sure. He's also a doctor and he's now at Mount Sinai, he's trying to apply his knowledge elsewhere. But I wonder are things like clicking on ads, do they fit into that psyche mining with maybe turning into behavioral economics? Yeah, in fact, it is there. Actually in 2006, no, 2005, I advised one of the, talked to one of the company.  So how many time you click? So how do you identify, how do you define, like if I'm a market, I'm broadcasting in the advertisement and every click will consume my one cent. So the competitor, they will have some robots, you know, clicking on to exhaustive funds. They have a Google can fund those robots, right? Right, so, but the thing is now, how you identify those, and also, Algorithmically, how do you? Exactly. Separate those. So not only that, how do you make the impressions? What time, if you're selling a BMW or you're buying a car or buying a BMW, your decision making process is different. So based on the context, how do you really engage them, so behavioral marketing to the contextual marketing, switching back and forth? So a lot of people talk about real time and the way we define real time on theCUBE is typically before you lose the customer, maybe you would define it before you lose the patient. So, all right, we're out of time. Great conversation, really appreciate you coming on to theCUBE, it was a pleasure meeting you. My pleasure. All right, keep it right there, everybody. Paul Gillan and I will be back, we're live from the MIT Information Quality Symposium. This is theCUBE. Thank you.


Have you bought yourself a set of Callaway paradigm irons this year and have you just noticed that there is a new set of tailor-made P790s that have been released? Are you worried, should you be worried and should you have in fact held on and bought the P790s? Right, I need myself a paradigm and I need myself a P790. We're going to have a good look today at these two clubs in detail. It's going to be that old-fashioned head-to-head. It's going to be two seven irons with Trackman switched on. We're going to have a look at all the different breakdowns in terms of data what separates these two clubs. But before we go any further, I think we've got to at least start with that old traditional, how do these two things compare in terms of looks? Now, this was nearly an element of the review that I started to omit because at the end of the day, my opinion on how two irons look, well, it's not really going to play any part in your decision-making process, but I'll give you my thoughts anyway and more so in these two because they are so, so different even though the sort of makeup of the two irons in terms of a hollow-bodied iron is the same. So they're definitely in the same category but very, very different. I'll put the paradigm on screen for you now and just give me your thoughts on the way this thing looks. Hollow-bodied irons, no cavity whatsoever. There's a sort of full plate inserted in the back there that's an element of I don't know what it is, plastic or whatever. Make your opinion on that one and I'm going to show the P790. Well, the P790 has got I think a slightly more premium finish to it. It's a satin, brush satin look if you like and it's very much streamlined with the P770s and also the new MG4 wedges whereas there's not quite that same sort of look throughout a whole set of paradigms in the fact that there's no wedges that sort of fit into this exact same line-up as well. So I think for me what TaylorMade have done particularly well in the looks department is giving you the ability to mix and match sets up including your wedge line-up as well and have a very much streamlined look through the bag and that for me is the first separator between the two sets of irons from a visual perspective but not necessarily individual looks just that option to get that look throughout the whole bag. Now I don't always get involved in sort of the pricing of products. I don't you know tell people how to spend the money but this is a sort of head-to-head and there's a noticeable difference between the two in terms of price so I think it's important I'll put those on screen for you now because I'm not exactly sure the number so I won't quote a figure but this is certainly sub £1,000 a set and they are not in terms of this was paradigm by the way that is P790 so that's you know that's a huge factor to consider. I'm going to hit a ball and talk about the next thing which is sound and feel. Maybe before I do that the one thing I've just noticed I've missed out the kind of profile in terms of from above and it is a real noticeable difference between the two. The paradigm is a more compact heel to toe iron but has a thicker top line whereas thinner top line on a P790 but heel to toe overall profile bigger so they're very very different and there's that chrome and satin effect between the two but that's another major consideration for me. It's almost like a kind of the paradigm is quite a stubby little iron head if you like so it looks as though it packs a fair bit of meat but the top line is perhaps a little bit thicker than you'd quite expect. Now the next bit is sound and feel let's see if we can get a decent ball. I'll say a decent ball it was a real decent ball but I got a little bit of mat first and what I want to try and do is if we can pick up any kind of acoustics in here I want to give you an idea of how these things sound by comparison. You tell me will you down below right now is does the sound of these things make any difference to you when you're buying a set of irons? Right that's better. You've got a real solid knock and hopefully you managed to get a real good understanding of how these sound. There's some people that come on and they comment and they sort of say well why would anybody buy a set of clubs based on how they sound and feel they also comment why would you buy them based on their looks. Well the thing is for me is that when we get to the end of all this we'll see what happens in terms of data parameters how they're split but in most instances when you're testing clubs like this they're often very difficult to split in terms of data but you're then down to individual preferences so that's why I sort of you know I don't want a set of irons that perform great but don't look good and the same in terms of okay so that's a good knock as well. Maybe I should have shut up for a bit because we could have listened between the two. Okay let's play them both side by side for a minute. Now I don't know can you pick up any difference I know that inside here it's very difficult the acoustics are different from inside than out but I would say that my comment would be this hollow bodied irons 2017 let's go back to these things the original version of these I hated the sound of them they sounded very very clicky they were clearly a hollow bodied iron in my opinion and you got that there's been a massive improvement in that sort of sound quality and one of the big leaps forward this year in particular has been exactly that so I'll hit one more with a P790 because I like it in golf balls can I tell the difference between them two no I can't I'll be honest with you I'll find it very very similar same concept they've got packed full of tungsten they're both forged face they neither sound like a forged iron as I would expect the forged irons to sound like and are really in a way I just wish they'd not make reference to it I don't understand what the forged face brings to the party because it's not a forged iron it doesn't have a forged iron feel so um yeah that's my opinion they sound brilliant for a hollow bodied iron but there are forged iron and my opinion on that I don't think he's ever going to change however hugely forward in both there you go I've said it anyway let's carry on I think what happened in terms of performance well the big deal is this I'm going to go back to the P790 apologies by the way that we've got no sort of shot tracking that you can see and I realise I'll keep this short and sweet because I know you like to see where balls are going but I don't have that software right now the big difference is this in terms of what I see on the course well on the course as well to be honest with you is P790s launched the ball incredibly high even with a shot like that which clearly hit the mat first and wasn't fantastic and it's a real visible difference it's um so much higher in terms of I need to do a P790 versus P790 the old version because I can't remember the ball going so high seven iron and five iron and it's bought you know I mean look that's not a criticism again of paradigms the all have done a great job in moving CG placement round we've all heard about it in recent years but there is a notable difference between the two and that is the P790 throws the ball up into orbit I'm going to watch the individual review because that and the five iron is tested in that and I cannot believe how how high the ball goes that's where the big improvement has been enough waffle let's go into the screen let's have a look at the data and let's see exactly what separates these two in terms of performance in my hands at least right that's it I think we're trying to keep these sort of head to heads very simple and straightforward at the end of the day there's only so much we can do to sort of help at least point you in the right direction um as I said earlier on paradigm a hugely popular iron four Callaway and this P790 is no doubt going to be extremely popular again for tailor made so an obvious head to head um we'll start off I think what I'll do as I've done with some previous heads to heads I've just filmed all the data I'll put at an end screen so you can sort of pick the bones out of each shot that I've hit so six with one seven with the other and I'll put right now the sort of comparison in terms of the averages so let's go with the carry this yeah let's start with the carry distance 149.2 150.7 nothing to split them there 76.6 average clubhead speed that's consistent and well done with a ball speed of 108.7 and 109.2 I think you can sort of get the gist of where this one's going 85 peak height 76 peak height well maybe you didn't get where this one was going 17.6 launch 19.4 launch spin of 5.6 spin of 5.4 descent 43.6 and descent of 46.3 right so what's the interesting bit there well it sticks out a mile for me and no doubt you as well and it starts off from that peak height and launch angle and it shows last four pieces of data which really separate these two and for me it was the bit that was the real shock in the test maybe not so much as what the P790 did because I've just been that's been a club that I've recently been reviewing I've said in each of the reviews and I've done some heads of heads as well depending on which these come out but I've commented on each one the P790 this year is got an extremely high launching ball they've done an incredible job of not only in the mid irons but also in the longer irons as well of getting the ball launching now that's got to be a big help and it's going to be a big selling point in my opinion for a lot of average golfers but they've done it without a loss of distance and without a loss in terms of spin but what it does if you combine a launch angle a peak height spin rate and a land angle those four last digits you compare those on a P790 to that of the paradigm and for me you've got a bit of a winner there to say the least because that's the key element that I'd be looking for carry distance is the same we're not losing out anything ball speed is the same so you've got when we're swinging a club in exactly the same speed we're getting the same ball speed we're getting the same carry distance but when that ball is coming into the green because of that high launch angle we're coming down at a steep descent angle and then we've got exactly the same spin number virtually on both so for me the ball at stopping quickest is going to be that P790 now that again depends on what it is you're looking for and you want your clubs to do but often and you go to a few years back I think it was 2017 was it when the first launch of the P790s that was in an era where there was a lot of criticism about strong lofted irons and how they were inconsistent in terms of ball speeds that's not happened again today where they were not stopping on greens because they were so low in terms of spin well I think we've got to our point now where those things have changed significantly I think most golfers now realize that as well so you can get help with ball speed with that strong lofted iron but you're only getting the same carry distance but it's those n parameters that are key like I said you can look through the individual shots at the end and maybe you can see a different story than the one I'm seeing but for me that is without doubt the key takeaway from all this and it's something that you've got to look at what ball flight you want and again there was different shafts in there so that's another consideration wouldn't necessarily see that as a negative in terms of that elevate shaft being in a paradigm you'd expect it to be it's there to launch the ball high so I wouldn't necessarily think that the shaft would play such a part but these are all of things that when you go into your your custom fit you've got likes the paradigm you've got the new t200 from tight list you've got this club obviously you've got some options there from shrixon in that hollow body category as well test them all and make sure you get a breakdown of the key figures and the key parameters that are key to your game and where they can help but for me the biggest deal and the biggest separator is just how high the p790 is launching the ball because okay on seven iron but then five iron was doing exactly the same as well sending this thing into orbit super impressive but there are other things to take into account those sound and feel issues the looks issue there and the cost issue as well so they're all going to be things that you're going to factor in but hopefully we've done enough that we can at least show you from my perspective how we would separate these two irons from at least what trackman says right thanks as ever for watching really appreciate your support on this channel and of course on testing the tips and if you're new to the channel in any way don't forget that that channel is in existence testing the tips go and check that one out and give that one a sub as well it's getting lots of love right now and absolutely flying so i appreciate that right i'm all done see you soon


Welcome to English in a minute. Cicadas are noisy insects. One very large group of them appears in the US every 17 years, and they are incredibly loud. Loud enough to wake the dead. So like I said, Jonathan, I can do that for you. What, Anna? I'm sorry, but I just can't hear you. What is that buzzing sound? Cicadas, millions of cicadas. They are loud enough to wake the dead. What are you saying? What?  And that's English in a minute.