WEBVTT 00:00:06.300 --> 00:00:07.800 Hello and welcome. 00:00:07.800 --> 00:00:12.400 I'm squirrels route a senior writer with cio.com joining 00:00:12.400 --> 00:00:15.000 me. Today is Shelby ramakrishnan, senior vice, 00:00:15.000 --> 00:00:18.100 president and chief digital and Technology officer a farmer 00:00:18.100 --> 00:00:19.100 commercial at GlaxoSmithKline. 00:00:20.900 --> 00:00:23.700 Like many other companies today GSK has spent the past several 00:00:23.700 --> 00:00:27.000 years driving to drive more value from its data and it has developed 00:00:27.000 --> 00:00:29.900 an agile approach to identifying opportunities and executing 00:00:29.900 --> 00:00:30.200 on them. 00:00:31.000 --> 00:00:32.800 Show me. Thank you so much for joining me today. 00:00:44.100 --> 00:00:47.100 Let me tell you briefly about jsk and I'll talk about my role, 00:00:47.100 --> 00:00:50.300 as many of, you know, just case of uk-based, 00:00:50.300 --> 00:00:52.600 global Healthcare company. 00:00:52.600 --> 00:00:56.800 That produces really important vaccines, ceutical, that treat 00:00:56.800 --> 00:01:02.900 asthma, lupus COPD and HIV in many forms of cancer risk is also, 00:01:02.900 --> 00:01:06.400 probably more familiar to many of you two are consumer, 00:01:06.400 --> 00:01:11.500 Healthcare products, Exedra North Sensodyne, best that many 00:01:11.500 --> 00:01:15.300 consumers use. So, we're on a journey to pleading to Great 00:01:15.300 --> 00:01:20.100 companies by 2022 of growing by farmer with a leading portfolio 00:01:20.100 --> 00:01:26.400 specialty & specialty medicines and vaccines that start with 00:01:26.400 --> 00:01:26.900 an r and d. 00:01:26.900 --> 00:01:30.400 That's based on the signs of the immune system and genetics 00:01:30.400 --> 00:01:32.700 and second company. 00:01:32.700 --> 00:01:34.400 That's going to be a world leader in consumer. 00:01:34.400 --> 00:01:37.900 Healthcare with category-leading brands that are based in the 00:01:37.900 --> 00:01:42.600 deep understanding of human human cycle is psychology 00:01:42.600 --> 00:01:43.800 and trusted science. 00:01:44.300 --> 00:01:46.800 So we're in the process of creating to create companies 00:01:46.800 --> 00:01:50.300 and important transformation, that that's on the way. 00:01:51.300 --> 00:01:53.500 My toilet. She is case, she said, 00:01:53.500 --> 00:01:54.800 she's digital and Technology. 00:01:54.800 --> 00:01:58.400 Officer found by farmer commercial business store on the technology 00:01:58.400 --> 00:02:01.500 side, my agreement includes the traditional responsibilities 00:02:01.500 --> 00:02:03.200 of delivering all the technology and systems, 00:02:03.200 --> 00:02:06.900 that support the launch in marketing of our medicine brilliantly. 00:02:06.900 --> 00:02:09.900 And on the digital side, I also have the responsibility 00:02:09.900 --> 00:02:15.000 to help as reimagine a better mood and Paxil customer experience 00:02:15.000 --> 00:02:17.000 through the use of data analytics. 00:02:19.800 --> 00:02:23.100 Okay, so I feel like you already touched on this a bit but let's 00:02:23.100 --> 00:02:24.200 let's go a little deeper. 00:02:24.200 --> 00:02:27.300 What what exactly do you characterize the mission of data and 00:02:27.300 --> 00:02:29.000 analytics at GSK as 00:02:30.800 --> 00:02:34.300 The art of our goal is to use data as an accelerator 00:02:34.300 --> 00:02:38.200 and an amplifier for how we discovered Avella make and sell 00:02:38.200 --> 00:02:41.500 transformational medicines and Health Products to our patients 00:02:41.500 --> 00:02:42.800 in a consumer's rights. 00:02:42.800 --> 00:02:54.700 That sucks with AI and machine learning techniques to accelerate 00:02:54.700 --> 00:02:58.500 from Discovery, that means that we are using data and analytics 00:02:58.500 --> 00:03:02.500 to digitize our supply chain extensively, it means that we are 00:03:02.500 --> 00:03:06.300 using both internal and external data as a backbone to drive 00:03:06.300 --> 00:03:11.000 experience for a healthcare provider. 00:03:11.000 --> 00:03:11.600 Consumers. 00:03:17.700 --> 00:03:22.200 So alarm companies in your position, start by hiring a chief 00:03:22.200 --> 00:03:25.600 analytics or chief data officer when they get serious about 00:03:25.600 --> 00:03:29.200 data. But do that, why is that 00:03:31.000 --> 00:03:33.600 First, let me say we're dead serious. 00:03:33.600 --> 00:03:35.700 About the volume of data. 00:03:35.700 --> 00:03:41.300 Simple answer to your question in my mind is focused and Pace, 00:03:41.300 --> 00:03:45.900 right. I believe that the skill and speed for translation 00:03:45.900 --> 00:03:50.000 requires us to innovate and scale rapidly in each of our business 00:03:50.000 --> 00:03:51.500 units are sick. 00:03:51.500 --> 00:03:56.600 And I also think that is a very different kind of talent leadership 00:03:56.600 --> 00:03:59.700 and expertise to use data and machine learning algorithms, 00:03:59.700 --> 00:04:08.500 to work with complex biological to think about how you can be 00:04:08.500 --> 00:04:10.500 a much more day to do then deliver. 00:04:10.500 --> 00:04:12.600 Much more data-driven customer experience in commercial 00:04:12.600 --> 00:04:13.700 that I can sue a business. 00:04:13.700 --> 00:04:22.200 So recognized the roles within each of the business units would 00:04:22.200 --> 00:04:25.200 lead us what empowered in each of these areas and allocate 00:04:25.200 --> 00:04:28.200 the resources that they need to move at PACE in line with their 00:04:28.200 --> 00:04:29.100 business strategy. 00:04:31.000 --> 00:04:34.400 Surprise lens on this, which is important in the global. 00:04:34.400 --> 00:04:46.600 That's what you get is the identify a sports core common in critical 00:04:46.600 --> 00:04:49.200 and then works on those aspects of it together, 00:04:49.200 --> 00:04:57.000 for example, be created an integrated et2 Richmond and we did 00:04:57.000 --> 00:04:59.600 that was entirely Federated approach not to essentially 00:04:59.600 --> 00:05:05.600 is value first. 00:05:05.600 --> 00:05:06.600 And then the Stratford 00:05:08.700 --> 00:05:13.700 Great Wall to the end GSK is taking an agile approach to developing 00:05:13.700 --> 00:05:17.100 Enterprise data and analytics projects that you call the value 00:05:17.100 --> 00:05:20.400 strikes program. And I have to say one of the things that fascinates 00:05:20.400 --> 00:05:23.000 me about it is that not only does each of these projects 00:05:23.000 --> 00:05:26.600 deliver value on its own, but the projects are also intended 00:05:26.600 --> 00:05:29.500 to develop experience and expertise to tackle more challenging 00:05:29.500 --> 00:05:30.500 projects down the road. 00:05:30.500 --> 00:05:36.500 What is the value strikes program and how and why did GSK development? 00:05:38.400 --> 00:05:42.400 Happy to, I think I got a bit of non-conventional 00:05:42.400 --> 00:05:47.100 starting point to our data transformation, or we did not start 00:05:47.100 --> 00:05:50.100 with a 3 or data strategy and a multi-million-pound 00:05:50.100 --> 00:05:53.100 basement I-beam, a tremendous investment. 00:05:53.100 --> 00:05:54.800 But that's not what we started it. 00:05:54.800 --> 00:05:58.700 We didn't try to gather and just clean connect all known Teeter 00:05:58.700 --> 00:06:08.900 in GSK into a data Lake before we started and the smallest 00:06:08.900 --> 00:06:11.800 possible effort and then created and confirm value. 00:06:11.800 --> 00:06:15.300 And then they traded from there to focus on identifying 00:06:15.300 --> 00:06:19.800 opportunities that we talked with create mass of Our Lives, 00:06:19.800 --> 00:06:27.300 which you did then reinvest in our elevation of realizing 00:06:27.300 --> 00:06:29.400 a billion pounds of belly fat to the use of data. 00:06:38.300 --> 00:06:41.400 Across the Enterprise, like how can be maximized yield from 00:06:41.400 --> 00:06:51.500 are vaccines and in a specific response to work together 00:06:51.500 --> 00:06:57.200 and develop you ate them, all those questions using coaches 00:06:57.200 --> 00:06:57.800 that you might have. 00:06:57.800 --> 00:07:14.900 Seen used to develop a solution and a delivered. 00:07:14.900 --> 00:07:17.200 Even friends. Like you would be the software products. 00:07:17.200 --> 00:07:20.300 That's the approach to setting up setting up. A 00:07:20.300 --> 00:07:24.700 bold, bold question sitting across multiple squads that work 00:07:24.700 --> 00:07:26.900 and then you deliver value of the new Skillet, 00:07:26.900 --> 00:07:29.800 then you maintain it and you crave Valerie's friends on an ongoing 00:07:29.800 --> 00:07:33.600 basis. We also use this opportunity to really important 00:07:33.600 --> 00:07:36.600 question around, what were the expertise and experience 00:07:36.600 --> 00:07:38.100 that was created. 00:07:38.300 --> 00:07:57.000 The process that allows you to select for EPS, 00:07:57.000 --> 00:08:09.800 be calling for initial minimum viable product information 00:08:09.800 --> 00:08:17.100 over time. But what, you rightly pointed out door around expertise and 00:08:17.100 --> 00:08:20.900 experience that was pulled from this effort and the teams that 00:08:20.900 --> 00:08:22.100 worked on it that. 00:08:22.100 --> 00:08:25.400 He took two working on, it just became seeds of both violent 00:08:25.400 --> 00:08:29.700 and ability. That's growing rapidly across the Enterprise 00:08:29.700 --> 00:08:34.000 to embrace, just a new way of working the data and. 00:08:34.000 --> 00:08:36.800 I believe is going to create sustainable and unsustainable 00:08:36.800 --> 00:08:37.800 momentum. 00:08:45.600 --> 00:08:49.400 So she'll be can you walk me through some of the projects 00:08:49.400 --> 00:08:53.000 that GSK has implemented as part of the value strikes program. 00:08:53.000 --> 00:08:56.300 I'd love to hear about how and why you choose this particular 00:08:56.300 --> 00:08:58.300 projects and what the results have been. 00:08:59.900 --> 00:09:03.400 Yeah, I got the Big Y, A B kind of value. 00:09:03.400 --> 00:09:06.900 Strikes program was to BDA identify opportunities to realize 00:09:06.900 --> 00:09:12.300 value for data immediately so that we can reinvest in best of 00:09:12.300 --> 00:09:14.200 resources in our in our company's strategy, 00:09:14.200 --> 00:09:37.900 Madison orange, Madison Co-Op strategy, the project. 00:09:37.900 --> 00:09:40.100 You know, about the example that I thought we talked about 00:09:40.100 --> 00:09:54.000 is our problems together. 00:09:59.900 --> 00:10:03.100 N2n. Really thinking about what are the opportunities 00:10:03.100 --> 00:10:06.200 that how do we create in this ability to orgasm entry? 00:10:06.200 --> 00:10:09.100 And then help these business teams, identify optimization 00:10:09.100 --> 00:10:14.700 opportunities, 235 million pounds in in value, 00:10:14.700 --> 00:10:17.700 which really helped invest in building our specialty supply 00:10:17.700 --> 00:10:20.000 chain. So that wasn't really concrete examples. 00:10:20.000 --> 00:10:29.000 In business, a Big Y behind, some of these, 00:10:29.000 --> 00:10:31.400 by his stripes, we are healed. 00:10:31.400 --> 00:10:37.100 So we can meet the incredible Supply them and our data analytics. 00:10:37.100 --> 00:10:42.300 Team book about predictive to understand the various drivers 00:10:42.300 --> 00:10:49.400 of the year that uses variables that determine and what date 00:10:49.400 --> 00:10:52.300 will they did was I made 12 specific recommendations 00:10:52.300 --> 00:10:54.800 that was in trial by are vaccine production teams, 00:10:54.800 --> 00:10:56.200 which resulted in at 20%, 00:10:59.800 --> 00:11:13.500 Did one of the most new feedback loops are telling us about 00:11:13.500 --> 00:11:15.600 new information on how to use these things. 00:11:15.600 --> 00:11:21.700 And he'll ask about the how we also had very capable and interesting 00:11:21.700 --> 00:11:25.000 Partners in. All right, so we had corn and black infant. 00:11:25.000 --> 00:11:27.600 We were delivering 849 value strikes at the time. 00:11:27.600 --> 00:11:29.300 So he couldn't just have one partner, 00:11:29.300 --> 00:11:34.300 we had corn and black with his neck and sees advance on a few of 00:11:34.300 --> 00:11:35.900 the value strikes and we had, 00:11:35.900 --> 00:11:41.700 which is bcg's Advanced analytics and these two Partners 00:11:41.700 --> 00:11:50.000 Health has jumpstart, you know, we have so much more Talent 00:11:50.000 --> 00:11:52.400 than you did two or three years ago when we started this journey 00:11:52.400 --> 00:11:55.700 and these least, you know, you know, 00:11:55.700 --> 00:11:57.000 I'm not talking about the big bang. 00:12:05.800 --> 00:12:10.700 Right. So that's a great segue because I here for a lot of it 00:12:10.700 --> 00:12:14.600 and data leaders that Technology's, actually the easy part of 00:12:14.600 --> 00:12:19.300 data-driven, digital transformation and getting the right skills 00:12:19.300 --> 00:12:22.400 and place in the right culture to leverage data is the really 00:12:22.400 --> 00:12:27.000 challenging part of skills and culture, change, 00:12:27.000 --> 00:12:28.400 have you or team had to drive, 00:12:28.400 --> 00:12:31.800 both internally throughout the company, and with Partners 00:12:31.800 --> 00:12:34.200 to be successful in this effort. 00:12:34.200 --> 00:12:35.800 And how do you approach that? 00:12:37.400 --> 00:12:42.500 I think I'm a technologist. 00:12:42.500 --> 00:12:52.300 I really do believe that it's still getting the texts Prodigy 00:12:52.300 --> 00:12:56.400 and saxophones ride is is definitely necessary but not sufficient 00:12:56.400 --> 00:12:59.100 condition, for or impact. 00:12:59.100 --> 00:13:02.500 And I think there are two things that are that are equally 00:13:02.500 --> 00:13:05.700 important when is getting to the challenge of right and others 00:13:05.700 --> 00:13:07.100 getting the culture, right? 00:13:07.100 --> 00:13:09.700 As you rightly pointed out, getting the talent, 00:13:09.700 --> 00:13:14.300 Riot on the town side in the nice areas. 00:13:14.300 --> 00:13:17.700 Like, like I said, a bunch song lyrics to Burn data science 00:13:17.700 --> 00:13:28.200 in cyber defense. 00:13:28.200 --> 00:13:34.300 We've got a lot of competitive, so that was an important 00:13:34.300 --> 00:13:34.800 part of 00:13:37.300 --> 00:13:53.000 Important business and technology team in the past 18 to 24 months, 00:13:53.000 --> 00:13:55.800 it's been unprecedented level of investment there. 00:13:55.800 --> 00:14:02.800 That sustainable transmission is not feasible at all, 00:14:02.800 --> 00:14:07.200 if without a combination of that knows what that looks like 00:14:07.200 --> 00:14:10.000 and internal gets transformation. 00:14:10.000 --> 00:14:11.000 That's moving at these. 00:14:11.000 --> 00:14:14.700 Along with that, we've launched an effort to create an opportunity 00:14:14.700 --> 00:14:18.700 for us to have to reschedule themselves in five areas that we 00:14:18.700 --> 00:14:21.200 believe are critical to winning the future and be competitive 00:14:21.200 --> 00:14:23.500 data analytics is one of them. 00:14:23.500 --> 00:14:27.200 So we hope to have over 3500 South with an AR technology 00:14:27.200 --> 00:14:31.600 organization trained with basic data that receipt by 2022 and 00:14:31.600 --> 00:14:36.000 approximately, 250 staff will be moving from basic data to more 00:14:36.000 --> 00:14:36.900 higher levels of proficiency. 00:14:37.300 --> 00:14:38.100 Data science. 00:14:40.900 --> 00:14:45.400 Squirrel. So we are also build a data analytics X reader within 00:14:45.400 --> 00:14:53.500 the close of business. 00:14:53.500 --> 00:15:06.000 It doesn't matter how cool, our capabilities are you mad at Academy. 00:15:06.000 --> 00:15:10.600 That will provide some customized for business. 00:15:10.600 --> 00:15:19.900 Users are the whole Rick and sitting out a big ambition. 00:15:19.900 --> 00:15:24.300 Now, that we have all these capabilities to really bored. 00:15:24.300 --> 00:15:30.600 So we believe that the cultures are Lord hardinge fish tattoo, 00:15:40.900 --> 00:15:54.000 Triple leader stop by and pick people who have the ability 00:15:54.000 --> 00:16:05.700 to influence their seed, cartridge. 00:16:05.700 --> 00:16:10.900 Me understand, that looks like but then it's also remembering 00:16:10.900 --> 00:16:12.700 that you're pushing against the flywheel, right? 00:16:12.700 --> 00:16:17.900 It's a part of people who understand the real estate with like-minded 00:16:17.900 --> 00:16:20.400 people. And then the flywheel tips. 00:16:20.400 --> 00:16:23.000 There's this incredible, momentum, and sustainable change 00:16:23.000 --> 00:16:26.200 that created. And until then computer, momentum. 00:16:35.400 --> 00:16:39.400 And that she'll be you you told me in the past that are thriving 00:16:39.400 --> 00:16:42.600 annotated economy requires being anchored in platforms, 00:16:42.600 --> 00:16:44.800 can you unpack that for me a little bit? 00:16:47.200 --> 00:16:51.000 Many of the things I talked about earlier and they usually 00:16:51.000 --> 00:16:56.500 done by advocating a random data and silos one time at the Creator 00:16:56.500 --> 00:16:57.700 type of value I talked about. 00:16:57.700 --> 00:17:12.400 So it's not it's not really a genius to do this ribbon is that 00:17:12.400 --> 00:17:14.600 they start seeing all kinds of issues with that data, 00:17:14.600 --> 00:17:19.500 quality, availability of data and assume you realize the time 00:17:19.500 --> 00:17:28.700 and resources right now by committing to a data platform 00:17:28.700 --> 00:17:39.300 strategy. The power of the data back bone behind neck and democracy. 00:17:39.300 --> 00:17:46.400 That skill so cross-functional like the one I described, 00:17:47.200 --> 00:17:51.000 Where finance and supply chain data have to be put together 00:17:51.000 --> 00:17:53.000 or shedding real-world data. 00:17:53.000 --> 00:17:59.600 Can be used to make proteins. 00:17:59.600 --> 00:18:04.800 So we can create this ability to effectively cost-effectively 00:18:04.800 --> 00:18:12.600 as well as you stated products, including volume 00:18:21.300 --> 00:18:25.600 All right, so ultimately, where has this approach to data and 00:18:25.600 --> 00:18:28.000 analytics taken GSK as a company? 00:18:28.000 --> 00:18:30.800 What is it taught you about operationalizing analytics? 00:18:30.800 --> 00:18:32.600 Because I know that a lot of company struggle with that, 00:18:34.300 --> 00:18:36.300 It's certainly certainly. 00:18:36.300 --> 00:18:38.700 I think we're in your Speedo for constipation, 00:18:38.700 --> 00:18:42.300 we believe that we've delivered value at pace. 00:18:42.300 --> 00:18:47.800 So like I said, value first Russian leader with normalize, 00:18:47.800 --> 00:18:51.500 the concept of you say, I think the biggest success in my mind 00:18:51.500 --> 00:18:57.400 and embedded analytics and machine learning technology 00:18:57.400 --> 00:19:00.900 to solve business problems and drywall company strategy. 00:19:00.900 --> 00:19:04.500 So it's really a big man in my mind than our general managers 00:19:04.500 --> 00:19:07.700 in our markets come come to me and say I'd like a data-driven 00:19:07.700 --> 00:19:10.500 customer experience and they any buttons to click for them and 00:19:10.500 --> 00:19:13.400 say, you know what, I can use this data to make this decision. 00:19:13.400 --> 00:19:16.800 I'd like to use this information to not your ex to go call on 00:19:16.800 --> 00:19:19.700 these doctors and educate them on the importance of this medicine, 00:19:19.700 --> 00:19:24.600 this language and thinks we can bear head that you can be able 00:19:24.600 --> 00:19:29.800 to predict them and much more using data to me much more Dynamic 00:19:29.800 --> 00:19:31.900 decision versus using dashboard. 00:19:34.300 --> 00:19:35.300 Think about what happened. 00:19:35.300 --> 00:19:38.400 I think that's a big one and we're seeing that just across 00:19:38.400 --> 00:19:42.800 the board and how are things about activating drug Discovery? 00:19:42.800 --> 00:19:50.000 Racine. Really, the data has become sort of like the groundwater 00:19:50.000 --> 00:19:53.200 in, in the way we think about this incident is still a long 00:19:53.200 --> 00:19:53.800 way to go. 00:19:53.800 --> 00:19:56.700 I wouldn't, I wouldn't be any flags on the on mountains 00:19:56.700 --> 00:20:01.000 yet, but I think I can feel that the flywheel will check and 00:20:01.000 --> 00:20:03.500 the momentum bowl with, then it'll be self-sustaining, 00:20:03.500 --> 00:20:08.200 it going. What is it? 00:20:08.200 --> 00:20:22.600 Would be my big, big things I could learn. 00:20:22.600 --> 00:20:26.200 As a leader, I've known to be an impatient optimists really 00:20:26.200 --> 00:20:26.400 important. 00:20:34.200 --> 00:20:37.300 Which means you are you it's read fast, 00:20:37.300 --> 00:20:38.400 increase value quickly. 00:20:38.400 --> 00:20:42.900 Keeping in mind that our patients mess with success in months 00:20:42.900 --> 00:20:44.100 of progression-free survival. 00:20:44.100 --> 00:20:47.200 That's the that's what that's what we're up against. 00:20:47.200 --> 00:20:53.400 That gives a sense of peace and just remembering that. 00:20:53.400 --> 00:21:11.900 So being patient being an optimist, what ultimately matters 00:21:11.900 --> 00:21:14.400 for impacts whether you can you have Adidas, 00:21:14.400 --> 00:21:17.900 bring others, who don't necessarily have a first-hand 00:21:17.900 --> 00:21:21.500 experience of what it looks like in the Target State on the journey. 00:21:21.500 --> 00:21:24.900 And that is what happens to collaboration that works. 00:21:24.900 --> 00:21:29.100 That happens to be thinking about how can I make others? 00:21:29.900 --> 00:21:31.500 Better more successful. 00:21:31.500 --> 00:21:33.200 And I think about that all the time that my, 00:21:33.200 --> 00:21:43.000 my fear doesn't think I would say that. 00:21:43.000 --> 00:21:47.200 It's talk me to stay humble and remember him Hard Day's my analogy, 00:21:47.200 --> 00:21:49.700 yet that I'm pushing against a flywheel and water wall. 00:21:49.700 --> 00:21:57.700 And then once the moment has created great advice all around 00:21:57.700 --> 00:22:03.700 to dig into that a little bit more advice or best practices. 00:22:03.700 --> 00:22:08.000 You can share with your peers are now trying to help their 00:22:08.000 --> 00:22:09.500 organizations Better leverage data. 00:22:10.800 --> 00:22:13.900 I think it's obvious somebody of some of the things I said, 00:22:13.900 --> 00:22:15.600 but if I have to really do it all together, 00:22:15.600 --> 00:22:17.600 I would stay focus on Value. 00:22:17.600 --> 00:22:20.800 First structure can follow later and figure out how to treat 00:22:20.800 --> 00:22:23.000 valley supposed to be a job first. 00:22:23.000 --> 00:22:27.200 And then make sure that you have enough people on your team 00:22:27.200 --> 00:22:31.600 in leadership positions and driver seats to who really understand 00:22:31.600 --> 00:22:32.800 what the target sink look like. 00:22:32.800 --> 00:22:37.100 I think I'm going your way to incremental changes speed, 00:22:37.100 --> 00:22:40.400 make it to Abbott's father, but not far enough for the impacts 00:22:40.400 --> 00:22:42.800 Oaks, making sure that you are you thinking, 00:22:42.800 --> 00:22:45.300 looking at your profile and making sure that you have enough 00:22:45.300 --> 00:22:49.600 people and drivers to understand the second piece of advice. 00:22:49.600 --> 00:22:53.900 And then I would say just back to my favorite flywheel analogy. 00:22:53.900 --> 00:22:57.300 Now, is just really be patient with yourself and remember 00:22:57.300 --> 00:23:02.700 that, remember that there are bringing the organization 00:23:02.700 --> 00:23:05.800 with. You is probably the most important part of the journey. 00:23:05.800 --> 00:23:08.800 Not just getting your one project rides are fat in sacks. 00:23:08.800 --> 00:23:09.400 At the end of the valley. 00:23:10.800 --> 00:23:11.600 Which we should do. 00:23:11.600 --> 00:23:13.100 We should celebrate, we should be happy, 00:23:13.100 --> 00:23:16.800 but the record 00:23:23.100 --> 00:23:24.800 All right, show me. 00:23:24.800 --> 00:23:27.200 Thank you so much for taking the time to speak with me today. 00:23:27.200 --> 00:23:28.000 This is been great.