#HRTechChat with Amaresh Tripathy: Upskilling 120,000 People for Data Awareness at Genpact


“How do I make a 120,000-person organization data-aware?” asks Amaresh Tripathy, my guest on this episode of the #HRTechChat video podcast.

Amaresh is strategic advisor for data and analytics at Genpact. A General Electric spin-off, Genpact is several billion dollars in size. A publicly traded professional services firm, Genpact mainly focuses on two things. One is all about running various digital operations on behalf of Genpact’s clients, which are Fortune 1000 companies around the globe. The other involves data, technology and artificial intelligence, wherein Genpact concerns itself with helping these clients transform some of these same digital operations for the better. Amaresh’s role is with this second focus, working to make “our clients more data-intelligent and data-aware,” he says.

You probably already see the tie-in with Genpact’s workforce. Amaresh believes that, at Genpact, he and his team have built the world’s largest data awareness program. Solutions such as EdCast, found in the Cornerstone suite, factor largely into the effort. We discussed this. An illustrative example of organizational and digital transformation, the initiative relies, critically, on well-sorted learning technology and modern tools for curating and delivering content just right for the task at hand.

Phenomenally, Amaresh is more than halfway to achieving an ambitious goal: so far, somewhere between 65,000 and 70,000 of the company’s own employees have completed the associated certification program, which leaves them highly versed in understanding the tools to extract and blend enterprise data. Graduates then go on to use their newfound knowledge and skills in order to help a client—in the process earning from Genpact what is akin to a black belt in data awareness.

During our chat, Amaresh shared the philosophy behind his vision and delved into the thinking that has helped make it a reality at Genpact. This vision is empowering staff with the high-impact upskilling that is an essential ingredient not only for their success individually, but also for Genpact’s overall. Indeed, like so many initiatives notable for their positive effects on business, Amaresh’s is redolent of the idea that an organization’s people are an asset to cultivate and engage. This is the model for success. All at once, Genpact’s data awareness program is good for the company, its clients, and its people. If you’re looking for an example of how the future of work is happening right now, look no further than this episode of the podcast. It was an absolute pleasure speaking with Amaresh.

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Brent Skinner 00:00
Well, hello everybody and welcome to this the latest episode of the #HRTechChat video podcast. And with me today I have Amaresh Tripathy who is senior vice president and global business leader at Genpact. Welcome, Amaresh.

Amaresh Tripathy 00:19
Thank you so much, Brad. Great to be here. Oh, yeah,

Brent Skinner 00:21
absolutely. And I’m really looking forward to this conversation. Today, you’re doing some really, really fascinating, big things at Genpact, and it hits a lot of notes and human capital management around career, you developing your people upskilling data, LMS content, all this kind of stuff, and I’m really looking forward to diving into it. But maybe first, you could just share with our audience a little bit more about what Jen Peck does. And then, you know, sort of what brought you to Genpact what your background is?

Amaresh Tripathy 00:56
Absolutely. So, for Genpact. For those who don’t know, it’s been a spinoff of General Electric. It’s an independent, like a publicly listed company, roughly four and a half billion dollars in size. And we kind of a large professional services company that does basically two broad things for our clients, which are fortune 1000 companies around the globe. One is what we call digital operations, which is where we are running the operations on behalf of our clients in finance, supply chain sales and commercial risk, there are a few areas that we can go and cover. And the second part of our business, which is called Data tech in AI, which is how do we transform some of those operations and when we are whether we are running it or not, in those same areas, using data analytics, technology, and artificial intelligence, that’s kind of roughly kind of this thing. Within that. My personal role is I run the data analytics and data analytics and AI, business part of the of that, where I’m helping clients drive those transformations and making our client organizations, I will say more data intelligent and data aware. But I have to play I play a similar role internally also, when we have 120,000 colleagues of ours, who are who are spread over the globe. And basically, how do you make our organization Genpact more data aware for us and for us on behalf of our clients? That’s kind of where I think this conversation will be focused on

Brent Skinner 02:24
Yeah, by the way, AI is one of my favorite topics, certainly not alone in that. It seems like you can’t talk about anything without AI permeating. Maybe the robots are already taking over. And that’s evidence.

Amaresh Tripathy 02:42
Who knows you’re not talking to a robot, right?

Brent Skinner 02:44
Maybe! Are you real? Not quite there yet. This podcast is not a deep fake everybody. In any event, yeah, I you know, you’re doing some really interesting things. And why don’t we dive right into it? 120,000, proximately, strong workforce, individuals at Genpact. And you’re, and you’re already you’ve already sort of brought about 65,000 of them through this data awareness program. And as a lot of people know, watching the podcast, you know, we have conversations before the podcast. And we were in the green room just a few minutes ago. And we were talking about how I think you were saying that this is probably the biggest data awareness program, at least in business in the world.

Amaresh Tripathy 03:35
Yeah, this is this is this is the largest, at least we know are definitely one of the largest data literacy and data awareness programs, I think in the world where we are essentially doing this entire program at scale for all the 120,000. Folks, the intention brand is actually very simple one I mean, like, I mean, curiosity and learning are kind of our two broad pillars around and values that we that we focus on for everyone. And obviously we were we are a learning organization. And as part of that, one of the things we discovered is what is what is what is what is what is what is what is what is what is what is what is what is what is the biggest trend in like next decade or so that is going to define work itself. And it is about how does data analytics gets infused into the day to day work that we’re doing, you know, don’t need to be data scientist, you don’t need to be a mathematician or a computer scientist, but you need to be able to use the data to do your work better. And that was kind of the core insight. That’s why we use the word data to be aware about the other words that we could use. And our vision was how do we kind of create a culture structure training, like the whole the whole, whole process around it, so that we can have all our employees, all our colleagues or in 20,000 of them, be data aware? Because once you do that, that becomes a competitive differentiation that we do for like a guest that we like, and also helps our clients helps our own people and helps jet pack them. And that on the highest level, that was kind of the broader mission that we kind of started the journey with.

Brent Skinner 05:12
Yeah. And you know, you bring up some good points here. And let me just kind of unpack it a little bit, because you’re doing a lot of really important things here. So first of all, this is about upskilling your workforce. So, this is this is an organization Genpact, putting in the effort showing the interest in making sure that each individual contributor in the workforce is, you know, is upskilled in the most optimal way for the particular task at hand, and they do a gem Gen pack. So that’s, so you’re showing, in a way, sort of in the 360, insights parlance, we talked about efficiency and empathy when it comes to the workforce. And this is very much an empathy play in that respect. But it’s also it’s also a sort of a, it’s, let’s say that Genpact itself is sort of organizationally self-aware, I think by doing this, because your org, you and the organization understand that if we do this, we are going to be better at doing the work that we do. And we’re going to retain more customers, we’re going to grow, and all these sorts of things. So, it’s, it’s one of those sorts of classic stories where an organization pays attention to and dedicates time to their employees. And that results in dividends for the organization itself.

Amaresh Tripathy 06:37
Absolutely. That’s and you just one more point I’ll add, it’s empathy. But it’s, it’s the depth of empathy also leads to efficiency, and it leads to value more important, it’s race to value. That’s, that’s at least how we thought about it.

Brent Skinner 06:52
Absolutely. Took the words right out of my mouth. And what’s interesting, I’d like to, could you just walk us through like, what it looks like, I understand it’s a certification program, and then there’s sort of an opportunity to earn a black belt, if you will, indeed, awareness after that, how does it work?

Amaresh Tripathy 07:10
Yeah. So basically, the, let me just tell you the history of what the what the influences have been. So one is, I mean, given that told you are our heritage and General Electric, what I mean, like this notion of black belt, and Lean Six Sigma that’s kind of very ingrained in us, right. And if you think about one thing that you would kind of want to take from that journey, and that big learning is how do you drive a philosophical change about how to do the work at scale? I mean, if you really think about it, Lean Six Sigma, absolutely nails it. I mean, there’s I mean, it’s, its raw mosques, and programs are going to go in doing that. And there’s a structure around it, which is, there is a little bit of learning there is the there is a self-learning, there’s a testing, then then you do a Greenbelt project, where you kind of like you have a little bit of support around it, then you actually go and go and go to a blackbelt, where you independently are doing something big and you bring the clients and you bring the business users in, there’s a there’s a structured process around it. And we actually pretty much adopted that we knew we could train things at scale, or we could write things at scale, using a very proven methodology. It’s not like the content, but the process and the structure. On top of that, we said, Okay, if there was what is what is data when this mean in terms of content? Right, that was the second aspect of that, that we kind of developed around that. And that’s kind of what we started filling out what the content was the project, what kind of projects so we kind of laid out kind of, I would say, the intellectual foundation support and the content part of this way on this picture, and we kind of combined both. And the way it works right now is there are three or four steps. One is we use a very distributed platform, and we’ll talk about that a little bit more called genome, which is based on that cast that we talked to talked about earlier, where if you are an associate, you can go and spend two, three hours, it’s a kind of a three yard self-paced learning where you are aware of Okay, so the basic data terms like think about visualization, think about anomalies, what is an anomaly? How do you think about whether it’s a mean and, and media? And what’s the difference between that? How do you actually think about what is a predictive model? What is data quality itself, so I would say some basic one on one things that you’re going to get a very high-level load. And based on that, you go and go and do what testing so you can go and get tested, and you have to get to get to whatever passing grade and that you kind of get to the next level. So that’s kind of number one, so that you go to the first discipline or the first gate. And then after you’re doing that there are some more learning modules that you have when you think about the two of wands kind of courses in in certain areas that you start taking. And then you would basically go and do a pro Project and the focus that we could put in the project was, it would be a prediction project, we kind of focused on it there, you’re going to predict something. So, we kind of up the ante a little bit. And then you do the project prediction project in context of a client work that you’re working on doing the context of the client working with them. And then that gets validated. And once again, that gets signed off and the value is signed off, then you essentially get certified. So that’s kind of the three step four step process that we’re going to have to do to the entire organization through.

Brent Skinner 10:29
Oh, that’s really interesting. And you were mentioning EdCast. What else do you have? So how does EdCast figure into this? That sort of development, I’m hearing that some of the content and learning contents are delivered, maybe in real time, while the employees working with the, with the with the client and some of this Yeah,

Amaresh Tripathy 10:54
So, there are a couple of layers of that, let me just unpack it for you. So one is that when there is an that some of the investments that we have already made, and we are writing on what one was like we had this program called, or entire learning philosophy, what we call collective intelligence, the idea there of collective intelligence, it’s actually kind of the some inspiration from MIT there, where the idea is, like, the best people to you have to learn in the context of work. And you learn not only from one individual, but you also learn from a group, right, and it’s the group that becomes a lot stronger. So those two things were principles we did. And we basically took EdCast. And we think about us, we skinned a layer on top of NK EdCast. And we kind of internally branded that culture, you know, and the idea was, and then so that’s kind of what the technology side of things basically take over the UI UX layer on top of EdCast. And then we kind of we have, we took a group of folks who are experts in their own work at supply chain experts, data experts, AI experts, and ask them to curate content, not kind of just by content, but curate content that they think that colleagues should not. So basically, you have experts, experts curate content. And that is what the colleagues learn, and so on a self-paced way. And once you learn that in a self-paced way, you have an opportunity to work with these gurus and master gurus, that’s what we got laid out. So, there’s a structure around that. So, there is a learning philosophy around this collective intelligence we already had in place. So, when we launched this program, we call this program Databridge, the state awareness program that we talked about, we essentially leverage the EdCast genome and the guru and Master Guru structure to accelerate our journey around becoming the data wherever organization. So that’s, that gives you a little bit of context of how these were we approached it.

Brent Skinner 12:43
yeah, that’s really interesting. So, the content is curated by experts. Yeah. And that in that in that content, where is it? Is it sourced from, you know, like, like MOOCs, or is it from anywhere?

Amaresh Tripathy 13:00
It could be YouTube videos, it could be MOOCs, it could be reports, it’s thought about it. So I am, I’m a, I’m an expert in data analytics, AI and everything. So, I’m reading things all the time. So whenever in the things that I’m reading, because I’m a Master Guru, I was like, oh, this is really interesting for a lot of my colleagues to know. And it’s not like sending email, what I basically say is, hey, listen, you’re I mean, we have so folks who helped manage and manage the channels, identify pieces of content, whether it’s a video, whether it’s an article that I’m reading, whether it’s this, I said, Okay, these should be part of this course. And then obviously, we can go and put a structure around it and kind of do that. But it could be books, it could be I’m learning a programming thing, and it’s relevant. So, it’s my job, or guru or master gurus, job, all the things that they are learning, it’s their collective learning, we want to spread very, very quickly. So that’s kind of how it is getting curated.

Brent Skinner 13:49
Interesting, great. Wonderful. And that is that, is that sort of distributed with? That’s distributed via EdCast. You TF cornerstone in place, as well, or?

Amaresh Tripathy 14:00
I think so I’m not, we I think we have cornerstones in place. I think in terms of probably in how we met, like, measure the certifications and everything like that, we also have that but we definitely have the head cast so that that to that content comes there gets curated, but we have essentially made created think about a UX UI based on persona on top of it, so you can create your own and manage your own learning journeys.

Brent Skinner 14:24
Okay. So, this, this is like this is like Sorry, this is a really good illustration of sort of a future of work, modern, that is a learning experience for, you know, like a white-collar professional, you know, high level professional. Because you have self-directed learning, you have the curated content you have, you have sort of the state of the art in terms of technology to get that content delivered at just the right time to the people when they need it. and also has the human element. That’s something that we talk a lot about.

Amaresh Tripathy 15:07
We have these gurus and Master Guru sessions. So basically, like once every month or woman as a Master Guru once every month, but as gurus, when we have people like that thing, every week, they will host sessions that will be open door, Hey, these are the issues, or this is the topic I want to talk about. So, there is a huge human aspect of it, where people will reach out. So, there is it’s a network human aspect. There are some structured programs, and then there’s a lot of one on ones.

Brent Skinner 15:30
Yeah, yeah. What kind of results have you seen for the business? And for? Well, you know, there’s all sorts of things, it’s holistic, right? There’s, there’s benefits, you know, in terms of, you know, employee engagement, retention, you know, revenue retention of not just employees, but also customers and, you know, length, length of engagements, what kind of results have you seen?

Amaresh Tripathy 15:56
I mean, I’ll give you one, broad statistics on the broader genome program, and then I’ll come to Databridge, right on the broader genome program when we launched. And I think, at least a year ago, or so, when we looked at it, the number of hours just on our ecosystem, the 120,000 people, was roughly a quarter of all LinkedIn learning hours. So, think about that. So, there was a lot of, so people are hungry to upskill themselves. And you when you make you when you make it open, and when you make it available, it happens.

Brent Skinner 16:28
Sorry, I want to make sure I’m understanding that correctly. I might have missed it and forgive me. So, a quarter of all LinkedIn learning hours for Genpact?

Amaresh Tripathy 16:37
No, for overall LinkedIn learning loads that was there at that point in time. And this is a little bit of an old statistic. Yeah. I mean, so the amount of learning per employee that’s kind of going on in number of hours at that point in time, obviously, I’m and I’m not familiar with the latest statistics, and obviously things that was moved on. But on the data breach coming back on the data breach side of it, we launched this program, and we open it up for signing. And here’s the thing, I mean, this is like, like pickup art, there are people all over the world doing different, you could be processing invoices, you could be doing, like managing claims, you could be, you could be a data scientist, you could I mean, there’s all kinds of roles there. And we, and there was no incentive to sign up. And we said, go ahead, this program is available, right?” Literally, within two weeks, we had 30,000 people sign up, and we didn’t even know what it was, I never expected that to be. And then, and then we started measuring that. And over time, I mean, literally in the first six months, this is like we’re probably covered two years into the journey right now. But at first, and obviously, like new people come in, and all the things that’s kind of it, there’s a, there’s a natural flow business, they’re brilliant, first six months, we had more than 55,000 people. And now it’s probably close to 70 75,000 folks who have signed up, and after signing up, they had to spend two to three hours and then do the training and testing. I mean, the number of sign up is a lot more probably close to 100 or 100 hours, but kind of studying and signing that itself is about 65 70,000 folks right now. And that just tells me the latent demand, people are our colleagues, or I think probably the entire workforce has on learning about being data aware, realizing that is the future in terms of how a lot of the work is going to get done. And because there was literally, they are taking time away from the family, they are doing it on their own time to kind of make themselves more relevant and kinder of just blew our mind when we found that out.

Brent Skinner 18:38
That is indeed mind blowing. You know, we use that term a lot. But this really is, you know, what’s interesting, also, is this, this fits into a larger sort of context here. You know, we hear a lot about why we don’t dive into AI just a little bit because I think it is relevant here, you know, a lot about artificial intelligence, you know, taking over existing jobs. And we hear a lot about all the new jobs that we don’t even know about yet, that will or roles that will exist in the future. And so some people say, Don’t worry about that, you know, there’ll be new, there will be new roles that we don’t know about, but you still need to think about, you know, you can’t remain static as a career professional, you have to learn new skills. And to me, it just seems that upskilling like real intention like upskilling with intentionality sponsored by, I guess that’s the word are encouraged and sponsored by the employing Oregon’s organization and sort of an indefatigable sort of, you know, inexorable march in that direction is just absolutely critical to make sure that I mean, not to sound to future of work here, but this might be science fiction aboard but to make sure humans actually can work in a sense, right? because this is what I’m hearing with this program, the Databridge Program is that you’re really helping your workforce to acquire skills that, that, you know, we’re really far off from Ai ever really mastering.

Amaresh Tripathy 20:15
100% I mean, you it’s, it’s funny, I mentioned that this morning, we just launched a generative AI I mean, obviously, we have to keep it, we basically generate launched the basic intermediate expert program of generative AI with content on the same channel right now. Right? For everyone, right. And we have done that. And our CEO just sent a note I said, Okay, I’m going to read all of it. And that’s, I think the oneness part of it is the culture of the organization, which I’m extremely proud of. But more importantly, it’s yours 100%, right? I mean, you have to keep pace and kind of continue kind of driving that. But the thing is just the other piece of evidence, I want to point out, it’s not about just learning, you have to apply it in the context of work you’re doing. That’s the piece, we figured out figured where it makes it sticky, because I can learn a lot of things where it’s like, okay, I watch a lot of stuff on Netflix, but doesn’t mean like, I mean, I’m applying to it applying in the context of work. That is the next that’s essentially what we did, which we haven’t talked about, but that result was a game changer for us.

Brent Skinner 21:20
It’s, well, maybe you could just dive into that a little bit more like how did you actually sort of drive that? You’re absolutely correct, you know, learning in a vacuum, okay, I’ve learned all this stuff, and I’m still in my basement playing video games or whatever. Wow, you know, maybe I learned the, you know, the meaning of life. I didn’t share it with anybody.

Amaresh Tripathy 21:43
I give you a very clear example, right? So, think about a personalized ad or a persona that you can export, extrapolate from that you are you just went to the database program, and you process claims, let’s say, let’s go for your own right. And you just learned about something called anomaly detection, right? Which is, if everything is like all the claims sizes that you are processing, and then you are you to someone else, the one of the Gurus of massive gurus translated it for you, hey, if all the claims that you’re processing is $1,000 claims work, and suddenly you see $100,000 claim, you need to start thinking differently. That’s an anomaly for you. But my point is, it’s obvious. But that is kind of anomaly detection. Is that being step one, you kind of form that connection and build the learning process. And then you’ve just learned, by the way, hey, here’s all these cool techniques about figuring out alarm detection. And if you figure out what I’m interested in, what else can you do with it? And then you and suddenly, it’s like, oh, I’ve seen all these claims are which are there? Is there a project here? Is there a project where I should talk to my client and say, let’s say you are treating, and this is a real-life example? You are, it’s the same process we are using when it’s $100,000 claim as the same process we are using $100,000 claim, I bet, while the effort of the process is the same, the or the impact and the value to you for $1,000, or $100,000 is actually completely different. That’s a much higher risk and everything should you be thinking about kind of identifying upfront, putting a different kind of skill set of people getting deeper into it, the investigation is going to be a little bit different. Why haven’t you Why should we think about that? You can propose a project like that, because you just learned it, and then you propose it. And then you say, Okay, can I actually predict much earlier and this is this is what actually happened, when the when every all the claims come in, can I just predict which brought which claim is more likely to become a much more expensive claim and going to take a lot longer to handle, because then I can prepare for it. And I can manage in a separate way than the other claims. And suddenly, it’s like, that becomes a project and then you actually deliver the project. Grant is for clients, it’s an amazing thing. It’s a value they’re getting, which they didn’t expect in terms of how you actually manage your operations and how you predict what is your high-cost claims or more complex claims going to be through a different process. And by the way, you are certainly applied a concept that you learn in the in what you in the car in the context of the work that you’re doing. And it’s a win you learn it in a very deep way, you are more valuable as an employee, you are more marketable as an employee to the to the to the to the to the to the to the to the to the broader labor market, and your client has benefited.

Brent Skinner 24:31
Yeah, it’s a win, win. You deepen the consultative relationship, you’ve potentially generated more revenue, frankly, and, and the client is happier because they’re getting way more value. So yeah, absolutely. It’s that’s just amazing. Really, really fascinating and, and it really does show how sort of sort of you know, in the moment, you know, application of the learnings, this is definitely where, you know, that’s where the rubber meets the road here, when it comes to modern learning initiatives in business. What is your vision for the database program? Or the next program? Like what is your vision? Kind of like using this as a launching point? Where do you want to go next?

Amaresh Tripathy 25:20
So, two, three things, I think, on the vision and that has been a vision from the very beginning, we’re kind of executing in phases. So there’s a big employee piece of it, which I think was kind of checkpoint one, the checkpoint two ways, which is like a checkpoint to is, or our clients getting value out of it because of the program that we kind of launched and whether we kind of get value, some value, or we get to keep some of the value that we are generating for our clients on that. So, it’s just kind of value for clients. And that means value for us, you kind of refer to that. I think that the so that’s kind of where that’s where we are right now. And the third part of the leg is do we actually change newer offering services? Actually, that is IP right now we are generating through all of this thing, right? So, does it do it? Does it change the newer set of the newer offerings altogether? That we did not even think, or it was there? What was buried under it? Are we able to create new services and products and offerings, and IP platforms and all of that, that’s kind of the that’s kind of where we are going to move towards next? And finally, at some point, can we take now this whole package that we have learned and help other enterprises take on this journey go on this journey? Right now, we’re doing it for ourselves, but we could potentially that itself, this itself is an offering and there are some parts are very interested in kind of getting some pieces of it. And that we are happy I’ve helped out we have helped on some data literacy and data awareness programs and some of our clients to base on our learnings, but it’s this is not a kind of a skill for us today. But at some point, it becomes more and more and more and more valuable. This could be a product offering itself of how do you create data where organizations?

Brent Skinner 27:05
Yeah, exactly a turnkey product offering itself. And I’m also hearing you know, just it’s a driver of, of surfacing up future value, post value.

Amaresh Tripathy 27:16
That was not the intent. The fourth one was not the intent, since we are sharing more with clients and clients are like, hey, why don’t you do it? For us? That’s kind of the first three was definitely that kind of creating new value new products and services. That was definitely a corporate.

Brent Skinner 27:29
Very strategic, very visionary. Wonderful. And you know what? I’m just looking at the time and but I wanted to just say that, you know, this is a great example, also of not that you weren’t a learning organization already, but there was some definitely some latent demand for, for learning, and you provided sort of the supply to satisfy that demand.

Amaresh Tripathy 27:55
And that I just said that was what was surprising for us as to kind of the take up and I think every, I’m just convinced we’ve got, I mean, obviously, when new people come in and everything, we see that even the new cohorts stick up the same rate. So, there’s just an inherent demand in the industry, I think, or, or, or eager deaths to kind of do that. And actually, the challenge or to figure it out, as everyone who knows that they need to be a lot of data aware or get closer to this. The challenge is they don’t know where to start. It’s there’s so much information, there’s a deluge and everything like this and that and I think this this process just makes it an easier and more structured approach. We’re going to go into that.

Brent Skinner 28:33
Yeah, well, I can’t wait for this podcast to be live because I think people will definitely reach out and wanting to learn more and, and Amaresh thank you so much for joining us for this episode has been really illuminating. This is really fascinating, exciting stuff.

Amaresh Tripathy 28:51
Thank you, Brent. I mean, it was a lot of fun kind of chatting about this. And hopefully some of these lessons’ other organizations kind of kind of takes take and adopt and always is always happy to share our learnings and our experiences that we have had. And there’s a lot of lot of roadblocks and scars that we also have and I’m happy to always share that.

Brent Skinner 29:12
Well, absolutely. You know, nothing’s perfect, but this is very inspiring. Thank you so much Amaresh.

Amaresh Tripathy 29:17
Thank you!

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