Knowing Your People Data w/Zach Ledford
Episode Overview
In this episode of "Making Better", we dive deep into the world of people data with our special guest, Zach Ledford. Zach shares his expertise on how understanding and harnessing people data can transform businesses for the better. From evaluating performance to calculating ROI, we explore the key questions that should be answered through people data and the immense value it can bring. We also tackle the challenges and pain points faced in areas like recruiting and manual data entry, and why clean integration between different systems is crucial. Join us as we uncover the power of people data and the strategies to unlock its full potential. Stay tuned for an insightful conversation that will help you navigate the world of data with confidence.
About Zach Ledford
Zach Ledford is the owner of ELJUN LLC, a Veteran Owned Small Business that focuses on creating data integration solutions that bolster productivity, reduce cost, and decrease risk. Incorrect people data is the biggest challenge I have faced when implementing learning strategies, so I wanted to have him on to discuss.
Full Transcript
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Zach Ledford [00:00:00]:
You can only do something in an automated way. Machines are only good at doing things if there's data to work with that's reliable and allows for repeatable processes. Right. In the context of people data, you are frequently trying to key off of things like job titles or organizational level or even just the department they're in, maybe a specific location. And if those things aren't well controlled, well defined, codified, there is no opportunity to do anything in an automated fashion to make sure those people are getting the learning and development that you want them to.
Matt Gjertsen [00:00:31]:
Welcome to Making Better, a podcast from Better Everyday studios devoted to helping small learning teams have a big impact. Today we are talking to Zach Ledford, owner of Elgin LLC, a veteran owned small business that focuses on creating data integration solutions that bolster productivity, reduce cost, and decrease risk. Incorrect people data is one of the biggest challenges I have faced when implementing learning strategies. So I wanted to have him on to discuss. Let's dive in. Okay, Zach. Welcome to making better. How are you doing today?
Zach Ledford [00:01:02]:
I'm doing great. Thanks for having me.
Matt Gjertsen [00:01:04]:
Awesome. I'm doing great. I'm really glad that to get to have you again, because we had a technical problem with the first time we tried to have this. So as is standard practice in podcasting, we will assume that that was the best podcast that was ever recorded and no one will ever get to hear it. But thank you so much for doing it again. We have a long history together, but for the listeners, I'd love for you to give kind of a one to two minute intro of yourself.
Zach Ledford [00:01:34]:
Sure. So, I'm Zach Ledford. I'm one of three co founders of an HR technology consulting company called Elgin LLC. So we're active in the laser focus in the people data, sort of HR vertical, specifically doing integrations, system to system, system to database data warehousing, modeling, statistical analysis, and strategic management as it relates to people data and people initiatives for companies of all shapes and sizes. Prior to getting started on this front, which we started up, I think, about three and a half years ago at this point, I was the manager of HR data and automation at Elon Musk SpaceX, which is where you and I kind of met and started our professional relationship many years ago now, actually.
Matt Gjertsen [00:02:25]:
Yeah.
Zach Ledford [00:02:26]:
Beyond that, I'm an army veteran, was active duty for four years, did a deployment to Afghanistan. I got an MBA, a PMP from the project management Institute, and married to a PhD in English, and we live with our one year old in Ohio.
Matt Gjertsen [00:02:45]:
Awesome. Yeah. I think I've always loved staying in touch with you because you are one of truly the few people I've ever talked to who I feel like understands the pain of people data. And when I say people data and the challenges that it faces, you're just like, yes, I get it. And even within HR, I feel like a lot of people don't realize why they're struggling with it or why they're struggling. And the source is often people data. So for those who maybe don't know what we mean when we say people data, could you define that term a little bit more for us?
Zach Ledford [00:03:21]:
Yeah, I will do my best and give you my working definition.
Matt Gjertsen [00:03:25]:
Excellent.
Zach Ledford [00:03:26]:
Because it is an interesting question, right? There's an argument to be made that all business data inherently, because it relates back to people, is sort of tacitly or second order effect. People data. Right. When we think about it from our perspective, our model is we think about this sort of core component of a person profile, a people profile, as a starting point, right? So that's broken out into three different questions. One, your people data should be able to answer, who are these people? So think, like, basic demographic information, the pedigree, their names, contact information, date of birth, like that kind of thing, right? Then you've got the second question, which is, what do these people cost to maintain? Really important for organizations of all stripes, right? So this is things like your compensation information are the hourly versus salary, what are the wages look like, the benefits, total rewards, like, that kind of thing. And then the last part of this core people trifecta is to answer the question, what do these people do? So we're thinking about things like job title, organizational structure, who's their manager? If they're managing people, who are those people and what does that look like? And so you got to be able to answer those three questions at a minimum. And that's kind of the central people data element. And then you can start to layer on more interesting questions, or what I consider more interesting, like, how do these people do what they do? Are they any good at what they do? Are they at risk of leaving? Do we care if they leave? What value are they bringing? Do we have a sense of what their ROI is? And can we get to something even more specific, like their Monetized ROI? And so suddenly you've got this core people data element that we talked about that expands out, blows up really big, but has a huge area of opportunity in terms of the value that you might get from really mastering it. Right?
Matt Gjertsen [00:05:25]:
Yeah.
Zach Ledford [00:05:27]:
But with that opportunity and value proposition comes some implicit complexity in terms of how you get there and how do you wrangle it and how do you do it.
Matt Gjertsen [00:05:36]:
Yeah, absolutely. So there's at least four buckets. They're your three core buckets. And then you could probably give a loose definition of just, like, operational people data, like all that stuff, of how they do their job or are they doing it well, all that kind of stuff. And, yeah, you take any one of those things, I was amazed. I remember one time looking at workday and thinking about just one data point of that bucket of what do they do? So, job title and you think like, what does somebody do? Oh, it's their job title. Well, if you look in the HRIS, very often there's like a job title, a position, a work know, there might be half a dozen different points of data that say just like what this person's job is. And then you think about all the ways that you could combine all of that stuff, and the complexity just start
Zach Ledford [00:06:33]:
To get pretty overwhelming pretty fast, no doubt. And that's things indexed on title. You start layering in things like level or band or if you're really sort of moving along the spectrum, skills or professional abilities and previous experiences, it can get very complex very quickly.
Matt Gjertsen [00:06:56]:
Yeah. So I want to ask you about some of the problems that you've seen companies face, but I want to start to frame this in the learning perspective since we have a learning audience. This is a very timely discussion because I was literally dealing with this yesterday. I was working with a client where my Purview was really I wouldn't even call it a learning needs analysis. It was just kind of like a certification needs analysis. I was talking with all the different leaders in the business. This is a small business, 300 Ish employees and looking at talking to all the work areas, just saying, okay, what are the key things that each person does or that you do on your team? And we had several meetings set up with all the leaders and you can't get ten leaders in a room without starting a discussion of, well, what is my work area Purview? Like I'm kind of in charge of this team and kind of in charge of this team. And I know you say this is my title, but it's really also this too. And I kind of have these people reporting to me and I'm just there as the outsider meant to have a discussion with them of like, okay, what's the thing your team does? What are all the things they do? And they couldn't agree on what their team was, let alone what they did, like who was on their team versus what their team did. They didn't necessarily know that. And so immediately you just run into the wall of like, well, I don't know where we can go if you don't clearly know what your department is or who the members of your team are. So that's where I've faced this is just this real, like, there's almost nowhere to start the learning strategy discussion if we don't have some of this basic people data in place, let alone implement it. Like try to assign out courses in any kind of automated fashion. So that's how I've seen it on the learning side. What are some examples of challenges that you've seen that people data have that people have with this.
Zach Ledford [00:08:56]:
Yeah, it's interesting, the sort of framework that you're presenting here. It's actually not super uncommon. I think it stems from one or two sort of common things we see as like a pain point or an obstacle. First is not necessarily having a real centralized and deliberate strategy about what your people data looks like. Organizational planning, organizational metadata, and sort of people structure is a big component of that. It's a foundational thing, I think that frequently happens semi organically. Just as the business starts to grow and things start to happen. You're just like, where do I slot it? It goes over here. Right. Because that's where someone notionally has capacity to manage it. Or it's a byproduct of finance making a decision and saying, from a costing perspective, this is what makes sense to me, and they do it in a semi vacuum.
Matt Gjertsen [00:09:53]:
Yeah, I see that a lot. It's actually really surprising to me how often the HRIS structure is driven by finance. It's a very common thing.
Zach Ledford [00:10:04]:
Yes. And it's not necessarily super clean, and it's frequently not clean at all. Right. Because your cost centers and costing allocations, your approval workflows for that section of the business may be very different from the functional component that actually says this person reports into this management chain. Right. And the bigger the separation between those two things are those two worlds, the harder and harder it is to get them to reconcile. And it causes all kinds of problems.
Matt Gjertsen [00:10:38]:
Do you have any examples of like and obviously not specifics, but when you say it causes all kinds of problems.
Zach Ledford [00:10:46]:
Sure. So one that comes up with virtually every client that we've had is around quarterly and annual forecasting activities. So think headcount, think spending, just overall operational expense planning and succession planning. Those are all kind of tied into this animal of labor forecasting and headcount control. Even something as fundamental as getting alignment on what headcount means can be vastly different because of the different frameworks that are in place between sort of the finance and cost center approach versus the HR approach. So, for instance, from an HR perspective, you probably don't really care about this idea of fractional heads. Headcount is how many people do you have in the organization that are doing things right? It's pretty straightforward from a finance perspective. You may want to make a delineation between, well, how many of those are w? Two versus contracted out with 1099 versus contracted out on, like, a fixed firm contract with a third party house, versus something that's wholesale offloaded to somebody else, versus a services contract where someone has access but isn't necessarily being actively managed. Right. And then layer in a third that we actually haven't talked about. And that's the It function because the access part, as we're talking about it kind of jog my memory. Now, you've also got the access control layer both in terms of physical security and to your network or to your various systems. So if you can even get baseline definition of something as simple as what does headcount mean? How in the world are you supposed to actually put together a program holistically to manage it?
Matt Gjertsen [00:12:29]:
Yeah, absolutely. Just to really quickly, again, for kind of the learning audience to put a pin in why this matters, because it can be like, hey, I'm the learning person, I'm just over here. We're kind of getting in the weeds here. I think not having a good understanding of whether it's like who reports to who or what departments exist makes it next to impossible to implement a big learning strategy, an automated in any way or scalable learning strategy. This is not a problem that we can solve by ourselves, right? Like, we have to engage other elements of the business that have very entrenched interests in this. And I think understanding some of the reasons why, like you were just talking about HR has a certain problem to solve. Finance has a problem to solve. It has a problem to solve. Understanding where those people are coming from is going to be really helpful to you as a learning person. Going out and talking to other parts of the business and saying like, hey, we need to fix this. Because I know when I first started in this, when we first got to know each other, none of it just it just didn't make any sense to me. It looked like everything was complete nonsense. Nothing made any sense. Why would anyone ever choose to set up and organize data in this way? But it's only by understanding the problems that these other people are trying to solve that you're kind of like, oh, I get it. And then you can kind of go to them with a little bit more empathy, a little bit more understanding. And that's the basis of having a true discussion where you can get your problem solved by helping them understand what you're trying to do and maybe kind of find a more holistic solution. So just for the listeners, I know we're kind of getting in the weeds on this, but I think this is really essential if you ever want to be able to solve this problem is understanding what it means to other people.
Zach Ledford [00:14:17]:
Totally agree with that. I mean, the empathy part is huge. And speak directly to maybe slightly more detail on one of the things. You highlighted this idea of programmatically in an automated way, assigning training to individuals, right? You can only do something in an automated way. Machines are only good at doing things if there's data to work with that's reliable and allows for repeatable processes. Right. In the context of people data, you are frequently trying to key off of things like job titles or organizational level or even just the department they're in, maybe a specific location. And if those things aren't well controlled, well defined, codified, there is no opportunity to do anything in an automated fashion to make sure those people are getting the learning and development that you want them to. It inherently becomes a manual activity.
Matt Gjertsen [00:15:08]:
Yeah, exactly. Because probably the two most common things that I would run into would be something like give this course to all the engineers or pick whatever job title. And it's like, well, do you mean software engineers or hardware engineers? They don't really have a clear knowledge of what they mean or what titles are in the system. And then the other place I get this is assign it to this whole department when that department doesn't even exist. Really what they mean is assign it to everybody who reports to this person.
Zach Ledford [00:15:43]:
Right.
Matt Gjertsen [00:15:43]:
But you don't want to ever assign training based on a person because then if that person moves, it messes everything up for us in the learning space. It becomes really challenging. So you mentioned all these problems when you start working with a company, what are some of the first things that you do to try to get past this problem or solve some of these data problems?
Zach Ledford [00:16:10]:
Yeah, the first piece is to have the various conversations with different players who might have different frameworks they're working with and meet with them individually first to understand what they're doing and why. Again, that empathy point is extremely important. Right. It's a matter of understanding their motivation and intent because there always is one. We'll go in with the baseline premise that there's no mal intent, there's not someone actively trying to subvert the business.
Matt Gjertsen [00:16:40]:
We're all trying to do the right thing. Good place to start.
Zach Ledford [00:16:44]:
Right. And so you go in with that frame of mind. I think it's helpful. But once you start to kind of see those things, there's generally going to be significant overlap. Right. It's the 1020 percent of things that don't perfectly align that cause the problems. Right.
Matt Gjertsen [00:17:01]:
Yeah.
Zach Ledford [00:17:02]:
So that's where the proverbial squeaky wheel is sort of starting from. And so that's the point of intervention, to kind of start to figure out what can we do, maybe to make that a little bit less problematic, a little less noisy.
Matt Gjertsen [00:17:17]:
Do you find that there's some easy kind of on that idea of there's quite a bit of overlap, but then there's these outliers? I find that in a lot of instances, those outliers, they take up all the time and you wind up trying to solve those. Are there often, like, early wins that you can get to really move the ball forward? Just because these things basically are the same thing. You're just calling them different things, but we can kind of combine them with relatively little work and then worry about the other 20% later on.
Zach Ledford [00:17:49]:
Yeah, sometimes that happens pretty readily. Right. Like you'll see a difference between even just terminology. Finance is calling something a cost center or as this notional idea of a cost center hierarchy and there just hasn't been someone to bridge the gap to say that in the HR speak, that actually means a supervisory organizational structure mixed in with a department, mixed in with a group or a division. Right. So it's as simple as really as crazy as it sounds, just putting together even an Excel spreadsheet that says, here's what HR calls it, here's what Finance.
Matt Gjertsen [00:18:21]:
Calls it, I've done it.
Zach Ledford [00:18:22]:
And here's where there's a mismatch. And so can we break apart those problem children and sort of figure out what to do from there? Right. But nine times out of ten, you guys are saying the same thing, just with different words.
Matt Gjertsen [00:18:34]:
Yeah, kind of on that. When you talk about meeting with all the players, what are the common players in this discussion? And is there a common head of it all, a decision maker?
Zach Ledford [00:18:47]:
Man? So the common list of players is an easier one to answer. So I'll start with that. Right. So you'll have whoever your head of HRIS might be your information systems person. Right. In theory, they're getting marching orders from the CHRO or the Chief People Officer or whatever else, and so they should be the representative. That person's probably a little bit higher level than what you need for this specific conversation, but if it's a smaller or mid cap business, maybe not, it might be the same person. This should be someone who understands the theory behind the HR core systems and what they're doing. It's really important too, to include not just core HR, but talent acquisition and recruiting in this part as well. Because if you think about end to end, how you get people into the business, how you're posting externally, and that sort of bridge, that's a really big component that frequently kind of gets like lost in the mix. And those frontline people, they know a lot. They know a lot. And they're also your bridge to the individual business leaders, because the hiring managers have to be present. Right. You need them as part of this conversation. The others would be members of the finance team. Typically. There might be someone from payroll that might want to have some play here. There's a lot of decisions that are made in terms of how to organize data from an organizational perspective because of local labor laws or tax laws, as crazy as that sounds like it's coming out of a legislative need. So understanding that if and when it pops up is helpful. And then anybody who's doing the forecasting components that rolls up into the CFO as it relates to workforce management and workforce planning, you want that person or those people in the room too, for sure. Because if you don't have them on board, that means you don't have the CFO on board. I don't care what you're doing, how persuasive the other executives are that you have in your corner. It's not going to work.
Matt Gjertsen [00:20:50]:
That makes sense.
Zach Ledford [00:20:51]:
CFO has to be down and then the learning function for sure, because that's the other part of it, right? You think about the major consumers of this data and someone who's also entrenched in with the different business leaders. It's learning and organizational development that should be plugged in with that. There is someone who can help bridge some of the operational needs and requirements and strategy with what's actually available from the people data side.
Matt Gjertsen [00:21:17]:
Yeah, so kind of to put big picture terms on it, it's probably so we got learning, you got HR, you got a couple of different modes of finance. So you got like compensation and then core finance. It and recruiting are probably some of the major players. I do want to highlight one thing that you mentioned that I think is really critical with this because this kind of stuff is so in the weeds and sounds so I don't even know what it sounds minimal or it just sounds like, why are you talking about this? There likely is a big separation between, at least in my experience, the people who can have your initial conversation of talk about what are the terms, how do I define them, how do I use them, and the people who can make a decision about making a change. And so when we talk about finance and you're talking about having those meetings to get set up, it's not about, hey, let me go talk to the CFO about this, because they're probably not going to take a meeting. They're not going to care. Even in a relatively small company, it just feels below their radar. You're going to need to talk to the people who are dealing with this data day to day to get that understanding, get them on your side, build their case. And so then you're having the ground level person in finance kind of requesting the meeting with the CFO of, hey, we want to talk about this change. That's something that took me a while to understand, is that separation between who can talk about it at a tactical level and then who can make the decision for the strategic change.
Zach Ledford [00:22:58]:
No, I think it's a really important point, right. You are probably not going to be going talk to the board of directors or the entire C suite and present your case with this very in the weeds component and then be like, and now give me a decision because I'm here and I'm ready for one, right? It's not going to happen. In over ten years, I've never seen that happen. But building sets of advocates that understand and have had the lived experience of the pain that comes from not solving this problem. The ones who really get it. And if you sat them down for a cup of coffee and you're like, tell me three things that you hate about what you have to do, and they tell you two of them and two out of those three are related to issues that we're talking about now. They're going to get it, and they've already got trust with the different verticals they're in. If you get them to become your advocate, which is easier because they understand what you're trying to do and how it will help them, they'll sell it for you.
Matt Gjertsen [00:23:53]:
Yeah. And I think that's huge because the pain that we feel in learning, like everybody has their own kind of that pain, whether it's recruiting and how they have to manually enter data. Because there's not a clean integration between the ATS and the HR system or finance that's got to rerun a bunch of charts because they can't automatically pull it out of their finance system because the data is not correct. Everybody's got their own set of this in those discussions, though. So when you're trying to build that case so getting back to kind of the core of what you do, you go into companies, you help them reengineer the back end to help these integrations. This seems in the weeds, but it has huge payoffs, not just for the frontline people, but for the business as a whole. What are the kinds of things that you've seen as the payoffs of doing this better that the people listening can kind of use as firepower to go push these conversations, get people to talk to them about it? So what are some examples of how this can improve a business when we do it better?
Zach Ledford [00:25:07]:
Yeah, for sure. So there's only three things that decision makers in business care about that's time, money, and risk, right? That's it. And those things are frequently very intertwined and very intermingled. But if you can put a narrative together that speaks to one or all of those things, it's going to resonate. Right. And this is a narrative that readily hits on all three. Right. So from a time perspective, manual intervention, repeat work, that's an easy one for people to understand, right. And it's easy to put something that seems esoteric and put a number on it. So we do this kind of thing all the time. We'll say, what does your overall recruiting activity look know you mentioned that maybe there's no integration between the ATS and the HR system, right. What does your manual activity look like per position that's being posted inside of the ATS? What does your overall time look like when you hire somebody to actually extend the offer, go through the whole process and get everything documented? What does it look like? And do you have to repeat work to move that person from a candidate status in the ATS to becoming, like, an onboarded employee in the HR system? We've literally sat there with, like, a stopwatch and done this to see collect data on it. And then we'll say, okay, maybe it's five minutes here, ten minutes here. It adds up to an hour or two per requisition or per activity times a throughput of 1000. There's 2000 hours. Well dollar cost average out what the average total rewards are for the employees. You're doing that function, there's your monetized costing, right?
Matt Gjertsen [00:26:36]:
Yeah.
Zach Ledford [00:26:37]:
So we've got time which carries opportunity cost that we've accounted for. Convert that to number of working days or weeks. It's opportunity cost, actual monetized cost of that activity, so there's a direct loss as well. And then there's the risk component where you might start looking at things from a reporting perspective that matter a lot. If you're somebody who's active in the space that requires like the OFCCP or EEO compliance components, you can't readily report on some of those things. It could kill your business because you won't be able to continue to support government contracts. If you're active at all in a space that has Sox regulations on it, you better be able to meet all of the regulatory needs. Same thing for GDPR, cal warn, regular warn like these are all things that from a risk perspective are very important because they're an existential threat to your business.
Matt Gjertsen [00:27:28]:
Yeah, I mean, I know I saw this a lot as COVID kicked off and people employees just started moving everywhere. And if you don't have a clean system to get that data updated, then it's one thing if somebody's living in a different state and so maybe they don't get the correct sexual harassment training or whatever. It's like, okay, it's not the worst thing in the world, but somebody moves out of the country and you don't account for that and there's like 1001 tax implications, god knows what else. These can have huge risks if they're not managed appropriately.
Zach Ledford [00:28:03]:
Definitely it comes down to access control and things on the It side of the house as well. Right. I've seen it where you have people that are just lingering in systems forever five years after they've been terminated and they still technically have a backdoor entrance into a key system. It's mind boggling, but it happens all the time.
Matt Gjertsen [00:28:23]:
Yeah, absolutely. Well, hopefully I think most of what I was thinking I wanted to cover today. What about you? Any other things when you think about people that are talking to a learning audience? Anything else that you wanted to cover?
Zach Ledford [00:28:39]:
Yeah, I think it's important to be creative and always have this mind towards pushing towards the automated solutions where you can so it frees up your time to focus on those things that machines are not good at doing. And there are many things that they're not good at doing.
Matt Gjertsen [00:28:53]:
Despite what we might hear with Chat GPT, there are still many, many things that computers are not good at yet.
Zach Ledford [00:29:00]:
Yeah, so I would proper up to the audience. We've kind of touched on it a few times, but what are different things that you can key off to? Kind of help assign training out or monitor It titles, skills, previous experiences, levels. I've done stuff off of payband. Don't be. Afraid of introducing new data to the data model. Too. You mentioned the engineering function. I've done this in probably 15 organizations now where we've made a delineation between engineering versus non engineering, and it's a binary flag, and we use it because it's impossible to account for all the variations of job titles. Right. Do you include solutions, architects or not? Are the engineers or not? Right. Put a codified workflow into place to help introduce that data, if possible, and don't be afraid to go advocate for that because a lot of times people say, never thought about that. Sure, why not? Right? And it's easy. And then the other thing would be along the lines of the organizational component, thinking about I want everyone who reports to this person. You could also think about positions and people and the interplay there. So maybe you're allocating training based on position and positional structure. Position management is a component of the business and assigning training based on that as opposed to the individuals in the position. So we've done this before, too.
Matt Gjertsen [00:30:23]:
Okay.
Zach Ledford [00:30:23]:
There's ways to get creative with it so that you've got something that's not super brittle but is still doing what you want it to do.
Matt Gjertsen [00:30:30]:
I've seen that before, and if I get what you're saying, it's like I've seen this in the workday point of view, where workday has the concept of a position that is separate and apart from the person in that position.
Zach Ledford [00:30:40]:
Right?
Matt Gjertsen [00:30:41]:
Yeah.
Zach Ledford [00:30:42]:
There's the organization with organizational slots, and then you put people in and out of the slots, but the slots themselves remain until there's a strategic decision to deprecate or move them.
Matt Gjertsen [00:30:53]:
Well, awesome. Well, thank you so much, because I really think if you start to think about a lot of the challenge that you have implementing a learning strategy and an effective learning strategy, it's really making a difference in the business. This is really one of the places where you start to run into challenges. You just don't know who's in the business, where they are and what they do. Right. And you don't know that because there's not a good data structure in place. And so starting these don't feel like you're just stuck and can't do anything. But also just don't go to the C suite and say, we need to change. There's other people in the business that are feeling the same pain for different reasons, and it's about getting those people together, understanding their pains, trying to come up with solutions to it, and then presenting that up above. I think that's the only way to move forward. So thank you so much, Zach, for being on today. I can always talk about this forever, so thanks a lot for being on.
Zach Ledford [00:31:54]:
I appreciate it. Happy to be here. Thanks.
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