In this episode of The People Purpose Podcast, Chas and Julie are together again, in person, in Indianapolis. They discuss data use at work and what you can learn from the data consumed by your organization. Plus, find out how many gigabytes of data the average American consumes in one day.
In this episode of The People Purpose Podcast, Chas and Julie are together again, in person, in Indianapolis. They discuss data use at work and what you can learn from the data consumed by your organization. Plus, find out how many gigabytes of data the average American consumes in one day.
Hey yo, welcome to the people purpose podcast, the show that explores all of the ins and outs, challenges and opportunities, HR, people, managers, and oh people face at work every day. I am one of your co host chez fields and I am with in person. My lovely friend
Julie Develin:Julie Develin. Hi, Julie
Chas Fields:Chas. It's so great. People tell me about my best friend, sorry. Angels as we start every show, tell me something good.
Julie Develin:Well, well, first of all, we should probably tell people where we are.
Chas Fields:Yeah, we're together. Right in Indianapolis,
Julie Develin:Indianapolis. Yeah,
Chas Fields:there was a hailstorm that just
Julie Develin:came a hailstorm that just came through so we thought it would be a really good time to try to record a podcast and hope that the Internet stays well, it's for me, it's not late. It's early, but it's late for me. For me. For me. It's the perfect time. Yeah. But something good Chas. I think I think you're gonna agree with me that we have the same something good and are something good is that we got to golf today.
Chas Fields:We did. We got to we got to golf today. That was going to be my something good. And I will tell you, Julie, we've played golf a few times before together. All right. And I was unbelievably impressed and proud of how well you drove the ball. Jam. How well you put it I did.
Julie Develin:I did put Well,
Chas Fields:the in between. There's areas of opportunity. There's areas of opportunity,
Julie Develin:and we call it that in business. areas of opportunity, weakness, no areas of opportunity, areas of opportunity I have are chipping around the greens. You know, the shorter the shorter chips and whatnot. Let's just say it's not my strong suit. But Chas, you. You had some amazing shots today. So you were hitting some lawn darts, especially from those par threes. Yeah, so good. Yeah, man. You know, I just I just for the record, would love to let everyone know that. Chas today tried to get me to buy him a shirt. And he made it seem like it was for his son who just had a birthday. But he said, Yes. He says my son would love a large men's shirt from the pro shop. And I said, that is not your son shall grow
Chas Fields:into it. No, no, no.
Julie Develin:No. But needless to say, I did not buy you a shirt because they were like, really expensive.
Chas Fields:Yeah, it was it was not an inexpensive shirt. You know, I may or may not
Julie Develin:have been myself. I'll tell you that feeling.
Chas Fields:So anyway, that was it was a good day. Bottom line is and by the way, if you hear some background noise, we're actually recording this in our hotel lounge. Yeah,
Julie Develin:because we like to do that stuff like that. Yeah. Change it up.
Chas Fields:Yeah, we're together. Look at this lovely background.
Julie Develin:I chose this location, by the way, just letting everyone so we don't do it. For those of you. For those of you who are listening, go to the YouTube and you'll be be YouTube. What am I the internet, the Google, go to the YouTube feed as I was gonna say, the YouTube channel. And, you know, take a look at our video anyway. So that's not why people tune in to hear us actually, maybe they do. But we we have had some feedback that folks love this little solace, little banter between Chas and I. But we are here to talk about HR topics. And we're here to talk about workplace topics. And that's what we intend to do today. And, you know, I want to start, we always talk about the business side of the day, of course, and today's business side of the day, I'll ask you Chas, how many? How much data do you earn in terms of gigabytes? Do you think that the average American consumes every single day gigabytes of data?
Chas Fields:So I have to think about it from my personal purse? Yeah. I know, I'm probably below the average. is like, you know, I think about like, my email doesn't take a lot of data. Yeah. Always on Wi Fi.
Julie Develin:Yeah, but how much does the American like how much do we consume? Meaning like in our brains? Oh, gosh,
Chas Fields:this is not a good alright, I'm gonna Okay,
Julie Develin:I'm just gonna tell everybody. So you can see, we consume about 34 gigabytes of data. This is according to a study at the University of California, San Diego. And that is estimated to be equivalent to 100,000 words heard or read every single day and what that's about the same number of words in a 300 page novel. I hope we haven't used that stat before, but even if we have
Chas Fields:I'm really disappointed in myself. Why? Because I, there's no way I could remember 34 gigabytes of data.
Julie Develin:No, our brains weren't designed, you know? So so what we want to talk about today is we want to talk about hrs relationship with data and data use at work. That's our topic. But But first has, why don't we get really deep with some some definitions? And this is certainly not to insult anyone's intelligence. But I think that it's important for us to discuss what data actually is. And by the way, it is data, not data.
Chas Fields:Is that the Oxford Dictionary? It is not, ya know, your writer journal, I get it. Yeah. But I guess in the south, we call it data.
Julie Develin:You call it whatever you call it data.
Chas Fields:So so this is actually really good data is a collection of individual statistics, facts or items of information. It's very simply put, technically, the singular form data is datum. Oh, saying that right? datum. datum. Yeah, data, right. But we don't use that No. And every now which, and Damien's raw form has to be organized and interpreted, to take out the information, really useful information. So data doesn't carry any meaning or purpose on its own.
Julie Develin:Right. And that's what we're gonna get to today. Yeah, we're gonna get we're gonna get to that today. Because, you know, I think that when we think about data, right, when data when data are processed, when data are organized, interpreted, structured, or presented to make them meaningful and useful, that is then called information and we say, how do we get information when we get information through data, right? So data by itself is generally meaningless. Now I know that you might say, Well, no, it's not meaningless. But you know, consider this consider if you have a list of dates, just a list of dates themselves, right, and say, a spreadsheet or something like that. The thing about that is those dates become irrelevant unless they're paired with something like a data group, like a data holiday, or something like that. So again, we're not saying that they're insignificant. But the thing is, I want to talk today, Chas about this and I want to talk about data and how we can utilize data better in HR and at work. And I want to talk about a few things related to data and HR. But the first thing I think is important is to talk about what is HR data? What, what is HR data? I mean, what's included with it? You know, I mean, recruitment data, right? Some of that, yeah, retention, payroll error rates, employee data, I mean, you know, play addresses, employee records, that kind of thing. But it goes a lot farther than that. And I think that when we talk about data, it can, it can lead to information that can be really, really useful. But organizations that lead with data, it means that when companies make decisions, it means that their decision making process is based upon facts, not upon opinion. Okay? See, I'm saying I'm on board with that, right. And so we're employees, for sure. So you know, the company's decision making process, when we're looking at numbers, when we're looking at data and HR analytics, this can help us to improve almost all areas of the company. And it but it's, it's about how we go about it. And, you know, we have to take the data and collect it, we have to process it, we have to analyze it. And then here's the most important part, we have to apply it, right. But the people who deal with the data also need to know that the data is there. So we in HR, what do you mean by that? So what I mean is we have to we in HR, if we're talking about HR data, we have to present the data to the stakeholders. Okay. Maybe we are not the only decision makers? Sure. Sometimes HR is not the decision maker at all. Right. Right. Right. So I think that, you know, it's important for us to, to talk about debunking some common myths, or what are some common myths about data because I think hrs relationship with data is kind of what's the word I want to say? It's kind of it's kind of struggling a little bit. Some of us, I think, yeah. What do you think some of the myths are?
Chas Fields:So my big thing about this when it comes to the way that data and information come together, a lot of times employees think that you are going so deep in their life, that it's like you're going to know everything, and what are you going to do with that information and who you're going to share that information with? And no, get me wrong, rightly. So they they should have to be able to ask that question or should have the opportunity to ask that question. But the idea of data like you said is to make a collect decision based on, you know, fact. Right? So I think the common thing is if you give information away, it's immediately going to be used to anyone in everyone's advantage versus a specific use case. Right. But it can
Julie Develin:it can be used to the employees advantage as well, that you know, so that, you know, I think something that I hear a lot of is that, oh, well, if we, you know, we have all this AI and analytics and all of that, then use data, it's going to make HR obsolete, to which I would say, No, I don't think that it's going to make HR obsolete. In fact, I think it's going to be just the opposite. And I think what it's going to do is it's going to elevate HR to greater heights. Because because we are now going to be able to give the organization insights that are going to even more so directly affect the bottom line? Yes. Because these are insights that directly affect our people. I see. So I think
Chas Fields:I think about it for my job to and not just my job, but like, let's say we're using this for advisory services, right? Like when you and I go in and talk to a company, like utilizing our HCM 360 tool, right, we get insight from the employees that we survey to understand, okay, you know, executive teams who are trying to make decisions, they're really good at making decisions. They're really good at making decisions. Sometimes they don't make decisions based on facts. Right. And therefore, we will come in and try and get that information and disseminate what employees are feeling versus the direction the executives are going. Right. So for me, I think that's a really powerful way for us as not only HR leaders, but anywhere within the business to backup, what we're trying to do, and, and really dated eliminates the disconnect. Is that That's,
Julie Develin:I think, no, I think you're absolutely right. Yeah, data definitely eliminates the disconnect, because it's, it shows us it shows it shows everyone in the organization, what truly is going on, you know, based upon based upon the numbers. So I want to put that right there.
Chas Fields:Do you think this is this is kind of rhetorical, but where do you stand on utilizing information when it comes to bias? Like the the important piece of
Julie Develin:Yeah, so So we as humans, we have over 200 unconscious biases ourselves. Okay. So these are biases that we don't know that we have of what data can do is it help us it can help us to uncover those hidden biases. You know, some people say, well, data can be bias. Well, so can we write so, you know, it's just something to consider? I don't know. But I think to Chas, when we talk about all of this, I think about the concept of time. The great philosopher Willy Wonka said, Time is a precious thing never wasted. Yes, I think you can learn everything you need to know in life by watching the original Willy Wonka. And I've said that on the podcast before. And maybe we use a lot of truth, we can do a whole episode. In fact, I may do a whole episode about it, even if you don't want
Chas Fields:so. I will say as you're one audience member, you're single listen.
Julie Develin:We have to deal with so much in HR, wouldn't it be great to have like more time in our lives and also give us tools like to have tools that give us insight on how to save more time how to have more focus, and figure out what's most important to prioritize? I get that question a lot. What's most important for me? How do I figure out what I should prioritize? I think data can help us do that.
Chas Fields:I wouldn't one thing that as you're talking to us as the change practitioner, if you will, someone who likes change, I've leveraged data in a multitude of ways to help lessen the fear and resentment and really resistance of big change, right. And I think that's where we often have this misconception. And we've talked about this before, we don't expect everyone to be a data scientist to understand it. But but there are ways to manipulate or understand information through great dashboards like HCM technology does a phenomenal job of this, where you see pretty dashboards and colors and like, red bad, you know, green, good, you know, things like that, that make it simple for us. And that's where, you know, when when we simplify the way our information is being fed to us. In fact, we talked about this before the podcast, or I was like, I get lost. We were talking about our schedules. Yeah, had someone reached out and was like, hey, six weeks ago, you spoke to thing and you talked to so and so. And I was like, wait, what, six weeks ago but like that's the consumption of information, right yet. I have a pretty dashboard that shows me where I was what I did, right. I did it right as data, right? But it didn't register with me. So I guess in my own mind and resistance to change. I can use this information to recall things that make it easier for me to be like oh, yeah, I remember so and so. And I talked to so and so and here's what the outcome of that conversation was
Julie Develin:right and I want to bring this back to a little bit, a little bit more clear, because I want to make sure that those of you who are listening are saying, Well, I do work with data. Yeah. Okay, you do work with data. And I mentioned earlier, you know about data itself. And there are some questions that you can ask yourself, within your HR department, within your payroll department, whatever, some questions, you can ask that you can get the most out of your data at work. So ask yourselves, where is that information stored? Right? And ask yourself who has access to it? Who has access to the data, you know, are important decisions being made using it? The way that you collect that data? Is that Is that something that is, you know, easy for you? Yeah. And is it? Is it useful? And then the most important thing, how can you trust your data? Because if you can't trust your data, then it's it's not good. And that's obviously the importance of a really good HR system, HCM system that can help to track that data.
Chas Fields:It was so interesting, because there's so much accountability on both sides. You use the word Trust, right? There's so much accountability on both sides of the information. And we've talked about this before. But that information in is bad information out right information out, leads to bad decisions, bad decisions destroys bottom mind. Right,
Julie Develin:right. Or unclear information.
Chas Fields:Yeah, yeah. So so what I'm hearing you say is, there's really as a story to tell here, this is there's a story to tell here. And more importantly, I think, we don't expect you to be data experts, right? I don't expect anyone who's listening to this, all of a sudden be like, oh, I want to be like Theresa Smith, who's a data manager. But the idea behind it, at least for me is if you have a problem, you can find some resolve within the information that you're collecting. If you don't have that information, you have ways to go collect it. And then if it's information you currently have, but it's bad, we need to, we need to go figure out what that is and fix it. Right? Because otherwise, otherwise, you're you're triple working
Julie Develin:and right. And if you feel like it's too daunting of a task to go and fix it, at least try take step one, right? Because the longer you wait, the worse it's going to be. Yeah. So here's the other thing. You know, I think that when we talk about data and using data to tell a story about what's going on in our organization, the quote unquote, words to the story are already there. Okay? Where do we find those words? Well, you may have paper files, you might have documents, you might have disparate systems, you might have, you know, systems that are being unused, maybe survey data, you might have, you know, different spreadsheets, right. So what we need to do is we need to find the words that story and then compile those words, quote, unquote, together to tell the story. And once we're able to do that, then that's when our data becomes even more powerful. And here's why we're able to tell the story, we can take one set of data, and it can mean one thing, but when we pair that data with other data points, that's when it really becomes powerful. So I think there's more angles to our data, then then we know if we're only looking at like surface level metrics, right, we need to look at the bigger picture. So I mean, just just an example. Like if you think of something like turnover rate, right? turnover rate, fine, right? Yeah, we can look at that data sample number. So simple number, it can absolutely show you the turnover rate. But what about if we did something like pair that data point, alongside average earnings? Okay, then what does it tell us? It tells us that maybe we have people who are making we don't feel adequately paid, right? Or we're lagging behind the market, right, that can help us to determine why people might be leaving.
Chas Fields:Yeah, the the reality of it is that when you look at information, especially with your people, leaders, and I'm gonna focus on people here for a second, I think we need to kind of peel that onion back a little bit. Because with the expectations that we have for our people, leaders, a lot of times good employees, individual contributors get promoted into a manager position. Yep. We actually talked about this in a former episode, where that's not always the best way kinda ladies don't make great managers all the time, right? But we look at people leaders to say, Okay, go make the best decision for your team and not necessarily extract the data to make that decision. My issue is not with the manager in that moment. My issue is we're not helping employees understand the data that we want to collect and the why behind it. So when that time comes, that they become a people leader, or maybe you and I as individual countries. Leaders call things out. We were just looking at data before we sat down and did this around the podcast. You know, what, are we doing different? How can we shape a message? But that was self taught for us, right? And had. And granted, we were blessed enough to have an education behind this. But for those that haven't had that, why would I not want to teach them that? Because they may think of a different story that you want them to tell? Or maybe thinking about it differently? Well, have you thought about it this way? Right? Because you as an individual contributor, and me and our teammates, we think about it that way. But the manager is like, no, no, no, I'm thinking about it this way. And this is why I'm making,
Julie Develin:right and everyone comes at it from their own their own bubble and their own their own viewpoint. So I mean, we can also look at something like open headcount. So if you look, and you see, okay, well, we have x amount of positions open. And, you know, what if you pair that with something, like time to hire or labor cost, etc, you know, that can tell you things like how much you might need to reduce or increase headcount or, you know, the costs and the people impact of open positions where the workload is heaviest. Right? So again, it's it's taking these datasets is taking this set these sets of data and pairing them together to be able to tell that story. And I think what, what another thing that's really, really important to recognize is that we, we have to know how to tell the story, we have to know how to present the data. Okay. And I don't know that I always did a great job of it when I was an HR practitioner, um, you know, I would go and I would find, you know, some kind because I didn't, I didn't have the insight or the foresight enough to pair those data points together, like I really should have, you know, I would just go and say, oh, you know, we have so many open positions, how are we going to fill them? Right? No, it's not the why behind the open position. I mean, it could also be where I was, you know, I didn't have data about where or metrics where I was advertising these positions, you know, maybe I wasn't advertising them in the right place. Yeah. Again, don't make these same mistakes. Yeah, we today, we have these tools at our disposal. I took Intel, you want to say something? Yeah, I
Chas Fields:do. I was thinking, say you're listening. And I'm like, Yeah, which direction do I want to take? That's a question. So let me ask you this. And this is kind of a pivot point. But how much of employee information and sentiment and data, let's call it data, really drives, team well being like overall wellbeing for the employee? Would you say it's 80% 90% 100%? No, it's a really hard question. Yeah. Right. But if if you want to focus, and the reason we took the HR angle on this is, for me, I believe that it's probably 95% Because of the tools that you have to measure what's going on with employees, and the use of artificial intelligence, Gen AI, you know, machine learning, as long as I have created a space for my employees to feel trusted, and to be transparent. I, and they operate as an open book, right with certain boundaries, but they operate as an open book, I can make really effective decisions, both for the business, but ultimately, the well being of that person. Right? Yeah. And it's not to say like, you're gonna, you want to impact your personal life. Anyway, that's how I'm saying it all I'm saying, if I fully understand where you're coming from, with that transparency, utilize the data presented upstream. Now we have new programs created, right. And all of
Julie Develin:which can lead to better well being Yeah.
Chas Fields:The bottom line, all of a sudden skyrockets, just by taking the information and utilizing it in a way that
Julie Develin:you're describing. And data kit data can be used for a million different things. It's not just employee data, right? I mean, data can be you can look at production time, you can look at, you know, basically, you know, the how well your workforce is is producing right, and or how poorly they're producing maybe at one plant, they're producing more poorly tie that data point along with the manager who the manager is at that plant, maybe it's an opportunity for retraining. Maybe it's an opportunity to retrain the employee. Yeah.
Chas Fields:Right. Yeah. I think for me, and as we start to wrap up here, I think for me, when, what do we do, like how do we go about presenting this information in a way and, and I remember when I was I was younger in my career, and I had a pretty big job. Like, I had a pretty big job at a younger age. And I thought, when I presented the information, it was kind of like, I don't know the buffet line. I'm going to give you a little taste of everything right? I don't think that's that was that was a hard lesson to learn. So maybe we should share with our listeners like how would you Was it the inference? Yeah,
Julie Develin:I mean, what if I so yeah. So when you have datasets, you have data points, you trust your data. It's all there. And absolutely has to be focused. I think it's also important to where I missed it. Yeah. Well, right. I think that it needs to be visual. So yeah, we love I know you love making PowerPoints. I literally like, I know. Yeah, he doesn't like it. But I know, but it does need to be visual. And it also, this is the most important, it has to be timely, because if you sit on data, that data may become irrelevant. Yeah, you know, in time. So you know, one of the one of the thing, one of the things things, while I can't even talk to the mothership, but yeah, for you one, one thing to make sure of is that you're presenting the data to the right people, the people that need to know, you know, people that are that are in the room, you know, this data is going to be relevant to them, and that you're presenting in a way that they understand. Yeah, not the way that you understand, but the way that they understand. And then that way, you know, once that happens, you're able to really work together to make decisions based upon what it is that you presented.
Chas Fields:Yeah, I think it's probably the thing that I respect the most out about that all of them are very relevant points. Timing really is everything. You know, what I mean, timing really, is everything. And we've said this before, when you collect all of the information, especially if you're going directly to employees, you need to help them understand how that is going to be used. And that's a common misstep, in my opinion. Yeah. Or it's like, I'm asking you this, because I am thinking about things for the company. Not gonna happen overnight, right? Like, it's the, it's the expectation and managing of the change, if you will. But I also want them to understand the timeline of how it's going to happen, or if it's going to happen that way. When we present it, it's like, okay, I can come back to you and say, you know, what, Julie, thanks for the information, I presented the information, it's going to take a little bit longer to know that we still care. Sure, yeah. That's, that's where the timely piece is so relevant. That's all right. Yeah, we're in the way. Yeah, I
Julie Develin:know, I know, allows us, like, it's all quiet in here. And then all of a sudden, maybe you guys couldn't even hear it. But anyway, you know, I, I just think this is such an important topic, and probably something that we can revisit later. You know, and we do
Chas Fields:have metrics specific. I don't know if we'd lose listeners on that. There's so much to measure, oh, my God, you know what I mean, but but here's the deal. What I will say is reach out to us, if you if you want to tell a certain story, maybe reach out to Julie and I on LinkedIn. But the
Julie Develin:other thing about it is you should check out the UK GS website. Because we actually have a data playbook resource, we're going to link to it. Okay. And this is something that you can utilize to get even more information on
Chas Fields:this from the mind of
Julie Develin:Julie definitely. Well, I don't know. And others and Megan and Kenya. Absolutely. But folks that we work with, but you're gonna ask me what I found my purpose and today that's exactly. And what I'm going to tell you is that what I find my purpose and what I continue to find my purpose in Okay, is that in a day and age where employees expect and in some cases demand transparency, the use of data and the use of analytics is becoming increasingly important. Yeah. And it will continue to become increasingly important as transparency at work becomes more of a topic.
Chas Fields:Yeah, I was I was gonna say today, this conversation has inspired me or my something good, if you will, to go learn more about how to understand that data, right? Like I need to go take a course or something I don't know how
Julie Develin:to do it, but the problem with but the problem about that is as soon as you go take a course it's already obsolete it's like buying a new computer
Chas Fields:to turn away myself.
Julie Develin:But honestly, it's like going to buy a new computer I remember I went to buy a new computer one time and I know we're wrapping up that's okay. Okay, I went to buy a new computer one time and I said to the gentleman who was helping me buy the computer this is years and years ago he's like doesn't matter which one you get because it's going to be obsolete tomorrow because there's so many there's so many improvements so yeah, but anyway, that's neither here nor there. We it's awesome being together it's a lot of fun to be able to like have a conversation this way and we're doing it
Chas Fields:again tomorrow. We are yeah we're actually releasing after that
Julie Develin:Yeah, we actually we get to go to our office you kg has an office here in the in the indie. Yep. And we get to our friends at Elevate we are They're awesome. They're awesome. Go listen
Chas Fields:to that episode, because this one will drop. Julie wrap this up.
Julie Develin:All right. So here's the deal. I'm gonna wrap up a few reminders before we leave. Don't forget, like subscribe, and use the hashtag well don't do it or don't none of you do. Respond. Yeah, people respond on social media sites and all So be sure to check out the latest blogs and research from the UK GE workforce Institute and visit workforce institute.org. And hey, give us a rating. That would be great actually gave us a rating. I don't know.
Chas Fields:We'll remember exactly.
Julie Develin:It's time for us to wrap up. All right.
Chas Fields:Thanks for listening. Bye