The Elephant in the Org
The "Elephant in the Org" podcast is a daring dive into the unspoken challenges and opportunities in organizational development, particularly in the realm of employee experience. Hosted by the team at The Fearless PX, we tackle the "elephants" in the room—those taboo or ignored topics—that are critical for creating psychologically safe and highly effective workplaces.
The Elephant in the Org
Average Lies: The Misleading Nature of HR KPIs with Ben O'Mahony
Ever thought your HR data might be pulling a fast one on you? 🤔
Join us in our latest episode where we debunk the myths of HR metrics with our special guest, Ben O'Mahony, Co-Founder and CEO of JobsASI. Dive into the tricky world of averages and discover why your KPIs might be telling you fibs.
Prepare for a lively chat with your Fearless PX hosts Danny Gluch, Cacha Dora, and Marion Anderson, as they explore the intricate dance between qualitative and quantitative data in HR. It's not just about the numbers; it's about what the numbers are hiding! Tune in for insights, laughs, and a fresh perspective on using data effectively.
Don't just trust us; listen to your data (but not the averages!).
Click here for full episode shownotes
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📩 Got a hot take or a workplace horror story? Email Marion, Cacha, and Danny at elephant@thefearlesspx.com
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Subscribe, leave a ★★★★★ review, and help us bring more elephants into the light.
🎙️ About the Show
The Elephant in the Org drops new episodes every two weeks starting April 2024.
Get ready for even more fearless conversations about leadership, psychological safety, and the future of work.
🎵 Music & Production Credits
🎶 Opening and closing theme music by The Toros
🎙️ Produced by The Fearless PX
✂️ Edited by Marion Anderson
⚠️ Disclaimer
The views and opinions expressed in this podcast are those of the hosts and guests, and do not necessarily reflect any affiliated organizations' official policy or position.
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Danny Gluch: welcome back to the elephant in the org, everyone. I'm Danny Glutton. I'm joined by my co-host, Cacha Dora.
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Marion Anderson: Hello, and Marion Anderson. Good morning.
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Danny Gluch: And today we have a special guest. Ben O. Mahoney Ben is the CEO and Co. Founder at Jobs Asi on a mission to give recruiters superpowers with AI and dramatically improve the candidate experience. Ben has spent the last 5 years building data and machine learning platforms and products, and before that had a career in people and talent in high-growth startups. Ben welcome to the podcast
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Ben O'Mahony: yeah. Thanks for having me. Yeah, delighted to to have a chat look, looking forward to our topic.
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Danny Gluch: Now we need to say, Ben also put in his bio that he was Time Magazine's person of the year in 2,006 extremely bold claim.
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Danny Gluch: What were you doing in 2,006? What was so spectacular?
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Ben O'Mahony: Oh, it's yes, it's a bit of a joke. It's a nice one to get get. Get a little bit of notice. But yes, the time person of year 2,006 was you? So technically. we're all times 2,006 person of the year. So it's just nice, I think, you know, to to pat yourself on the back every cell phone and say, Hey, yeah, I did win.
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Marion Anderson: I'm putting that on my recipe, although I understand, if I understand correctly what you were actually doing in 2,006 was getting pitched on whiskey in Edinburgh. Am I right?
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Ben O'Mahony: It? Yeah, it was. It, wasn't it, wasn't it? Yeah, discovering the good stuff clearly. Time Magazine thought it was spectacular.
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Danny Gluch: So
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Ben O'Mahony: clearly, clearly the only awards that I've won. I probably shouldn't have done that, hey? Hey?
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Danny Gluch: They really ruin right by by Time magazine, saying, It's you. So everyone can now claim it really muddles the water, and sort of the statistics of the importance of that. And and
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Danny Gluch: lo and behold! The elephant in the org today is the misleading nature of statistics and key performance indicators in Hr. And the people space and you with a background in data and machine learning with the is such a great idea to come in and talk about sort of like, what are these assumptions that we've made or been led to to make
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Danny Gluch: in the Hr space. Right? We are not data analysts for the most part, and we're just like, Oh, someone trained me when I got on board is this as how we're using data. This is what we're measuring. And it's like.
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Danny Gluch: Oh, wait! Someone who knows about this stuff is telling us we're wrong. Maybe we should listen.
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Ben O'Mahony: Yeah. Well, I think you know. And we we spoke about this on the on the sort of build app. But you know, I think, that
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Ben O'Mahony: we often saw say, Oh, I'm not. You know about data. Actually, you know, in the people in talent space. We're often really excellent at the sort of qualitative data. And that's actually what a lot of what you know, where we get our ideas from where we get the sort of hunches for these things is speaking to lots of people within the org. You get a feeling for these trends that actually, when you come to look at them, a very difficult to get down into numerical data. So yeah, for me, I think.
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Ben O'Mahony: like, what you'll find is a lot of people and talent. People are very data driven, but they're gonna be focused a bit more on the qualitative rather than the quantitative. And you know, unfortunately, we tend to run our companies on quantitative data so numbers and yeah, sometimes we can get sort of bamboozled by by that data, and
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Danny Gluch: that's a great distinction. I think some of that's the background of who Hr. People are, tend to be very quantitative as opposed to the sorry qualitative as opposed to the quantitative data they're so easy to mix up. But one of the things that you first mentioned to us was that averages can really really make the the data that we are pulling together. Nonsense. And and I wanted to hear from you and caution Marian. After that, on what? What is it about? Averages? Cause
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averages average right? That that shows like a well balanced. But what is it that we get wrong when we do averages.
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Ben O'Mahony: Yeah, I mean, like, you know, from from my point of view, I think it's almost every
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Ben O'Mahony: metric that you see in the people. Space tends to be an average of some sort. And you.
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Ben O'Mahony: you know, II sort of very influenced by the the good grips design people. They talk around actually, you know, when that design they they designed scissors and other utensils, and everyone designs for the sort of average user and and what they did was that was different. Was, they were like, right well, what are the extremes? And can we? Can we look at them? So? They? They think right, you know. The the you know, the 25 year old bodybuilder who, you know, can't
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Ben O'Mahony: you know their fingers are too big to put inside normal scissors versus the you know, the the 92 year old grandmother who, you know maybe, is, you know, struggling with grip, strength, and those sorts of things. And actually, if you design something that works for both of the extremes, then the middle is covered, you know, and and I think it's the same. Right? We when we're thinking about average.
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Ben O'Mahony: we're just thinking about like, what's the average employee, you know. And and and that's not actually that useful or interesting or or unlike. There is no such thing as an average employee. Right?
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Ben O'Mahony: But actually, what do we think about looking at is the extremes of the data and how they can, how we can make decisions around that.
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Ben O'Mahony: You know, a worked example. Might be I think you know, around absenteeism. Where actually, you know, you might have an average absenteeism over the year of.
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Ben O'Mahony: you know, 5 days sick or less. I don't know more. I'm I'm not not afraid with what the benchmark for this particular step should be.
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Ben O'Mahony: but the reality is is like you might actually have you know, a small proportion of your workforce, who are long term sick, who are dramatically skewing that that data. And actually, you know, like, that's that's something that is very misleading. If you've got those scenarios in a smaller company when it's like
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Ben O'Mahony: likely that you don't have someone like that. And then, if you do have someone like that, you know, and and you're doing the right thing and making sure that they can come back to work. You know, when they're fit and healthy. Actually, that's skewing the rest of your data. And you might make decisions later on down the line that are, you know, not representative of, you know, not not backed with evidence, because, you know, you've you've got this skewed data
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Marion Anderson: so logical, you know, it's funny because there's so many Kpis.
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Marion Anderson: the feature within the people realm that just inertia, you know, someone started measuring that in 19 canteen. And
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Marion Anderson: we've never questioned it. And we've just kept going with it. And actually, like. you know, you're smart, and you've stopped and went.
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Marion Anderson: That's yes, like, why are we even looking at that doesn't make any sense, I mean, and we're all pretty smart people. So when we actually stop and think about it, we're like
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Marion Anderson: pile of crap. And I've wasted so many hours trying, you know, with all these awful formulas to you know how to calculate attrition and all. And oh, my God! So actually, it makes sense, II think, obviously with tech. Now, we're getting a lot better quality data. And
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Marion Anderson: but you know, and we're learning how to leverage it. But we really need to
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Marion Anderson: think about it in a much more sophisticated way.
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Cacha Dora: I'm with you, Mary, and on that I think also, too, what what Ben was saying around the concept of averages, not taking into account
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Cacha Dora: the things that the circumstances averages don't take into account circumstance. So when, if you're looking at certain averages, and you've had, like either, like big world change, like thinking about absenteeism during 2020.
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Cacha Dora: Well, you had a covid pandemic.
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Cacha Dora: So like you had these like really long leaves for some people, and then some people never took sick leave. So if you only looked at the average for from a couple of years during that period, and you didn't take into account circumstances, your sick time or your leaves that you had
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Cacha Dora: there. There was like this huge anomaly. It just looked really really big for some reason, and in
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Cacha Dora: taking, I think there's a little bit of that logic aspect of it's not just
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Cacha Dora: a number. What? What is causing that causality
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Cacha Dora: of where your numbers are coming from. I think that's where, like, we're kind of in a unique place to kind of talk about this in the people space because numbers are always gonna be important. But the story that you build from them and the impact, you know, like, when when anyone either like the C-suite, any place that we're having this conversation only like, Well, why did this happen like, why is this average so low or so high, and it's like, well.
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maybe not. Look at the number for a second.
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Cacha Dora: Maybe like talk about the rest of it, cause I think that that's kind of how you get there. Ultimately, right? It's not just this average.
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Ben O'Mahony: Yeah. I think for me as well. It's like, you know, we're like working in data for the last 5 years or so I've worked with teams of engineers and analysts. And what you find is that actually, you know, we can come up with a number.
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Ben O'Mahony: and we can come up with a defense of our of why, we've got that formula right. But the reality is that that is, that isn't that useful on its own? You do need the context for the business. You need the analysis that goes deeper. You need to look at the spread of these things. And you know a lot of business people business, a lot of businesses. You maybe don't have enough
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Ben O'Mahony: volume of data to go too deep into this. So especially the start up world, we're in the scenario often where we're like, right? Can we have, you know, can we have some data on this. And you're like, right? Well, you know, I could go away and manually do a lot of work. But, like, what's what's the problem that we're trying to solve here, and actually, more often than not, I think you do also have to have that understanding, and it's one of the things when I was looking for a role a year ago was like, right? Actually, who's
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Ben O'Mahony: do the do? Do the leadership team understand? That there's a that qualitative data
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Ben O'Mahony: is important as well, and you don't have to have a number for everything but having something that's sort of, you know. A little bit more like right like this is how people are thinking about it. You know, this is what I've surfaced from these conversations, actually, and especially in a high growth, start up.
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Ben O'Mahony: That can be like way more useful than than actual numbers, especially if like said you've, we've aggregated them up into an average to the point where we've got rid of all the information that actually went into making that number. And now we just have a number, and we
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Ben O'Mahony: is it going up or down, you know, that's actually like that's, I mean, that's it right? That's what Kpis are often like. It's like
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Ben O'Mahony: dashboard. And you know, some of the numbers are green and some of the numbers are red. And you're like, Okay, cool, like more green and red, like, I suppose, business going right direction. No. But I think that's what brings up the the green and the red and the just numbers that. And and I I'll never get over that good grits with the scissors. Example of
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Danny Gluch: again, if if you're averaging everything out and not paying attention to both outliers right like, if you're designing scissors and only the the elderly and like close to the average, can use it. But these slightly above average hands, and the 25 year old weightlifter, like they're just not going to be able to use your scissors. And if we think of this on like what Hr teams are doing, let's let's like
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Danny Gluch: manager effectiveness, which is like us just trying to come up with a number that is like, what are the vibes on your managers? Right? What? What's that actual qualitative like? How are, how are people really feeling about the managers?
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Danny Gluch: and
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Danny Gluch: what II want people to realize is that if you get the, you know again like don't just come up with a number for a number's sake, but if you're able to to say like, Hey, for the most part we have, people are happy with their managers. We have some just absolutely love them, and we have some who
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Danny Gluch: really are unhappy.
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Danny Gluch: How we can't just focus on the ones that are really great. And you know, you can't do one outlier. And the average, you have to do both. Or you're really gonna miss something. You're gonna miss something important, and it's going to affect the the overall manager. Effectiveness of the organization. If you don't address both right, boost up the great ones and address the the poor ones. Not just aim for the average.
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Ben O'Mahony: That's I mean, that's a that's a perfect example, right of like, I think we we naturally do do this right. We look at the underperform, the the the peak performers, and the the the real underperformers. That's something we naturally do right. But then, like turning those into metrics would be really interesting, you know, actually have, like, you know, I've used like tools like peak on for like measuring internal engagement. Other tools are available.
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Ben O'Mahony: But yeah, basically, right, do you wanna look at? Right? You know.
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Ben O'Mahony: we want less than 10% of our managers to get a manager score of below X,
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Ben O'Mahony: you know. So rather than being
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Ben O'Mahony: Like, okay, we want to move the average up.
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Ben O'Mahony: You're not saying actually, no, I want to remove the the bottom.
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Ben O'Mahony: and that's 2 very different approaches, because you can average up by making your your best better.
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Danny Gluch: You can do it by
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Ben O'Mahony: training everyone and moving everyone up a little bit, or you could make it better by, you know, you know, potentially putting on a pit, or even moving out the people at the bottom end of the spectrum. These are different ways of moving that average. But if you have those different treatments for all of them. So maybe you say, actually, let's flip that round. I wanna positive I want, you know.
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Ben O'Mahony: at least 20 of our managers to have an employee net promoter score of 50 plus, you know, you can then say, right, okay, cool like.
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Ben O'Mahony: it starts to lead into that strategy a lot more of like, okay, cool. What do we think about these things? Do we want to like
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Ben O'Mahony: double down on our windows? Do we want to potentially cut all users like, what like do we want to? Just actually do? We want to flip that and and do that? And you actually have.
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Ben O'Mahony: you can have different kpis that you'll think about. Or you know, in in engineering, they're more like service level agreements where you've got. You know what what service level of management do you want in your organization? And actually, you can move those over time and see where they are? So you have a little bit of a better understanding of like, what's the distribution of management? Not just
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Danny Gluch: what the average manager is like. Because, yeah, like, we said, there's no such thing. And and I think that makes a great transition to so often in business, we only get data to sort of like
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Danny Gluch: justify decisions that have been made right to to show like, Oh, and that's why we did it. The data backs it up and like you can even massage those a little bit and ignore some and do others to like, really prove like, yeah, we're supported by data to do what we just did on instinct.
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Danny Gluch: And what you're showing is this really
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Danny Gluch: alternative solution, where you can just be curious, you can get the numbers just because you're curious about the numbers. And then, after you see the numbers, you can say, Well, here are the different strategies we can do. We can get rid of the bottom, and that by its nature will shift. We can do all these other number of things.
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Danny Gluch: This is just what the data is telling us. How do we want to address the reality that the data is showing us, and I think that that using it as a way to have discussions about choosing
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Danny Gluch: strategy and and like, how are we going to embody this philosophy that that goes with our our management philosophy or organizational philosophy that is so different than I think a lot of people who aren't used to data to do. And and thank you so much for sharing that I think that's really gonna empower a lot of people.
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Ben O'Mahony: Yeah, absolutely right. Cause that's the thing. If your if your strategy is one of those right, let's say for your argument, because I don't want to talk about the negative. Let's say it's doubling down on your your winners. Can you move more people into that? Right?
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Ben O'Mahony: You know, as a Hr leader, you might say, Okay, cool like, we have this cohort of managers who their teams love them right? And they're doing good work
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Ben O'Mahony: by some other hopefully objective metric. But unlikely, potentially right, could we get them to do some sort of mentoring? Can we bring more people into that group?
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Ben O'Mahony: And then you've got that. If you've got that measurement there of like right. This is the benchmark, for what we think is good, you know. I don't know what the net like. If you're using a net promoter score or a score at 10, or whatever it ends up being in a survey.
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Ben O'Mahony: Right? Can we get our our managers that you can show then, because you've isolated it down to the treatment as well that you're moving that number. You're saying right? We're gonna
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Ben O'Mahony: We're going to try and move more managers into the, you know, 8.6 out of 10. And above
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Ben O'Mahony: bracket, we've currently got 10%.
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Ben O'Mahony: Can we make it 20%? And what are we gonna do to do that. And if you move more people into that area, you say, Hey, look, we're we're doing that as opposed to it, just being the average moving up, and it
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Ben O'Mahony: less tied to. And I think this is another thing we spoke about in the beginning is like how difficult is to tie back metrics to like you know, business goals and metrics.
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Ben O'Mahony: And you know this is the thing it's like, if you can then follow that thread through, you know, like I said, if you've got some way of linking, say, for example, again, to make it simple. This managers in the sales org. So sales is classically a place where you can just put a dollar amount on performance.
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Ben O'Mahony: And if you can tie that back to sort of right. Okay, here you go. This is the manager. Top 10% manager in sales. This is their performance. We're linking that back to value. Now, you're like, Okay, cool.
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Ben O'Mahony: Now, if we go and take this sort of coaching agenda, we want to take these top 10% managers and ask them to coach and bring up. Some of the other managers say, Hey, look! Here's why? Because this top 10% of people who report into these managers. They are.
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Ben O'Mahony: They are now producing more revenue for the company. You can tie that back, and you can start weaving that thread of like. Oh, this is actually like one of our most critical things that we could do and kind of people know that people are incredibly important to business. That's they tend to. They tend to forget it unless you can boil it down to like a number. And that's the problem that we face constantly, I find, is just getting it to that point.
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Marion Anderson: Well, on that very point about numbers, because.
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Marion Anderson: you know, sharing kind of personal anecdotes over the years. But unless you're you know, you're in a progressive organization trained really? Well.
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Marion Anderson: In my experience, when you enter the company, there's an expectation that you know how to measure all of these things and know how to apply them, and I think many Hr. People would agree that they learned on the fly from someone else who learned from someone else who learned from someone else, but
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Marion Anderson: quite frankly brings a lot of anxiety. Right?
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Marion Anderson: and I think that that's shifting now, because we're actually able to get your hands on data that makes sense. And isn't just some random equation that someone told us to work at attrition like 45 years ago. And you know it. It can inform better those conversations that you're having with other business leaders, particularly ones that are numbers driven like your Cfo, your cru.
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Marion Anderson: I think, though.
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Marion Anderson: So we talk a lot about psychological safety, right?
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Marion Anderson: And speaking quite frankly from my position, there's nothing more terrifying and UN psychologically safe than being an sat at a board meeting and talking about numbers.
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Marion Anderson: whatever those Kpis are to.
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Marion Anderson: you know a room full of your peers, or your bosses, or your board. and
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Marion Anderson: th. There's really no th. Yes, there's a logic to it, to a point, but it actually doesn't tell you anything.
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Marion Anderson: And there's such a mismat mismatch. Sorry between the understanding of the the, the qualitative led. Cpo, quite frankly. Right. Versus everyone else in the room who's pretty much, you know, leaning into quants.
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Marion Anderson: I can think of how many times I've been in those situations, and there's like cold sweat dripping down my back because it's absolutely petrifying.
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Marion Anderson: So I think
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Marion Anderson: II am such an advocate for what we're talking about today. And we were at because we need to use data that makes sense. We need to stop using antiquated, you know, numbers that actually mean nothing that tell is nothing. Going back to an earlier point is really just ours covering right?
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Marion Anderson: What's your take on how to build the notion of psychological safety into this? Ben. I mean your product that you're developing, you know.
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Marion Anderson: on the on the. And I'm thinking, on the recruiter side rather than the candidate side.
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Marion Anderson: How do you think we can do better at having data that then supports really psychologically safe conversations amongst leadership teams.
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Ben O'Mahony: Yeah, I mean, yeah. So that's a million dollar question. Right? There's there's a lot there. I think you know. for me. I always think of like curiosity as like that. That. Right? You know it's like, and
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Ben O'Mahony: I don't think the Board Room is necessarily the time for that curiosity to be flushed out. Sometimes, unfortunately is, but that's the thing right. II like so I don't. I don't. I don't think board meeting should be run into like a very incredibly linear way. And like, Oh, here the numbers that are all good tick box, right? That's not what they're there, for they are there to challenge to see if you know the data.
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Ben O'Mahony: however, like the level of sophistication that we can do in our day to day jobs, often because of the platforms that we use and the the the lack of prioritization of building people tech. And to be fair, like, I said, the worries around really using quantitative data around what is, you know, around people which really, you know, can backfire. If that's all you look at, which is why it's very important that
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Ben O'Mahony: people understand the quality. We know why sick days are going up, because you know such and such is having a you know, a horrible time with Xyz, and that's expected. And it's not actually changed the whole organization. You know, we've just got one person or or several people going through a really tough time. And we're supporting that. So you know, it's about having that that sort of
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Ben O'Mahony: that curiosity beforehand where you go through, and and not this sort of route like like you said. looking at those numbers and that sort of thing. And and I think for me, if you get the leadership team
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Ben O'Mahony: like bought in on those bits. And like I said, that sort of that starting, it doesn't have to be well worked through. But that starting of linking that golden thread through. Talk about what we thinkively because we've seen it right? You know.
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Ben O'Mahony: people don't leave good managers. People who stay get better do a better jobs. Then, you know, we know these things like that. Yeah, they they tend to be true. Obviously, there's exceptions. But we know these things happen, tying that to like real value in a in a, in or like, even if you're just drawing a line yourself.
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Ben O'Mahony: that's where we start changing that narrative. And that's where you get
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Ben O'Mahony: the leadership team like curious and not sort of
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Marion Anderson: hey? Tell me, what's this? Tell me what's that. Tell me on this. Tell me that, you know, and and you get a bit of a better dialogue going on. That's that's my rambling on. Sorry, Danny, I was just gonna say, I truly believe that this is a gateway to help improve one. The relationship between you know, heads of people with the rest of the leadership team. If the relationships not great, and I don't mean personally, I mean, based on
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Marion Anderson: quite frankly the baggage that comes with the title of Hr. You know we, you know, be people, have P. Conceived notions, and sadly, sometimes they're right.
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Marion Anderson: and we do have a responsibility to be much more informed and and accurate on the advice and strategy that we're providing and qualities of, and quantitative data backs that up. So I think the more tools we have at like this at our disposal, and then, you know, the ability to have those really good conversations, like really informed detail, oriented
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Marion Anderson: business, savvy conversations that inform the rest of the business. It's only going to help improve
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Marion Anderson: us and the services that we offer, and ultimately the business and employee experience.
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Danny Gluch: Yeah, Marian, that's I'm glad you said that before I chimed in, because I think it it really.
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Danny Gluch: it's even also the the just, the general employee experience, right? If you're able to be like, have the transparency of, you know, you obviously have to make a lot of this anonymous. But like, here's the curve. Here's where people are. These are the data.
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Danny Gluch: And we're deciding to take this action or enact this new policy
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Danny Gluch: in hopes of affecting this, like we are. We're looking to get rid of the bottom 10% through pips and upscaling. Maybe a reorg. We are look like they can actually share some of that thoughts cause. I think, one of the parts that I've a a thread I've seen over the last couple of years in the the burn out, and the the not feeling of stability and psychological safety for normal employees is the just sheer randomness it feels for
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Marion Anderson: big decisions from leadership that affect their day to day live, and their stability as like humans on the planet.
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Cacha Dora: Well, and we've seen how many times have we seen like I'm just thinking of, like the sheer volume of Linkedin articles over the last few years, around the craving of transparency, right? And data is a great tool to actually explain things in a way that makes sense for people who are right or left, brain right? Cause we. We have these different options when it comes to how we we spin the tail. Weave the yarn. However, you wanna say it but like.
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Cacha Dora: I think that when you have that lack of transparency in an organization regardless if it's top down all the way through, only at the bottom levels. But everyone at the top understands what's going on. Wherever wherever that breakdown happens.
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Cacha Dora: people you see it all the time right? Simon's neck is like made a career out of talking about why people need to know the why they need to understand these things.
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Cacha Dora: and I think that
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Cacha Dora: the data can talk to you about that. It can help. It can make people like Marian was talking, feel more comfortable and typically pretty, pretty knuckled relationships when you can find a way to talk about it. Well, and to Danny's point, II fully agree when when you were in when you do not have a role in a company where you have a decision making control
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Cacha Dora: aspect. And you're just being told what's happening that y component
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Cacha Dora: that could potentially dictate what we're talking about. Attrition. What your retention rates look like if they're just seeing all these surreptitious decisions being made without actually truly having that lack, that understanding.
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Danny Gluch: th, the data could actually bolster that employee employee relationship. Yeah. And II wanted to maybe bring this back. Because again, the the Hr people, the people space, we're we're really good on the qualitative data. Right? If you want to talk to Danny about. What are the vibes? I will give you very accurate vibe checks without really being able to tell you why. But just like I read the rooms. Yada Yada, like right? That's the tool you are. We're poker players.
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Danny Gluch: but like the old school poker players who could like read tells. But there's also this like new sort of I don't know why I'm going into poker right now. Trust me, there's there's also this, like new wave of poker players who are very quantitative who understand all the probabilities and the odds and the situation, and and marry it altogether.
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Danny Gluch: And I feel like that's where we need to to go and and we're missing
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Danny Gluch: as as hr as people who aren't like data scientists. I think we're still missing some of that quantitative stuff. And I wanted to lean back into some of your expertise on that, Ben. And ha! What's your experience and sort of blending those 2, or taking a step more towards the quantitative that can be really useful.
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Ben O'Mahony: Yeah. And I think, it's a really, it's a perfect example, right? Because poker is exactly
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Ben O'Mahony: if you are only a bluffer or or reading tells, or you're only knowing the statistics like you're missing half of the game. That. And that's the thing for me, right is like, that's that's where you know. Certainly my career. I've always sort of thought, you know.
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Ben O'Mahony: Rather be a
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Ben O'Mahony: crap. What's the phrase like, not master of master of none of all trades. Yeah. So yeah, for me, I think there's definitely benefit in learning some of these other skill sets and and play around with them, and sort of understand more, you know, especially within your organization, learning how people do their roles.
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Ben O'Mahony: It makes your, you know, understanding both positively and qualitatively. Way better at understanding how to design that org or or work with those people.
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Ben O'Mahony: yeah, I mean, a couple of like acronyms, for we talk about which I always find funny whether, like the hippos, she's the highest paid person's opinion.
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Ben O'Mahony: That's you know, something that's something happens. Obviously worse than that is the zebra, which is like 0 evidence. But really these are these are the kind of decision making things that we're trying to avoid right where? Actually, if you can bring some sort of data to these sorts of things, then
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Ben O'Mahony: you really do stand a stand a good chance. Now I had. I had an interesting one in my last role where I was talking about communication. We had consistent problems with lack of communication. And and the the leadership team felt that they were communicating very well and
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Ben O'Mahony: individually, not in public, but individually. I reached out to all the other leaders in the engineering org. And I just did a very quick, brief search on slack, which is our primary communication of public messages
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Ben O'Mahony: that my team could see about them.
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Ben O'Mahony: and the reality was that
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Ben O'Mahony: you know, like they had, or like several of them, not all of them. Several of them had almost 0 communication publicly.
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Ben O'Mahony: So there was, you know, when they sort of came in and made decisions, and people like
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Ben O'Mahony: people would literally like, Who who is that person? I don't know who they are. What's their role, how they do. You know these sorts of things, and and and it's very easy for us to be like right. But you know
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Ben O'Mahony: I've been introduced to done all the things right, and actually just showing that stat to people saying like right? Like, just to be clear like
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Ben O'Mahony: this is your footprint
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Ben O'Mahony: of. If I was to search for stuff that you've said. yeah, like not have had a meeting with you. That's the only way. I know you. And and we were a very small organization, like 200 300 people. Right? So
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Ben O'Mahony: you know at that point, it's like, actually. yeah, E, even data like that. You can, you can make a real impact by sort of saying, like, Look, you know.
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Ben O'Mahony: I am not saying that this should be of key metric. In fact, someone who's always on slack when they should be actually strategizing and leading
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Ben O'Mahony: is is also a bad thing, right? So it's about this nuance of like
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Ben O'Mahony: what the what's the right amount. But also, like, you know, hit like, you know you. You think you're communicating effectively, and you're very eloquent in person.
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Ben O'Mahony: Here is what I here's what one of my team members sees of what you've said.
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Ben O'Mahony: and you know it's not very much so, you know II can't point to any documents you've created. I can't point to this. I can't point to that, you know. Like
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Ben O'Mahony: that's fine. None of those things are
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Ben O'Mahony: what you have to do in your role.
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Ben O'Mahony: But given these things, you should be less surprised that people don't know who you are. And and actually, that was one of those things that you know. A couple of them got it.
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Ben O'Mahony: Oh, okay, right. So like, actually, you know.
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Ben O'Mahony: while we are communicating effectively to our teams.
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Ben O'Mahony: what we're not doing is communicating to anyone outside of our direct orgs, and as always has to happen.
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Ben O'Mahony: You know you have to collaborate between Orcs for things to get done effectively. You know, no matter how.
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Ben O'Mahony: no matter how perfect the old design is, and I don't think there is such a thing you have to communicate. And and so showing like showing that sort of mirror, I think was really effective.
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Ben O'Mahony: And there's there's other things like that that you can do that.
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Ben O'Mahony: It that's never that should never be anywhere near a performance criteria for an exec right.
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Ben O'Mahony: But it is an interesting, you know, what's it called anecdot, whereas, like an anecdote, but with bit of a numerical number, right? You're like, Hey, I love that. I love that.
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Cacha Dora: Consider that. Consider that poached.
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Danny Gluch: Yeah, no, no. And I hope everyone can take that. And and I think that's where.
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Danny Gluch: Oh, man, that's it's so. We're, you know, we're running out of time. These can't be 3 h long episodes.
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Danny Gluch: Because, like little notes of of that curiosity right? Th, that wasn't a standard nor nor really, as you mentioned, should it be a standard measurement of performance or anything like that. But it's data you can search for just to be like, Hey.
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Danny Gluch: you want people to feel like they're connected and related, and in and in proximity with each other.
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Danny Gluch: Guess what
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Danny Gluch: are the way that our little Forum is slack? Why aren't you there? No one feels connected to you because you're not there. You have no presence. You're not in the office because our office is called slack. Yeah. And how many surveys have been done around executive presence? A ton of them a ton of them. And and II was just wondering.
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Danny Gluch: how can people in in the people space do a better job calculating? Roi!
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Danny Gluch: Right? Because that's well when you're talking to Ceos and Cfos cros like, that's that's their
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Danny Gluch: bread. How can we butter it a little bit?
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Ben O'Mahony: Yeah. So since kinky. But yeah, so my boss's listening.
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Marion Anderson: because,
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Ben O'Mahony: there's one, there's one thing that does like. It's very interesting. Having moved from people into data is that
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Ben O'Mahony: one thing that does really sort of cut through that is that culture idea and data people
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Ben O'Mahony: and people people tend to want a very open collaborative culture. And and and it's it makes sense right? Because they mo both tend to be slightly to the outside of the main thrust of value. You know. And unless you're literally building a product, that is a data product, it's most likely your data team is more looking at, like.
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Ben O'Mahony: you know, Bi, and and you know some other bits and pieces that are trying to give you some insights, and how you could do better, how you can market better how you could, you know, sell better how you can convert back to how you can retain better. Maybe you're looking at it actually, the org itself. So, you know, first thing I would say is like, just
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Ben O'Mahony: make best friends with the head of data, or whoever's in that that arena right? Because you have the same objectives like, they're really closely aligned. You know. And I think I think they're they're also some really same principles. When you look at data. And you look at Hr, I, one of the things that, like
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Danny Gluch: people get scared about Hr. Is is they want. They want reality like, Don't sugar coat. This like, we need to know what's really going on. And the data people are the same thing. They just want their numbers and and to devise their whatever survey and and the way they're gathering data to reflect reality as closely as possible. So I think there really is a natural connection there like you were saying.
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Ben O'Mahony: absolutely. And you know they'll help with ways of setting up your Hr systems in ways that will allow you to in the future ask more questions of it. So you know.
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Ben O'Mahony: great examples would be. And and this is really like low level stuff, some of it. But great examples are like no text fields, but more like categories. So you've got a dropdown for, like, you know, are they regretted lever or not, you know, like, because this is all of these things that are like quite annoying admin type setup things actually do have far reaching effects. If they're they're worked on overtime right where you've got like
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Ben O'Mahony: if you, if you think about like a great example, is when people leave, do you have a structured way of capturing
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Ben O'Mahony: like why, they've left, you know.
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Ben O'Mahony: Are you seeing some themes from that? Right? Like, if it's if it's all written down.
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Ben O'Mahony: or a transcribed interview.
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Ben O'Mahony: you can't really mine it for data in a, in a, in a, in an easy way, you've done them.
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Ben O'Mahony: So it's in here. And that's the qualitative stuff. Right? You can say, yeah, like, yeah, everyone's talking about salary like these, you know.
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Ben O'Mahony: Xyz stops keep pitching on stuff like, because, you know, they keep offering bigger salaries. So we know. That's the reason, you know, that's not like it's very difficult to to say to back that up with evidence if you don't do these things. But yeah, no, for sure. Like
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Ben O'Mahony: pairing with that day team. And like working on that like.
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Ben O'Mahony: can we get more data into people's hands right? And like. Then when people start using it and seeing it, they also start to care about the data quality. You know, when they start to see that it becomes something that the whole organization cares around. And it's something that's like, you start having these things like, you know, and probably not in people, because not that ethical to do
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Ben O'Mahony: a B testing on pips or something like that. That would be ridiculous. But you know
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Ben O'Mahony: something. You if you're in college, it's the excuse, right? I'm just in college. I have to test these 6 Stanford experiment kind of thing, you know. Give them this feedback. Now give them some more feedback. Now give them if you just keep telling them to give this feedback.
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Ben O'Mahony: but no like, you know, bring it back to like having something like that where you're like. Actually.
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Ben O'Mahony: you get that experimentation and curiosity throughout the organization. You tend to have more nuance and interesting discussions. And also what you do is you start to see right? Data goes from being that like, I think there's there's a sort of I always talk about that.
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Ben O'Mahony: The curve sort of understanding when it's like when you get going. You're naive. And you, you know, as everyone is in the beginning of that careers. And you're like. I know this to be certain. This is true, right?
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Ben O'Mahony: And then that's like simplicity before complexity.
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Ben O'Mahony: Then you've got complexity, and you wait in the deep end you're like, I don't know which way, up or down, and you know you you could take years to really untangle some things. It's funny enough when you go through the complexity on the other side.
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Ben O'Mahony: you tend to have kind of
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Ben O'Mahony: similar opinions you had at the beginning where you're like, hey, yeah, like, you know, the high Teno is bad, right? You know. Yeah. Like, you know, like, low, low, low experience schools are bad, like, we want people to have a good time here. Right? So it's the same opinions. But you understand the complexity there. And that's kind of that journey that not only, you know, we, as individuals, go on and every access. But it's like the org as well. You need to guide it through that way. You're like.
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Ben O'Mahony: Hey, like N, data is no longer necessary. God and log, we've got this like, oh, only will only do something if the numbers are right. You're like, Hey, we know
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Ben O'Mahony: that the data on this is gonna be a bit spotty. So we're comfortable using our experience combined with the data. And we're measuring it in a more nuanced way that says, like rather than like, we're seeing where the average goes. And it's too noisy to actually do it. We've zeroed in on one thing we're like, Oh, we think we can move this level. We think that that's gonna have a positive impact because
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Ben O'Mahony: we've linked it to Roi in some way, because we're saying like, Look, this is where the higher performers are. We followed that chain, and we found that they all have manage. They love their managers right? Okay, cool. So okay, we've got some linkage going on here. It's not
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Ben O'Mahony: perfect. But we can kind of, we can kind of tell that story. And and like everyone else, passes the sniff test. People say, yep, that kind of makes sense. Okay, cool, like, can we make more people in this in this area. Okay, cool. We're doing that. And now we're measuring
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Ben O'Mahony: our improvement along that area. And we're we're putting in some strategies to do that.
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Ben O'Mahony: Then you then, you're like, right? Okay, cool. And you do that for a number of quarters. And like all of a sudden, you have a much better.
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Ben O'Mahony: much better leadership team conversations. And actually.
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Ben O'Mahony: people are like, right, you know, okay, cool like, this is what we're trying to do. Increase. It's just like, well, I'm a leader in this organization at this leadership team.
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Ben O'Mahony: Well, how do I make sure more of my people are in that top 10%. I want, you know, I want people to see how other people in my world to be very happy. You know. How do I? How do I help on this journey, and and you move it from like a a people objective into a company objective. And then that becomes like
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Ben O'Mahony: really powerful for me. That's that's how I think about it. I love that I love that. I just want to move us towards wrapping up. I love that you in in that little
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Danny Gluch: answer specifically talked about it being a journey.
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Danny Gluch: And II want to give everyone who's new to this and who hopefully, is excited by this, but maybe a little scared that it's okay, that it's a journey. You're not gonna be great right away, right? You're you're you're still a rookie, or you're you're just getting getting a little bit better in data.
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Danny Gluch: And I also love that curiosity right like, be curious about the full distribution, not just the average. What are the stories behind those. And how can you, you know strategically, then address that like, what? What are? What's your actual strategy gonna be in addressing this distribution of am I gonna focus on the the outliers on the low end or the high end like.
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Danny Gluch: don't just be like, oh, well, we're gonna make the average better. We're gonna make it go up into the right. But like, actually, how are you gonna do that strategically, and the numbers can really give a lot of transparency and psychological safety and stability and predictability around those decisions and policies. And I love all of that. I would like to go around the room. Ben, I'll let you choose. Do you wanna go first or last?
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Ben O'Mahony: Yeah, no, II was just gonna say, that really reminds me like again, like one of the best resources for this like kind of strategy framework is like good strategy, bad strategy. And it talks about like a diagnosis, and then a prescription or treatment, and that's kind of that journey of of going on those sort of things. But yeah, so sorry. Yeah, I don't know. I've
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Ben O'Mahony: hijacked it again. No, no, no, I would. I was. I was literally just looking for an amazing little nugget like that. Is there anything else you'd like to add before we go to caution, and Marion to wrap up.
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Ben O'Mahony: Oh, no, you know you put me on the stop. No, no, we'll let you go last. Kasha. What? What are some of your like final thoughts as we as we wrap up?
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Cacha Dora: You know, I think I'm thinking I'm in this conversation. I've thought really heavily about what the experience looks like for people who aren't familiar with using data. Right? We're so in that qualitative space that the quantitative seems like a really big mountain, and I think that
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Cacha Dora: there's so many amazing things that Ben has said to really, I think, help Le bring those fears down and help to continue to take a look at the big picture and start to isolate little things. And I think that as we in this space
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Cacha Dora: have that opportunity, we'll be able to tell better stories with data. I think that's really important.
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Yeah.
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Marion Anderson: Marian, yeah, I mean for me, it's it's that
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Marion Anderson: Cpo relationship with the rest of the business and being able to find commonality and really
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Marion Anderson: together, work together on that quote and quant data and do good work right? It's not a battle. It's not you against them. You're a team. You're doing it together. And you know the fact that that data is going to be is here, and we can leverage it to make all of our lives easier, and ultimately give the employee a better experience.
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Marion Anderson: I'm here for it.
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Danny Gluch: Last thoughts. Ben.
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Ben O'Mahony: yeah. I mean, I think, yeah, sure realize what you said. They're around like taking away the the sort of fear from it. And I think you know, there's a classic situation of like.
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Ben O'Mahony: everyone thinks someone else
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Ben O'Mahony: has work this out, you know. They haven't, you know. And you know you can go like the best thing for that for me, I find, is like, meet ups and events, and you go. And you're like, like, have you done this? And they're like, no, we want to. We've been thinking about it. We've been talking about it. We've not got that, you know.
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Ben O'Mahony: And you just realize right. Okay, cool like you. You don't have to be. You don't have to have know it all to to start the journey, you, you know. And really there isn't an end. You know, this is just your career, right? So you know, like sometimes that growth. It looks like a brick wall in front of you. But that's actually when the growth curve is like
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Ben O'Mahony: at its highest, and you're learning the most when it looks like you have no idea of the way forward, but actually the the ways up. And you just need to just keep at it breakthrough. So yeah, like for me. It's about these little you know, these taking those baby steps, and you know, soaking up that that,
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Ben O'Mahony: you know, like you said, be becoming best friends with the head of day soaking up everything that they do. And you know, collaborating with them. And and I think, yeah, you'll find that everyone's interested in this sort of insights that you can bring once you start going down that journey.
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Danny Gluch: Wow! Well, thank you so much. This was an amazing conversation. I hope everyone feels just ready to go and measure everything. One thing I would like to measure is how many 5 star reviews we can get on itunes and spotify, be sure to like, subscribe, leave a review. You can contact us at elephant@thefearlesspx.com. Remember, we have episodes posting every Wednesday.
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Marion Anderson: Anything. I miss Kasha Marian, on that one sounds perfect
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Danny Gluch: anyways. Thank you again, Ben. You guys can find them on Linkedin. Check out jobs, Asi, and you'll see links and things in the show notes. See you next time, everyone. Thank you.
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Ben O'Mahony: Thanks. Sit up, cheerio.
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Cacha Dora: Thanks, Ben.
