The Blend Podcast
The Blend Podcast
#9 Data-Driven Learning
Brendan welcomes special guest Anja Hartleb-Parson where they discuss the role of data in eLearning and learning development.
Welcome to the blend podcast with Tom and Brendan discussing all things e-learning digital marketing, design and entrepreneurship. The podcast is brought to you by blend interactive content. Find us on LinkedIn or www.blend.training.
Brendan Cox:Hi. So welcome to the podcast. In this episode we stuck Tom on the bench. And instead we're going to do a bit of an interview. So we thought we'd speak to someone with a bit more expertise. And obviously data is a massive thing now and with elearning moving in the direction is going in knowing why you're doing something and being able to check if it's working right is more important than ever.So we thought we'd speak to a data specialist. And so today on the podcast, we're going to chat to Anja Hartleb-Parson and find out a bit more about what she does her sort of background and the way she sees the industry going. So, hi Anja.
Anja Hartleb-Parson:Hi.
Brendan Cox:How you doing today?
Anja Hartleb-Parson:Pretty good.
Brendan Cox:Good. So you're you're over in the US at the moment? Yep.
Anja Hartleb-Parson:Yeah, I'm in the Midwest.Close to Chicago. It's very cold and snowy.
Brendan Cox:Yeah, everyone's got problems with the weather at the moment. It's been crazy. Yeah. So tell me a bit about yourself. How would you describe yourself as a data specialist?
Anja Hartleb-Parson:So I guess I'll back up a little bit. So you know, the background. I actually did not start in data, per se, until maybe about a few years ago, I originally went into, I graduated with degrees in philosophy and psychology and political science and Organisational Behaviour. So, so yeah, that's a lot of education. I know. But what I was doing, originally was actually building startups and startup nonprofits to be precise. So I worked in a lot of different areas, which is sort of the nature of startups in general, you know, you just have to have your hand on everything, because they're just never enough resources. Yeah, you have to have a lot of hats on. Yeah, exactly. And the, the nice thing, you know, apart from this just being very suitable to my generally very diverse brain and skill set. The nice thing is that you just learn a lot about different areas, in business or in organisations. And so what always intrigued me is the people, the people development piece. And so that's not just human resources, per se, but the training and development piece. And I did a lot of training in my previous roles. And I do that right now, as well. And last year, I kind of wanted to go start looking back into training roles into learning and development roles, because I was really maxing out my potential and what I'm doing right now, which I'll explain in a minute, but the learning and development field in and of itself with a community was fairly new to me. Even though I had done a lot of training and my my other jobs, and as I was completing graduate education and data science, I poked a little bit into the data aspect of l&d and realised that I kind of poked the bear there, it seems that data in particular and learning and development is is kind of part of the challenge for learning and development. Yeah, and I thought to myself, well, while this is kind of for tourists, since I just, you know, got more education and data, and I've been really fascinated with data for a while. So that's been the pivot that I've been trying to make professionally out of what I'm doing right now, which is mostly Professional Services and in the financial realm. So anyway, so that's kind of the short background of that.
Brendan Cox:Okay, so the, with what you do in the life financial realm, I'm guessing, because it's, it's a lot more data driven at this point. So there's a, there's a lot more of a kind of established role for data analysis and things in that?
Anja Hartleb-Parson:Yeah. So in the round where I am at, which is mostly sales support, and programme support, it the data is focused primarily on on sales efforts on marketing efforts. And then, of course, lead generation, etc. So, you know, those areas in general are fairly well established when it comes to data, for obvious reasons. Yeah, but the training area, you know, which I also do, I, you know, I train financial advisors, and they train banking staff, on the flip side really doesn't have very good data. And so, you know, I would run into these issues of, you know, training people, and not really knowing whether what I'm doing is really taken hold or unit, the methods that I'm using, for instance, or what really the impact is, I mean, you can see it a little bit in terms of, well, is this advisor getting up to speed and generating new business. But yeah, it's kind of a grey area.
Brendan Cox:There's no Yeah,
Unknown:exactly.
Brendan Cox:They sort of, say a great course, thanks for that that was really entertaining. And then you don't get to find out how much is actually being? How much difference is actually tangibly being made? The funny this is, what you'll have done might have made a massive difference. But it's not the proofs not there. So it's, it's always a bit kind of a guess as to how much impact you've got at the end of the end of the day kind of thing.
Anja Hartleb-Parson:Yeah, it's there. But it's also the fact that training is kind of seen as something I don't know, that must be done. And it's sort of tangential, and it's not really seen as a strategic piece. So, you know, when it comes to wanting to improve data collection and data analysis, that's not where the resources go.
Brendan Cox:Okay, yeah, cuz we did notice a lot of work from our side of it, when we were exploring things like compliance. More often than not, people are just trying to mitigate risk. So they, what they want to do is just sort of do the bare minimum to make sure they don't get in trouble. And so they're not really going to want to spend more money than they have to. They're just want to get they want to just get the job done in the cheapest way possible. And yeah, whereas some other types of E-learning, everyone's a bit more interested in making something creative out of it, but with the compliance stuff, it's always a bit like, like, just what's the lowest you do on this? To get us past the kind of posts? So I can Yeah, I can imagine them sort of being open to spending more time analysing the data. They just went? Well, no, we don't need that.
Anja Hartleb-Parson:Yeah, that is very true, the compliant piece of sort of massive in the financial industry. And, you know, a lot of the course learning you might say that takes place is centred around compliance, and a lot of it is extremely tedious and very poorly designed. And you know, when I asked the question, well, what impact is this actually having on compliance? people sort of shrug their shoulders and well we just check completion rates because that's basically what we need to report.
Brendan Cox:Yeah. So was the the the subject matter itself one of the reasons that you wanted to change or was it more just it's because it's a you can it's like a new pond that's got not as many fish in it.
Anja Hartleb-Parson:Well, it to it both of those things. I mean, the the people development piece has always been a very big part and a professional passion for me. And combining that with data, which is also something that I'm extremely passionate about, just from an evidence, evidence point of view. In other words, do we have actually evidence? Do we actually have evidence for what we're doing? So that's always been big with me. But, you know, figuring out that L nd D is struggling with data was sort of a fortuitous event, I didn't realise that just, you know, till Silly me is thinking, Well, you know, we spend a lot of money on training, we sure sure would be having good data on whether that's a good return on investment. So I was, I was a little surprised, speaking to a lot of people with way more experience in the lmd space than I have complaining about this piece. And actually also getting really excited that someone comes in, and Hey, can I help you out with data?
Brendan Cox:Yeah, totally. I mean, I, from my background, in animation, there's the same sort of thing you'd like we make a tonne of content. And it just sort of gets sort of burped out onto the internet and disappears. And it's amazing how much money is spent on content that has absolutely no metrics attached to it. And yeah, you just kind of go, Well, you spent all this money. What was the point? And yeah, I think that was one of the things that we found about the the, it feels like the eLearning, the learning and training sector has got so much room to grow. And so much enthusiasm for embracing kind of like, oh, let's get let's get cracking, especially with sort of a change in in with COVID, and working remote and all this kind of stuff, that maybe it's kind of going to be a bit of a renaissance with the business side of things. So having more design, having better quality design, better analytics, all this stuff that's traditionally in the business sector is now coming into the learning. And it's like, yeah, there's lots of lots of potential.
Anja Hartleb-Parson:Yeah, there is definitely a lot of potential. But I, I do see the movement to be fairly slow. So you know, someone like me, who goes on the job boards and looks for data analyst roles in l&d is not coming up with a whole lot. Yeah. Anyway. So, you know, that's, that's a bit. You know, organisations recognise that they need to expand that capability. But, you know, they're not really putting resources behind it quite yet. Or they do kind of have the thing where, you know, we, we want it, we're going to hire instructional designers are learning and development specialists who are also really good at data. And well, I'm not sure that's going that, well. It's just for one thing, data in itself is usually a full time job anyhow, buta lot of people go into l&d because they want to create learning, you know, and that they they're not I mean, yes, they want to know whether their learning actually has impact. Most of the time. beyond the usual, oh, I enjoyed this course evaluations. But the data piece, in particular, getting good at data analysis and figuring out a good way to approach and analysis of data is a skill set in and of itself that requires experience.
Brendan Cox:Yeah, I think the thing is, is that like, especially with things like instructional design, and things like that, it's like a quite a fluffy term that could include almost anything to the point where they're like, oh, yeah, and a bit of data. And a bit of this, oh, and a bit of development, can you put some aid, like augmented reality and VR in there as well. And I think that, that mistake of like you said, just kind of tacking it on as a, as a little side skill is, is not really making the most of it, because it's kind of, it's a bit crazy, because it's basically like, at the beginning, you have a goal that you want to do. And then you do the whole project. And you never kind of come back to working out if the goal was achieved. And so it's like, data is such a boys this this the, the other side of the sandwich, it's like you need both bits. Otherwise you don't. Why did you don't know if it was a success or anything? So
Anja Hartleb-Parson:Yeah. And, I mean, maybe if you want to ask some more of your questions, that'd be fine. But I do have my own thoughts on on that?
Brendan Cox:Yeah, it's Yeah. Go ahead. Sorry, what do you think? So how do you feel about it all? In terms of
Anja Hartleb-Parson:How do I feel about it? So I mean, in I tend to be pretty blunt about, about stuff. So I don't want to step on anybody's toes. But what I'm seeing from the outside is, the first problem that I see is kind of a fixation on on tools. And I find that is not uncommon generally in most business domains. But it's, it's sort of this. So just even if you're looking at instructional design or l&d specialist job descriptions, you know, must be proficient in X, Y, and Z authoring tools, and this LMS or LSP, as they're now called. Andi t's sort of the the latest, the latest fashions when it comes to learning design. And that focus in and of itself, to me is a bit problematic, because the tool is just the tool. The question is, what do you want to achieve with it? And are you achieving that, and that's really where you need good data. And speaking to LMS in particular, you know, there are loads of vendors out there. And of course, they're marketing themselves in the talk a good game. But if as an l&d department or a training department, you don't have a clear data strategy, you're just looking at it as a shiny object, and oh, look, they can say they can track this, that and the other thing, the question is, is that useful for you given that you want to actually create impact on business goals on KPIs, etc, with your training. So I guess it's nice to know that your trainees are watching videos, you know, 95 to 100%, all the way through, but that doesn't tell you anything about whether they've learned. And so that this sort of, I'm going to be blunt, this tool fetish is a little disconcerting to me, but it's, you know, it's something that a lot of business domains struggle with. But the other piece of that, is that if, and I think this might be the more fundamental question is how you're perceiving l&d and training in the organisation in and of itself. And I find, at least from what people are telling me that a lot of times, it's still viewed as a cost centre, as opposed to an investment centre. And so leadership, you know, they're looking at lmd as a cost, and they want to contain costs. And so what, you know, if you're looking to get more resources, that that is your first barrier, so to speak, to convince people that this is a good thing to spend money on. But then you're also not reporting the things that might influence leaders to look at what you're doing, it's more of an investment. So if you're not really able to report impact on business goals, or in KPIs key metrics that the business is interested in, then, you know, your seat at the table is going to be a lot smaller. So you know, a lot of this follows on to perspectives within the business on l&d and and what role data should be playing in particular.
Brendan Cox:What kind of what sort of stage would you traditionally start being involved on a on a project? Do you start as early enough in the project as you think you should be? Because that's one sound, depending on what the job is you're doing? Yeah, often, you're never quite in at the stage that you want to be, or would be optimal stage to be in?
Anja Hartleb-Parson:Yeah, that's a really good question. As I said, I'm trying to pivot into these roles. And so right now I'm doing basically a lot of free advising. And I find that usually the strategy for data collection, that piece isn't established early enough. And so when you start with a learning project, and you're looking at, okay, what is actually the problem that we're trying to solve, or the need that we're trying to address? You're already falling short, sometimes on on data there. So it's like the some, you know, if your internal MD, some manager from a department comes to you, and says, Well, we need a course on this. And then you start poking a little bit and wonder and ask, why do you need this course? What do you think? Well, our people are, you know, not strong on this particular piece. It might be a soft skill, for instance, or it might be even something more hard skill related, like in sales, they're not hitting their numbers, for instance. Or they're not using the new CRM system efficiently, or whatever it is. And so then you ask well, okay, so how are you seeing these things? What makes you think that these are the problems? You get opinions and not hard data. And so that, that that's a starting point, that's already problematic.
Brendan Cox:Yeah, you already going off course before you even start.
Anja Hartleb-Parson:And then, as a lot of seasoned instructional design designers know. The problem that is being asked of you to solve isn't always the problem that actually needs to be solved. Yeah. And if you don't really have good data, then getting to that actual problem that needs to be solved, it's going to be a lot harder. Yeah, and I mean, sometimes it's an issue of, well, you know, that department isn't really good at tracking data, or the right data anyway, or, you know, people have preconceived notions and their own assumptions about what the problem is. And so that's, that's what they tell you. Yeah, so the starting point is often an issue already.
Brendan Cox:Yeah. So do you find? So do you find that soft skills play quite a role in actually getting them to, to bring in data, or like analysis at the right time as well, as well as the soft skills involved in extracting that data and putting it across? How many? How would you say that that kind of the sort of overlap between analysis bar, and by soft skills? Can you give me an example? What are you thinking of? But like the communication, the kinky communication aspect, the basically the psychology of the people that you're not just, I suppose it's actually is twofold? Because you've got the psychology of the people you're trying to analyse, but then the psychology of the people that you're analysing it for? And so, like you said, is that they're not actually you're educating the client about the importance of data at the same time as using the analysis as the job, if you know what I mean? Well, I was wondering, kind of how do you how do you sort of see this that sort of side of it? The Psychology part?
Anja Hartleb-Parson:Yeah. So I try to do my best not to speculate too much about what's going on in people's heads. But you know, you can't really escape that sometimes. I do, I do find that. And this is just my experience. A lot of people look at training or learning as a good in and of itself. And this is more so I see this more in higher education than then in business, but generally, in you know, when you have that approach, that it's in there is an intrinsic value to learning and I'm not disputing that there isn't that I'm not disputing that there is but when you approach it from the perspective of, you know, learning in and of itself is good. And, you know, it doesn't necessarily need to be justified with data. It generally leads to activities that aren't measured in terms of return on investment, and are not measured well enough. And so, or at the very least inefficient approaches to learning. And so, you know, that mindset sometimes is you kind of need to uncover that and combat it a little bit, it's easier to do that in business, because the business businesses generally are concerned about the bottom line and the cost of things. And more so. And I'm not saying that institutions of higher learning are not but um, you know, things are a little bit slower, as we know, in the, in the higher education and government, Rome. And then you also have the fact that you've got, you know, somewhat at least from a perception point of view, unlimited coffers, you know, because, hey, we can always tap the taxpayer. And so that's not the greatest basis for developing effective learning and training. That's my opinion. I freely say, I'm that's an opinionated opinion. Yeah, I think the thing is, is that education has everyone is in it, because they want to help people and share knowledge and things. And sometimes the focus purely on that, yeah, they do miss setting goals properly. Yeah, the goals mean that it's difficult to get data. And it's like, we feel like we're doing a good thing. So you don't measure it as much. Yeah. So. But in terms of your sort of interests, then so you, obviously, psychology and your background and stuff like that? Would you apply data analysis to softer skill training and things like that, as opposed to something like sales training? That's a really good question. And it is definitely a big topic peak, because it's soft skills are much harder to measure, in many cases anyway. But I think the approach there that I find more helpful is to not let the perfect be the enemy of the good. And so if we are looking, for instance, I'm just going to give an example. piece that might be easier to understand. So let's just say we're looking at our employees experience and job satisfaction. And we recognise that leadership, you know, so for instance, the role that the department managers play is, is pretty important. And we we have pretty good research from many decades as to what leadership skills are generally effective. Yeah. So if we, if we do surveys of our employees of what their job satisfaction is, or we go more specifically into if they think their department leaders are good leaders, then we take that as a baseline. And if we're seeing the nominee, if we're seeing results that are not very encouraging, or where to us definitely room for improvement. In other words, job satisfaction is, you know, is fairly low or too low anyway, then we develop training based on the leadership skills we think are lacking. Just you know, this is where when you establish your baseline through through surveys, you know, you would you would be looking at how employees are assessing these particular skills in their in their leaders. And of course, yes, this isn't pure objectivity. I mean, it is certainly subjective. But nevertheless, when to have the, the, the baseline and then you Institute training, you can then again, perform the same measurements and see if the needle has moved. And while these qualitative assessments like surveys are certainly more subjective, and it's not the same as quantitative, quantitative data is still good to do that, I think provided that the tools you're developing for that are very well developed, of course, you know, we all know the pitfalls of surveys and survey design. And so, you know, that's, that's where you have good data people. Good. Let's just call them instrumentalist. And then, in other words, people who can who have experienced developing qualitative instruments. Yeah. And so you can then from that, see, you know, training seems to be moving the needle and this particular aspect, or it's not moving the needle. Granted, you can't attribute 100% of that movement to training. Because there are always other factors. But that's not what you're trying to do anyway. In, in, obviously, it wouldn't really be a good use of your time to do that. You know, so what you're doing when you communicate your results is kind of hedging and saying, look, this is what we're seeing there is movement, and we think that training has definitely played a role in that. And that way you can you can justify, or at least you can tell whether you've designed good training or not. So that's the way I would approach soft skills in general. Yeah, so I guess it's kind of like you're measuring, you're moving the needle, but you have less of this, there's not a dial of numbers on the go around it, but at least you're getting a sense of you moving in the right direction is positive. Yeah. And, you know, I think it's also good to remember that that's often the case with hard skills to you know, sales training is not going to be the 100% effect on the sales numbers, either. There are other factors that always contribute to the numbers that you get, as a salesperson - any salesperson can tell you that. It's not just the training that matters for them, whether they, you know, meet their goals. So, you know, even when we're measuring these hard things, we, we always need to be mindful that training isn't the only the only variable.
Brendan Cox:Yeah. So what kind of, obviously, everyone's starting to realise data plays a bit more of a role in the learning process? What's your what's your kind of your sort of predictions for the kind of the future? Have it? You said, it's moving, but moving slowly? What kind of things are you seeing?
Anja Hartleb-Parson:So what I'm seeing right now is an actually, this is something I been monitoring a little bit for the last, I don't know, decade or so, when you look at human resources, in particular, human resources is getting better on the data piece. It's not where for instance, sales and marketing is or supply chain, or these as a big, big business areas, but there is definitely movement in the right direction. and human resources in particular is a head of, say, training and development, I would say. So I think once we, I guess this depends on organisations, you know, sometimes training is really integrated into human resources into that function, sometimes it's not as much integrated. There may be data sharing issues there. You know, some of the time. So once that improves, I think, and we are not just looking at human resources as more of a strategic capability and an investment. You know, and again, I said that mindset has changed. I think definitely over the last decade or so, from what I've seen, and we apply that same reasoning to training and development in particular, the movement will hopefully be faster. I think with a lot of the technology being developed right now, I do fear a little bit that you are applying bulldozers to things where you haven't even managed to shovel a hole. So we need to be careful with that. You know, everyone is kind of looking at AI as a next thing. And someone who's trained in machine learning algorithms and AI,I can tell you it's not a panacea. And there, you know, there are definitely a lot of things that need to be carefully worked out before you can more generally apply AI to various data issues. But, you know, technology in and of itself is moving pretty pretty quickly as it always is. And I hope that that is something that l&d will further take advantage of to really develop the data piece in and of itself. But it all kind of depends on whether l&d in general says, you know, what, we actually need data analysts on our team, not just, you know, that person that we borrowed from, and, you know, two doors down, and who has like, two hours to devote once a month? Because they also have, you know, a regular job.
Brendan Cox:Yeah, so I guess that's the main, the main challenge now is educating the educators of the importance of investing in data really?
Unknown:yeah.
Anja Hartleb-Parson:And again, you know, like we've been doing in human resources, where we're hiring people on the data side and human resources. I see much more, just looking at the job market, much more movement there. So there are certainly, if you wanted to get into data and the people development space, there are many more opportunities in HR than in training in particular. But so you kind of have to, I think, that's what I learned anyways. You know, take one step into it, and then pivot from there again, possibly. You know, which is a little bit frustrating for people like me, who are very impatient and just want to solve the problems they want to solve.
Unknown:Yeah,
Brendan Cox:I totally empathise. We mean, Tom are the same. We basically have pivoted multiple times in the last year, and it's just a thing of is, it's just a massive landscape for learning. And we're realising that maybe compliance isn't the place for us, maybe, actually storytelling aspect needs to be is more of a thing. And then we're finding out analysis at the beginning is actually what we're good at. And so yeah, I totally get it. And we're super impatient as well. So it's that thing of just like, I want to find my or you want to find your perfect sweet spot in the, in the learning community.
Anja Hartleb-Parson:Yeah, yeah. So, um, and there are certainly people I would say, you know, recognised voices in the community, they've been a, you know, pounding the data drum for quite a while. And, I mean, a lot of them I see actually, they're, they're, they, they're independent consultants. So they work with, with clients, and I don't see too many people who have a full time job within an organisation. But, you know, that's kind of, at least the the folks that I've talked to seem to a lot of times have gotten into it, and they basically had to start from scratch. And, you know, that's kind of what happens when you're trying to get a new capability launched or made more visible within an organisation. So I also talked to people have also talked to people who are you know, they're trained in it seasoned instructional designers are learning developers and so on, so forth. And they are just used to, when it comes to data, we're, you know, we're just reporting this, the level one and two, if we're taking the Kirkpatrick scale here, the Kirkpatrick Patrick model, and there used to not really being asked for much more, they might be interested in reporting more or looking at data more deeply, but It's sort of a thing of, well, if you have time in between projects, and of course, that never happens. Yeah, it's like on the would like to have someday in the distant future list in many cases.
Brendan Cox:Yeah. Yeah, I think it's gonna be, it's gonna be interesting. Once you spit, it's a bit like the Wild West at the moment. But once everyone's starts to find their footing with everything, I think that like, they're going to be like, actually, we should take this seriously. And I think like, you say, the people that are banging the drama already. They're gonna be, they're gonna there's going to be more and more proof of how valuable it is. And then didn't just bit by bit, and then yeah, it's gonna be interesting.
Anja Hartleb-Parson:Yeah, and the, you know, I'm not sure if this is true, but my, you know, just thinking about it, logically. It the larger organisations might be leading the charge there. And that's probably purely a function of how much they spend on training and development. You know, if you have a multinational with 50,000 people, I mean, you're spending millions and millions of dollars every year on training. And so, it Yeah, that's definitely something. But then again, you know, I mean, you know, there are certainly companies that, you know, just have accepted that that's just what they spend. And so I don't want to say that that's necessarily true across the board. But smaller organisations, you would think that having to be scrappier would, would turn the focus more on return on investment, and I want to say, return on investment sounds kind of so cold and calculating. But it's not just saying, Okay, let's look at what we spend in what we brought in, and then take the difference. I mean, return on investment is to me anyway, it's, it's more than that. It's, it's, it's a richer concept, you know. So, and oftentimes, it it's, it's not that easy to measure when you're looking at soft skills, for instance, you know, you do end up making some estimates about what the actual dollar impact there is. And yeah, so it's not a perfect measure, anyhow.
Brendan Cox:But, yes,
Unknown:no, go ahead.
Anja Hartleb-Parson:I was gonna say it's like that thing of, like, measuring happiness for people. It's a bit tricky. But then there are things like you say, where, even if you're measuring your kind of staff turnover, it's not got a number, maybe you can't, it's not going to be 100% down to it. But if you've put the effort into improving the soft skills of the management, and recording to their forms, everyone's a bit more happy now. There should be less people leaving. Yeah. Yeah. So we tend, yeah, turnover, retention, those, those are definitely things to look at, I think we have a pretty good establishment of engagement as a measure. And we know that engagement impacts productivity, and it impacts on employee experience. And so even looking at that, from a return on investment perspective, makes sense to me. And then, you know, you look at something like sick days, you know, just the number of days that people are not at work, but you're still paying them. And, you know, it's it's a reasonable assumption, that when you have a lot of people taking a lot of sick time, it's not that they're all sick, that maybe they're, you know, kind of burnt out, not really enjoying what they're doing. But really what you're looking at so, so that's kind of the thing to to look at what what things are already being measured in other departments, and how can we tie reasonably tie training to that? So the exchange of measures of numbers of data instruments, etc. is really important there so that your l&d department isn't starting from scratch. And sometimes that's really part of the problem, right that you know, you kind of exist in a vacuum when it comes to data and you know, your marketing and sales area. Or your human resources, folks are not really sharing data. So well. That's not good place to be on.
Brendan Cox:Yeah, I suppose that's the thing is near the bigger a company gets, the less the more communication internally becomes a problem. And what one person knows is common knowledge isn't someone else's. So yeah.
Anja Hartleb-Parson:So as an undergrad, I studied philosophy and psychology. And then in graduate school, I went to focus on political theory, political philosophy and biopolitics. And the biopolitics area is, is sort of a hybrid field of philosophy, psychology, anthropology, sociology, neuroscience, biology, I mean, it's literally everything thrown together to look at human behaviour, and how it has evolved, evolved over time. So that really kind of shaped the way I was starting to think about why humans are doing the things that they're doing, or at least trying to analyse those things. And what's,you know, out of those things come things like behavioural economics, for instance. And it's just absolutely fascinating to me, as we look at those things over time, but at the same time, we are also seeing that human nature is quite enduring, in that it doesn't really change much over I mean, our circumstances change, right. And we have, for instance, more access to technology, and all of those things, but the principles of what drives human human nature, a pretty fixed and not very malleable. And, and I think that...I'm not a behaviourist in this in the BF Skinner cents, because I think that's a little myopic from an analysis perspective. But I do think that this behavioural piece is really important to understand and where it's coming from, and what is driving it. Because otherwise, you're just trying to change people. And effect changes in them that are very hard to change are next to impossible to change. And I mean, you know, if you want to talk political, we know that engineering human behaviour leads to very disastrous results. Anyway, that's kind of how I got into the Organisational Behaviour piece. And from a data perspective, that's definitely something you can you can measure more easily, but you do need to understand why you are measuring it, and what it actually tells you, you know, in the end, so in other words, your interpretation is just this map. And the limits of your interpretation are just as important as the approach you're taking to measurement.
Brendan Cox:So it's a kind of, I suppose, it's a thing of some people like to look up at the sky and imagine the universe and some people look up at the sky and get freaked out that maybe aliens are gonna come and get them and they just sort of put the head back down. There's that thing of dislike humans, we all kind of, we get stuck in the moment, and we don't step back from stuff. And I suppose the data side of it is like, is stepping back and seeing the bigger picture. And like not Yeah, reacting to things instead, actually observing them properly. Like a scientific approach.
Anja Hartleb-Parson:Yeah, it is that, but it's also hard. I don't like doing hard things. I mean, how many people are making new year's New Year's resolutions to actually start exercising and eating right? So when we need to do hard things even though we know we need to do them. That doesn't mean that we're motivated enough to do them. And that's, that's a big piece of the puzzle. You know, human motivation in general. How back to human motive. I mean, you know, the ancient Greeks have already wondered that, and I'm not sure how far they got. So it's, it's very complex. I mean, we're dealing with human beings. And granted training and development has recognised that learning is more than just, you know, pumping knowledge into people. And that light it is, that's why it is it's a complex thing to measure. But that's where I was saying earlier, don't let the perfect be the enemy of the good. You know, you can do some things, and you should do some things in terms of measurement. And as long as you have the caveat of, well, we do realise there are other variables, and we can't measure every possible variable in this to ascertain the impact of our training programmes, but we're doing something, and we're getting some idea of whether it's effective or not effective, or at least where we need to make improvements. And so you need to it's sort of how you set the goals. Right? You know, they should be ambitious, of course, but they shouldn't be unreachable.
Brendan Cox:So that smart goals thing. It needs to be it needs to have a logic to it and not kind of just go, oh, we're just gonna do it. It'd be great. Anyway, okay. It's like, there's no way that we could do this, or there's no way we can measure this, or there's no way that it actually helps is, it's funny how much we just kind of we get enthusiastic about the ideas of things and forget to actually make the work.
Anja Hartleb-Parson:Yeah, and I think it's good to have big ideas. I mean, there's no doubt about that. But I do think sometimes we get stuck in this, well, if we can't do that, then we won't do anything. And I'm not sure that that's always the best thing to look at it. The best way to look at things either. So, you know, anyway behaviour, tells you some things, it doesn't tell you the whole story, of course. And that goes back to the point I was making about quantitative versus qualitative. That we do need both, and we should value both types of analysis. Anyway, I mean, it's just all very fascinating to me at the end of the day, and I just get very nerded out about it. But I also get very frustrated about it as well, because I, I'm passionate about it.
Brendan Cox:I think knowledge is always a burden. Because you basically, the more you analyse stuff, the more kind of holes that you see in things. And the further you sit back from things, you can see the errors of stuff. And it's like it is frustrating, because you want to be able to fix everything, but you can't if you actually look but the general idea is as long as you're going in the right direction, you can be happy with what you do kind of thing. So yeah, being too self aware is almost a burden.
Anja Hartleb-Parson:Yeah, it's a curse of knowledge piece.
Unknown:that makes
Brendan Cox:I always don't I always paraphrase it completely wonky. But the gist of it. Yeah, knowledge is a burden.
Anja Hartleb-Parson:Yeah, it makes sense. That's why we kind of should be looking at people who don't necessarily have l and d experience in particular. And I know, that's not how the job market works. But you know, when you have people who are coming from different areas, and from very different perspectives look at what you're doing, they might be able to tell you, you know, this doesn't make as much sense, as you think it does. Of course, you would be saying it way more diplomatically than that.
Brendan Cox:Totally. You know, it's like Silicon Valley, when they've got the Guru's come in to help the CEOs and they do it from a completely different perspective, or they get the CEOs go off and go on a retreat where they do our Ayahuasca and have like a trip that then balances out the business side of them. But that's what I find really interesting about what you're doing because you're basically you're driving to understand people, but you're coming in from a behavioural side, but then also from the truth from the data side as well. So it's like, it sort of balances out the, the kind of the lenses that you're looking at it from.
Anja Hartleb-Parson:Yeah, another way of putting it would be, you know, when we're looking at the behavioural piece, we're looking at the behavioural piece, but we also know what it's not telling us, or we, at least we should know, and be aware, and have some humility about what it's not telling us. So the same goes for data, you know, we look at data. And it's telling us something, but it's also not telling us something, and we need to be very aware of that. I mean, the the opposite of people being too data driven is also a problem. And, you know, I haven't seen that problem in l and d. Yet, maybe it'll be a mark of, of progress if we ever get there.
Brendan Cox:Yeah, the thing is that humans have a tendency to swing out like a pendulum. So if you're all in wonder, like, like, we're not gonna do anything on data, now we're gonna analyse everything. And then it's like, No, that was too much. And then eventually, you find the kind of slowly swing back and forth. It gets into the middle. But, I mean, how if we end up having too much data in l&d, then that at least we're going in the right direction.
Anja Hartleb-Parson:Yeah, yeah, that's true. I think that's the part about when you're hiring people in data analysis that you need to be very aware of. So I think we kind of tried to talk about this earlier. But then I got off on a tangent, which is the communication piece that you mentioned. Data analysts, you know, can be extremely skilled and highly technical. But that's not going to help you very much if they can't communicate to you what the bottom line is that data? In other words, what, what interpretation we should take from that and what we shouldn't take from that. So I think that's a soft skill for data analysts - they definitely need to develop if they haven't already anyway, or that also needs to be taught when in data analyst programmes. And I luckily, kind of developed that skill on my own. But I will say that in the data science programme that I just finishing up, the focus hasn't been so much on that communication piece. So I worry sometimes that when you're hiring people who are very technically talented and skilled, how that's going to affect you in terms of what you what you can take away from the data. And particularly, communicate to your stakeholders who often don't have anywhere near that technical knowledge, but will often also lack lack more basic data analysis or data literacy skills, unfortunately.
Brendan Cox:I think that's the thing when you're Senior Technical is difficult, because it's, that's one of the things if the more technical the role gets, the more the more jargon, the more analytical person is, but they're analytical for themselves. They're not talking about it in the sense of like a regular person. Thay are used to discussing it at an expert level. And like you say, that is definitely a really important skill to basically be at work as a translator. Because that's like, one of the lovely things about really good scientists, like you Bill Nye, the Science Guy, is that his art is in being able to explain something really, really well. So you don't feel like you're stupid. But you can actually learn it from him, in the way that he's, yeah, he can translate in a way where it's like layman's terms and you learn without being talked down to or being kind of, yeah jargoned.
Unknown:Yeah, exactly. So that's that. Yeah. And I, you know, I think l&d people kind of have an advantage because you know, they teach. And hopefully, they have acquired the skill to teach well over time, and so which is breaking complex things down into bite sized digestible pieces. So, you know, when I look at job descriptions for data analysts or data scientists and like must write x y&z algorithms or be able to write those types of algos algorithms? To me, I think about it from the perspective of Well, I mean, that's you can learn that fairly quickly. By comparison, the soft skill of effective communication takes a lot longer. And it also requires a certain attitude. And I think attitude can't be taught. You know, so when you're hiring people, you want to look at getting that right balance, and so net, you don't necessarily, it might not be the best idea to hire the most technically skilled person. But you kind of get someone who, who is very teachable, or who has had the ability to gain knowledge very quickly, and who is comfortable with gaining with learning and knowledge.But who also have a good repertoire of the necessary soft skills.
Brendan Cox:Yeah, I select that thing we said quite a few times with the you promote people to the level of their incompetence- the Peter Principle. Everyone's everyone's really technical. And then you because they're technical, you make them the manager of the technical department, but you don't train them in how to manage, which is a whole different skill set. So
Unknown:yeah,
Anja Hartleb-Parson:Or you do train them, or you offer training or whatnot, and it just doesn't work out very well, for various reasons, because this person just doesn't have the right attitude. And they'd much rather would be, would like to be still the coder or whatnot. But somehow, you know, leadership has convinced them that, you know, they really, if you want to make more money, or whatever, then you really should be acquiescing to our demands of becoming a manager or whatever it is. And so, you know, there's certainly these types of internal, like, pushes that happen.
Brendan Cox:There's kind of this assumption that the direction is always up. And that is naturally just keep going up. That's how you get more successful. And actually, it's like, especially for for creatives and technical roles, I guess, as well. Like, as a designer. It's like, it's weird. It's like in the back of our head, we've all been, like conditioned to think that right? Okay, we have a designer, now we're head designer, certain point, we become successful enough that we should open a studio and be in charge of a design studio. And then that's kind of like the pinnacle of our thing. And then we win loads of awards. But running a design studio is not even slightly the same as Yeah, actually being a designer. In fact, I don't think any, anyone that I've really spoken to that is running any studio, that's not just like a two person, kind of group. They don't even get to do any of the day to day design stuff anymore. So it's a weird mentality to dislike, we've all got it in us, we all think that it's like, oh, you just keep going. And then you become a manager? And actually, yeah, like says it's a whole different set of skills.
Anja Hartleb-Parson:Yeah. And it's, it's this part of the skill, this skill set that's really necessary to keep your, your team, you know, your employees happy and producing well, because, you know, crap managers, they have a really negative effect on the bottom line, when it comes to the employee experience and subsequent productivity and retention.
Unknown:you know, so
Brendan Cox:No one's ever left a company for a terrible coder. Cannot work there, that guy's just shocking at JavaScript.
Anja Hartleb-Parson:Yeah, yeah. So it's, I don't know. This is also just one of those things when it comes to people development that always baffles me a little bit. Because, I don't know, but then again, I always think certain things are common sense. And it turns out they're actually not common sense.
Brendan Cox:Oh, yeah. Yeah. Yeah. All the things that that Yeah, There is no such thing as common sense. That would be a good name for the podcast. There's no such thing as common sense with Brendan Cox.
Anja Hartleb-Parson:Yeah. I mean, we shouldn't assume it. It's such a fascinating thing to me Organisational Behaviour. That, you know, the impacts are so vast, and sometimes the things that we need to do, at least appear on the surface to be so simple. But we just don't do them.
Brendan Cox:Yeah, I mean, even seeing the bigger picture has always been a problem with everything from the environment, to society to general personal well being and everything.
Anja Hartleb-Parson:Yeah, so the the bio politics view there is that we oftentimes need things to touch us personally, you know, to affect us personally, before we deem it important enough to act on like, COVID. So that happens a lot. I think that's and and sort of this in group out group thinking or, you know, this idea of tribal mindsets, it's still you know, as much as we like to consider our styles advanced, it's still very much part of, of our human experience. And, you know, I don't look at it from the perspective that we need to stamp that I don't think it's a, we are able to stamp it out. But I think that what you were saying about self awareness is just the critical piece that needs to happen. And that's very hard. being objective with yourself is extremely difficult, because we don't like to admit our own failures. And we don't like to think about having done something wrong, having made mistakes, or having even believed in something that's not correct, or that's not right. You know, because we invest energy in that. And that goes back to your point about conserving energy. So the sunk cost fallacy is very real and human beings, which is that idea that, you know, we keep doing something, or we keep a software around, that's not working properly, because we think, well, we invested all this money in it, or we invested all this time in it. It's like that person who goes to the movies, and you know, like, 20 minutes, and they realise this is a crap movie. I guess I'm gonna have to sit here because I already paid for the ticket.
Brendan Cox:Yeah, I did that with catwoman.
Unknown:Yeah.
Anja Hartleb-Parson:I did not see that movie, but I don't think that was a lot. Anyway, so that's the that's the thing, you know, that we kind of need to combat on an on a daily, daily basis, almost.
Brendan Cox:So start looking at the data and don't take the easy way out.
Anja Hartleb-Parson:Yeah. And that's, that's also the thing that affects data, though, right, which is where I'm going back to this point about interpretation. You know, we do we do have data isn't data itself is neutral, but what we collect in terms of data and how we interpret it, and what we decide to focus on, that's not neutral at all. It's not value neutral at all. It's it's very much influenced by our preferences and values and biases. So let's again, the point about don't focus so much on getting the most technical person, focus on a person who, who has the ability to approach data and interpret data in a meaningful way.
Brendan Cox:Yeah. Okay, great. Um, where can we where Can someone find you online, if they want to chat to you and find out more about what you do?
Anja Hartleb-Parson:Yeah, so I am on LinkedIn. And that's pretty much the only place you can find me right now because I try to really curtail my social media to be as productive as I can with it. But I do love LinkedIn. And you know, definitely reach out to there, reach out on there and send me a message or whatnot, I am always open to connecting with new people.
Brendan Cox:Cool. Well, it's really nice chatting to you. And that is really interesting to kind of get your insight on it all. And the data side of stuff, I've always been obsessed with, like process improvement, but I've never really done it for other people's businesses. I've always done it for like my kind of like freelancing stuff and like building templates and keeping records of everything to the side work out what was quicker and stuff like that. So actually kind of chatting to someone who really knows what they're talking about on a grander scale. And from the business side of things is really interesting.
Anja Hartleb-Parson:Yeah, and I think it's really important for your career development also, too. Because, you know, you want to be able to, to report some numbers based achievements when you're working with clients or possible potential clients or, you know, when you're trying to find a new job. I think that's always really valuable to show how you've actually moved the needle on things.
Brendan Cox:Yeah, totally. I think that's a that's a really good point. Great, well, lovely chatting, and thanks very much.
Anja Hartleb-Parson:Thank you for having me.
Intro/Outro:Thanks for listening to the blend podcast. It's available on Spotify, Google and Apple. You can find blend interactive content on LinkedIn, or www.blend.training. Don't forget to like and subscribe. See you next time.