organisations, data, people, employees, analytics, workforce, insights, business, decisions, Visier, resignation, talking, hr, research, leaders, capability, understand, talent, role, managers
Andrea Derler, Kathryn Hume
Andrea Derler 00:00
Usually on time, enhancing her work on time. And suddenly I stopped doing that. Or suddenly I have a lot of sick days. Or suddenly you overhear me talk really cynically with my colleague about the company, that these are, for example, pre quitting behaviour stats, little alarm bell that should ring in any manager’s head to say, “I should have a conversation with this person” and not a accusatory conversation, but basically, “how are you doing? What’s going on? How are you?”
This is the reimagined workforce podcast from Workforce transformations Australia, the podcast for people and culture professionals seeking to drive meaningful, impactful and financially sustainable workforce transformation through curiosity, creativity, and data science. In this podcast, we hear from talented and innovative people making a positive difference for their people, their organisations, and those their organisations. So they share stories and learnings to help others on their path to transforming their workforce today and tomorrow. Now, here’s your host, Kath Hume.
Kathryn Hume 01:11
Andrea Derler PhD is the Principal of Research and Value at Visier.
She collaborates with a team of data scientists, people, analytics experts and HR professionals to help produce data based and practical insights for organisations.
Andrea has written many publications that provide critical insights to help organisations make better decisions that gives them a competitive advantage.
Welcome, Andrea. Thanks so much for joining us on the podcast.
So happy to be here. Thank you, Kath.
I’m very excited. We’ve been arranging this for a couple of weeks. So it’s really exciting. I think it’s 2pm, where you are in 6am, where I am. So it’s great that we’ve been able to find a time where the time zones match up. So I’m going to jump in.
Could I just ask you to start by providing us with a little bit about your journey so far, and what you are dreaming of achieving in the future?
Andrea Derler 02:05
I love that question. I thought about this and I’m thinking I’m a researcher by heart honestly. Already back in middle school in Austria, I used my lunch breaks and my own pocket money to conduct opinion research with people I just picked out of a phonebook.
I think I’ve always been just that curious person who has more questions than answers often. But since I’m a researcher professionally, I’ve been fascinated by human relationships at work.
So Leadership Research is where my journey started. 10 years ago, were still my main interest lies. I think, if in the meantime, peeked into research around the world of psychology and neuroscience, I’m always fascinated by how we work as humans. However, biology actually really still plays a huge role in how we are as people and employees as well. And now 18 months ago, I landed in people analytics, working for Visier, the leader in people analytics and I think this is one of the most mature HR practice analytics and data, and one that will become convinced the glue between, you know, business in HR, my dream for the future.
That’s a really interesting aspect of your question. I think I love if I could, you know, paint the Visiern that every decision maker in an organisation who touches people should think data first. That’s a big grand Visiern. But that’s you know, since you’re asked, that’s my Visiern.
Now, I think it’s, it’s true. And I think we’re getting closer to it. But it’s interesting now that I’ve had my eyes open a little bit to the people analytics function, I can reflect on the decisions I’ve made in the past and think I was relying on a little bit of gut instinct and beliefs and just thinking about what impact that might have had and how it might have led to better outcomes if I’d have data and insights and actual factual evidence to base those decisions on. So it’s really exciting that we’ve got this opportunity to leverage that data. And we’ve got people like you in this space who’ve really got that holistic view. I love that you’re blending the neuroscience. I’m really into that to my background is L&D and I’m very into how we perform better because of neuroscience. And when you have insight into that, and when you realise that humans are actually a bit more predictable than we would like to think it really gives you a bit more power to make decisions that are going to have an impact on an organisation and the people in them. Yeah.
Kathryn Hume 04:38
So you say you “study the humans behind data”. Can you expand on that for us.
I develop that slogan because I’ve spent as I said about 10 years now in HR talent management, business research and I found that still there is a lot of compartmentalised thinking. What I mean by that is we’re thinking about the business on the one hand and the people on the other hand,
Right, we think about HR practices on the one side and the business leader, the function manager, on the other hand, and really, when we think about this, there is no business without people. And so we can’t really change HR practices without data. And so humans are affected by every decision that any leader makes by the way we work together. And so the research that we conduct at Visier in particular, is we’re trying to bring together workforce related data graphs, but behind every data point, there are people that are really human beings. So when we think about the great resignation, for example, that you can just throw a metric at people like, that’s the resignation with this month, for example, happens to be 1.7%. But there are people behind that data who have either decided to leave an organisation for whatever reason, or not decided to leave an organisation. So I want to remind everyone in our audience, about this interconnectedness between the organisation and the individual that lies behind or like really forms the organisation. Many, many examples of our research shows that but that’s what we mean by studying the humans behind the data.
And maybe that’s a good segue, because we’ll maybe talk a little bit more about what Vizier does, because I was actually quite fascinated by the size of the data sets that you have.
Andrea Derler 06:22
Visier is a Canadian based People Analytics, company that has been around for 10 years. Now, we started by realising that so many HR is systems out there have disparate data in it. So one may have information about the employee, demographic, another may have information around talent processes, the whole employee lifecycle in it. Another yet may have payroll data in it. And we found that it is very difficult for any business leader to look at all the information together in one place, and to really be able to analyse what this data tells us.
So Visier as a platform as a service enables organisations to combine very, very many different types of data sets within themselves in the Visier platform. So every business leader can go in and look at the business related metrics in one place. And this enables not only to have data at their fingertips, but also, you know, data quality issues are really a thing of the past with Vizier, because we are a big data science team and developers team helps organisations load data correctly in the system, and then be really reliant on in a correct amount of data. So the data set of 17 million employee record, since probably more by now, the number is growing almost every week, means that organisations who are using our Visier customers have, are using Visier as a place to put their data and to analyse it throughout.
So we have information about, events that these employees go through.
So they are being hired, they’re being promoted, they get a compensation raise, right, or they’re being let go, or they resign by themselves.
So every single one of those employee records has almost another, a variety of events related with it. So you can see it scrolling, of course, every day because people do things make decisions that are tracked in the organization’s human resource information system. And then also, if they use Visier, you know, in the Visier platform.
In my work, we talk a lot about impact versus effort. So if the effort is too great to justify the impact that you get, you can understand why some organisations might opt out of people analytics. But I think if you make that simple as your you’ve done, I think that makes it easier for people to adopt and see the value. And that’s only going to mature the function. And that’s going to have the cyclical impact. So it’s everyone’s going to benefit. And in the long run, it’s not just the analytics that we’re wanting to improve, it’s the outcomes that it delivers.
So on that, what would you say is the thing that you love most about what you do?
Andrea Derler 09:14
I always say I have a luxury job here at Visier. I love three things the most about this. The first one is the opportunity to work with the data science team at Visier who are really able to help me explore this data set that we just discussed, with analysis with math was that mistakes to really understand what are the trends, the talent trends that the employees in the database are going through? Secondly, we’ve already mentioned that the pure knowledge that the Visier community data that’s how we call the data set contains so many millions of real life employee records. It always feels like a lived it is actually a live data set. Right so we don’t have to rely on survey research which is always by us, which is always sentiment research, which is always based on a small sample, we have this plethora of information. So we love actual data. And the fun part as a researcher for me is that we don’t sometimes know what we will find here, we’ll find something else of what we actually expect it to find. We don’t always know when we enter a research project, what the relevance will be of what we find. And what I really also love. And this is modern three, I’m sorry, cat, there’s so much I like about this role of this company is that we see our audience responding, connect with our findings, that’s probably one of the most important pieces that we can do all the research in the world if nobody sees it, and finds it valuable is really not valuable. But we find that what we find what we discovered, is relevant is highly relevant for business leaders and HR leaders. So that’s what’s fun about. And that’s what’s wonderful about this. My work.
Yeah, and it does sound awesome. And I love that you say it’s a luxury position. And I feel like that a little bit with my work in health just feels like a privilege. But I absolutely wholeheartedly agree with you. There’s no point in doing all the hard work unless you say to people benefit in the end. So I love that you get the opportunity to say that. Can I go a little bit off script? I’ve got a question around, you talked about the proliferation of data that we’ve got this plethora of data. And I listened to a podcast you were on recently around the need for capabilities in utilising that data. So we’ve kind of got a little bit of a problem, because we’ve got a bit of a head ahead of ourselves with the data that we have, and and that leaders are now thrown into this washing machine. And because we’ve had COVID emerging out of it, we’ve now got this hybrid context which we weren’t necessarily geared up for. We’ve got employee expectations that are many and varied. And what’s the role of data? Do you think it’s helping leaders? And so that’s what first question, what’s the role of data in helping leaders? But also, secondly, how do we develop the leadership capability to utilise that data?
Andrea Derler 12:08
They’re all off data, I think there’s no world anymore in 2022 and going forward, where we can’t even imagine a world without data. So it’s almost a given that’s naturally developed out of the technological revolution. So the complexities that you are addressing here are still vast, there are lots of really good books out there that have also been, you know, trying to understand more about how can we deal with this, there are challenges around what data is actually valid and true gives us real answers versus what’s just, as we’ve seen politically, in many, many countries this year, where data is also used, misused, and people are being abused with data. So that’s a big challenge there. So the role of data itself is growing almost, daily, I would say the more data we produce, I think data is the most produced, you know, if you can call it a good, because it’s in many ways free. So the role of data is not going to go away. I think what’s a lot more important in this discussion, I think is what you suggest which its capability to deal with it. If we perhaps hone in on organisations, which is the context in which we and you and I are talking about today is, we found that missing a lack of data capability is actually the number one concerns of people analytics teams that I spoke to this year. And what does this actually mean? It means we need to be able to translate complex ideas because we have so much data. First of all, we need to analyse it. And what that means is that this is exactly what Visier does. What’s the question you’d like to answer? If you have a huge data set, and you’ve seen this two spreadsheets of numbers in the survey, even if it’s just survey data, responses, if you don’t know what you’re looking for, you can have all the data in the world and in really not have any insights at all. So asking the right questions is a main capability, knowing what one wants to know needs to know for the benefit of in this case, organisation and employee. The second one is that was highlighted by my interviewers was the storytelling skills. And once we understand what the metric is, for example, that we’re trying to track or understand, that’s only the first part, trying to translate that and making it valuable and digestible for the partner that we’re talking to whether it’s the CHRO, the CEO or senior leadership team, or the people manager, who’s at the end of it is critical because without me being able to tell the story of my numbers again, it just causes noise. The third one that stood out to me is it was mentioned a few times by those people, analytics professionals was emotion, something hijacked people, they find data points that are in contrast with their beliefs with their opinions with the history of the organisation perhaps, and that causes emotional upheaval, they get angry, they get confused. I’ll give you one example, one company shared with me that they wanted to test the hypothesis that in business units, when more tenured employees were working, there would be higher productivity due to the experience of the tenured employees. Now, their analytics teams found actually the opposite was true. It was those business units who had the least amount of tenured employees and very, very young new generation, you know, workers, who would just come out if university were actually the most productive, you can already sense that it’s a very sensitive story to tell, need to know exactly why am I even looking into this? What’s potentially the outcome? How can I communicate this message, so it doesn’t get misused? So there’s a lot of we talked about psychology, biology, we’re still human beings, we still need to learn how to deal with that type of data and information and insight, to really make it valuable, and not destructive.
Kathryn Hume 16:19
You know, it makes me think I spoke at a conference last week for strategic workforce planning. And our topic was curiosity, creativity and courage. And I think you opened by saying, you’ve always been curious, and I think you said there about, we have to ask the right questions. So I think that you’re covering off the curiosity there, then there’s the creativity of bringing together what is the story by going to tell, but that emotional intelligence that we need, and that courage to say, there’s a risk here? What’s the benefit of sharing this story versus what’s the benefit of maybe telling it a different way, or doing some more investigation or, just holding out for a little bit, and I, maybe it’s just the lens that I’m seeing the world through at the moment, but I can really see that you’re moving through that process. And one of the things that we do talk too about is that cognitive bias codecs, which I don’t know if you’ve seen it, this really beautiful image of, I’ll put it in the show notes. But it’s a really beautiful image of all of the barriers that exist to us being able to think clearly and make sound judgement. And I think, raising our awareness to those biases and understanding why we make decisions. And when you talked about, we look for things or we say things maybe based on our biases that we already had,
Kath Hume 17:45
I think that’s a really critical thing to raise people’s awareness to, but also take them through then this process of curiosity, creativity, and courage when they’re working through this and making a little bit more human. Because I do think people analytics gets a bit of a there’s an assumption that’s.mathematical.
But as you mentioned, we’re talking about humans, we need to bring that human side of things, the machines and the computers can do the number crunching. But we need to bring the insights we need to bring that curiosity and understand what is it? And how is this actually going to benefit what we’re doing.
Andrea Derler 18:22
And like to add some feedback for me. Great when you summarised it so beautiful, in that I love the three, the three items, you mentioned, think the question is yes. What does it bring us? What’s the impact of that mindset, that data oriented mindset, if we may call it that.
But the other component of that is, there is no option for any of us to avoid it, and we can’t do it anymore without so the younger generations, my kids, students who are now graduating from university, they’re going to call us out on this on our in our lack of data capability at some point. So I don’t think we have an option, it’s more about we are going to have to learn this as an organisation as individuals, because not doing it is not an option anymore. Therefore, there is too much data out there too much information too much choice for young workers, for example, where they want to work, or they want to work for. So I want to remind leaders, my agent and you know, more mature that that’s the only way to go. Yes.
Kath Hume 19:26
And I think employee experience, we’ve got all these companies who have worked out customer experience. And so our experience in the world is seamless. In most cases, we don’t tolerate inefficiencies. So it’s unrealistic to think that we can bring people into a workplace and I think we can not mirror that experience outside of the workplace.
So I think you’re absolutely right. And they don’t necessarily need to understand that the people that analytics is driven it but they’re definitely the lived experience is going to be that they expect us to provide them with happier place that provides them with everything they need to do that their job and that it’s going to progress their career. And, there’s, there’s lots of things that we need to address. And I think the data is how we how we make sure we understand what the expectations are. So we can deliver those or at least have a conversation if we can. Yeah. So moving back to the script, sorry. So what are the most important workforce trends you’ve studied in the last 18 months? I know that I love following you on LinkedIn, I love the insights you share. And so I’m really keen to explore that with you.
Thank you so much. I mean, what we’ve looked at the last 18 months was, of course, coming out of the pandemic, going into the almost post pandemic growth here, if we can call it that at the moment. A couple of things stood out to us as we were tracking it.
Overall messages that talent retention certainly is the number one issue. I know that that’s a very wide and broad topic, but many things fall under that, but it really emerged based on the workforce and the labour market had developed. And you know, that there are actually fewer people now out there who are prepared to work. That’s a fact that’s been in development over the last many years.
But it all started in last year, towards the end of 2021 with the great resignation. That’s something we’ve studied in depth, because we were the only ones that apart from of course, the Bureau of labour Statistics, perhaps the data, we saw that the great resignation was a reality.
Coming out with the great resignation, then earlier this year, we wanted to know have organisations been able to replace the talent they lost. And we found, yes, they have more than replaced what they lost by 170%, which surprised us, we also found that hiring externally has been of course, a much much stronger trend than you know, internal replacement, which of course, is naturally coming out of losing so many people. So we started the great rehire. But then we also found recently that when we stick with the fact that you know turnover is the new reality, turnover, of course means talent moving in and out of the organisation. That turnover is actually contagious. We found two things. First of all, if people resign, their colleagues on the same team are more likely to resign as well. We can dig into that if you’d like a little more. But we also found in contrast that even if layoffs are happening if people are being terminated, there’s also an effect on resignations of people on the same team. In other words, do organisations know that do HR and finance leaders as they are pondering layoffs and terminations to pay and know that they may as well add 7%, for example, because people will leave if others are being terminated on their team. Same with a resignation. So we can’t look at any of those events anymore in isolation. And say, actually, we need to understand there is a social effect on people around the employee and what’s happening to them.
And then we asked ourselves, well, all those people who’ve left the organisations what happened to them and we realised, you know, many of them actually went back to their previous employer, they realised either that the grass isn’t greener on the other side, if they left for another employee expectations were met.
So we started what we call the boomerang employee trend, which was a really interesting story of the summer. One of the components I want to highlight there is, it is a stronger trend that we expected. So a third, let’s say a quarter of most new hires have actually new hires in our database where boomerang employees. The interesting component of that is, it can be actually quite expensive, because boomerang employees tend to negotiate their contracts in really well, they get the 25% pay raise. So a couple of interesting items that we started. In the last, I would say 18 months they all connected to some way because it’s all about talent movement. But I think digging into each of those insights will help HR and business leaders and the managers out there to handle the situations when it comes to talent retention a little differently.
One of the things that you called out was that 13 month sweet spot? And I think that’s a real eye opener. So if I can use health as an example. I get the sense and this is all anecdotal. This isn’t based on my work in any way. This is just what I sense from what I’ve read in papers and things but I just wonder if the health workforce got to a point where they didn’t feel they could go any longer and that healthcare organisations weren’t able to be flexible because they desperately needed the workforce. And so I wonder if there were conversations that happened where people wanted to reduce their workload, but weren’t able to give them that, and then felt that they had no option other than to leave. But then at some point, once they were rested and recuperated to some degree, if they’ve then not necessarily regretted it, but if there wouldn’t be an opportunity to then come back, because a lot of those would be long tenured employees. So I just love that you’ve got the evidence behind it to say, this is still an option, because we’re talking everywhere about skill shortages. This is a workforce that have got the capabilities have got the organisation, I’ve got knowledge I’ve got the relationships that can train your new employees. They’re really valuable workforce. And I think we can really leverage those. But I think that call out around the 13 demands is absolutely critical. And I really liked that you’ve raised that.
So Andrea, people analytics seems to be an increasing priority for organisations today. But do you think we have a handle on how to make the best use of what we have available?
Andrea Derler 25:58
What we found in our research with organisations over the years is that data capability, I think that’s what we’re aiming at here varies really widely. studies that we’ve done, what my colleagues have done back at Bersin by Deloitte many years ago was that only about between five and 10% of organisations in our database, or in our you know, then survey database, were really, really well versed in all things to do with people analytics. So that means what’s available best practice even mean? It means that people analytics and data oriented mindsets have a strong business alignment so that business leaders know what they’re asking for and the analytics teams can actually provide those insights. That’s one component of a well functioning analytics unit.
Another one that came up recently in work by my colleague, Lexie Martin was that organisations will have a grip on this, have people managers throughout the hurricane actually using analytics. So it’s not just you know, top leadership, who has the biggest insights, it’s actually everyday people, managers, basing their decisions based on data. So that’s also an aspect of our criteria of a well functioning, data oriented business. And but they’re really rare still, but we know that many, many others are working towards that goal. So I’m talking about five to 7% is the creme de la creme, they’ve been doing it for a long time. But we’ve seen an increasing number, of course, in our customer base. And of course, also organisations who are interested in Visier. But we can tell they’re really developing and ramping up their capabilities. Another component I found recently interesting is that many now have psychologists on staff that they’re part of the HR team, part of the analytics team, sometimes because of that human behind the data component. Right? So I found that an interesting development, I always like to say, when I think of all the data that we have, and their organisations have, that we are drowning in data, but we’re still striving for insights. That’s always what I think of because there is just too much out there. And it’s really increasingly difficult to do what we’ve discussed, namely, asking the right questions. What I found working really well for those who are on their journey, who are not part of the 5% yet, is that when HR teams collaborate closely with their analytics teams who collaborate closely with business, so I found it beautiful to see in all the stories that I’ve been able to hear from our customers and non customers, that the more teams come together with different perspectives around a business problem, let’s just pick one. We need more female leaders in senior leadership positions by 2030. Yeah, that’s a goal I’ve heard by a couple of really large global organisations. That just doesn’t mean that the diversity, equity and inclusion head gets together with a tiny team of analytics teams and gets this sorted, as you know, coming from learning and development and also talent management in general, it requires a village to get this done, to even think about why the goal would support the business to think about who would get engaged, which stakeholder we need, what actions we need to take on the training side. And of course, always, what should we track in terms of success. So the collaboration between those stakeholders has been a major finding in in our research there to help us that’s what we really need to do. That’s how we can make best use of the data we have is only by none of us thinking they are the experts in their own right.
But all of us together will solve this immensely and increasingly complex problem together that does just beautiful. And that collaboration. What I was talking about last week too was around creativity is making something new. And so how do we draw that knowledge from people and bring it together and join those dots together and to create something that didn’t exist before. So I think it’s really the collaboration piece is really quite critical. So what role do you think data can play in solving some of our really complex workforce challenges?
Andrea Derler 30:12
In my view, you know, we shouldn’t even try to start to solve any problems in the absence of data. Let’s, let’s, let’s look at a few examples. For example, when you have a retention problem in certain business units as a major manufacturer to speak one industry. Now, how do you even know that there is a problem until it’s too late, and you’ve lost so many people that productivity actually suffers? You need data for that you need to understand and track your, you know, retention or attrition figures all the time? Where would you even know where the problem lies? And what you can do in terms of interventions? If you didn’t know the demographic of people, for example, who leaving is it? Is it mainly women who are leaving because they can’t make the 12 to 15 hour shifts anymore, I’m just making this up, right? You need data for that, again, you cannot solve any of those problems, or even look at the employee experience. You mentioned employee listening, really knowing what employees expect, and one that need to do their jobs really well. You need data on collaboration patterns, you need data on that burnout status. And again, in an increasingly virtual world, which many of us are in, or large organisations who do not have access, like personal access to employees on a daily basis, there is only data that you have to rely on to measure where people are, the way they collaborate, or the way they are burned out, or the way they are, you know, happy about the existing inclusion work that’s been done. You need the data. So the role of data isn’t just that we have a choice, do we need it or not, we don’t even need to start, you need benchmarks. You need to know where you are, you need to probably want to know where your competitors are. There are a lot of ways Vizier has a benchmark offering where organisations can benchmark themselves against others, so that they understand Aha, others in my industry, others with the same organisation size, have those numbers, we are actually below or above. That gives us an additional, maybe motivation to change something. So, you know, again, but I’m working for a data company, of course, I will say that, but no problem solving without data doesn’t make sense, just and I think we’ve already probably addressed that. But the next generation of topics that emerges out of all the metrics that we’ve been talking about today are things like leadership styles, productivity, you know, it’s getting really to the business impact of HR decisions. And that’s more complex than you may think. Because the data around you know, all those, you know, productivity measures, or collaboration patterns, or resignation numbers, they usually living in many different systems. So have them all in one place is critical. Otherwise, you can’t see it all and understand the problem at hand.
Kath Hume 33:02
And I’m interested in one of the things that I’ve hearing a lot about recently is the how do we return to the office? Or how to what how do we move forward after the experience of working from home? And I get a sense, just from what I read on LinkedIn, and from talking to people outside of our organisation more generally, is just that that seems to be a bit of a tendency to make a decision that isn’t evidence based that doesn’t rely on data, because of someone some leader’s preference, potentially. So I think it was Elon Musk, who decided he’d bring all people back into the office full time, for example, what are the dangers of doing that in the absence of data? And how do you think data can solve that?
I agree with you. One thing that comes up for me there is the fact that we found across studies, and I’ve personally found this across studies across different organisations I worked for as a researcher, is that senior leaders consistently seem to have a lot of blind spots when it comes to the type of decision making happy to share the research that we have. We’ve done this research at Vizier. I’ve done that in my previous work. For some reason, we found consistently that senior leaders opinions about how things should be, are varying vastly, sometimes from what employees think things shouldn’t be like. I don’t have an explanation yet. But we know that it applies to hybrid work. It applies to transparency during COVID response, either plays to pay transparency, and or thinking that things are actually better than employees tell us that they are. So I think that’s worth highlighting. For senior leaders in particular who are at the end the decision makers around hybrid work. It’s going to be really important
They gather all the data that they can get their hands on to understand a which jobs really need to be done in the office versus what can be done on the office of a flexible work models, I think hybrid or flexible work models is probably the way to go. That’s not going to go away. Be aware of that. But also, secondly, if the organisation does pulse service engagement surveys, opinion, research, focus groups, whatever information they can gather from employees is really just shouldn’t always just determine the way we’re not saying the employee has all the decision making rights. No, but I think most people are reasonable. And say, I’m happy to go back maybe two days a week. And that works for me, I can make that work if my leader really wants that, for cultural reasons. For whatever reason, they need that. So I think that’s where the sensitivity of particularly senior leaders come in, because they are at the end of the decision makers.
Track mobility patterns, for example, right track resignation rates, you can detect usually, where in which business units are losing the most people, and then you of course, look at your exit interview data. And then you look at them or talk to the managers there to find out what could have been the majority of reasons for people to leave or stay. And so but it is getting, I mean, again, time consuming, and get it we can’t always do that legwork. You know, senior leaders certainly can’t do that legwork. So they rely on a well functioning HR analytics function, to give them the data point. So they can that a picture emerges about the decisions or I should say, preferences of their workforce, the roles and the regions and all of that, so they can then make a decision. I don’t think there’s a one fits all decision at all, like I wouldn’t even assume that that would be reasonable.
Kath Hume 36:56
Yeah, no, I completely agree with you.
And I think that goes back to what you were talking about in that collaboration space. So the people analysts are sharing the insights, but they need to understand what keeps the leader awake at night. So as I can give them the insights that they need, and I think you call that around collaboration is absolutely critical.
So we’ve spoken about boomerang employees, we’ve spoken about understanding hybrid work to make sure we’re meeting employee expectations and all the other things that we’re doing in my area of work, I really want to focus on creating positive staff experience. So as we ensure that people stay with the organisation will the people that we would like to stay, stay.
That ideally, it will be best if we could prevent employees who we would like to stay from leaving, what suggestions do you have around that?
Andrea Derler 37:44
It really comes down in many cases to the individual manager and the relationships but that’s not new to any of us. We know that. So apart from organisations, and when I mean when I say that I mean HR business leaders that talent retention is the number one issue this year and next year, because resignations are not only expensive, we want to keep people but we also want to make the most of the people that we have, like you said, so what we’ve learned in external research, you know, supporting the boomerang research, for example, where we realise so many people leaving and coming back, and this causes disruption. For everyone involved, right? We’ve learned that there’s a couple of things that managers people leaders can do basically, almost frequently and regularly. The first one is always look out for what the literature calls pre quitting behaviours, there are changes in a person’s behaviour red flags, if you know me as a reliable person is usually on time, enhancing her work on time. And suddenly I stopped doing that. Or suddenly I have a lot of sick days. Or suddenly you overhear me talk really cynically with my colleague about the company, that these are, for example, pre quitting behaviours, that’s a little alarm bell that should ring in any manager’s head to say, I should have a conversation with this person and not a accusatory conversation, but basically, how are you doing? What’s going on? How are you? So really not rocket science.
But that’s one thing. The other thing from a data analytics perspective that I find critical is constantly be aware of a person’s risk exit profile, and that sounds really theoretical, but what it really means is managers and unit leaders and HR with the support of HR or HR VP should be really aware of any person’s fixated profile, for example, when had they had their last compensation review? When was the last promotion How long have they been with the company? You know, have they had any experiences outside of the team? Really just an overview of how that employee from a little bit of a bird’s perspective has been doing that journey throughout the organisation? Because you know, some flags again in comparison to their peers could tell us aha, this person hasn’t had a review in four years, you know, and their market value has increased. So they’re at risk probably of leaving due to compensation reasons. But I want to be aware of that and kind of know that on a regular basis. Another thing we learn is the interesting, really interesting finding from the boomerang research is if many employees had the chance to explore our internal opportunities in the same company, by working on other projects, for example, or just kind of changing teams once in a while, whether it’s possible, it really helps them to retain employees, because employees sometimes just want to see something new, they want to learn something new, they want to grow a little bit. In sometimes that’s what boomerang employees told us, I left because I just didn’t see myself growing. So I got my growth, fix almost in the other organisation before I realised actually to like my job. So that’s an indicator, so enable that opportunity. Don’t be a talent hoarder. So these are three things that come to my mind immediately, but I’m sure many more.
Yeah, and I love, love that idea about “Don’t be a talent hoarder”. At this conference. I was at last week, someone said, and it was my favourite comment from the whole conference, “we’ve got to get less possessive about talent”, and just freeing up that we don’t own people. They come to us, they work for us and work with us. But they are human beings with lives outside of work, so how do we attract them, because it’s beneficial for them mutually beneficial, it’s beneficial for us as well. But I really love that don’t be a talent hoarder, that that’s a great slogan. Andrea. I think this is all amazing. And I think you’re really showing how we can transform the workforce as we have today to what we need tomorrow with the data that you have available, and how we can draw those insights and collaborate with others to share them throughout our organisation. So what recommendations would you have for people who are seeking to transform their workforces through data?
Andrea Derler 42:07
First of all, I would commend anyone who is planning that because that’s a wonderful mission and wonderful goal, transform their workforces with data.
A couple of things that we learned from our research that I see organisations do, I shouldn’t see organisations that I see people in organisations do is they collaborate with across teams, we discussed that the collaboration between the business, the reason why we’re here, with HR, who are looking after the people, including the people analytics team is key. Again, without data, you don’t know if you have a problem and what you can do about it.
Andrea Derler 42:46
The second one is a realisation that we work and the workforce have just become too complex for one function to know again, that’s why it’s so important to collaborate.
But never take no for now. So when it comes to let’s get some data for that, I think that’s just want to emphasise again, take a data analytics approach to decision making before you make a decision. Just make a little read takes it to a half what I need to make a solid decision and we are all humans, we are going to be biased, that’s not gonna go away, we can only mitigate biases, we can never, you know, make them go away. Otherwise you wouldn’t be human anymore. But always try to double and triple check. And also don’t want to dismiss the role of gut feeling. I think we all like you said at the beginning we have we have made gut feeling decisions. That doesn’t mean that everything that our you know, our sentiment tells us is always wrong. As long as you double and triple check it as honest as affects other people, which in HR often does affect other people. We just want to be extra sure it’s a solid decision, we can justify
the last one and I mean this not because I work for Visier. But I really think that technologies have come so far, that have made this much, much easier. We don’t have to worry anymore about data quality so much, but it’s still a concern, but get the right technology in place and reduce that risk.
Get a technology in place that helps you in or provide insights at your fingertips. You don’t need to have a whole large team of statisticians anymore. I mean, you may need some of them. But it is really the case that you want access to the data for everyone in the organisation. It’s called democratisation of incense and three for dental. I wasn’t sure what to think about that.
But it is like get anyone in the mindset of making those decisions based on data. Let’s just make it a habit. I think that would probably be something we all have to work on, you know in many years to come. And I will just go back to that. Comment around gut feel and I know I said earlier we relied too much on gut feel and I would like to also reiterate that there’s absolutely a role for that gut feel and intuition, we just don’t want to be over reliant on it. So my colleague, Tamara, who presented with me last week, and I know that she listens to this podcast, so Hi, Tamara.
So we often talk about the role of intuition and the fact that we don’t necessarily recognise it when it happens. So we’ve got to value it. And I think it goes back to that neuroscience and understanding that what the brain is doing is processing all of that, you know, plethora of information that hits it every day. And those times just before you go to sleep, when the way brainwaves in your in your head are changing, and just when you’re waking up and or when you’re in the shower, when you’re having those aha moments. It’s it is real, that that is your brain processing information. And those insights can actually be quite critical. So I think we can get better at trusting and or identifying that intuition, and then trusting it, but also having the critical thinking capabilities to to then bring the data in and do a balance of both. So we’re not overnight on one or the other.
So beautifully said. So Andrea, sadly, we are out of time. I’ve really enjoyed this conversation. I knew I would. I’ve been looking forward to it for such a long time. And I hope we have more conversations like this in the future. I do recommend people follow you on LinkedIn, because the insights that you share, you’re very generous with all of your research. So what’s the best way for people to connect with you?
Thank you, Kath. First of all thanks, for having me. It was a wonderful, delightful, interesting and inspiring conversation. I’d love for people to get in touch with me. And then minute, my email is andrea.dollar@Visier.com. You can also find me on LinkedIn. And for those of you who are interested in all the publications I’ve worked on in the last seven years, I have a personal website, andrea-derler.com.
Thank you. And I will put all of those links into the show notes to make it easier for people. So thank you. Thank you, once again, I will leave you to the rest of your day. And thanks so much for being a part of the reimagined workforce podcast.
Thank you so much. And I do want to compliment on you on the work that you do. I’ve looked at your podcasts. And of course of all the podcasts that have happened in the past, I really think you creating something very special here. Very meaningful. And the diversity of panellists or people who speak on the podcast is outstanding. So really what you do, I hope that you hear this also from others, is very special and feel honoured to have been part of this. So thank you so much for the opportunity.
You’re a very good human. But no, I do appreciate that. And I have heard that and I, you know, I love the feedback. And if I can help people to do this job better and make people’s working lives better. Yeah, then that’s a great thing. That’s a wonderful opportunity for me. So thank you so much, but it’s only the guests who make it possible. So thank you. I really appreciate it. We do it together. And thank you for taking the early call. Have a wonderful day. And yeah, I look forward to hearing the results of seeing the outcome.
Thanks for listening to the reimagined workforce podcast. We hope you found some valuable ideas that you can apply to transform your own workforce today and tomorrow. Additional information and links can be found in the show notes for this episode at workforce transformations.com.au/podcast. Please share this podcast with your community and leave us a rating to let us know what we can do better for you