Navigating Uncertainty: How HR can make a positive impact in a turbulent market

Jeffrey Smith: Hello everyone, and welcome to the webinar navigating uncertainty how HR can make a positive impact in a turbulent market brought to you by AON Service Corporation. I'm Jeffrey Smith of Canadian HR reporter for the host for today's webinar. Please note, we will be holding a live Q&A session at the end of the presentation, you should see a Q&A button at the bottom of the zoom window. And you can submit your questions by clicking on that button at any time during the presentation. And if you have any technical issues or inquiries during the webinar, please use the chat button which is just to the right of the Q&A tab at the bottom of your screen and our support team we should be able to help you also note that the recording of the presentation will be shared on the website following the webinar. So with that, let's get started. With dire predictions of a recession, a rising healthcare costs and a turbulent economic market. HR professionals are faced with a daunting challenge. But challenges can bring innovation. And I'm pleased to welcome our speakers for today's webinar who will discuss the essential tools and strategies to overcome the pressing struggles that are affecting the hiring landscape today and how to leverage data driven solutions to create value and cost effectiveness and Talent Management programmes. Now Joey Rahab is a Senior Vice President with Aon’s Canadian Health Solutions practice. He is responsible for Aon’s national strategy for growth and client engagement. And he's also the organization's chief broking officer, managing Aidan's relationship with insurers and non-insurer partners. And Scott M rifle is the director of people analytics at AON as well as the people analytics teams retail sector lead. Over his 15 year career in consulting Scott has led engagements and delivered solutions to a spectrum of client organisations across a broad range of industries. Now we'll take a look at the agenda today. In this webinar, you will learn about the macro social and economic forces that will continue to shape and disrupt our industries. The key is to utilising data to optimise investment in people and how organisations are using analytics to optimise their decision making. So those are some key elements that we can look forward to learning about today. And now I'll turn things over to Joey and Scott to get things started. 

Joey Raheb: Thanks, Jeffrey, for the introduction. Hi, everybody. I'm Joey Raheb as Jeffrey introduced me. Let's, dive right into the deep end. Because I there's a lot of meat and information in our topic today. And want to give some time to for everybody to ask questions and engage with the topic. We will have polling questions throughout too. So just to make sure you guys are paying attention and in a way can keep this engaging. And please pass along your questions in the Q&A chat box, as you see fit as you see them come up, and we'll try to answer them as much as possible at the end. So today's economic and challenges that we're facing with regards to workforce drivers are creating a lot of uncertainty and a lot of difficulty for the HR professional. As Jeffrey mentioned, we're dealing with a highly volatile macroeconomic environment, things like rising interest rates, which is being used today to try to temper our ever increasing inflationary environment. There is a push for businesses to manage their costs, both operational and people costs to keep things moving and manage to remain competitive in this environment, and keep their business sustainable as things move. But also HR professionals are facing with the continued challenges around attraction and retention. We're still seeing while job opportunities are starting to decline, we're still seeing employees leave jobs and in certain sectors demands for talent remain high and remain challenging to replace or fill roles. There's some more some sectors like health care as an example, still reeling from the impact of COVID whether that's individuals in their businesses who have decided to leave the sector altogether, or are facing challenges in terms of the types of work that they're willing to do versus not anymore. And if anybody has been paying attention to the news recently, there is constant debate about whether we will have a recession whether that will be a significant recession, soft recession, or what that might look like, altogether, that continues to plague newsreels daily. Again, back to the talent side of the equation, unemployment rates are low to the tune of around 5%. We've seen that improve since late last year, and people continue to face challenges with being able to fill that talent gap. Again, slowing there's been a slowing down in terms of hiring, but there's the concept of as organisations look roles and look at efficiencies in those roles. How can one organisation look to build from within and leverage resources, talent and capabilities that already exists within your four walls and learn to deploy that talent. And the focus on employee resilience has not gone away. And in fact, we just closed up a poll which we'll be summarising and releasing a little bit later, and which will inform a little bit of on our white papers as we continue to build. But employee resilience came out as number one issue for HR professionals in the pool. So there is a constant focus on how we can help keep our employees resilient. You know, if the pandemic didn't teach us one thing, it was that change is a constant evolution and the pace of change continues to be quicker and quicker each year. And if I can bring in a statistics from our statistics, excuse me from our global well-being survey, we know that a 4% increase in well-being performance correlates to a 1% increase in company profits, employee or customer satisfaction and a decrease in employee turnover. And inflation continues on the rise. And while there are some months we've improvements, we sometimes don't necessarily see that implication the same way when we head to the grocery store or look to purchase the goods that we normally purchased a year ago at significantly lesser prices. So inflation continues to plague us. And that means organisations but also people are facing real world challenges in terms of deciding between what is important. And you know, again, if you're paying attention to our neighbours to the south, you're hearing real world trade offs going on in people's minds whether they're going to pay for food at the grocery store, or whether they're going to fill a prescription drug. That takes us to the next topic of the conversation which we like to coin that discussion between playing defence or offence and, you know, if you've played a sport, and I know sports analogies aren't so popular anymore, but you can't win championships without playing defence. But you also don't want championships without scoring some goals. So you do need to think about as an organisation how you are playing that defence and protecting the business optimising where you're spending your money. optimising how you're spending that HR or its budget. But you can't do that, that at the expense of planning for future growth. Again, inflation has been on the rise. And while you know, in healthcare, we've been used to healthcare trends outpacing inflation, you know, this, this does create challenges, because what's very unique in today's environment, is that organisations and the people that work in those organisations are facing their own challenges with regards to how inflation is impacting their daily decisions. From an organisational perspective, you've got that pressure play with regards to the impact on inflation with regards to wages, the impact on inflation with regards to the goods that you need as inputs into your business, which you will turn into the end product. And then you know, how you translate all that to the expectations that your employees have with regards to the increases in costs and fees and all those sorts of things that they're facing in their real world, purchasing decisions for their own families and themselves. I encourage you, as you're, as you're thinking about this, to include it in the chat box here, if you're comfortable to share, how maybe your business is, facing these challenges, maybe explain how you're maintaining a balance between that near term defence and optimising spend with that long term optimization and planning for future growth. So while you're doing that, and thinking about that, why don't we open up with a poll? So if we can bring that poll up? How many of you feel like your organisation today is playing defence? So in terms of definition, managing cost control, headcount management? Or is your organisation playing offence, setting the foundation for future growth and success? 

Joey Raheb: Give some time for the poll to collect. I'll say that, you know, as somebody who's been working with clients for a number of years, I have seen an increased focus today in terms of better understanding where the dollars are going. I think in Canada in general, I think we've been fairly lucky as a result of our health care system, the dynamics of our economy, in that I Haven't seen a broad scale cut in terms of where organisations are spending. But there certainly is a lot more, a lot more interest in terms of understanding where that spend is going, and how much of it is going towards programmes that are being valued and optimised. So do we have results for the poll that we can pop up? Here we go. So 70% of people feel that their organisation is playing defence and in 30% Playing offence that's interesting. So that'll help inform as we continue to go through the presentation. Thank you for sharing everybody. And again, remember in the chat if you feel comfortable, share your own experiences with your own organisation. You don't have to name names, but be good if you if you share. And if you want to share that with the host and panellists exclusively, we can try to put some context around some of this for you. So as we go on and talk about competing priorities, and, and, you know, dive a little bit deeper into what we'll be digging into today, you know, we talk about, you know, how do we manage the spend today in terms of rewards, costs and rewards costs can be a number of things, both cash and non-cash. So both about how you're competing with base pay and short term and long term incentives, but also how you manage things like your benefits, plan, your retirement programmes, how you manage the communication, education of those, how you look at the utilisation of those programmes, where do people value what they're getting? Are they getting the most out of them? And is money being spent in places where your employees don't see any value. And therefore, you know, try to re-optimise those dollars into places where there is value or take them back into the business to help offset some of the challenges that you're having from an inflationary or macro economic perspective. versus, you know, looking at the future and how you attract and retain talent? What are those programmes that you're putting in place? And how are you creating better alignment with what your organisation is trying to achieve from a business perspective, from a business strategy perspective, and then translating that into whether that's your culture, whether that's your, you know, diversity, equity and inclusion, your ESG goals and strategies, but also supporting the health and well being of your population? You know, and this is when things like thinking about your employee value proposition and building out that story in connection with what you're trying to do as an organisation, but also the connection about why does somebody want to come work for you? Why does somebody want to stay working for you? What do you bring to the equation that others cannot bring to that equation, because if we all tried to differentiate on pay, there's always going to be somebody down the street, who's going to be willing to pay more, offer a little bit more cash to attract away that talent. So how do you create something that's unique within your organisation that another organisation can't replicate. And your next if we, again, set the stage a little bit with regards to how we're defining people analytics, and you know, while this may feel intuitive, I want to make sure that we're all kind of speaking from the same, the same book. So it's really about looking at the power of the data that exists, whether that's internal into your organisation, or looking externally with regards to benchmarks or other items or other components of data that can help lead and point to issues that can identify or create solutions. And then also, and probably more importantly, is to sort of is to measure those results. To understand, you know, when we put a programme in place, do we put us do we put a stake in the sand and understand like, Hey, here's the goalposts and here's what we're shooting forwards towards? And then we continue to monitor and manage those results. Are we getting closer? Have we hit challenges that we did not face? Is there? Is there a place for us to reset? Or are we exceeding expectations and do we need to set a new goal post based on the takeup or whatever the programme has been doing? key here is to make sure that what you're doing is being based on data and facts, and that you know how to interpret that data and that you're able to use that data to inform on your decision making capabilities. So when we talk about people and analytics, that's, that's our starting point. And we give you a couple of examples to go off of here as you're thinking about, you know, the issues that you may face and how Analytics can help a face to address those Excuse me. When you think about, you know, compliance and fairness and managing pay transparency, it's that pay equity analysis that you could do. Or when you're thinking about, you know, health care costs, and what's challenging you from a health care cost perspective, you know, doing a, doing a review in terms of where those where that spend is going, and how that spend is, is being directed to the different providers. So what you're seeing, I think their presentation fell off the zoom session, but maybe when it gets back up there, what you'll see here on the screen is the various issues that you could face and some of the analytics capabilities that that you can use to solve for them. 

Unknown Speaker: Sorry, Joey, I'm having trouble with my connection, apparently. 

: Okay, maybe I can share my screen here. One sec. Yeah, go. Back in Business. Alright. So that's, that's what I was talking about here. And maybe as you're looking over at that, we'll have a new poll pop up on the screen for you. And so this question today is asking you to think a little bit about how are you using data in your non cash rewards programmes? So you'll get four choices, Are you using it to measure utilisation of benefits against the budget to determine if the ROI on your programmes aligns with your rewards philosophies, identify opportunities for engaging employees in ways that increase their value or their perceived value of their programmes? Or maybe the last one applies to you and you're having a really hard time getting access to the right data? 

Give you guys a couple of minutes to answer. 

Joey Raheb: All right, how's the results from the poll showing? 

Wow. So good number of you having challenges with getting access to data, maybe we'll dig into that a little bit more. And then identifying opportunities for engaging employees came up as a very close second. And I see a lot of people still in that primary bucket about measuring utilisation of benefits against budget. And I think this is, you know, really commonplace, like when I think about our portfolio of clients, you know, this tends to be that starting position right to you, as long as you're kind of using that to draw a line in the sand. And then, you know, as we get into this a little bit deeper, think about how you use that, to manage your programmes and help develop strategy going forward. So let's think about the different types of data that can help inform and in you making a decision with regards to your programmes. So we've got, you know, three categorizations, descriptive and contextualised predictive are scenario based and then prescriptive. When you think about the far left side of that slide, it's really about getting the fact that that answer that 26% of you said that you were in today, it's understanding where you are today. Where are things going? What are the baseline measurements? And these are things that you would typically associate with benchmarking, because they are they're static, they're point of time, they are their current fact based measures of information. They don't necessarily tell you what could happen, they don't necessarily give you a recommendation in terms of what you should do. They just paint a picture of what is currently happening today. When you move on to the next phase of that analytics component, that's the predictive or scenario based models. So this identifies what potentially could happen if you made changes or you modelled against certain scenarios or situations. So I have a current I'm just going to use benefits because that's my forte, if I have a current benefit programme today, you know, call it a traditional benefits plan design. And I wanted to move to a flexible benefits plant design. What could happen in the event of that scenario? You would do a number of things like look at your employee demographics you would look at, you know what types of programme you have in place versus what sort of programme Are you trying to implement? You may be modelling what that claims utilisation future claims utilisation pattern might look like. You may be also thinking about what your future workforce might look like the portfolio of individuals that you they have working for you their needs, their demands, what are the things that might keep them retained at your organisation and interested in a position with you, ongoing. So those are the things that you might see in a predictive or scenario based model. Prescriptive takes us sort of to that next level. So this is where you use that, that data, to recommend or provide the most effective and most optimal solution moving forward. This is analytics at its best in terms of how it informs and helps manage HR and in other parts of the organisation today. So I'm going to so now that we've kind of set the stage in terms of what's driving this conversation and in bringing up a couple definitions, so we're all speaking at the from the same playbook. We'll move on a little bit to contextualise the data and what good organisations doing and again, I'm going to spend a little bit of time talking about health care, and it's in how analytics plays a role in health care today in Canada. You know, we're faced in the healthcare industry, in HR professionals, the clients we work with, it's a constant, constant conversation, you know, 15 years ago, you would design a plan, and you'd say you'd be good for five years, maybe 10 years. because not a lot was changing. At the time, I think we thought the pace was fast. But fast forward to 2023. And we've got a different definition of the pace of change. Today, organisations are being faced with multiple demands and needs not only from their, CEOs and the C suite, their shareholders, their boards, but also from their customers, their employees, and other stakeholders in the equation. When you look at things like ESG, diversity, equity inclusion, HR professionals are constantly being faced with the challenge of how do I make that story relevant within my employee context. You know, one way you could do that is by diving deeper into the benchmark of where things are, where things are being at, or spent, excuse me, and how things are being distributed. And if you can define what that all means to you ESG DEI or whatever that is the problem that you're facing. This is where you can start to pull on those levers around the data and start to break down where is there relevant information in my plan in my population, with my partners, using organisations like AON or others to help assess this and provide some, you know, lines in the sand and then like to say in terms of where we're at today? Where are things being spent? And how are things being done? Do we have a good sense of, you know, for example, the distribution of spend between the different age groups, are our younger employees utilising our plan the same way as our older employees? Are there specific nuances with regards to geographic locations of our sites, or specific workforce demographics based on perhaps a component of your workforce that works in the assembly line, and on the shop floor versus those that may be in your offices or at a sales distribution centre or something like that. There may be unique needs and unique demands from each of those populations. And, you know, that's what you're seeing over on the right hand side of the screen here is we use this data to help visualise and help create some context for our clients around breaking down and assessing what are the key drivers of spend, including, what are the costs, including what are the conditions that are driving those costs? And what are those things that you can do to help address that, but also looking at what are the influencers of health and health care based on the demographics? So is it again, back to the socio economic or other components of the demographic profile that are contributing to, you know, positive or negative health? And are there programmes that you can implement that might help affect that. And that's really all about kind of setting the stage and understanding how you can use that contextualization of data to better understand where you're at as an organisation. And then where possible, you know, benchmark or using other external factors to kind of set and understand where that where you sit with regards to others in your organisation or region. I'm showing an example here in terms of from our neighbours to the south. And while this is not Canadian data, there, there's a lot of correlation one can draw between what the US is seeing and turn terms of health equity, and, and Canadian health equity. I mean, the one, you know, major nuances that we do have public health care here in Canada. And that does, you know, take away some of the burden on individuals. But nonetheless, there still is a constant demand and a constant need. And, I mean, again, we're in an environment where we continue to see a decline of disposable income, like we talked about earlier, you know, inflation is on the rise, salary adjustments have not been the same and nor do they normally keep pace with inflation, but also the other impacts so healthcare costs, again, trend typically is higher than regular inflation, and has typically outpaced GDP. That's not a new story. But what is new in the current context is that while that is true today, salary adjustments have not also kept pace. All the other components around what an employee will typically spend on whether that's groceries or other health care needs have all gone up in costs. So the ability for somebody to afford what they might have been able to afford previously, is continuously be challenged. We in our US practice, use something we call our heat tool. So it's the AON health equity and affordability tool has shown correlations between this data. And so when we use that, that tool, which uses machine learning and information on just over 1 million lives, we see that there are there's key drivers influencing the future health care expenditure and affordability. And some of these are our age, geography, and costly health conditions. And I think these are, you know, the typical things that we would normally associate with, you know, increase in cost versus lower costs. But we also find some interesting ties and drivers to affordability. And these are things like anxiety, mood and substance use disorders, musculoskeletal conditions, but also a specialty drug utilisation. So it's interesting here. And when you think about that, you know, those who may have the least means in terms of being able to afford some of these things have the greatest number of challenges or the greatest need with regards to addressing some of those conditions. And then understanding like how these drivers impact an organization's population can also shed some understanding in terms of why employees are more likely to avoid healthcare needs. And this can include not going to see your primary care for the physician why some of these preventable conditions like cardiovascular or muscular skeletal disorders are not being treated and therefore finding their place in the workforce. And therefore causing increases whether that's in health costs, disability costs or absences from work. But also less likely to adhere to medications, which means that the likelihood of hospitalisation is higher, but also the likelihood of the aftercare treatment, as a result of that poor adherence is typically higher. And that also increases morbidity or increases disability costs, but also could increase mortality costs, which has, again, downstream impacts not only to things like life insurance, and other things like that, but also to, you know, employment issues like you're going to have to replace and the talent that disappears, whether that's as a result of death, disability or otherwise, is got a lot of the information and insights and knowledge that maybe some of your newer employees don't necessarily have. So there are ties here with regards to not only how you keep your health care, health of your employees, strong, but there's ties to that in terms of what that means in terms of keeping your business moving in the path and pace that you need it to. And then moving on to assessment. Again, we use some of that US data to lead and inform us, right, plus better understanding your own population, your demographics, how your planned design is built, etcetera. You can start to build out a picture and understanding for the impacts of your own population, and how best to start to address the issues that impact you, both on your defensive play but also your offensive play. So how you attract and retain your key talent. So when we talk about things like this, we're there's some basic things you can do. Right, getting the core right, this is the defence right getting your defence, right, find the right partners, making sure that pricing is in the right place, whether that's on your benefits programme, your retirement programme. rounds or whatever the case might be in terms of your compensation arrangements and otherwise, and understanding if those plans, those rewards plans are addressing your organisational strategies and objectives. Next, you know, switching into offence, listening to employees. Again, this is not a new concept, but it's disappeared in the last five years, and we've found a resurrection in terms of organisations who are willing to listen check in with their employees understand what those employees see value means that they have the better ability to take that listening and turn that into solutions, which employees value more, which connects in with the employee value proposition, connecting with your total reward strategy. But you know, also and more importantly, connecting with your business objectives and strategy. So don't always have to spend more to generate more value. These are key things that we do in human capital, whether that's Health Solutions, talent solutions, or what solutions are they on. And then finally, monitoring performance and performance management. So monitoring performance, I'd say you know, that's the defensive play, but performance management is the offensive play, you've got now from point number two, the listening in the connection to strategy. Now it's time to hold your partner's and others accountable, and setting direction for where you need to be in what you need to do. This is how you take your defensive plays, and you turn them into the offensive plays. So I'm going to after that I'm gonna pass you now to Scott and Scott's gonna take us through his portion of the presentation. 

Scott Reithel: Thanks, Joey. And apologies for the connection hookup earlier. Perhaps you can continue to drive. Thanks, everybody, for joining us today. So that's a great overview Joy much appreciated. You talked a bit about, you know, understanding your own population and using that data to drive these decisions. So what I want to do is, first of all, open the next poll. And we just want to get an idea does your organisation use analytics for the following, select all that apply. And you'll see in the poll, it doesn't show it on the screen, there should be a none of the above option there as well. But some of the options were identifying labour needs, examining compensation and pay, identifying skill gaps, making talent decisions. All of the above or none of the above. And if none of these apply, feel free to put in the chat, what you are using analytics for. 

Scott Reithel: Says you know there's a lot of things that you can use analytics for. So just curious out of these options, what you might be interested in, can we show the results? Great! So 37% selected all of the above, which is great to hear. So these are all really good ways to use data and analytics. The second most common was examining compensation and pay. Interestingly, 0% mentioned identifying skill gaps. So thank you for responding to that much appreciated. What I want to do today is so Joey gave that great overview. What I wanted to do is give some concrete examples of how some of our clients have had a lot of success with workforce analytics. So the first thing I want to talk about is pay equity. So it's great to see that a lot of you are already using your analytics to examine pay. Pay can have a really big impact on your organisation in terms of uncertainty. So in this example, there was a, you know, executive level concern for what the risk exposure was for pay equity. The company was not sure if they had a problem. If there was a problem, how bad it was, is their pay transparent, how does this impact ESG reporting and to on top of that the workforce is highly fragmented, so different locations, different jobs, different areas of the organisation, may be doing their own thing, then which can lead to pay disparity for people who are in similar jobs. Joey mentioned you know, you can't just pay people more. Right these days that's pay is not the only thing that is going to impact. How people perceive the organisation? So pay does impact things like fairness. It impacts your DE&I efforts, it impacts transparency. So when talent is scarce, pay is a piece of the puzzle. There's more to it than that, right? If you're not getting opportunities if you have a poor manager, but pay can sometimes be the starting point of turnover and be a key input into that. So there's a lot of reasons why it's very important to focus on pay equity, and your compensation data and analytics are really is the key input to that. So having that data on hand, allows you to perform this type of analysis, it's really important to be compliant with different laws and regulations. Canada has recently passed pay equity laws, and there's very specific reporting policies and ways that you have to report data. So staying on top of that, if it applies to you, if you're a federal contractor, if you have a, you know, so many employees that that you would fall under that, it's really important to stay on top of that. So I'll give you some more specifics. But essentially, what we did with this client is looked at their looked at their segment and groups and use pay regression models. And we use that to really factor in legitimate pay factors and looked at the things that should be driving pay. We looked at different mediations strategies. And then what is driving pay. As a result of the analysis, we found that most of the segments were paying people fairly, which was great news. But there was a significant gender pay gap in one area of the organisation that had to be addressed. So there's specific strategies to address that. We also supported that reporting in requirements of the local regulations. It also enabled a review of the diversity representation of the goal. So it really the pay equity is a starting point to look at what is going on with pay. But there are other impacts as well, and other analytics that can be drawn from that. Go to the next slide. So this is an example of how pay equity was modelled. And you can see that on the left hand side, the raw pay gap is a negative 34.9%. So what that means is if you just compare the pay of males to females, females are paid 34.9% less. That's a pretty big scary red bar and number. But the regression modelling approach allows you to control for things that account for the legitimate pay differences. So when you control for job function, going from left to right, that explains part of that gap. The salary grade explains a lot more of it. So that's where you see a big reduction in that pay gap. And then as you continue to account for things like location, tenure, education, and experience, that difference goes from statistically significant to not statistically significant and very small and negative 2.2%. So, this approach and using this analytical, in more complex analysis allows you to factor in what should be driving PE and to see Is it a real gap, or can we explain that gap? If you go back one sec enjoy. The other interesting thing is that, you know, salary grade is a legitimate factor to explain pay, right, if you're in different salaries, and you increase in grade your pay gets higher. What this does suggest, though, is that females may not be as well represented in those higher salary grades, given this big difference in the pay gap as you account for that. So again, that's where there's not really a problem in pay per se. But maybe it's something that you know, the representation of females across the organisation is something that should be considered right so you get a little more of that insight when you start to account for these different factors. Okay, if you go on to the next slide, please. Joey also mentioned getting to a point where you can predict, you know, have predictive analytics and forecasting. So with us with this regression approach, we can model out what people should be paid Based on the factors that we discussed previously, so their tenure, education will grade there and what have you. So with that we can model what they should be paid, and then provide scenarios based on what happens if we want to fix this, right? So scenario one, we would address people who are lower limit outliers in terms of being, you know, statistical outliers. Scenario two, we would look to eliminate the statistical significance of the difference. So that, you know, pay is maybe there's still maybe a small gap, but it's no longer statistically significant. And then scenario three would be getting to a zero difference. Most clients would aim for Scenario number two, that's really where the courts, you know, and legal guidelines would suggest you look at, but you can model out what that looks like, what is the cost for doing that. And then one last thing I'll mention about pay equity is that this is internal benchmarking. So you can, if you think about your external benchmarks, and pay and paying fair to the market, right, so we have the, we have like the red for compensation surveys. So you can use that to see if you are paying fair compared to what's being done externally, this is more of an internal benchmark. But it's important to connect the two, right? So if you are using that external perspective to set pay, once you make those adjustments and changes, you want to make sure that's not negatively impacting your pay equity. Great. So the next example, is skills. So 0%, in the poll indicated that they're not using analytics to look at skills. Skills are, it's an interesting topic, because it's something that, you know, skills, knowledge, skills, and abilities had been around for a long time, for a while, there's maybe more of a focus on competencies. But a lot of our clients are talking about skills. And a client in particular, had a lot of uncertainty about skills. So they didn't have an idea of what career paths were available in their organisation, how people could move from one job to another. And really, for the sum of their critical roles, they weren't really sure if they had the talent that they needed, if they could upskill talent, or if they needed to hire key talent. So thinking about a critical role, like, you know, a data scientist or, you know, software engineer for a technology company, they have those jobs, but maybe some of those jobs need some specific skill sets. And they just weren't sure, you know, if we have the people who have these skills. So, what you really need, though, in order to define that is you have to identify what the skills are for the roles, right, so you can have an idea of, you know, we want people who can do Python programming. But do you know what jobs actually require that skill? So we help this organisation identify for their key roles, what the skills we're using, using an external approach. So we use analytics to look at job postings, and see what are the skills that people are asking for in the market? What are your peers and competitors looking for? For the same roles? Once we had that indication of what the skills most frequent skills were, we took that back to the business and confirm that with the internal experts, so that they could take that skills framework and adjust it based on their particular needs, or maybe future focus skills. And then we develop the ways to measure those skills. So they can see, you know, do people have these skills? Currently, who has these skills? And if not, what should we do about it? That gives them the idea of what they want to hire for in terms of their job requisitions what they want to focus on for development. We also looked at the proficiency level needed for skills in those roles. So that helps track not only talent in terms of our people proficient, but also, you know, are people progressing in their career so as you move from if you forgiven In Job, family or role, you know, if you think about, you know, a computer engineer, and then more senior computer engineers, that skill set is relatively the same. But the proficiency level that you need, you need more expertise, potentially, and your role gets more strategic and you have more scope as you advance in your role. Another future state outcome is to upload the skills to job profiles on workday, and use the skills cloud to enable career mobility. And I'll talk a little bit more about that in a bit. So taking a step back, skills have become really important in a lot of different areas. And it's really thinking about, you know, first of all recruitment, you know, what, what are the skills that are needed in the organisation? In this has a DEI impact as well as organisations are thinking about moving away from focusing more on what skills do you have, and how that how that is what is really needed for the job. Learning and Development, you know, knowing what skills are needed for the job enables you to create those development plans. Performance management, where you can assess, assess those skills, really articulate what are the expectations for the job and what people need to do to move forward. And then workforce planning is really important because you need to know, you need to be able to project out, you know, do we need to upskill people do we need to go find the talent elsewhere. And then that helps you plan for those emerging skill needs. So not so this is really all important. But if you don't have that skills framework in place from the beginning, it's hard, it's hard to do this. But once you do have it, it really impacts that employee lifecycle. And that is a that is a key part of that retention argument, right? If you have scarce talent, which you want to, you know, what you want to do is invest in that talent, make sure they're building their career in your organisation, instead of looking for those opportunities elsewhere. And this enables you to show them, you know, how they can get there. Next slide. As I mentioned, a lot of our clients are thinking about skills. Here, you see that 79% of firms that were polled, looking to understand and identify current and future skill gaps. There's a big focus on rescaling and upskilling based on the future. And then 52% of firms are using data and analytics to measure talent mobility. So it really is an idea that knowing what skills we need for the future and being agile with skills, right, so being able to quickly, more quickly adapt to what's being demanded and mark in the market. And really the dynamic nature of how jobs are changing and how new skills and you know, new ideas are really coming to the forefront things like, you know, AI and chat GPT and all the all these things that are coming out. And really disrupting, you know, the traditional view of, you know, you could have a competency model. And that might be good for five years. But now it's really more important probably to be more dynamic, and maybe focus on something that's a little more agile, and scalable. Next slide, please. I mentioned the workday skills cloud. And really, if you have a skills framework, you don't have to have workday, a lot of our clients are using workday. So it's a really good example of how organisations are thinking about using skills. But if you create that skills framework, and you can then map that to an HRIS system, or software tool like Workday skills cloud. Once you have that skills framework in place, again that helps you track things and report on things. So you can actually use analytics to not only identify the skills but also track and report out on them. So that if you have your skills mapped to the skills cloud, people can endorse themselves on skills they can have other people endorse them. Work these skills inference based on your experience the jobs you've had to suggest what your proficiency is on the skills. It also will suggest roles career paths, gigs projects. Because if people are putting that into workday in the skills that they need, workday finds that and connects that. And then it also can suggest that next role and create that career path, right that people can see in us. Real quickly wanted to show an example of how this can work using a skills graph. So if we, if we look at our universe of skills, right, so we think about a data scientist, they have certain skills that are required, one of those being Python programming. Once you collect this data on skills, and we do have the ability using a read for benchmarking data, to really look and see externally, you know, what are the skills that people are requiring other organisations are requiring for these jobs, we can see that, for example, Python programming is related to some other things like machine learning and in AI, and then what it's a subclass of, and then also, what are some of the softer skills that are required as well. So using that skills, data and tracking it, you can really start to create these networks of skills, that then can really inform not only how you can create a skills framework, using this data, but also how different jobs may connect, based on these different skills. And real quickly, is because we're running a little low on time, so I'll go through these kind of fast apologies for that. A sample journey, right? So once you have a skills framework in place, your experience today, you know, there's a lack of understanding of gaps, career progression, there's not a lot of career information, you know, support from the manager may be able may depend on the tools that that manager has, right. So once you have that framework in place, that really enhances that employee experience, and makes their what's required for their job, what they're thinking about, that makes it all very transparent, and allows them to really look out and say, Oh, I can get these different experiences, no one's gatekeeping, this information, it really opens up that world of possibilities. Next slide.  

And this, this ties in also to, to what Joey was saying is that, you know, by having this information, you can look at these gaps, right, you can look at what is the labour demand that you have, and what you might predict, based on, you know, some external benchmarks in what your goals are, and then determined, do you need to buy the talent? Do you need to borrow? Do you want to develop tools that will build and bind people to your organisation, and really help boost their experience? Next slide. So key takeaways is, as Joey said, we had to play both defence and offence. In some time, sometimes it's, you know, it's playing both and connecting these things. So skills framework is a great example of this where, you know, you have to build it up to play defence and keep your employees happy. But you also want to use that to build out your future capabilities. So it's a really great play to do both, because it has a lot of, you know, important advantages. Again, that the long term implications that employee value proposition, you know, focusing on not only what you need for the business to, you know, to make the numbers, but also how that's going to impact the employees, right, and how you have to achieve those results to people. So how to make that come alive for them? And using all this different data together, right, looking for those insights, looking for those analytics. Joey anything that you would add? 

Joey Raheb: No, Scott, I think you covered it really well. I mean, you can't win this game without playing a little bit of defence and a little bit of offence. And I think it's really comfortable or probably more intuitive for organisations to jump into defensive mode, protect costs, do all those things, and then not have that line. sight and in terms of the future vision, future opportunity, future growth, right. And then you find yourself as the economy changes a little bit on your heels. Right. So that's why I think it's important to think both defence and offence as you're, as you're going through this. 

Scott Reithel: So I think we have a few minutes for questions. Yeah. 

Jeffrey Smith: Yes, that's right. So yeah, thank you very much, Scott and Joey, for that informative presentation and your insights. And now we will take the last a few minutes to open things up to any questions that have come in for those of you listening in. So yeah, I guess first of all, get right to it since we're up against the end. First of all, really, we have someone asking regarding the data analysis, or sorry analytics and contextualization, can this be done for organisations that are more on the smaller side? And specifically, they mentioned less than 400 employees. But I guess that I can apply for even smaller than that. Oh, yeah. 

Joey Raheb: I mean, let me start in that capacity. Scott. I think on the health side of the equation, it does get challenging once you get sort of below that, you know, 50, 25 employee count, because of privacy and those sorts of things. And foreign lives. I mean, you've got robust data, as it relates to both your demographic population where health dollars are being spent, all that sort of stuff. So yeah, I think there's nothing limiting you in terms of being able to analyse or contextualise data that size. I mean, challenges in the smaller market because of privacy. But there are things you know, that we've done for clients in that size group to better understand whether that's design or typical spend in you know, when you're that that that large, you're typically insured for a lot of your, your programmes. So there's a little bit of de risking that's already in play. But certainly it's not like there's an answer of no opportunity. There are some it's just maybe a little bit limited. I don't know, Scott, if there's anything different on your side. 

Scott Reithel: I would agree with that. I mean, especially in relation of what I spoke about pay equity definitely would apply that probably is enough people where you would fall under regulations. And I think it's still important to think about, you know, that's, that's a smaller size company, but it's also a typical size company, I think what we see, so there's, you know, in terms of things like Radford, so lots of benchmarking and data available. 

Jeffrey Smith: And so how do we create a focus on the data that is available? Like there's, there's so much out there? How do we make sure we're looking at the right components to help make these decisions? 

Joey Raheb: I can start, I mean, I think really go back to something I said earlier in the presentation, it's understanding where you're trying to be, right? Because it's, I think it's natural to kind of start to download, and, and then, you know, try to collect the data. But I think what that can do is create a bit of analysis paralysis in the sense that it may be telling you a bunch of different things. And I think, you know, if I lean on my math background a little bit there is a bit of a hypothesis or, or a component around, what do you want to do? Where do you see yourself? What does the organisation trying to achieve? And then working backwards into that or so what are the questions we need to answer? How do we identify gaps in those in those questions or answers that we have to provide? And then how do we fill that with sort of data and information and insights? 

Jeffrey Smith: Yeah. And just finally, I guess this will be your last question, but is there a difference between pay equity and pay transparency? 

Scott Reithel: Yeah, so pay equity is looking at, you know, is your pay fair within your organisation? So is there a gender pay gap, for example, pay transparency is a little different in that, I know, some states in the US are passing laws about having to be transparent about salary, ranges, and how much a job pays and that has to be in the job postings. So they're related, but not the same. Pay transparency also can extend to how your organisation communicates about pay with its employees and do if you do a pay equity study. Are you transparent about the results or that you're looking at that and what managers are allowed to share? 

Jeffrey Smith: Okay, well, that's just my perfect time. We've just reached the end of our hour here so we will wrap things up. Thank you very much to Joey Rahab and Scott Reifel AON for sharing your time and knowledge for this webinar is a lot of great information there. So I hope our audience enjoyed it and found it very informative. So and again that thank you to everyone out there who was listening. It was great to have you here and have a great rest of the day. Thanks, everyone. 

Joey Raheb: Thanks for having us.  

Scott Reithel: Thank you