In the interest of time, we will just get started and we'll just let people in from the waiting room as the session continues. I would like to start this session by acknowledging the Wurundjeri people of the Kulin nation as the traditional owners of the land where I sit and also take a moment to acknowledge elders past, present and emerging, and extend that respect to any Aboriginal people who are here with us in the session today. Before we do move into the session, I would just like to confirm that the session is being recorded, those of you have just heard that voice or see that up on screen. And this recording is for those in the room to reference later, and we'll also be sharing it with entities who are unable to register to attend today. Along with the recording, we'll also be sharing a PDF of the PowerPoint slides following the session. I will just note for those of you that have been in earlier sessions, we have had some challenges with editing the front and backend of those sessions already delivered, but they will be shared with you shortly. So today we're looking at Indicator 3: Equal Remuneration. You will have heard, I'm sure lots of different terms: pay equity, gender pay gap, salary gap, wage gap. What we're going to focus on today is really demystifying some of the elements around the analysis of the specific remuneration related dataset that you're going to be looking at as a part of this workplace gender audit. A couple of notes before we get into the content of this session, Kathy and I as many of you will know, you'll be very familiar with my roof in the background here, we're your co-facilitators for the session today. We're not commissioned employees, we're a third-party provider on the commission's panel of providers and we're supporting entities to meet various obligations under the Act. As with all workplace discussions of gender equality, I do wanna start the discussion by noting that participating in any gender equality discussion can raise issues for individuals at any time. And if participating in this session or any of our other sessions does raise any issues for you, I would encourage you to contact your organization's EAP provider as a first point of call or any number of those other specialist services that are available, including 1800 Respect or Safe Steps to access further support. As with all our other sessions, please use the chat function, ask questions, note comments. We've got a significant portion of the backend of this session left aside for Q&A. So if we don't pick up your questions then, in the initial stages we'll pick them up then. Please do feel free to come off mute and shout them out to the group so if we've missed anything also. And then last point as we've noted in our other sessions, really the focus on these sessions is analysing your dataset, not those troubleshooting challenges with the template or manipulating the data. And just related to that, putting the context of what we're doing in these sessions, you will, I'm sure all will be waiting wildly, patiently, excitedly for the next version of the commission's indicative reporting template, version three, which is due end of June. So any moment now by the end of next week or we get that late in June at this stage. And that's sitting really within the responsibility of the commission, any questions you have today on the template, we can address some, but we'll really be documenting them, taking them back to the commission. Our role is in the analysis, running these sessions, providing feedback to individual entities and groups of entities and developing narrative guidance document that will be released in July to help with the analysis process once, so you've populated your final version of the indicative reporting template. And then in terms of what happens next with the data that you analyse, that sits also outside the scope of these sessions today. Lots of you I know will be attending gender equality action plan training sessions, which are really are there to help you get from the analysis through consultation responding to your data and the publication of your gender equality action plan. The data, I will note the data that you're populating your version three of the template with and the analysis you're doing, there's no need to submit that to the commission at any point through this year ahead of the 1st December deadline for your gender equality action plan. It's at that point that you need to be submitting your datasets either as an annex to your GEAP or into your gender quality action plan or in uploading to the commission's reporting platform, if that's ready by the 1st of December. But what we're looking at today is Indicator 3. Before we look at it, I just wanna run a very quick poll for those in the session, just to get a sense of who's done gender pay gap analysis of any kind in your organisation in the past, or if this is new to you, just one quick question. Can you see that up on the screen that poll? Yeah. Can other people see that? Are you seeing results come up, Kathy? Okay, I'm not seeing results at my end. Can you just let me know once that comes through?
- Yeah, I can see results, and I can in polling with 97% of people voting.
- Thank you.
- And then I'll share results.
- Perfect, thanks. You may also have to tell me because there's a glitch that's not sharing the results with me.
- Can you say them, Jen?
- I can't, no.
- Oh, okay. Can everyone else see them? I can see Alexis and Mary. Yep, okay, great. So 24% of organisations have previously completed a pay gap analysis, so 10 organisations, 56% no, and 20% were unsure.
- Okay, perfect. Thanks, Kathy. So we can see that for lots of you in the room, potentially three quarters of you, this is going to be new territory, I guess that you're moving into. For those of you that have completed pay gap analysis before, it may be different to the requirements of this workplace gender audit. And a lot of the recommendations do say that you really should, this is something you really should be doing regularly, but perhaps you'll be a little bit further along in terms of communicating the importance of pay gap analysis across your workforce, and making sure that you can have your employees comfortable with this kind of analysis. For those of you that haven't done this before or you're new to it, we will talk a little bit about the importance of how you communicate, what you're doing in your analysis to your workforce, to combat any potential nervousness with this kind of data. So what our dataset is for Indicator 3 is, for only workforce data. We've got no employee experience data that we're looking at analysing under Indicator 3. We've just got our Table 3.1, which is your pay gap data by gender and also Sheet 3a, which is your pay gap data by gender and intersectional identity, so there's a table there for each, there will be a table there for each of aboriginality, age, disability, cultural identity, religion and sexual orientation. For most of you I imagine, you won't have data for, no one will have data for all of those tables as we understand, but most of you may potentially just have age, also possibly aboriginality to analyse. There may be some of you, I think, as we understand who may have enough data to be looking at disaggregating by gender and disability as well. So that's where we are with our dataset. A couple of points I just wanted to note in terms of what we're trying to understand with our analysis before we look at the actual table that we're analysing. And really there is, mainly this is legally employers must pay men and women and gender diverse people equally for work of equal or comparable value. In practise, currently in Australia we see a gender pay gap favouring men for full-time workers across all industries and all occupational categories. And that's based on analysis done by federally by the workplace gender equality agency using ABS data. Nevertheless, even though we know the legal protections, we understand what happens in practise, there's often lots of disquiet, nervousness, concern within an organisation when you do start to see pay equity analysis come onto the radar. And those of you, the one in four of you that have done this kind of analysis before will understand some of those challenges, but what you will generally see as you do your analysis, you talk about your analysis, you bring your analysis to consultation is that the data you find, the data you're looking for, the notion of a pay gap might be rebuffed because of those legal reasons, because of awards banding. And in lots of ways, those structures really do protect pay equity to some degree. We can see in recent VPS analysis, for example, of pay gap data that in departments where there is a bit more potentially of a strict adherence to that kind of hierarchy and banding that the pay gap data does, it shows a reduced pay gap compared to other sectors. But nevertheless across all sectors, people are going to get nervous because you're talking about confidential figures in salary arrangements. And really what's important to remember in terms of your communication, for those of you who are going, those three quarters of you that are going into this analysis potentially for the first time is communicating with your workforce, that in your initial analysis you're really not looking at individual salary figures. The point of your baseline analysis of pay gap data is not to stand two people next to each other, compare their individual arrangements. The analysis really sits at a much higher level than that in this workplace gender audit. And the second point to make really is that in your analysis here on the Indicator 3, it's also important to communicate, to remember that salary gap information you find, you identify is only going to form one component of your organization's response to pay equity. You will be using this information, this analysis to pinpoint and recognise inequities, but the response to that analysis is going to be about looking at a whole lot of other things, not just straight up adjusting people's pay packets, but looking at cultural change, things like flexible work arrangements, balanced workforce composition, equitable recruitment and promotion practises. So it's really important to have that general sense in mind and to communicate that to your staff where necessary as you're working through your analysis because this is one indicator where we do have seen and will see potentially more disquiet across the organisation and concern. So that's our general introduction to the indicator. We will look now at what's actually in your dataset for Indicator 3. As I mentioned, you've just got your workforce data, no employee experience data. So Table 3.1, what that's going to show you is your average annualised full-time equivalent salary gap between genders. So in short, what we mean by that gap here is really the difference between women's and men's average salary or people of gender, self-described gender and men's average salary, and that difference as a percentage of men's average salary. One thing to note here is this table, you can see up on your screen, it is not the same as the table that you currently see in version two of your indicative reporting template. This is what the table is going to look like in the next version of your indicative reporting template. The data you need to input is not changing, but the way it's going to be presented to you for analysis in Table 3.1 is gonna be slightly different than what it looks like now. I just note that for those of you who may be, well, already have had a good look at the current indicative reporting template. So before we look specifically at how you might use this data for analysis, I will just note and revisit where the dollars and percentage figures in this table, the salary gap dollars in percentage figures come from. You don't necessarily need to know this, you don't need to know this, how this backend calculation works, but it is worth looking at briefly for those who are interested and if it does help you when you're communicating with your workforce, preparing for consultation on your analysis, to really understand just the basics of where the figures are coming from. So as you all know, the first step you've inputted, once you're looking at this table, you will have already inputted into your unit level upload in the indicative reporting template those three salary measures: base salary, fixed remuneration and total remuneration. You input those for each employee in your unit level upload, and at the backend the worksheet is then calculating average salary figures for women, men and self-described gender. These won't be displayed in your table, but that's the backend calculation that happens. It calculates two averages, so mean and median, the difference... Mean is your standard average, so if you've got 10 women adding up, the salaries for those 10 women and dividing that by 10 to understand the average salary. Median is another type of average, it's the midpoint. So if you've got 10 women, it lines those 10 salaries up in a row from biggest to smallest, and the median is the middle figure in that list. So they are a little bit different, often you might end up using median because if you've got outliers, so if you've got six women grouped in the middle, and then your first woman and your 10th woman have a really low or a really high salary, the median is a bit more representative in terms of an average of where most women in the group are sitting. There's lots more you can read about mean and median, and I'll share some resources at the end of the session, but that's just, I guess, a simple explanation of the difference of those two averages. So once the worksheet has calculated that, those average salary figures, it uses these average salary figures to then calculate the differences between women's and men's average salaries and people of self-described gender, and men's average salaries. It then populates this table with your full-time equivalent salary gap. That's the figures you're going to see represented. I'll just give a very quick example, I will run through this, it's also going to be in the PowerPoint that we share later. Just as an example, for those that are interested of that calculation I just mentioned in terms of calculating the salary gap. So using these figures, this is for VPS workforce, your worksheet will calculate it within each classification, grouping and employment type, but this is just an example of the calculation. So to calculate the salary gap as an example for the VPS workforce, we know men's median salary, it sits at about 97,000, we know women's median salary, it sits at about 87,000. So if we wanna calculate the salary gap as a dollar figure, simple calculation, you just look at the men's median salary, take away the women's median salary, there's your figure. That's your salary gap as a dollar figure. The salary gap as a percentage, also a relatively simple calculation. You take the men's salary, take away the women's salary, and that difference is then a percentage of the men's salary, so we get that gap at about 10.7%. That's just a very simple example. If you've got enough people who identify a self-described gender, then you would be using the median salaries for men and the median salary for people of self-described gender. So it's two different calculations, one is the difference between women and men, and one is the difference between people of self-described gender and men. It will come up as an in some, you may find in some classification levels, in some sectors that the pay gap favours women rather than favours men. The reason we give the example is because across most, this example is across most occupations in most sectors, the pay gap does favour men. If it happens to favour women, you'll end up with a negative, a negative salary figure and a negative percentage. So looking at, this is what your workforce dataset is going to look like when you're looking at it. So you'll see, it's all by, you'll be looking at salary gap within each classification grouping, so there'll be a row for each classification grouping. So how you have mapped your classification in your organisation for your employees really does influence what you're going to be able to do with your analysis of your remuneration data. So for those of you who have been able to map your classification by reporting level to CEO, then that's how you'll be able to analyse your pay gap data. We'll talk about that a little bit more shortly. For those of you who have not been able to map, fully map your employees classification by reporting levels to CEO from top to bottom, I know some entities are only able to do that at management level, below that they're grouping people by occupation because that's all they're able to do this year, then that's gonna influence how you analyse your pay gap data within each classification grouping. So you'll see the classification grouping. Within each classification grouping, you're going to see a salary gap for full-time workers, for part-time workers and for casual workers. And that's gonna be a dollar figure and a percentage similar to those calculations I mentioned on the last slide. You're then going to be shown two different types of salary gaps. So there'll be a salary gap for base salary and a salary gap for total remuneration. To get a better sense of what those two measures are, take a look at the definitions in the indicative reporting template in the tab for unit level upload and instructions. And it does explain to you what those two measures are, and you will have understood those measures as you populated the template as well. And then it shows, as I mentioned, within base salary and within total remuneration, you're going to see the mean and the median figures. So based on that definition of mean and medium that I mentioned earlier. So you'll be able to see those as well, both on your table for analysis. And then this is just one example of, in Sheet 3a the intersectional tables. So what you're going to be able to see is the same data disaggregated by gender, but further disaggregated by the intersectional identities. So you can see there, this is for the table that is for Aboriginal and/or Torres Strait Islander individuals. You'll see this table for those who identify as Aboriginal and/or Torres Strait Islander, the same column is next to it for those who don't identify as Aboriginal and/or Torres Strait Islander. Similarly for age, you'll see columns next to each other, you'll see this table for each age range, so 15 to 24, 25 to 34, etc. etc. And I just mentioned those two examples because it's likely, most likely that those are the two intersectional tables you might be looking at. I will note that in the current version of the indicative reporting template, all those intersectional tables aren't there, but they will be there and automatically populated in the version three of the indicative reporting template. So a couple of, so when we get to analysing this workforce dataset, what are we gonna to do with it once that table is automatically populated? As we've mentioned in our other sessions, there's a couple of key principles. Really the main one is that you're disaggregating by gender as your primary measure, and you might be disaggregating by intersectional demographics if you have data available. So always gender and then adding those additional measures. And the additional components of the data that we have to reflect on our classification level, as I mentioned, within and between classification levels. If you've classified by reporting level to CEO, you will be able to cross-compare across classification levels, so looking from top to bottom or bottom to top in your organisation. If you've been unable to do that classification by reporting level to CEO, that's going to limit the comparative analysis across different classification levels. You might just be able, if you've been able to map your management levels, you might just be able to compare across those management levels, but there won't be really be anything you'll get out of necessarily comparing occupational levels below that, if that's what you've had to do to map your classification with management levels. And you may not end up looking beyond your management levels with your data this year. And then we're able to disaggregate by employment basis, as mentioned, remuneration type, and then the different types of averages. So what you might, the kinds of things you might be looking for, lots of different questions you can ask as you interrogate the data. I've got a couple of graphs just to show some relatively simple examples, and then some resources I can share with you to guide you of the other questions you might be asked when you're integrating your data. But the kind of things you might do first comparing, looking within a classification group, so choosing either your upper level management or another classification group and comparing your full-time, part-time gender pay gap within those classifications to see if there's any differences there to see whether in part, those working part-time there's a great agenda pay gap, and then you can start to understand what that might mean for different genders if you have more women represented in part-time employment, more men represented in full-time employment. What's going to be the cumulative effect of a much greater pay gap in part-time employment for women, if over time, and how is that gonna to affect their super and things like that. You might then compare, look at your full-time employees across each of your classification levels if you've been able to map by reporting level to CEO and start to compare the gender pay gap across the different levels, so to see if the gender pay gap potentially might stay steady, might be much smaller in your banding levels. And then once you move up into executive levels, you might see that it gets bigger. And then you can start to, once you've identified that, that shift, that inequity, you can start to think about why that happens, what that might mean. And similarly you can do the same thing for your part-time gender pay gap as well. And then we've just got a couple of graphs here to show you before I just open it up to questions that anyone might be asking. A lot of these graphs, they're drawn from the workplace gender equality agency who do a regular pay gap analysis, as I mentioned, based on ABS data, and also as the administers of the federal Workplace Gender Equality Act also produce regular guidance, regular information on the pay gap across the private sector, those that need to report under the Federal Act private sector, but still might be really relevant for you to have a look at to see what kind of information that might be there that might be useful for benchmarking in some way. So what you can see up on screen here is your full-time total remuneration gender pay gap. And the way this is grouped is, you're looking at your management levels. So key management personnel, other executives, senior managers, other managers, and looking at the pay gap, and there's a dollar figure down the right-hand side. This is a graph you'd be able to produce from the data that you have in your table. And then you can also see in the lighter orange here, it's by type of employment, occupational grouping. And for those of you who have potentially mapped your classification in that way, I know across the health sector, I know that's happening. You might be able to use this kind of graph as well to map that. And then here's an example, similar example, I'll just note this example does graph hourly wage, not annualised based salary gap or total remuneration gap by gender and employment type. It's really provided as an example of the kind of information you'll be able to pull from your table, really splitting it out, the pay gap for permanent full-time casual. So full-time casual and part-time employees, you'll be able to create simple graphs like this also to really unpack. Potentially you might see that actually there's a much greater pay gap for full-time employees, as it shows in this example, but you might actually end up seeing that in your organisation as a greater gap for part-time employees at particular levels, at particular classification groups in your data. Again, a graph that you'd be able to create to bring to consultation potentially with your executive or with other staff members, so that they can quite easily visually understand what the table is telling them. And also potentially it's a source of assurance that individuals really are invisible, will be invisible in this data in the sense that it is talking about salary gap data, which is confidential, but it's at a high level in terms of percentages and differences. So it does potentially, showing graphs like this as an example hopefully reassures staff that they as individuals, their confidentiality and privacy won't be compromised in the analysis of pay gap data. And then just one final graph really is just very much as an example showing the pay gap across age groups because you may start to understand that the pay gap does get much larger as you work through the ages. So potentially for those, and maybe that can be mapped to seniority level. You can map that to workforce composition if under your other indicators, potentially Indicator 1, which is workforce composition. If you're graphing workforce composition by age, you might also be able to, if you're graphing your pay gap data by age, cross-compare some of those graphs to see what effect age, gender and age has on the information that you're finding, and what you might need to do to start, if you see that in your entry-level positions in certain levels, particular gender and age groups in particular levels, and how you can maintain, address pay gaps for those individuals through their employment lifecycle at the organisation, and potentially use that group as a cohort to follow, to start to understand what promotion practises, what access to flexible work, what access to other caring and leave arrangements, how that through their employment cycle might affect, exacerbate, reduce the pay gap as they get older and progress through the organisation. But that's just one example of how age might be relevant as in your intersectional tables. I will stop talking now and just throw it open to questions. If people wanna come off mute, or Kathy, if you want to pull out any particular questions that have come up in the chat as we've been going for discussion.
- Hi, just some earlier ones, will the acronyms change in the unit applied? So W for women, M for men, they've already had to change it a few times due to the two templates already.
- It will be W, M and S for self-describe. Is that the question?
- Yeah.
- Yes, yes. At this stage, I have not seen version three, the full version three, so I can't be, I'm not... That's a question that will have to be answered by the commission, and you may potentially need to wait until the version three comes out next week.
- Just some concerns that the mapping of pay data on level to CEO won't give robust data.
- In terms because you haven't been able to, just to make sure I understand the question and also come off mute if you need to, the person who asked that question.
- Oh, it's Mel here.
- Yeah.
- Yeah, I'm happy to talk to it.
- Yeah, perfect, thanks, Mel.
- Well, I attended a previous session I actually had understood that there was choice available, so that you could actually be comparing jobs at the same size because reporting line to CEO doesn't make sense in every organisation. For example, the executive assistant reports to the CEO, but then also directors do, and then there is sort of anomalies like, that as you continue down the line. So in order to compare apples to apples, I would have thought it would be done based on job size, and I thought that we were able to do that, but earlier this session it sounded like you said that you can do that only if you can't report by level to the CEO. So there's two questions-
- Yeah.
- There I guess.
- I'll clarify that just in terms of, you do that only if you can't classify it by reporting level to CEO. What I guess I meant by that is that's the general guidance to do that, reporting level to CEO, but if it doesn't make sense in your, if you can't, by that I mean, if you don't have the data available, also if it doesn't make sense in your organisation to map like that, the commission is encouraging people to map this year, to map those classification levels in the way that makes sense to them. And I would say that reporting level to CEO is the default, do that if you can, but if it doesn't make sense to your organisation, or if you do that, and then you need to do some additional manipulation of data. So that example you gave, pulling out EAs, and so not leaving them in a negative one, alongside directors who report to the CEO, for example. That's also okay to look at that. I think this year, it really is going to be a process of learning for lots of entities and learning for the commission as well once they hear back on the challenges. And I know they're very aware also of those challenges, particularly around classification. So there's not, I guess that's what I meant by if you can't classify by reporting level to CEO, there's leeway there on what that definition of can't is. You may choose not to because it doesn't make sense in your organisation.
- Right.
- Or you may not be able to do it through all levels of the organisation.
- All right, thank you. That's really clear, I appreciate that.
- No worries, thanks Mel, thanks for the question.
- There's a number of other questions, but maybe people might like to come off mute and ask them for themselves. I think it might give a little bit more clarity given where they are against the session content. Jo?
- Hello.
- You put something up earlier, Jen, that showed how you could map the levels to CEO by management and how that went. I'd love if you could put that slide back up again-
- Yeah.
- So I could copy it. I haven't seen any guidance, and that's really useful.
- So was that the example from WGEA?
- Yeah.
- Yeah, so that is, that's not necessarily me saying that's how you should do your classification mapping, but I do know particularly that some health entities are, quite a few are looking at being able to map the higher levels by those key executives, key management, senior managers, things like that. Below that they're not able to because you get into 15 different awards, different occupations, they're not able to group them. So then they're at naming the classification levels by the occupational group. Does that make sense?
- Okay.
- And then I'll leave this on screen for you, but does that make-
- I'll copy it.
- Oh, perfect.
- Could you put the link up to the WGEA stuff because I had gone on and done quite a bit of searching, but I didn't come across this, this is useful.
- No worries.
- Thank you.
- There's a question about, when the recording will be available? Early next week?
- Yeah, by the latest, yeah. I really was hoping to have already shared the recordings from the sessions we've already delivered by now, but I've just had some challenges with editing out some of the things in the beginning. So I'll say by Monday at the latest, but I imagine it will be by Friday after we deliver the final session on Friday on Indicator 7. And apologies for that delay. What we can probably do is, today at least share a link to download PDFs of all the PowerPoints, and then add the recordings there later for downloading.
- Anyone else wanna pop their hand up or come off mute to ask their question?
- Thanks, Kathy, it's Sarah from Alfred. I just had a question that's perhaps building off a couple of others from Mel and Jo. Just whether you are aware of any other advice coming out from the commission regarding the classification levels. Particularly related to health sector, the consensus is mapping to the CEO level, that doesn't make any sense. And I appreciate people can go and do it in different ways, but then there's no consistency, sort of moves the ability to compare baseline data across our sector. And that's a key part of doing it.
- Absolutely.
- So is there any further advice coming out about other ways we can do it before July.
- As I understand it, the commission are focused on the health sector in terms of additional guidance, but I don't know when or what that will look like, what it may actually be is just a summary of what different entities are doing. And I'm sorry, I can't give anymore clear information on that one. And it's only the health sector that I have heard that there may be any additional guidance coming forward in terms of mapping classification levels. Other sectors there won't be, there absolutely won't be additional guidance. Sorry, Sarah, that I can't provide any clear information than that.
- No, that's fine, thank you. I appreciate that, I just wanted to check.
- Thanks.
- Gonna be interested to see what they come out with. I think the health sector is quite connected in this work, and I don't think that anyone has a clear solution yet-
- Yeah.
- That's come up. So it'll be interesting to see what their advice is. Thanks. And also if anyone else in the health sector wants to jump in and respond to that.
- Yeah.
- Please do feel free.
- Yeah, if anyone does have a solution that I'm not aware of, please yell out.
- Jo has raised her hand, Jen.
- Hi, Jo!
- Oh, I thought you are feeling, you might-
- Yes, yeah, sorry, I'm sorry. So I have a question, I don't know if you can answer it, and it's something that needs to, or the others can answer it but, for example, when I've met according to our EDAs, it seems logical to place or the heads of disciplines against each other. So you're comparing the heads of both in my organization's heads of OT, social work, psychology and psychiatry, but that creates very different pay levels because they've got different levels of education and different levels of pay. Given the gender equality, given psychiatrists tend to be mostly male, and social workers, OTs tend to be mostly female, is that a fair gender pay gap that we're looking at? Or should I be further dissaggregating it by education levels? Does that make sense?
- Yeah, no, the question makes sense. Absolutely, I'm just trying to think of the, if whether or not we even have an answer for that one, and guidance.
- My sense is it's a great conversation to have within the organisation.
- Yeah.
- Anyway because of these gendered ways in which those roles tend to play out, and I'd be wanting in an organisation to have those conversations as a starting point. Jen, do you wanna...?
- Yeah, I think so. And potentially it's the chicken and the egg, isn't it? But might inform how you do your classification as well because what your organisation may choose. Okay, these are our priority areas for management, which you can map by reporting them to CEO, if you can. And then other areas, so heads of disciplines or other areas you might think, that's where we want to analyse pay gap data. So that group in classification might be much smaller, much more, you might disaggregate it specifically into three classification, groupings or something, and then everyone else might be grouped together because in 2021 that might be how you decide within what's possible, within your capabilities to map classifications. That's what you're gonna focus on. That's more a general thinking rather than a response to your specific question because I think it's a difficult one to answer without knowing it might be best answered in a longer conversation possibly. And if anyone else in the health sector who is dealing with that similar challenge to Jo wants to add any comment, please do feel free to jump off mute now or type things into the chat.
- Thank you.
- I think that, and Lisa has just added in the chat where is the consistency across the sector then? That's an outstanding question. We share that question, the commission shares that question, I don't have response to it. And it may be that consistency comes in later reporting periods once the commission really understands and the sector broadly shares and understands with the commission, the challenges, and what the effects of that lack of consistency are. It's a great question though with at this stage, no answer.
- And we'd expect to see sort of similar differences in other industries as well, so in the local government sector, you'd think that there may be paid differences or gaps between roles that have engineering requirements and specifications and degrees compared to community development and those kinds of things. So it's a really important part of the conversation, I think to unpack why we value those different roles in different ways and those types of education in different ways too.
- Absolutely. And it's where you might be able to bring at least this year some of the findings of analysis you get in Indicator 7 when you're looking at gender disaggregation to start thinking about maybe in the next reporting period, how you might wanna address pay equity for those gender segregated workforces, maybe down the track, it's just, it's a thought as you start to bring your analysis together across all of the seven indicators.
- Any other questions that we're seeing, anyone wanna pop their hand up and ask?
- Matt here from Royal Melbourne Hospital. Hospitals again are very, very complex, I agree with you, Sarah from Alfred. The difference, why in the unit level upload data, there's a column for base salary. So my understanding is that's the base salary of the position, not the person.
- Correct, yeah, so that's the full-time annualised salary, not their actual earnings, that's correct, yep.
- And then total remuneration is what they actually earned for the whole year?
- Yeah, so it's base salary plus bonuses, allowances, things like that, there's further guidance on what the, in the annex to the guide.
- Yeah.
- Yep, you know that, yeah.
- So why is there a fixed remuneration column?
- Excellent question. I think that the point is that if you're pulling out the fixed remuneration, that may be, it's not data that goes into the calculation.
- Yeah.
- But it may be data that might be used to understand what the additional payments are, what those fixed remuneration payments are in later reporting periods or for the commission to analyse. But you're correct in your understanding that it's not used-
- Okay.
- In the calculation that goes into your reporting table for Table 3.1.
- Okay, okay, I think I got it. Thank you.
- It may be that it was going to be previously presented in your reporting Table 3.1, but not, at this stage it's not being used this year.
- Okay.
- For your analysis.
- Just, yeah, hospital's ABI's, there's like 22 different ones, and then we've got so many different pay types. I just wanted to get that proper understanding between fixed and total.
- Yep.
- Amy, he is just asking, so do we still need to include fixed remuneration if it's not being used?
- It's still required in the unit level upload. As far as I understand, it's absolutely still required, but wait, let's wait until we see version three next week.
- Do we remove people on work cover?
- I have no... That is not a question I can answer. Has anyone else come across that problem, had advice from the commission? Otherwise we can take that one to the commission.
- Given that no one else seems to have the answer. What about if somebody or we're also adding on service leave as well we pull them out.
- We will take these to... If anyone else has any additional questions on who, if they should be removing anyone, just pop them in the chat now or come off mute, and we'll take that as one question to the commission to hopefully get a response for you.
- And some councils share resources across councils. How do we include those people? So maybe multiple councils might contribute to a role. Is it the lead council? Is there a lead council, Amy?
- Yeah, I believe there is a lead council that is responsible for the rem.
- Yeah.
- But the resource is shared by time, so potentially we're doubling up across entities. However, internally not, and then whether we have to work out their equivalent EFT.
- Are they just in one payroll system though? Are they just in the lead council's payroll system?
- Yes, but they're in the HR data of both, I would presume, and they can be significant roles.
- Okay.
- Jen, anything to offer on that one?
- I'm just trying to think. I haven't had specific guidance on that, but I'm trying to think of other examples that might apply in terms of shared resources across the entities, but there's not really any that I can think of that would apply specifically.
- Some in the health sector. Yeah.
- I can also see lots... Yeah, that's a question that we'll also have to take to the commission, and I can also see lots of different things coming up about exclusions and inclusions. We will list these out. I'll put them all together in one email to the commission in terms of excluded, included; excluded, included. So we can hopefully get one response to that, that full set of questions. Please do add, keep adding in the chat, so that we can document that to bring to the commission as one question.
- Do we have an answer, Jen, on the multiple intersectional questions? So if you've got multiple cultural identities, how do we capture that as it only caters for one per person?
- At this stage, there's no, the commission has that question in their design and troubleshooting of the template, but at this stage there's no response on that in the indicative reporting template. In your People Matters Survey, for people you will have also, you all are completing that, there's the option to provide multiple responses to that, but in workforce data table, you're still correct, there's only an option to provide one response. It may be shifting in version three, but I'm not sure. I don't know.
- Do you want me to go through any of the other inclusions and exclusions in general? Do we just take it that we'll take those ones we can't answer on notice for a combined response to the group? Yeah?
- I think that we'll take that approach, yeah.
- If there are any other questions... I'm sorry, Kathy.
- No, it was an identical question. Anything else apart from inclusions and exclusions noting that obviously that's where everyone's focus is given June 30th's imminent approach.
- Yeah, hi, it's Amy. Oh, sorry.
- Hi, Amy, oh-oh.
- Sorry, keep going, Amy.
- Amy, yeah?
- Okay, sorry, I just checked it in the chat around calculating rem for counsellors when it's an allowance.
- Hmm. Yeah, I'm quiet on that one because when I'm in conversations with the commission for your governing body, it's been when the general consensus has been, there will be gaps there, and you may not actually be providing anything, but gender for your governing body. And that's probably the guidance that I would suggest there that they actually don't have a figure in there.
- But doesn't the guidance materials say that they are to be included in the Indicator 3 that we do need to report on governing body for both Indicators 1 and 3?
- I am not sure, sorry.
- Is that, does it say that? Does it say that?
- Pretty sure, otherwise I wouldn't be worrying about it. Sorry, I'm...
- No, no, no, it's a perfectly reasonable question. No, no, absolute, yeah. I don't have the guide open on my screen, but I imagine it is because that's where you've read it.
- Yeah.
- But that's, we'll have to take that back to the-
- Okay.
- Commission as well in terms of the way to report that. Kathy, do you have it there?
- Do have a are we looking at the measures because or you're looking at the indicative reporting template? Sorry, are you looking at-
- In the measures, in the actual guide, yeah.
- Well, I can't see it in there.
- I don't have it open.
- For number three, there might be in maybe a definition somewhere.
- Okay, sorry, I'll go back and if I find it I'll shoot it through.
- Yeah, exactly.
- Absolutely, yeah, do follow up on that, Amy, because my understanding was also what Mel has noted there in the chat that as they're not employees, they don't need that data, but absolutely please do. We'll have a look after the session as well, and, Amy, please do follow-up on that.
- Yeah, great.
- I'll add it as a question anyway to the commission.
- Okay.
- But the response may be that, yeah, they're not employees, so you don't need that pay data, but we can-
- Thanks.
- Check up on that for sure.
- And while I have you, can you go back to the other slide, the graph before the one that you have available?
- Oh, yeah.
- Oh, maybe...
- This one?
- Yes, that one, please.
- Yeah.
- Thank you, the question I was asking earlier on is just a small technical one regarding the indicative reporting template.
- Yeah.
- Will there be a summary, mean, median for each of the classification reporting levels, which would allow you to do the data for all?
- Yeah, at this stage, not on the version that I've seen, it's only by full-time, part-time casual.
- Hmm.
- There isn't at this stage and all, but there may be in version three. I can confirm there will definitely be salary figure and percentage for full-time casual and part-time. I don't know if there'll also be a summary at all for each classification grouping. At this stage in what I've seen, there isn't one.
- Okay, thanks.
- [Jim] Just a question from myself, it's Jim here from SRLA.
- Hi, Jim, yeah.
- [Jim] So I appreciate obviously we've asked a number of things in your collating needs and going to seek this from the commission. Do we have not to hold you to it, but do we-
- Yeah.
- Have an ETA when we might get a response on them?
- It's really dependent. So what we've been doing is grouping the questions and sending them on after each of the sessions. Once we do the-
- Yeah.
- Final session on Friday, Indicator 7, we'll also collate them into an FAQ for all of them, for the commission to then fill in the gaps and respond. We'll send that to them on Friday afternoon, but I can't really give an ETA when they might be able to respond because I know their focus at this stage is troubleshooting the template and getting version three out there. But, yeah, apologies, but Kathy do you have-
- [Jim] No, that's fine.
- Yeah.
- It's just because some of the responses sounds like it's going to inform how we input the data into the template-
- Yeah.
- And undertake the analysis, which then obviously it's got the dependencies onto each consequence steps, so yeah.
- Yeah, no, it's an excellent question. And I'm sorry that I don't have a more expansive answer. Probably I know that some of the questions that we've already passed on will actually come through as part of version three, so they're being responded to in that way.
- Okay, yep.
- So they are, you will see some, the responses to sector wide or organisational challenges-
- Yeah.
- You will see a response there in the new guidance, but not for all of the questions that have been asked.
- [Jim] No problem, thank you.
- Thanks, Jim.
- It's Lisa here, I just want to ask a question just to clarify. So if we are extracting the data by the 30th of June, but that data doesn't have to be really, is attached to the gender equality action plan that we submit in late November, early December now.
- Yeah.
- So we will have time within that between June and December to actually rework analysis if more guidance comes up. Would that be correct?
- Absolutely, time to, so you'll be extracting the data probably after 30 June. So based on that point in time, 30 June. So through lots of entities will be doing it-
- Hmm.
- Through July, actually populating the template, but then exactly that you will have that time to do some checking, do some verification and checking of your data, and it'll inform your analysis. And even through your analysis and consultation, you might find that there's quirks and things in the data potentially as well, but you're absolutely right, there's no need to submit anything, you don't need to have completed all your checks on that table in terms of privacy, things like that.
- Hmm.
- To submit to the commission until December, 1st of December, yeah.
- Okay. So I'm tipping, then we might have more guidance throughout that time space as well from the commission on some of these questions that are being raised today.
- Yeah, I would say that really the key guidance is going to come with the release of version three of the indicative reporting template. And then I imagine the intention after that would not be to provide any guidance in terms of shifting what we know from version three. It might be just more further, further detail that might help in the analysis of the data. So I wouldn't be, I'd probably give that answer because I wouldn't be worried if you get version three of the indicative reporting template and the updated guidance, you do your data extraction and populate that template. Don't then be worried that guidance might change after that, it's probably why I would highlight that.
- Thank you, there's only so many times you can pull out your data and change, yeah.
- Absolutely. Yes, indeed. If there's no other questions, we-
- I've got another question in the chat.
- Oh, thanks.
- That might be one that you're taking forward, and it's about whether over above... Sorry, over what allowances are included in annual base salary or not.
- Okay, we'll record that to on the inclusions and exclusions also to on the questions.
- I'm not, I won't. I prefer to leave that with the commission just to give the specific answers on inclusions and exclusion, inclusions. The cap on the number of sessions, we cap it because that's what was in account, we cap it for Zoom reasons. And also just to make sure that this is just responding to the question from Joanne in the chat, but they're capped really just to make sure that people do get to ask questions and have them responded to is the reason for the cap. We do know they have sold out quickly, the commission knows how quickly they've reached capacity, and they may look at providing funding for additional sessions in July, at this stage nothing confirmed, but based on the popularity of the sessions, they may look at providing funding for additional sessions. And really those sessions then would be similar, but based on confirmed indicative reporting template and people will have already populated their templates and might be having additional questions on analysis. That last question I don't quite, for us the state is different. Oh, that's actually a question that's come up, so where people, where it's been the last pay period, it may not be, your pay period might not end on 30 June, but it is that last pay period to 30 June. And it's a question we've raised with the commission also as well if there's additional guidance they can provide to clarify that. If I understand that question correctly, is that the question that where the pay period doesn't end on 30 June?
- Yeah, thanks, Jen.
- No, you're on to that, correctly known as I was just there wondering because for us every year it's different. So it'd be 23rds or 24th, so.
- Yeah.
- So that's what I was wondering.
- Yeah, so is that last pay period?
- Yes, and I understand that that relates to the Indicator 3, but what about all the other measures? Do they need to then link up the same date or it has to be 30th of June?
- That is an excellent question. From the guidance, it says, it's 30 June, so the financial year it's 30 June, but I guess if you're looking at things like higher duties arrangements or promote that, it may be to whenever the last pay period ends. That's one I can't answer though, I'll need to check on that. It's a question that actually hasn't come up in any of our conversations.
- Cool, no worries, thanks, Jen.
- We'll add that to the list.
- I was just starting to do my mapping of the measures before so, and that's what I kind of looked at the template in more detail and I thought, hmm, that's a question I should ask you.
- Yeah, thanks, Sandra. And also that question from Brent in terms of the last pay period includes a public holiday. It's also one that's come up, and that the commission are looking at as well, whether it's at this stage go with that last pay period as per the guidance, but we have raised that question, that's the casuals. It does shift pay, it's not necessarily representative if we've got a public holiday in there. 20 June, yeah. We'll come, well, that's another thing. I'm just seeing that question from Lisa on, their pay period ends on the 20th of June. We'll come back with what the commission says on that one. We may end the session now, though we've gone a little bit over time. Just confirming, we'll share a recording and we'll share the PDF of the PowerPoint. I'm also conscious I said, I mentioned I would put some links into other resources. What I will do is when we send out the PowerPoint, I'll add in the links there to the Workplace Gender Equality pay equity resources and the Fair Work Commission pay equity resources. Those are probably the best two sources of additional information. Otherwise we may close off the session now. I will stop the recording. Thank you also to all of you for your patience in the delay of this session, that was originally supposed around last Wednesday. Thanks all for your patience with that.
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