- [Jen] This is a recording of Workplace Gender Audit training delivered by consulting partnership, GenderWorks Australia in April and May, 2021. This training was funded by the commission for gender equality in the public sector. And it's been designed to build the capacity and confidence of Victorian Public Sector entities as you work to meet your auditing obligations under the Gender Equality Act 2020. So this file is the third in a series of five recordings and this particular recording focuses on step three of your workplace audit process, collecting your workforce data. My name's Jen Branscombe, I facilitated these sessions along with Kathy Oliver and we're principal partners at GenderWorks Australia. We deliver these sessions to more than 200 defined entities across Victoria and session materials have been designed to meet the varied needs of these different entity representatives. So your Workforce Data, as a reminder, is the data you're already collecting in your internal systems. So we'll be looking at what are the specific data measures that you need to report on, how you might approach your data collection capabilities assessment to meet the requirements of the Workplace gender audit, and why some of these areas we're looking at are important for gendered analysis. So to guide you in the collection of your workforce data, there's two key documents produced by the commission. So the first is the regulations, the Workplace Gender Audit guide, 2021. You can see the cover of that document up here on the screen that's available for download from the commissions audit website and what the workplace gender audit guide defines is the data measures that you need to be reporting on under each of the seven indicators. It also suggests an approach to preparing for data collection. We've also got the second document, which is the indicative reporting template. That's an Excel document at this stage, also available for download from the commissions audit website. It's currently in version two, and we do know that there is a version three coming likely in June this year. It's also going to be replaced later in the year by a reporting platform, which is under development with the commission, but at this stage, the Excel format indicative reporting template defines the way that you're going to need to upload your data that you extract from your system. So we'll take a bit more of a look at that through the session today. The final thing that we're going to discuss in this workforce data discussion is gendered analysis under each of the seven areas, the seven audit indicators and why it's important. So we'll be looking at what you might be looking for in the data you have once you've populated your reporting template, the kind of questions you might ask and how you might initially start to think about approaching this analysis. Just as a side note, this is not an analysis training and also one other thing we won't be looking at is, the specifics of data manipulation, how you might design reports and extract data from your system or how you might need to manipulate that data to match the requirements of the reporting template. We will touch a little bit on the reporting templates setup but not on any Excel techniques in particular. So the first thing we're going to look at is, planning for data extraction. So if you do take a look at the workplace gender audit guide, which I mentioned in the previous slide, you will see there that, it outlines a few key steps in data preparation. So after you've appointed your data custodian, looking at mapping the required data measures with a data source, establishing a process and timeline for data extraction and identifying any risks and challenges and resolving issues throughout this process. So what this might look like in practise in your entity from our experience is really that it is best to approach this task with a working group method, I guess, looking at making sure that the burden or the challenge or the discussion around data extraction is not sitting on one person's shoulders, but that you're really approaching this task as a shared responsibility. So you'll remember that Kathy talked about in step two, when she looked at engaging your systems holders, making sure that you are engaging all the different systems holders that are responsible for data under each of the seven indicators, presenting on the requirements, getting them up to speed in the beginning, to make sure that they're aware of what their requirements are and how they need, what format and when they need to hand that data off to the data custodian off to those responsible for gender analysis. So when you're starting to do your capabilities assessment of your data collection, what you really gonna be asking to start with is, for each indicator is the required data available? The important thing to note, I think is that, if it's not available, it's not necessarily a compliance issue for 2021. What you will need to do is make a note of that GEAP and look at actioning that GEAP in your Gender Equality Action Plan. So look at making sure that you're including strategies or actions to be able to improve your data collection when you get to your next reporting period in 2023, 2025 and beyond. If the data is available, you're going to start looking at needing to document the process of extraction and completion of the reporting template. So when you're looking at that process of extraction, there's a lot of different questions that you do need to be asking yourself. And some of you who are much further along in this process will be really keenly aware of these questions. But we do know that in our pre-training survey, quite a few entities noted that they were really just becoming familiar with the audit requirements. So we're really gonna step through some of the questions that those entities, those of you who are just starting out on this journey might need to be asking yourself in planning for extracting your data. So some of the questions you might ask are, which system holds which particular piece of data is it a computer system? Is it on paper? Is it a mix? Who's going to extract the data? So can a report be designed by someone in IT? Can the report be designed by the systems holder and how long might that take to design that report and extract that data? Is it a simple case of an automated report or will someone need to spend some time manually extracting the data and then manipulating the information that's extracted to make sure it matches the requirements of the commission's indicative reporting template. Other questions you might need to ask are around data storage. So where will the data be stored once it's extracted and getting ready to be reported to the commission, particularly for sensitive data until it's de-identified, you're going to need to be thinking about who has access to that data and systems, for example, for capturing sexual harassment incidents or family violence, leave uptake might have their own privacy protocols in place, but how are you going to make sure that any data that leaves those systems is also managed sensitively in confidentiality before it's de-identified and reported to the commission under the requirements of the workplace gender audit. Other questions you might be asking related, who's going to de-identify the data, will it be the data custodian, or will it be different systems holders who are going to need to do that? Who's going to upload the data to the reporting template? So will it be one person who's going to have the data skills to manipulate the data, make sure it satisfies the format and requirements of the indicative reporting template, or is that going to be something that's a shared responsibility across systems holders. Who's going to perform data quality assurance? Again, will that be your data custodian or will it be a series of individuals? And then who's going to take on the data for analysis. So we know that in some entities, it might be one and the same person who's going to be working to support systems holders to extract the data and then taking on the data for analysis. But in lots of other entities, potentially larger entities, you're going to need to think about who you need to have in the room to get that data ready for analysis. Do you need the systems holders to be able to explain what's in the spreadsheet to support those who have the gender expertise to do the analysis, or can it be done in a staged way with each person handing data off to another person, to then hand off to another person? And through this whole process, you really need to be asking, what are the privacy concerns, risks, and challenges that need to be considered? So lots of questions that you're going to need to be asking. And we don't really, you know, we don't share these questions with the intention of overwhelm or to concern people, it's more about really, once you start to understand these questions, understand how your entity responds to these questions, you may start to get a better sense of the allocation of resourcing required. So in terms of human resources time and potentially the financial implications of getting this work done. So when we get to the next step of the process, populating the reporting template, it's gonna be really important just to make sure that all those involved understand the requirements of the reporting template on a high level big picture understanding there's really two methods of populating the reporting template. The first method is for four of our indicators. Indicators one, two, three and seven. So what you're looking at needing to do to meet the reporting requirements, the indicators one, two, three and seven is complete a single unit level upload. So what that means in practise is that you need to upload to the reporting template a single Excel file, your unit level upload, that includes a line for each employee and employee data for each line against a series of 10 additional measures. And we'll talk shortly about what each of those 10 additional measures are. But once you do complete that single unit level upload, the reporting tables for indicators one, two, three and seven will be automatically populated based on content that's provided, included in that unit level upload. The second method of populating a reporting template relates to our final three indicators, four, five, and six. And for each of these indicators, you're going to just need to complete a series of individual tables in the reporting tabs for indicators four, five, and six. What I'll probably note there is that, the key reason to highlight these different methods of populating the reporting template is that, for that second method indicators four or five and six, it will really be possible for you to take a divide and conquer approach. So you can sit separately with indicator four, work through what you need, manually complete the tables in that tab, similarly for indicator five and indicator six. But for that first method, the unit level upload, you are going to need to make sure that you allocate some time internally to pulling the various data from potentially multiple systems and collating that, manipulating that into that one single unit level upload. So it might take a little bit more time, depending on the sophistication of the systems and the number of different systems you have at play, which are holding the data required for that unit level upload. So for the unit level upload that I mentioned that satisfies the requirements for indicator one, gender composition of all levels of the workforce, indicator two, gender composition of governing bodies, indicator three, equal remuneration and indicator seven, gender segregation within the workplace. So what we're going to look at now is the series of measures, data measures that you need to include in your unit level upload to satisfy the requirements for these four indicators. So the first one in your unit level upload is a sequential number for each employee. So the important thing to really note here is that you need to make sure you don't include in this column or elsewhere in your workforce data set any unique identifiers that could be used to identify employees individually. So for example, a unique identifier from a payroll system. What your defined entity will need to do is keep a secure record internally, which maps the sequential numbers for each employees in this column, in the unit level upload back to your unique employee identifiers, to make sure that really, purely for the purposes of rectifying in the future any errors that arise in this workforce data set for 2021. The second column that you need to include for each employee line is Level to CEO, and that is known as classification. So it's the grade or level of the employee within the defined entity. For the purposes of this reporting, we're looking at the classification system of zero for CEO or director and moving through minus one, minus two, minus three, and continue until all people have been captured. Additional guidance from the commission notes that, if your defined entity, for example, has an existing enterprise bargaining agreement, which incorporates its own classification instructor, which structure, which sets out the levels of the defined entity, then they do recommend you use this for your existing classification structure as a basis for this column on reporting levels to CEO, really, to avoid duplication. Through our discussions with lots of entities in this session, we do know that there is a lot of outstanding questions around this mapping of classification, mapping of reporting level to CEO, particularly when we're looking at, for example, health sector entities who have a number of different awards at play and trying to make sure that they map these classifications correctly and in a meaningful way. And this is an ongoing conversation with the commission and there may be additional guidance that comes through from the commission on this measure. The third column that we're looking at in that you will need to provide in your unit level upload, is gender, which we've talked about briefly in the session already. So the acceptable measures there in that column are woman, man, self-describe or prefer not to say. We do know as already discussed that lots of entities may not be able to provide full and complete data for all these gender options. And they may, at this stage only be providing data in the binary. So a woman or man, and some may also be in their own systems, only able to capture male and female at this stage. So what you need to be providing this year is the data that you do have available. The fourth and fifth measures are really standard workforce data. Collection measures, so looking at employment type, full-time, part-time casual, ongoing fixed term casual. The next three measures are all salary measures. So if you're looking to support your payroll systems holder with completing the figures in the unit level upload for these three payroll measures, clear definitions are provided in the annex of the commission's workplace audit guide. So you can take a look there. There's also some additional definitional information in the indicative reporting template. If you have a look at the tabs unit level upload and the tab acceptable measures. But in summary, we're looking at base salary. So full-time annualised salary specified in the relevant award or agreement, fixed remuneration and total remuneration. And again, there's further information on those, the definitions for those measures in your workplace audit guide and the indicative reporting template. The 10th measure we are looking at is occupational category. So the regulations are asking you to map your occupational categories to the ANZSCO codes. And that mapping has been done to ANZSCO codes, the Australian and New Zealand Standard Classification of Occupations for a number of Victorian Public Sector entities. But we know that it hasn't yet been completed for all sectors. We're awaiting additional guidance from the commission for local government sector. And some health sectors are still working through their mapping of ANZSCO codes to occupations. You can find additional guidance on ANZSCO coding guides from the VPSC on the VPSC's website. And the final measure that we're looking at, you need to include in your unit level upload is a governing body measure. So stating whether a person is a member of a governing body, a chair of a governing body or not a member of a governing body. We have had lots of questions from entities where they don't necessarily consider their governing bodies, so their board, their council on the payroll, so they won't be able to extract data for their governing body in the same ways that they would be extracting data for other employees. So there might be some additional manipulation here that needs to be done to ensure that that column is completed from members of your governing body and to check what other data you're able to complete in the unit level upload for those lines that relate to members of your governing body. We will briefly touch on that again when we look at the specifics of indicator seven, indicator two, sorry, which looks at composition of your governing body. When you do look at your unit level upload, you will see that there are also an additional six columns on the far right hand side for you to report on intersectional measures. So these are those measures we already discussed when we're looking at audit requirements. So looking at Aboriginality, age, disability, ethnicity and race, religion and LGBTIQ identifying. If you are looking for further guidance on the reporting options under these intersectional measures, the best place to look is in your integrative reporting template and either the instructions tab or the acceptable measures tab. So if you take a look at the instructions tab, there is some guidance on the definitions of these measures and also the options that are available for you to report on. For all those measures where you don't have any data, you do need to include an N in this column for those employees, which denotes no response or not collected. There is also the option for all of these measures, prefer not to say, if your employee, you do collect this data, but your employees prefer not to report against this data in your systems. And then when you look at the acceptable measures tab in your indicative reporting template, you will see the range of other options that are available to report against. So for example, if you're looking at cultural identity in indicative reporting table in the acceptable measures tab, you will see that there is a list there of 15 different options, plus I prefer not to say, or an N, not collected that have been widely consulted on. And they may change in the future as the regulations are updated, as the indicative reporting template is updated, but that's what the acceptable measures are for 2021 for your reporting data set for 2021. So what we're going to look at in a little bit more depth now is the content of each of these indicators that are covered by your unit level upload, and start to ask some questions about, how you do gendered analysis on the data that you're going to be capturing. So we're looking at indicator one, as a reminder, gender composition of all levels of the workforce, indicator two, gender composition of governing bodies, indicator three, pay equity and indicator seven gendered segregation within the workplace.
- [Kathy] Indicator one is gender composition of all levels of the workforce. The data that we're looking to report on here is for each individual employee across the organisation. You will need to identify and report on gender for each employee as either woman, men, self-described or prefer not to say. We know that many organisations are currently collecting along the lines of male, female or other, or that some can only do male and female other than making assumptions based on titles, such as, Mr. Mrs, Miss, for example. At this stage for the audit reporting phase in 2021, you will use the information that you have available. However, you will need to consider how you will improve this data to accurately reflect the gender of your employees moving forward. This can be included in your Gender Equality Action Plan as a strategy for improvement in the immediate future. The second measure that we will be looking at will be the classification of each employee. So that is looking at the level an employee sits within the organisation, your CEO or your head of business would be zero and each subsequent level below the CEO will drop down by a negative one and beyond. So for example, a director of an organisation who reports directly to the CEO might be a negative one. The next level of leadership, for example, a manager may be a negative two and so on. If you have an existing enterprise agreement, which incorporates a classification structure and sets out the levels of your defined entity, we recommend using existing classifications to be the basis for your reporting levels to your CEO. This will avoid you duplicating work that has already been collected. Your third area for collection is around employment basis and looks at the ongoing arrangements that your employee has with the organisation as to if they're full-time, part-time or casual or on an ongoing fixed term or a contract. And additionally, you will also need to report where you have information available around intersectional attributes, such as Aboriginality, age, disability, ethnicity and race, religion and sexual orientation. This is what the indicative reporting template looks like. So your single unit upload will report all your information from each employee and upload it automatically to the sheet for you. So you'll be able to see all your employees at a particular level, the numbers of people based on their employment basis and on their agenda as well. So just thinking about why we collect gender composition at all levels of the workforce and why this is so important, when we don't have gender desegregated data workforce composition, we can't see if people within our organisations are experiencing organisation in different ways. So for the example on your screen refers to local government, and we can say that women are not equitably represented at any leadership level, with the most significant being 41% is counsellors, 40% as managers, 38% in executive roles and 29% as CEOs. When we start to reflect on this, we can unpack the barriers to women achieving equitable leaders of leadership across organisations, and develop missions and strategies to rectify this. By collecting this year on year, we can start to see trends across organisations and in particular roles in areas where people of different genders are or are not represented. We can also start to consider other aspects of people's identity to see if we've got additional information missing within our organisations. So that the information on your screen does not articulate the number of women with disabilities, Aboriginal women or women from different cultural backgrounds or gender diverse people who are in leadership roles in local government. And this might be because we don't have the information currently or we may not be collecting it, or we may not be reporting on it. And it's important to have these conversations across organisations about why the data doesn't exist, or if the data does exist and they're not representative of people within our community, why there are barriers to people, different identities, achieving leadership roles within organisations. The second indicator that we'll be looking at is the gender composition of governing body. The governing body will most likely be your board committee of management or council if you're in the local government sector. So you'll be needing to report on the gender of each member of your governing body, whether they are a woman, men, or self-describe or prefer not to say. Additionally, you will also need to be collecting on the role which they have within that governing body. So a member or a chair, and for chair, that's also equivalent to mayor in the local government sector. And additionally, where information exists, you will also be required to collect on into the sectional identity factors as well. So many issues to think about when you are collecting information from your governing body, particularly if they sit outside your existing organisation structures is how have you communicated to your governing body the Gender Equality Act 2020 and the use of their information and their inclusion under this act, and how you collect any information from them, how you enable them to self-report on aspects of their identity, and how are you communicating how that information will be used in their privacy upheld, because given the small numbers of board membership, people may have very justifiable concerns around privacy and it's really important that you've considered these well in advance. This is a little bit more of a simple looking table than the previous one. So you'll see that you'll be required to report on gender with a head count against each of those roles, chair or other member. And this information will then be available for you to analyse and use as you develop your strategies to go into Gender Equality Action Plan. Why is gender desegregated data so important when it comes to gender composition of governing bodies? Well, it enables us to track information across time. What we do know is that, historically, women have been underrepresented within the boardroom and as councils within the local government sector. The example that we've got on your screen does refer to the local government sector. So we can see by tracking that information, that in 2000, 26% of counsellors were women and in 2016, this had risen to 38%. And by 2020, of the 272 who stood for local government, women who stood for local government, a total result was 43% of counsellors were women. So that's a substantial change between 2000 and 2020. We also know that in terms of mayors within the local government sector, we've seen a significant increase between 2000 and 2016. It went from 19% of mayors as women to 40% in 2016. And we also know that in 2020, 28 successful members identified as LGBTQI and six as aboriginal. So we're starting to see increased diversity of representation. And if we don't have this data, we can't track that to make sure that we're continuing to improve over time and that we're seeing greater representation from across our community.
- [Jen] Our third indicator is looking at equal remuneration for work of equal or comparable value across all levels of the workforce, irrespective of gender. So we're looking at remuneration data by gender, classification and employment basis. One key thing to note here on the data measures, you can see up on the screen that remuneration measure average full-time equivalent salary gap between genders is not something that your payroll systems holder is going to need to calculate themselves. We did talk earlier about the three payroll figures that need to be calculated to be included in your unit level upload, based salary, fixed remuneration and total remuneration. And once those are included in your unit level upload and the reporting tab for indicator three automatically populates, that calculation is automatic also. So you will see in your reporting table for indicator three, that we'll look at shortly, that calculation will be done automatically. And you'll see there, the average full-time equivalent salary gap between genders. If you do wanna have a look at how that calculation is made in the background, you can take a look at the annex or the appendix of the workplace audit guide, which provides a little bit further information on how that calculation is made. I think probably a couple of other quick points to note here in terms of pay equity when you start to have conversations with your colleagues in your workplace and start to look at beginning to analyse the data that you do come up with through the audit. One of the first things that you might receive in workplace has pushed back on, I guess, related to pay equity, is that, the pay gap doesn't exist for lots of reasons because it's illegal or because there are awards in place and things like that, but there's a really clear distinction to be made quite practically in response to kinds of comments, I think. So the first point to really make is that, that notion of equal pay that being the right for women to be paid the same as men for doing the same work or work of equal or comparable value, that's correct, it is illegal right and it was one decades ago back in 1969. But that notion of equal pay is quite different to the gender pay gap, which in practise measures the difference in a workplace, in an organisation between the average earnings of women and men in the workforce. And that's caused by a range of social and economic factors that do combine to reduce a woman's, for example, earning capacity over time. And it's really important to make that very clear distinction, that while equal pay is illegal right, that has been one, the enabling environment and the different kind of pressures and practises, policies and processes in workplaces don't necessarily mean work at this stage to enable that legal right of equal pay and we do still see the gender pay gap across workplaces. The other thing to note before we move on to looking at the reporting table under pay equity indicator three is that you are also asked to report on these intersectional measures where available and there will be a reporting tab for those intersectional measures where provided automatically populated for indicator three. So this is what your automatically populated reporting table is going to look like for indicator three once you complete your unit level upload. You're going to see your gender pay gap on annualised based salary in those two left-hand orange columns, and also your pay gap on total remuneration in those two right-hand columns. And you're going to be able to also disaggregate that by employment basis and by employee level, based on the classification levels and the employment basis that you reported against in your unit level upload.
- [Kathy] So why is gender disaggregated data important when you're looking at remuneration data? As I mentioned earlier, we do know that conversations we often hear across the public sector will often minimise the pay gap largely based on that perception that due to laws, awards established pay grades, there isn't really a pay gap. What we do know from data that's available from the Victorian Public Sector Commission is that there is currently a 10.7 pay gap for the non casual workforce. And what we really need to start thinking about when we begin to collect and analyse pay gap data for your entity, really, what are the cumulative effects of this kind of pay inequality? How do we start to unpack how different things like bias might affect remuneration decisions? So looking at those remuneration decisions on commencement, during promotion discussions, and because this kind of bias is often unconscious, for example, you know, a perception of women who may be more comfortable or sitting in support roles where men might be more comfortable in an operation roles because of these perceptions, these stereotypes, data and remuneration data and pay gap data really need does need to become your best friend in a sense to act as the evidence base for your strategies and measures to progress towards gender equality when you're looking at remuneration data. We know that on in an individual level, many of the differences in pay can be explained away along the lines of length of tenure, grandparent closes in contracts, role responsibilities and things like that. We sought expertise from outside the organisation rather than promoting within, and this is the market value for recruitment. But when you do start to collect and examine in a really systematic and deliberate way, your organisational pay gap data, you can start to find ways to address these pay gaps that may in the past have been more easily explained away on an individual level, and really start to build organization-wide strategies and measures to address the inequalities that you do find in your organisational data.
- [Jen] The final indicator on the single unit upload is indicator seven, gendered segregation within the workplace. This refers to where particular genders are either, highly represented or underrepresented within certain workforces within your organisation. What you'll be looking to collect through these is your gender desegregated information. So women, men, self-describing or prefer not to say. And additionally, you'll also be looking at collecting or chatting information across the ANZSCO codes for each of your employees. So the ANZSCO codes of the Australian New Zealand Standard Classification of Occupations, and these will allow you within the template to record at the minor group level, which is three digits and the reporting template will automatically aggregate the data into major groups and chart the data at the major group level. There are guides available for different sectors, including the Victorian Public Sector on the VPSC website, which you will see below. And so you can go and check that website out to look at the specific guidance that is available for your organisation at, vpsc.vic.gov.au/resources/anzsco-coding-guides. The only exception as of the end of May, 2021, is that there isn't currently a guide for local government and that is scheduled to come. So please keep an eye on that website and on the commission's website for additional information for the local government sector. Additionally, you will also be required to upload information around people's identity more comprehensively as well across Aboriginality, age, disability, ethnicity and race, religion and sexual orientation. It is important to note that these indicators, as we have mentioned will be reported on as a single unit upload. So this is an opportunity for you to now have a chat with some of your colleagues in this area, and think about the four indicators that we've discussed to see what challenges do you think you will experience in collecting this information. It might not necessarily all come from a single source of data. So which sources of data will you need to track this information across, who will be supporting you and what are those challenges in collecting and loading it up into the indicative reporting template. And the additional question at the bottom is what do you think you will see in the data. Most organisations will have a pretty strong sense of what type of data will be coming out or what information. For example, you will know if you've go to an area of your workforce with a high level of gender segregation, and now is a really good time to actually start thinking about what you will be doing in response to that as an organisation and flagging this with your leadership groups as well. But there might be other indicators in your particular organisation that you think now that you've listened to each of these four indicators, that it might be timely for you to start planning on your response as well as an organisation. So just take the time and have a bit of a chat and think about some of these issues. Thank you. We move on now to look at the final three indicators, which will each be uploaded individually with the data that you gather from your systems. And this refers to indicator number four, sexual harassment in the workforce, indicator number five, recruitment and promotion practises, and indicator number six, uptake of and utilisation of flexible work and leave provisions. We move on now to look at the final three indicators, which will each be uploaded individually with the data that you gather from your systems. And this refers to indicator number four, sexual harassment in the workforce, indicator number five, recruitment and promotion practises and indicator number six, uptake of and utilisation of flexible work and leave provisions.
- [Jen] The next thing to kind of that we're looking at is number four, sexual harassment in the workplace, and just noting that this indicator is being finalised by the commission. So it will be wise she checked back on the indicative reporting template as we move closer to the reporting deadline. Currently though, at the moment, you'll be reporting on three different measures under this indicator. The first of which is the number of complaints by gender and classification of the complainant. So we're talking about formal complaints that are made here. And the complainant is the third person who is alleging that sexual harassment has been perpetrated against them. You'll also be looking at the number of respondents by gender of respondent. So we're looking at the gender of the person who has had to respond to an accusation of sexual harassment. And the final one that we're looking at currently is the number of outcomes by outcome type and the gender of that, of the complainant in that case as well. So just noting that there's a whole raft of different ways in which a sexual harassment complaint can be resolved. It might be that a nondisclosure agreement is signed, there might be financial compensation, it might be determined there wasn't enough evidence or somebody might withdraw their complaint. So have a look at the indicative reporting template to understand fully what those outcome types are. And just noting that we will be capturing that information, I guess, intersectional identity factors as well. It's important to ensure that the data that you gather on sexual harassment is gender desegregated. As we know that people of different genders experience sexual harassment in the workplace in different ways, and a number of investigations into workplace sexual harassment undertaken by the Victorian Auditor General's office into both the Victorian Public Service and the local government sector have identified a very significant difference between the number of people reporting incidences having occurred against them or that they've witnessed through employee experience type surveys, being significantly higher than the number of formal complaints that are made through formal processes, such as through your human resources department. And we do know that we're probably expecting to see that again as we complete both the workforce audit collection through this indicative reporting template, but also the information additionally, that will be gathered through the employee experience survey as well. We also know that it is important to consider sexual harassment through the lens of power relationships. Previous surveys have indicated that people experience sexual harassment sometimes from a supervisor or someone more senior within the organisation, which obviously has a power imbalance and also from members of the community or customers, which they're obliged to serve in their community. And just noting that that power imbalance is very challenging as well. Additionally, we do know that we need to, if you use sexual harassment through an intersectional lens, the information that you can see on the screen has come from the Victorian Auditor General officer's investigation into if local government, what places are free from sexual harassment. And we do need to consider that sexual harassment needs to also be viewed through a lens of racism, ableism, homophobia, and transphobia as well, because as you can see, particular cohorts and groups of people are at increased risk of experiencing sexual harassment within the workplace. And the response that organisations take need to have a deep understanding of this and to be looking at sexual harassment not just as a policy or a process issue, obviously it does need to be looked through this lens and improvements made, but all through a cultural lens, as in what aspects of the organisation culture enables these situations to happen at such high numbers against certain people within the organisation as well. So when we get to indicator five, we're looking at in the indicative reporting template, completing five separate tables manually. So each of these tables is looking at data for the numbers over the financial year from one July, 2020 to 30 June, 2021. If you are looking for definitions of each of these measures, so new recruits, permanent promotions, career development opportunities, higher GDS and internal secondments, the best place to look for those definitions is in the appendix in your workplace audit guide, which revise and provides an alphabetical list of definitions of the terms you used in all of the data measures. A few things to note, really the definitions are quite specific when you look at most of these measures, the one that is more general and will require a little bit more consideration in your workplace quite specifically, is that measure on career development opportunities. So when you look in the appendix in the audit guide, you're looking at career development training opportunities being defined as those opportunities which assist staff to progress their careers by building on their capacity and skills through specific training. And it might include training opportunities, specifically designed for preparing staff for career progression or promotion, for example, within your defined entity. So it's really quite a generic definition, I guess. So there'll need to be some work done within your entity, looking potentially at your learning and development systems, to be clear on what your entities definition of career development opportunities is, which informs how you record those opportunities in your internal systems. Just the other thing to note quite specifically under this indicator is this is still some outstanding questions around the higher duties measure in the audit guide at this stage. It notes that you're looking at number of people in higher duties arrangements as at 30 June and in the indicative reporting template, you're looking at numbers over the full financial year. So that is likely to be updated and clarified in the next version of the indicative reporting template. So do watch out for that one when you see version three over the indicative reporting template come through the commission over the next month or so. So why is it important to look at gender dis-aggregated data on recruitment and promotion practises in your workplace? What we do know from looking at this data across the broader public sector and at federal data and private sector data is that recruitment and promotion processes and practises in the workplace often tend to be highly gendered. So there is really going to be a rich source of information that comes through in your data tables for this indicator that you can start to unpack to see what's happening in your entity and the kind of questions you might be asking when you're looking at your data on new recruits, you might be asking are new recruits of certain genders clustered at particular levels or particular employment types? Where are they going? Who's permanent? Whose contract? Who's full-time, part-time and casual? You might also be looking at differences in gender representation across two measures, one being permanent promotions and one being higher duties. What we do know from looking at a broader sectoral data is that women can tend to be overrepresented in higher duties arrangements, where men might tend to be overrepresented in permanent promotions arrangements. This isn't necessarily going to be the case within your entity, but it is a type of trend that we can see when we look at broader data across the public and private sector. And it's going to be important to really understand how, if this is happening and how this is happening in your workplace. When you look for example at career development opportunities, the thing to look at might be are those opportunities being offered evenly across genders, across employment basis, or is being a particular agenda or a particular employment in a particular employment type appearing to have an effect on equity of access to career development opportunities? And if this is the case, then you might be able to start unpacking whether or not then how then that starts to have flow on effects to career development pathways for individuals in particular employment types or individuals of particular agendas in particular employment types across your organisation. So the sixth and final indicator in our discussion of workforce data is uptake and utilisation of leave and flexible working conditions. Similarly to indicator five, when you do look at your indicative reporting template, you will see that there is a series of smaller tables in your tab for indicator six which need to be populated manually. And the first two of those tables looks at formal flexible working arrangements. So looking at proportion of your employees with formal flexible working arrangements and then secondly, looking at number of senior leaders who are working with flexible working arrangements. A few or the main thing to note there, I guess, is that key word, formal. So we are looking at formal flexible working arrangements, not arrangements that maybe informal within your organisation. And when you look at the workplace audit guide, there is a definition in the appendix of flexible work, that being defined as access to one or more of a series of arrangements as chosen by the employee. And the example list in the guide includes things like working part-time, where it's negotiated by the employee, shifts swaps, job sharing, purchase leave, using leave to work flexible hours. There are in that list when you look at it in the appendix to the workplace audit guide, a series of particular specifications, which it would be worth noting a couple of them, I guess the main one really is that, working remotely is only considered in 2021, a example of a formal, flexible working arrangement where it's been negotiated by the employee. So not as a requirement of COVID-19 restrictions, which affected many in the workplace in 2021, that's not a formal flexible working arrangement that you need to be reporting on. When we look at the other measures, leave uptake, the types of leave we're looking at under this indicator are parental leave, family violence leave, and carer's leave. Again, you will find clear definitions in the guide of how to capture that leave. The main thing to note, I think is when you're looking in particular at family violence leave, you will need to be sure that you are maintaining privacy protocols when you're starting to pull that data out of your system, when people are starting to look at it to analyse it, you will need to make sure that it is de-identified and that you are adhering to many of the privacy protocols that are in place within your organisation to collect and record that sensitive data in the first place. When we start to unpack why gender dis-aggregated data is so important in understanding workplace gender inequality, when we're looking at leave and flexible working conditions, there is so much, again, similar to indicator five, which we just talked about so much data that we can start to unpack here. Really, when we're looking at formal flexible working arrangements, the question you might be asking yourself is, who's accessing which arrangements and what is this doing to their career and earning capacity? So one of the things, once you collect your baseline data in 2021, and you start to track that over time and check in on your data in the next reporting period in 2023, 2025 and so on, you really will actually start to be able to understand where change is happening and understand where there has been significant progress and where progress hasn't happened. We do know in particular, in the public sector, there has been over recent years, really significant progress in the areas of flexible work. We know now that 46% of employees, for example, are making use of fixed, flexible working arrangements across the Victorian Public Sector, which is a huge shift over recent times and it's one of the benefits of starting to track data over time. So we can really start to understand where increase or increased uptake of flexible work might be, particularly when we start to look at number of senior leaders who are in flexible working arrangements, we can also start to understand availability of flexible work arrangements at that level and whether or not it's acting as a hindrance or a barrier to career development pathways. Some questions you might also be asking yourself if you are seeing that there is not over time an increase in uptake of flexible working arrangements in certain employment types, certain employment levels, sorry, you can start to ask yourself what fixed mindsets or excuses you might be hearing, which might be discouraging use of flexible work policies. Similarly, when we look at uptake of leave, particularly carers leave, parental leave, and we start to track what kind of changes we're seeing over time for different cohorts of women, men and gender diverse people's uptake of parental leave and carer's leave, we can really start to put in place responsive strategies and potentially measures, which might ensure or can help to ensure that women, men, and gender diverse people are all feeling that uptake of parental leave or uptake of carers leave is an opportunity that's available to them and not just that's available to them, but an opportunity that if there's uptake, won't create a barrier or hindrance to their future career development pathways and their employment life cycle within your entity. And this is where we end our discussions of workforce data collection under your workplace gender audit. If you do have any questions about the materials that have been presented in this session, you can email the commission at enquiries@genderequalitycommission.vic.gov.au. We really do also encourage you to stay in touch with us at GenderWorks. You can find us on LinkedIn or on our website, www.genderworks.com.au. And if you do have any particular questions that you would like to follow up with us on, you can email us at auditing@genderworks.com.au.
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