Nigel Cassidy: Organisations everywhere are struggling to build inclusive and diverse workforces, so is it time we turned to technology to help us with this very human workplace challenge? I'm Nigel Cassidy and this is the CIPD Podcast.
Now the benefits of a diverse workforce where all are valued and able to participate are unarguable, not just because it's the right thing to do for social justice, but for the business. To broaden your talent base, boost creativity, innovate more and keep staff longer. So it is a stain on employers and people managers that in spite of all the policies and promises progress is slow or stagnant. What's the answer? Well this month’s podcast asks, could digital technology be an unexpected friend in creating fairer, more equal and inclusive workplaces? To help us, three top guests in the field, joining us from Chicago in the United States, the Head of Belonging, Diversity and Inclusion Solutions for Cloud software providers, Workday, he says he strives to shatter and disrupt biases through a digital lens. It’s Kevin McFall. Hello.
Kevin McFall: Hello Nigel. It is a pleasure to be here with you today.
NC: Great, you're very welcome. From the home team we have the CIPD’s own senior research advisor in data technology and AI, with a background in both IT and HR, she has a deep interest in how the people profession can contribute to good work through technology. She’s Hayfa Mohdzaini. Hello.
Hayfa Mohdzaini: Hello Nigel.
NC: But let’s kick off with Dr Zara Nanu, who tells us that she founded her company on learning from the World Economic Forum that it would take 217 years for the gender pay gap to close. Gap Square helps clients measure and end unfair pay. Hi Zara.
Zara Nanu: Hi, hi Nigel.
NC: Now before we get stuck into possible tech solutions, I wondered if you could give us a bit of a sense of our mission here. I mean, where do the fails lie in organisations that are just not getting to grips with unfairness of all kinds?
ZN: So unfairness at an organisation is something we’ve inherited, the world of work as we know it with current jobs and the way the jobs are structured, have been built mostly in a post second world war structure, where men were kind of at the helm of economies and of organisations and companies. And we've inherited that system where certain jobs are valued in a certain way and we find ourselves in a world where for instance, nurses get paid a certain wage whereas software engineers, or engineers altogether get paid a completely different wage, much higher than that. And we have an economy where occupations that are dominated by women tend to be less paid than occupations that are dominated by men. And in addition to that, we have less women in senior leadership work and also more women in support roles within organisations.
NC: And Hayfa, of course it’s not just about pay gaps, be they ethnic pay gaps or gender pay gaps, it’s about organisations really not being fair across the piece, isn't it?
HM: Yeah there’s a whole range of areas that organisations could do to make the process fairer. All the way from the attractional through to retaining and when they leave the organisation. So for example when you are attracting people, pay attention to what words you use, where you're advertising, so what algorithms are used to advertise it, we then come in the organisation reviewing the pay gaps of course and understanding the staff surveys, what the feedback is and also when people get promoted, understanding who gets promoted, what the demographics are. And basically taking action. So we have a lot of data we can work on and it’s just wanting to take action and monitoring progress. That's the bit I think that is lacking in organisations.
NC: Now Kevin McFall, it does sound a bit counter intuitive doesn't it, to turn to technology to solve this very human issue about how you treat people? So can you talk us through how tech can help?
KM: Certainly and it would seem somewhat counter intuitive, but what I think is an important take away is the understanding that it is an opportunity to augment the processes of assisting organisations to identify the issues that exist and then measure what their performance is against their intention and ultimately take action. And that is where the technology really helps. Being able to guide the right actions for organisations to take, not just for the business imperatives that rely on being in compliance with government regulations and such, but also to foster greater cultures for employee belonging and inclusion efforts that will help improve the business overall.
NC: And to do that Zara, how much technology are organisations typically using at the moment? Obviously there’s a huge difference between multi nationals and a small company with its tiny HR department, but broadly where are we using technology and where could we use it?
ZN: We find in working with organisations that the HR departments in particular are less, are using less innovative technologies than other departments. You have high use of tech in business development, in marketing and in all kind of digital approaches to growing a business and less so when it comes to HR. When the World Economic Forum is telling us that we are 260 years away from achieving gender parity, at the same time the World Economic Forum is telling us that us three will likely be in self driving cars by 2030 and NASA is telling us we’ll be waving people off to Mars by 2030. So technological advancements are happening all around us, that they're just not currently utilised in an innovative way to help us address things like pay equity and overall diversity, equality and inclusion at work.
NC: Now Hayfa, is this about using people analytics? I've seen this phrase often, I would imagine that being able to look at what’s happening by job, location, department and manager is huge, but it’s an awful lot of steps on the way to actually knowing what software, what platforms you need to start logging the right information and then acting on it. Where do you start with scaling up and seeing where technology might be able to help you do better?
HM: I think Kevin made a really good point earlier that technology can augment our ability to know where to start and where to prioritise. So looking at what data we have in the organisation and what tools we have to pull that data. So your HR systems, how easy is it to pull out your regular pay gap reports, is it a huge industry to do that? And if so, maybe it’s time to shop around for new tools that make it easier. So anything that you are going to need to regularly pull the same questions again is actually a candidate for something you probably want to automate or have a system that you can easily pull out that data.
NC: OK so let’s take that on a bit more with Kevin, let’s go through the, there’s so many things that people managers have to do in the course of their work, but let’s start with people joining the company with fair selection, how can technology help us have a more diverse range of people working for the company?
KM: I think the key component there is removing biases from the talent acquisition processes. The ability to ensure that various bias considerations that tend to seep into the recruitment process there can be interventions for those as well as best practices around talent acquisition. So for example, ensuring that interview processes consist of diverse panels of interviewers can help enable the removal of one subjective hiring decision maker from the process. So when you start with a set of opportunities that at least reduce bias in the selection process, you have a higher propensity of moving more diverse candidates through the talent acquisition funnel. And so technology can enable some of that process, but it’s also about the people involved. So your recruitment and talent acquisition tools can certainly ensure that you have job descriptions that are inclusive in nature and there is technology that helps scan those job descriptions to ensure that that’s reflected, but ultimately, I think you also have to ensure that you have interventions to help your recruiters and others in that hiring process, mitigate and reduce the bias associated with how they perceive talent.
ZN: What I would love to add to this, research shows that a 50/50 shortlist does not necessarily result in a 50% chance of a female candidate being recruited for that role. So we have to be extra kind of, doing, going the extra mile in terms of ensuring that shortlist is really diverse to ensure the recruitment of diverse talent and --
NC: But what’s that got to do with technology, that’s just a human thing of going through is it? Or what?
ZN: Well so we, as a company that uses tech to create more equity at work and more fairness at work, we've resorted to using a piece of software ourselves for recruiting talent for our own organisation. So we’ve moved away in the early years from looking at CVs, even when we anonymised CVs we ended up having very similar candidates, because biases do come in when you look at someone’s address, when you look at someone’s education, when you look at someone’s previous work experience. So we started using software that was just focussed on asking some questions of the candidate and would really highlight more where the learning skills of that candidate are and kind of approach to different situations. And so candidates would answer different questions and then we would have a committee that would score those answers, but you get the answers in a random order, so you can never piece one person together. So if someone says, when I went to Oxford I did this, what tended to happen that answer gets a lot of ten points out of ten. If they never mention Oxford again in any of the other questions, they may get twos they may get ones, so altogether it’s easier to end up with a very diverse candidate pool at interview stage.
NC: I want to go to Hayfa on this, but let me just ask you Zara, you were telling me when we spoke briefly beforehand about, was it Amazon or somebody and how their selection produced some rather curious and very unwanted effects?
ZN: Yeah there was this case that made the headlines a few years ago, where a handful of data scientists in Edinburgh were tasked by Amazon to put together a piece of software and help them identify top engineers around the world to join the company. And what happened as a result of that, was a piece of software that was discriminating against anyone who had the word woman in their CV. And ultimately when we revert to technology and we start using data and tech, we actually have to be careful about bias even more than we are about our own internal biases, because what data we put in, that’s the data the software will analyse and make conclusions and in that instance that piece of software concluded that anyone with the word woman in their CV or LinkedIn profile, wasn’t a good candidate for Amazon.
HM: So getting a system that’s not biased is not an easy thing to do and thus we can easily pull out examples, oh and this is why we shouldn’t be using tech. But I think if we’re a bit more patient and try to work with the text, we could iron out all those potential biases that seep in, so it is like probably we’re looking at an immature solution that perhaps might be reliable in the next few years. So where tech can help in achieving a fairness is, as been picked up earlier, it is about being able to filter in thousands more applications so that you end up with a more diverse workforce. And the thing is, you can have all these checks and balances beforehand, but if the final decision maker, the humans, have not really moved on and they're still quite biased you would still not be able to iron it out. So it is actually both ways, we can design the tech to help the processes to achieve that diverse workforce, but at the same time we do need to train our managers to be able to be, to think more inclusively, to think about how can we achieve an organisation that’s diverse? Yes.
NC: On a simple level with that example, you would think people might have noticed that there were no women on the list --
HM: Yeah.
NC: You don’t need a computer to do that. But I did see this thing that the UK government said very, very recently, it was the reason they gave for not having mandatory reporting on ethnicity as well as pay gaps and what they said, quoting a report was, there are significant statistical and data issues that would arise as a result of substituting a binary protected characteristic, male or female, with a characteristic that has multiple categories. I guess you might say this is, this might be construed as an excuse, but it does show that this is a really complex area isn't it, knowing what questions to ask and then how to process what comes out?
HM: Yeah for something like ethnicity pay gap it’s, I guess, difficult to institutionalise what is a fair set of measures? But that’s not an excuse for not doing it at an organisational level, even though the government like might not feel that’s the right time to do it. So if it’s something that’s important in your organisation by all means carry on. Because I know there are organisations who are already doing ethnicity pay gap reporting, even before the, it’s been consulted by the government. You touched earlier Nigel about other ways we could be more inclusive in the organisations, apart from just looking at the analytics. So there are tools around us that we can, we can use already to be more inclusive, for example like we are having this team, this meeting in Zoom, there are video calls that allow live transcription which would make a meeting for people who are hard of hearing more inclusive, they can join in meetings like this. So it’s just looking around and being critical and saying, OK, well we want to make this, our workplace more diverse, more inclusive, what in the workplace, well how can we make, how can we do that, how can we make small changes in our workplace to make that happen?
NC: Let’s ask Kevin about that, because this is a kind of hidden bias, a hidden unfairness within an organisation and it’s a long way from just meeting an obvious obligation not to discriminate.
KM: I wanted to add that one of the emerging technologies that companies should be thinking about and ultimately adopting, is also that of skills based sourcing and skills based matching to their job requirements, with a movement towards skills as a source of professional capital if you will. It’s not necessarily going to eliminate those instances of referring to the other attributes that tend to influence the bias of a hiring manager, but at least in sourcing and again moving through the talent acquisition pipeline, the focus on skills enables a higher confidence among organisations that they have the right people, for the right need, at the right time. And so I certainly know that our organisation is creating solutions that help managers ensure that they use and put skills matching at the centre of a lot of this work.
NC: Well Zara’s organisation does similar things I guess, though perhaps a bit more in the pay area. But just give us a sense of when you go into an organisation Zara, what sort of an issue, because they probably don’t come to you and say, let’s buy another piece of technology. So how do you assess where there are issues of unfairness of any kind and then work out what technology might help them improve their performance?
ZN: It’s really interesting Nigel, I was just reading a book actually called, it’s a new book called Work Without Jobs and actually speaks to a lot of the things that Kevin was talking about and how we need to look at deconstructing skills and deconstructing jobs themselves, because jobs are changing all the time. You recruit someone into a digital marketing role, two years down the line that role is going to look completely different, because technology is changing and reshaping everything about our work. So you need to link skills into that and focus on talent and how talent can actually pick up on those new skills and grow and develop as the world of work changes too. But I guess this is where it becomes really complex for organisations to understand how they can create fairness within all those roles. We've seen the cases that ended up in employment tribunal in the UK from supermarkets where people at the checkouts were being paid differently from people in the warehouse and they won the case against the employer on the grounds of equal pay for equal value. So when you start looking at things like that, like what does equal value mean? How are jobs changing to ensure that you remunerate that equal value across jobs at all times? It becomes really complex to do it on an excel spreadsheet. So you need to start looking and unpicking issues more in depth and we use our software to do statistical regression models and really help employers understand where they may be paying some employees unfairly, even though they have the same skills, they bring the same value, they perform the same tasks within a job and they have the same experience. And where for instance, some gaps can be justified by things like location, so someone who’s in London will be paid differently than someone who’s in Bristol and get a more in depth picture. As Kevin was saying earlier, it’s about understanding the benchmark and understanding where then you're going to go from that benchmark, where you can remediate and where you can actually plan more successfully from a financial point of view, from a talent point of view, for the future workforce.
NC: OK and Hayfa, assuming you've decided that you are going to try and gather and use more data to inform you in changing how people are managed and looked after and all that, do you always need expensive extra software to do that? Where does the tech come from and how do you learn how to use it effectively?
HM: Well first start looking around in the company what you’ve got, so what software have you got, does it do the job well? What’s the skills level in your department to be able to analyse that job, because the more skilled you are the more complex tools you can use. And then decide, OK do we need to invest in new software, or can we just repurpose what we've got?
NC: OK and Kevin, once you’ve got a picture of what maybe diversity is looking like in your organisation, you begin to know how departments work, how people are treated and you start addressing it, you still maybe don’t know if that’s good, just OK, or if in need of some work. It sounds odd, do you need to benchmark your performance or is it just very obvious doing the right thing?
KM: Oh that’s a great question. Because one of the things that is important that we’re finding is building a sense of community around these issues and understanding what corporate peers are doing within their workforce planning efforts.
NC: Because of course you can't always tell if you look at their website, or you look at their reports, they often paint themselves in glowing colours as to what they're doing and as I said right at the beginning, the problem seems to be in the execution and people aren't living up to what they're promising to do.
KM: Yes. That too has been a challenge and again, when I talk about community, I'm talking about these safe spaces that organisations are coming together to share and exchange best practices, challenges and in some instances how they're overcoming these challenges. At Workday we say, we want to make a better Workday for all and that mantra is certainly fostered in the solutions that are created, but it’s also fostered through the community opportunities, community building opportunities that we create. So that there is a sharing among chief human resource officers and chief diversity officers and H officers and HRIS professionals that have an understanding. We have a great instance of a customer in the information services industry that began a campaign around ensuring that their workforce was confident and comfortable in sharing who they were in terms of their identities. So that they could self identify themselves within the HRIS systems giving this organisation that baseline data to being to analyse and derive insights and benchmark, so that they had that level setting and set goals and objectives of what they needed to improve upon and what, where they wanted to go ultimately in terms of thriving, having a thriving culture that fostered diverse equity and inclusiveness. There’s no panacea of course around this, but I think it was said earlier that, you must at least have a goal and objective in trying to achieve a better workforce.
NC: Zara it was interesting that Kevin mentioned diversity inclusion officers, people who professionally look at all these issues. Is there a danger that you can do quite a lot with these people analytics and everything, but because the senior managers didn’t commission that, they don’t own it?
ZN: Absolutely, there is that danger, but Kevin also mentioned the magic word and that’s community and in a similar way you want to mobilise community within organisations and support people to be themselves and disclose their identities, you need community around these pieces of tech to help you really foster and implement that diversity and inclusion. So the fact that we have a piece of software that you click a button and it tells you where for instance you have pay inequities, or where there’s a glass ceiling and women aren't making progress above a certain level, you need a community around that, that includes your rewards specialist, that includes your HR manager, that includes your diversity and inclusion person, that includes the CEO and people from the C Suite and the board room so that they can really own this and really understand what the software is telling them and pick up on those action points and take them forward. This is not just the job of someone who does people analytics, or software, it’s everyone’s job to make it work.
HM: So I agree with what Kevin and Zara said, I think you need a support from all levels to mobilise and create an inclusive and diverse workplace, it is not just HRs job, it’s not just the CEOs job, it’s everyone’s job.
NC: And you don’t see any dangers in the tech, the doing a job, pointing things out but not winning hearts and minds, that it’s a, it becomes a process?
HM: That’s an interesting question because in some cases, I said at the beginning in this particular case tech can augment our ability to achieve an inclusive and diverse workplace, but if not everyone’s bought in, you could put in processes to say, OK we will look at this data on a regular basis and then we will show you some quick wins and then through the quick wins you gradually win the hearts and minds of small clusters of people. And over time, as people see progress, people buy into it. So sometimes you do need to have that process of actually being, actively looking into it, to win the hearts and minds of people. We can't just talk about it and expect people to immediately buy in, you need to convince them.
NC: And Kevin I was struck by something you wrote about your own father’s life and purpose, I don’t know if this was in Chicago, but trying to diversify the engineering profession there at the time and I wonder if you’ve ever thought about whether he would have approved of reliance on software for us to behave better?
KM: I appreciate the reference to my late father, he certainly was a pioneering figure in ensuring that stem opportunities were made available to both women and other underrepresented groups. And I think he at some point was looking for additional support and as a scientist himself, I think he believed that technology could augment and support some of those efforts. But it really does start with people and a need to ensure that, technology ultimately again can be an aid but is not the silver bullet. One of the things that I believe today is, our current generation of new entrants to the workforce are particularly demanding that organisations do better, right? And whether those organisations adopt technology to do better, or the perceptions and the practices of the people change, I think the forces are all there to enact a different outcome.
NC: Which I suppose Zara only goes to show that organisations in the UK shouldn’t breathe a sigh of relief because they don't have to do the ethnicity pay gap reporting, because somebody who might want to work for them will be looking for that information, it’s not just about compliance is it? Even though HR people seem to have to spend an inordinate amount of time on it.
ZN: Oh absolutely, this is not just a tick box exercise on compliance, the younger generations that are coming into the workplace, they're very much interested in that fairness across pay, across promotion levels, across representation in different occupations and seniority levels. So they are looking at this data and they're asking questions. I think over 70% of new and post grad employees were asking employers about what their diversity and inclusion policies are. They are looking on websites like Glassdoor in the US, websites like BuildIT, Blind and a few others where they're finding a lot of information about how much people had offered for certain jobs and for certain levels and career progression, so that they can understand better where the organisation sits with the fairness agenda.
NC: OK, well we’re coming to the end of our time, so just quickly before we finish, from each of you maybe just a quick thought to bring this together, where can you start to maybe deploy a bit more technology and avoid the pitfalls on this agenda?
HM: Definitely look at the diversity figures by different groups of people, so not just looking at the average across an organisation, look by departments, by grades, by seniority, that kind of thing. If you're finding it’s a bit of an industry trying to analyse all that, definitely look to software to see whether it can simplify that work for you, so that you can focus on convincing the employee population to make, to do something about it, to convince the managers, to convince the senior people to do something about it.
KM: We have an approach at Workday, we call it VIBE, valuing, inclusion, belonging and equity for all. And in that approach, we definitely look across the entire employment life cycle but encourage beginning at the data collection and the talent sourcing point to ensure that you begin along what we also call as the VIBE maturity model in which you're committing your organisation to improvement. And from there you would move to drive and then ultimately, hopefully, having an organisation that thrives around that VIBE model.
ZN: This is a big issue and sometimes it can be overwhelming, you look at all those data points, you look at pay, you look at attrition levels, career progression, it can become really big and then once you start looking at size, tech and engineering, you see that not a lot of women are in the talent pipeline anyways and all of a sudden it becomes like this big mountain that you have to climb. And I think the key to addressing this mountain is taking small steps, so doing a very small data analysis over, for a department, just looking at a department, or just looking at the team and slowly growing from there will help us get on top of that mountain.
NC: Great, well let me just thank Workday’s Kevin McFall, Zara Nanu, founder of Gap Square and the CIPD’s own Hayfa Mohdzaini for that excellent insight. Now the CIPD website has a really good factsheet and a thoughtful report on building an inclusive workplace and it’s also got a clever health checker that you can use which tailor’s ideas for your particular situation. Lots of positive comments on social about our previous and still very current podcast, just when you thought work pressure might be a bit much, we explained how a measure of good stress, just outside your team’s comfort zone, could be just the thing to get the job done. So do check that out. And become a subscriber wherever you get your podcast because you’ll be alerted to our forthcoming bonus edition, we hope to be recording live with an audience at the CIPD’s Festival of Work at Olympia. Be great to meet some of you in person. But for now, from me, Nigel Cassidy, and all of us here, it’s goodbye from the CIPD.
