Episode Transcript
[00:00:03] Speaker A: I think augmenting what AI is exceptionally good at with a human construct really gives you a multiplier effect of the impact that you can have. But you need to have both. You can't have one or the other. But make sure you augment the technology with human qualities.
[00:00:20] Speaker A: Welcome to a new episode of the what Works podcast series. In this episode, Cathy and Darry sits down with Tristram Gray, Chief people and Corporate Affairs Officer at Kmart Group in Australia, to discuss how the retail giant is using AI to transform high volume hiring. They explore how Kmart recruits 12,000 people annually with better speed, quality and candidate experience while increasing diversity and reducing bias across 450 stores. Let's get to it.
[00:00:51] Speaker B: Tristram. Welcome to the what Works podcast.
[00:00:55] Speaker A: Thanks, that's fantastic. I'm really looking forward to it today.
[00:00:58] Speaker B: Let's jump right in. I know we have lots to cover, so tell us about yourself, Tristram, and about your company.
[00:01:04] Speaker A: Sure. So I'm Tristram Gray. I'm the Chief People and Corporate Affairs Officer for the Kmart Group here in Australia. For those who may not be aware of us, we're Kmart and Target in Australia and New Zealand. We're 55,000 people. We have 450 stores across Australia and New Zealand and We've got about $11.5 billion in Australian dollars revenue for ourselves on an annual.
What do we do? We're a apparel, home and general merchandise retailer in Australia and New Zealand.
[00:01:33] Speaker B: Wow. Yeah. So big company retail, obviously. Very interesting, I think, in the people and talent space. So what business problems are you working on? What's keeping you up at night?
[00:01:46] Speaker A: A few things.
[00:01:48] Speaker A: I think, but I'd say firstly in the area of productivity, how do we keep driving productivity? Particularly how do we leverage AI? Of course, everyone's talking about AI, but how do we do that in a way that makes sense for not only our business and our teams, but also for our customers? So that's a big topic. And the implications for roles and organizational design. We're also very focused on our culture and the engagement and our team experience. And then in the talent space, both attraction and development, of course, but also the focus on leadership talent to help lead our large team.
[00:02:22] Speaker B: Yeah, and no doubt the retail space is ripe with opportunities. And I mean, the turnover in retail is kind of a multiple of what you would see maybe in other industries. So how are you dealing with that? Like heavy turnover of the frontline employees?
[00:02:41] Speaker A: Yeah, so we recruit around 12,000 people a year, you know, particularly through peak periods around, you know, Christmas, those sorts of things. It's quite a challenge. And particularly across 450 stores, how do you do that faster? But how do you also ensure great quality and better quality of candidates? How do you ensure those candidates hopefully join you, enjoy the work experience and stay longer, which ultimately reduces the number of people you're recruiting, but which has a cost and commercial benefit, of course. But importantly, it has a customer impact as well, because people who stay with you longer understand your business, your products and can provide better services to our customers. So. So that's been a really big challenge for us that we've leaned into. We've looked to use AI as part of a solution to that.
[00:03:26] Speaker B: Yeah. And AI can do, of course, so many things. I mean, speed is certainly one of the things, and efficiency. Right. When you're talking about maybe volume, hiring and these peak periods and application volume is we hear from everybody is going up, up, up. So how do you use AI for that?
[00:03:43] Speaker A: Yeah. So what we've done, we engaged with a company called Sapia AI and we worked with them about how could we try and hit what may be seemingly diametrically opposed objectives? As he touched on speed of hire, but better candidate experience. We also want a better quality of hire out of this and also making sure that we could have a system. And one of the things that I was worried about as we went into this is will this affect the diversity of the team members that we hire or will it affect inadvertently have a bias that might exclude some great team members? And we really didn't want to have that.
So we've used this platform in a way that helps automate interviews. So it's not CV based, it's a mobile first application where prospective team members answer a range of questions. It's around 20 to 30 minutes maximum of doing that. But they're all related to fit. And what we've worked in the background with Sapie AIs is we've done a lot of analysis on what makes a great fit or a great team member in our environment. In Kmart and Target, we've then tuned the algorithms to ensure that when we're asking questions that are critical to what we know as successful team members, but also their attributes that they bring remembering in retail. A lot of people don't necessarily go into retail as their first career choice or a longer career choice. Often they're young people with little experience.
So it wasn't particularly useful for us doing a whole lot of a technical interview around. Tell us a time when you've used a checkout, register or you stack things on shelves because often these people haven't never done that before. So how do you do it in a way that's more about fit? Because we can also train people to do those things. So that's not the core piece. It's more about do they have a cultural element? Will they like the pace and the team collaboration? Are they good at those things? How do you draw that out? So we've tuned the algorithms and to select people on, on that basis, but they're blind. So in terms of when I say that there's no CV so it removes all the bias.
[00:05:44] Speaker B: So, so how, what makes a good fit? Do you have any specific things and what, like what behaviors or what kind of experiences makes a good fit for your company?
[00:05:53] Speaker A: Yeah, so. So there's probably a few key things. One's people who like to work in a high pace environment, retails high pace. So if you, if you like high pace and moving around doing different things quickly, then that's a great fit. Curiosity is a big piece. So people who are willing to learn and adapt and try new things or you know, be open to doing new things and are willing to ask questions about things, that's really important for us. People obviously, you know, customer oriented or have a, have a customer service sort of bent, if I put it that way.
But really importantly, people who are team players, people who collaborate, nothing happens in our business because of one person, it's always because of a team. So you have to be somebody who enjoys working in a team environment and it's driven by results. We're a highly competitive sector in the economy and people who are motivated and challenged by how do we do better every day is really core part of it. So those four or five areas, we've really tuned the algorithms to try and draw out people who motivated will work well in that type of environment.
[00:06:58] Speaker B: What you're describing is of course people not being evaluated based on their experience because as you said, most people don't really have a lot of experience or not like really directly applicable. So it's less about the experience and more and more about just attitudes and behaviors.
[00:07:14] Speaker A: Right, you're absolutely right. Absolutely right. And to your point, we can train the technical skills relatively quickly, but what we find is important is that the behaviors and the values someone comes with are far more important than the technical skills for our frontline staff. So that's what we recruit for.
[00:07:32] Speaker B: So how does it work?
Let's just say I'm applying for one of these positions on my mobile phone and I get a link and then I get through a simulation or what, what do I do?
[00:07:42] Speaker A: Yeah, through a simulation and through a range of questions and you respond to those questions, you know, they're scenario based and how would you approach this and what would your view be on this? And it draws out those things and that then, then goes into the system, the system and then analyzes those, those responses to match it against the benchmarks or the criteria that we've put in place that we, we know is important, we know leads to success for our candidates. So then it's basically like matching, if I, if I put it that way, then matches. I think what also is important is that everybody who undertakes one of these applications through this process gets a feedback report. So whether you're successful or you're unsuccessful, you get a feedback report. We think that's been really important because just because someone isn't a fit for our environment or our role that they're applying for, that doesn't mean that they are not a good person or won't be a good employee or can't be successful, but just not in our environment. So what we want to do is try and help everybody to say here's where you were strong or here's where you know, in our environment these things weren't quite a match. But it helps gives them some, hopefully some insight into themselves. So from a personal development perspective, everybody walks away with some feedback that hopefully is beneficial for them as they develop further self awareness as they progress their career, perhaps in other organizations.
So we think that's a really positive outcome out of this as well.
[00:09:05] Speaker B: Oh it is. Because I think that usually more traditional recruiting process is first, it's very biased. So having this AI based makes takes all the human bias that we all have out of the equation. Right.
[00:09:18] Speaker A: I think that's a really good point and another reason why we wanted to do this, if I think about what we're always striving to do from a customer perspective is have a consistent experience. In every Kmart or Target store they walk into, they should have the same experience or at least within a narrow standard deviation of different. This has enabled us to drive consistency on of both type of people recruiting, but also their experience and their fit with the organization. So we take out that variability out of the system which is, which has been excellent.
[00:09:48] Speaker B: Who is a good fit? I presume it's based on actual performance of people. Right. And how long they stay and what their sales performance is, what their customer satisfaction is. All of those. You didn't just make it up.
[00:10:00] Speaker A: No, it's based on data. And the other piece is we did it based on roles. So we've clearly defined what are the key attributes in each role, whether it's a checkout operator or whether they're a manager in the store. We're very defined on what those roles are and then we know what the key attributes are that are important to succeed in those roles.
[00:10:19] Speaker B: Yeah, well, the other thing I think that solves in the another problem that's in the standard recruiting process is this. This process actually gives people actual usable information and insights about themselves. And it's not not a judgment call, it's just you didn't match to this maybe high paced culture so it wouldn't be a good fit for you. And in other cases it's always like, am I not capable of these things?
People take it much more personally. I think when you don't have anything useful to give to you.
[00:10:49] Speaker A: I think that's absolutely right. You leave it to a very subjective outcome both in terms of a manager making that decision. To your earlier point, we all have biases and they come to play whether we are cognitively aware of them or not. But this process and the way we've adopted this is every candidate, whether successful or not, gets a report. So we've had tremendous feedback from candidates who've been successful, but equally from candidates who haven't been successful. So it's been fantastic from that perspective as well.
[00:11:18] Speaker B: In a retail environment, of course, every person is a potential customer or probably a real customer. Right. And if they don't have a good experience, they're probably not going to come back to you versus now they get the gift of feedback after they put some time in. So it's a return for them.
[00:11:35] Speaker A: That's right. And I think from that perspective, I think there's an old retail adage that says someone who has a good experience might tell one or two people. Someone who has a bad experience generally tells 10. So it's not only the individual themselves who might say that's a terrible experience and a terrible company, but they'll tell other people. And that's really a big issue for us. From a brand perception and reputational perspective.
[00:11:58] Speaker B: How does it impact your HR team, your recruiting team?
[00:12:01] Speaker A: I think, you know a couple of things. When we first talked about bringing it in, I think there was a little bit of nervousness. Maybe the moment you mentioned AI people can take a bit of a negative view, but if we wanted to take this out, I think they would kill us.
You know, it's enhanced their lives and their jobs. It's meant that it takes a lot of administrative work out of it. And if you could imagine, you know, as I mentioned, we hire, you know, 12,000 people a year.
If you've got to do each one of those individually and manually on top of, you know, 3, 400,000 applications a year to sort through, that's a lot of repeat, repeat, repeat. This releases time to think about, you know, more strategic matters about workforce planning. What is our turnover rate in our store in Melbourne? What do we need to plan for? We know this is the rate. We know we'll need this many people. So it's focused on being more pre planned and it's also more interesting. Yeah, it's, it's a much more enjoyable, fulfilling role. So it's really improved their, their experience of their own roles actually.
[00:13:01] Speaker B: So they like it too and they were nervous before, but now, now they don't want to give it, give it up anymore, which is fantastic. That's what you like.
[00:13:10] Speaker A: That's really been based on the, the outcomes or the KPIs if you like. So, you know, a few of those just quickly, you know, candidate experience is 9 out of 10 of them rating it. They rated 9 out of 10 on the chat interview. In terms of speed that we talked about before, we've reduced hire time from 2023 before we had this program in place by 73% from 44 days in 2023 to now 11.8 days. So that's been great retention, which is the other point, what we've been able to find is that Those who the AI tool matches, they are 2.5, stay 2.5 times longer than our average hire if we don't use it. So that has convinced our operational teams now they wouldn't give it back either because the conversion rate is much higher now. I touched on diversity as well previously and that's really important for us and well, it was one of my concerns going into this program. But what we found is 8.25% of our hires identify as first nations people in Australia or indigenous employees. The ratio in the general market is around 3%.
So we're actually getting better diversity out of that. And the same with three and a half percent of people identify with a disability. That's way above benchmarks. So what, what's been pleasing are that it has proven out that it's not biases to, you know, racial background or, or upbringing or any of those things. And bottom line is, you know, we've avoided, we think between 2 to 3,000 hires a year. Now for us, that's around 1,000 to $1,200 per hire. When you think about management time and induction training, all those things. So, so it's in the range of 3, 2 to 3 million dollars a year. Bottom line that we've been track. So it's been been a very big success for us.
[00:14:52] Speaker B: Wow. And I love that you were very clear about what you're going to measure and how you're going to measure, how you're going to know. And all the metrics that you just stated to me were exactly fitting into these buckets. Right.
[00:15:04] Speaker A: I would say the other two learnings, I would say one from a change management perspective, you have to be open to and willing to reimagine your recruitment operating model because it's not about just slot this in on the side. You need to integrate it within your underlying HRIS system. So you know, we use successfactors, but people use workday or whatever it happens to be. You've got to be able to integrate it into that. That changes ways of working not only for your recruitment team and the roles that they then play in the way you want them organized, so the organizational design, but also you need to bring your operational managers along for the ride early, engage them early, don't impose it on them later on and say here it is. And then with the metrics as we were talking about, so we're really pleased with those, but we monitor those on a monthly basis. So one thing I'd say is it's not set and forget you've got to keep monitoring it. What's it telling us? Is anything changing? The great thing about the data is it enables you to have deep insight and notice early, maybe early or weak signals out of the noise of everything that's going on. You can start doing, but you need to focus and make sure the team are looking at that and adjusting and adapting to what's happening in the market or what candidates are telling you or what line managers are telling you in the process.
[00:16:19] Speaker B: The way that you're talking about the kind of this change process we talk, like to talk about change agility because it's not just pushing it on people, but really you gave people, for example, a choice, right? You give managers a choice. You don't say, oh, you have to pick the candidate that the AI. So the same suggested. But then when they see they stay 2.5 times longer, they'll make that change anyway.
[00:16:40] Speaker A: So they adopt it, they'll adopt it pretty quickly.
[00:16:43] Speaker B: Exactly.
[00:16:44] Speaker A: So they're like, I mean everyone in retail and particularly managers, you know, they're really pressed for time. Right. So something that can take time out of their day, that they can dedicate to other things, they, they adapt it, adapt to it and also adopt it pretty quickly because the data, the data driven people, they love data every day.
So also it's putting in their language. So in their language they can interpret and understand it better and then you find adoption rates dramatically increase.
[00:17:11] Speaker B: How did the role of the recruiters change? Tell us a little bit more about that.
[00:17:15] Speaker A: So a number of things. It's taken it from a very highly reactive role to a far more proactive role and it's more about selection than it is around attraction. Because we've got lots of applications coming in but then we've automated that whole front end and the fit. So a product pool of pre qualified fitting candidates is already dealt with for the team in volume hiring. Then it's about when will we need those? So creating pools of those people, how do they then organize some of the logistics and helping line managers make those assessments, but also then working with the data to help smooth that flow.
It's just a much more interesting role, more fulfilling for them. Plus because we've taken the volume down because better fit, we've given them some time back to think about other things and involve them in other things. It's been a great impact on their lives and their role experience with the business as well.
[00:18:03] Speaker B: So much less of just here's a kind of requisition and you're just going to fill, fill, fill and like speed up and just basically look at probably candidate quality, probably working more with hiring managers, talking more about kind of the overall workforce plan, those kind of things.
[00:18:22] Speaker A: Yeah, because not every market has hundreds of candidates that are a good fit. Some of our regional areas it's quite difficult to find quality people. So this enables them to work on talent pooling, external perspective to have job ready candidates ready to go. We want it pre qualified. So it then means, you know, speed to hire is much quicker because they've already gone through the process automated in a mobile app enabled way. Rather than a recruiter having to talk to every one of those people through a typical phone interview type process. I mean it's just thousands and thousands. You just can't, you can't do that with any level of quality individually.
[00:18:59] Speaker B: Yeah, totally.
Where are you taking this next? So where are you going next? I know you already mentioned you're taking this to kind of Professional roles, maybe other roles.
Anything else that you're thinking of doing here?
[00:19:13] Speaker A: Yeah, so. So we're looking at it in our, in our distribution centers for our team members. So we've used it in stores is where we applied it. We're now going to apply the same thinking to distribution centers. We've obviously got a few thousand people in distribution centers, different skill set that there is some technical elements to that and there's a physical piece to that in distribution centers. So there's a few others. So we're tuning it for that. We're looking for management. We're going to apply to professional and technical roles now in our for our office based team members, whether that's in finance or marketing or technology or how do we augment, do we use it just for fit and then do a separate technical piece? We'll need to work through that. But that's how we're going to look to apply this now.
[00:19:56] Speaker B: Well, I know we're almost out of time, but anything, any other kind of one piece of advice that you would like to give to our listeners as you were kind of one of the front runners of pacesetters of using AI in the recruiting space.
[00:20:11] Speaker A: Yes. I think one piece I would say is embrace AI, particularly in this space. And I think using it properly, ethically and responsibly and in a way that fits your organizational culture can actually have a deeply human impact. I think there's an opportunity of augmenting the AI and what AI is exceptionally good at around algorithms with the human construct really then gives you a multiplier effect of the impact that you can have. But you need to have both. You can't have one or the other. So my biggest piece of advice is embrace it. But, but make sure you augment the technology with great human qualities such as awareness, compassion, some wisdom and judgment. Discernment. Those elements together are really powerful packages.
[00:20:56] Speaker B: Wow. What a powerful piece of advice. I think it's the way that I'd sum it up. It's not about is it AI or people, it's AI and people. And that way you get much better results.
[00:21:09] Speaker A: 100% agree with that.
[00:21:10] Speaker B: Fantastic. Well, thank you so much, Tristram. It was such a pleasure talking with you. I learned a lot and I know our listeners will learn a lot too. So really enjoyed it.
[00:21:20] Speaker A: Thank you. It's been an absolute pleasure. Nice talking with you today.
[00:21:26] Speaker B: What an insightful conversation with Christian Gray, the Chief People Officer at Kmart Australia.
He talked about how he and his team use AI to streamline the frontline hiring process. AI based assessments make it easier easier to determine values fit and data analysis shows that the candidates recommended by the AI stay 2.5 times longer.
That's a significant impact on the bottom line in retail where high turnover is so common.
In addition, candidates much prefer the AI based screening as a more engaging experience that also gives them relevant feedback after the assessment.
Thanks for listening to the what Works podcast. Until next time, keep exploring what works in your world.
