ReThink Productivity Podcast
In this exciting podcast, Simon Hedaux from ReThink Productivity shares his insights and strategies for improving productivity and efficiency in the retail and hospitality industries. With the help of clients, partners, and the ReThink team, Simon covers everything from measuring and tracking productivity to developing and implementing effective strategies.
Whether you're a business owner, manager, or employee, this podcast is a must-listen for anyone who wants to learn how to get more done and improve their bottom line.
Here's what you can expect to learn:
- How to measure and track productivity
- Proven strategies for improving efficiency and reducing waste
- How to create a culture of productivity and innovation
- Tips for motivating and engaging your team
- Real-world examples of how other businesses have used ReThink Productivity to achieve success
Don't miss out on this opportunity to learn from the experts and get ahead of the curve with your own business.
ReThink Productivity Podcast
The Robot Won't Steal Your Job, But It Might Make It Awesome
Rob Bate, Co Founder at FrontlineXP, shares insights from his extensive retail experience and explains how FrontlineXP is working to improve the experience of customer-facing employees through innovative technology solutions
• Frontline workers and operations teams are chronically underserved by technology and expertise
• The genesis of FrontlineXP came from wanting to help retail operations teams improve profitability and performance
• Successful transformation requires balancing technology, business process changes, and frontline worker experiences
• AI differs from automation in its ability to learn, adapt, and make decisions based on multiple data inputs
• Real-world AI applications are emerging in closed-loop workflows like Starbucks' drink preparation optimization
• Clean, comprehensive data is essential for effective AI implementation - "eat your vegetables" before expecting results
• Using AI primarily to reduce headcount in customer-facing roles undermines the service experience
• Technology should enhance rather than replace human interactions in retail environments
• Properly implemented AI can reduce employee stress, improve decision-making, and create more flexible scheduling
• Bringing loyalty and omnichannel data to associates can enable personalized service that doesn't feel like forced upselling
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Welcome to the Productivity Podcast. Today, I'm delighted to be joined by Rob Bate, co-founder at Frontline XP. Hi, rob.
Speaker 2:Hi how you doing.
Speaker 1:Yeah, good, thanks you. Yeah, good, good, good. So we're going to, I think, have a really interesting conversation today about the work you're starting to do at Frontline XP and how that kind of works into the world of retail, hospitality and any of those organisations that have got lots of people engaging with customers. Before that, let's find out a bit about you. So I know some of your career background from Boots, but for the listeners that maybe haven't heard you before, do you want to give us a bit of a career bio on how you ended up starting Frontline XP?
Speaker 2:Yeah, I'd love to. Yeah, I'll spare everyone the gory details of how you and I know each other from our boots days, but I'll pick up from there, I guess. So I probably spent the last 25 years or so in the retail space and workforce management as a sort of discipline probably an equal split actually in retail industry and consulting, and also an equal split of US and UK. So I actually moved to the US for the best part of 11 or 12 years. So when I left Boots in 2012, I joined a small consulting company called RPL Group and they landed a gig with a large US client, otherwise known as Walmart, and they said we need you to go out to Bentonville and help Walmart do this workforce management project. Would you be up for that? And it sounded like a great idea.
Speaker 2:So I went out there for what was supposed to be six months to 12 months ended up turning into many, many years and actually we grew, grew a business around that. The company got to a size of around 600 globally in the US. We had a practice of about 95 to 100 people, which was, which was quite sizable, and we delivered lots of workforce management implementation and strategy projects. Walmart was one of them and there's some other customers like Starbucks, lululemon, giant Eagle and a few others and we then got acquired by Accenture and I spent three years integrating the RPL US practice into the Accenture business and then I moved back to the UK in 2023 to focus on a company called Avanade is what I moved back to the UK in 2023, to focus on a company called Avanade is what I moved back to the UK with, and that company is basically the Microsoft practice of Accenture.
Speaker 2:So I spent the last couple of years really focusing on frontline worker technology through the Microsoft stack and, in addition to that, helping roll out and help clients realize value from the co-pilot package and, naturally, ai, generative AI and everything that falls off the back of that is what I've been involved with over the last couple of years. And then, truth be told, I got a little bit kind of fed up with big consulting and wanted to get back to retail ops, hands-on solving business problems, and I thought the best way to do that would be to start a business with some co-founders that I trust and have worked with in the past, and that's where we find ourselves today.
Speaker 1:Excellent, so a varied career. It's amazing how many people I've spoken to at the moment that have kind of spent some time working abroad. It feels like a more common thing than not. Did that make a big difference and kind of shape your views or, I suppose, market insight and how you approach things now that you've come back to the UK?
Speaker 2:Yeah, honestly it did. I mean the sheer size and scale of the US, not just in terms of a sort of landmass, I suppose you could say, but the business culture. There's a certain level of adaption that you have to go through to make sure that you're understood. It's a little bit tomato-to-tomato in some respects, but the scale of business out there and how it's done kind of really gave me a sort of broad exposure, if you like, to how decisions get made. We worked with lots of different clients, but the scale of business there is really the thing to behold. And just to give you some idea of that, I think Asda in the UK has got something like 630 odd stores, something like this.
Speaker 2:And in the US, like I mentioned, giant Eagle earlier on and people are probably thinking who the hell are Giant Eagle? But they are bigger. They're a regional grocer, they operate in just two or three states and they are bigger than Asda, both in terms of turnover, employee count and number of stores. And nobody's probably ever heard of them. But that's the nature of the US. And when you look at companies like Walmart that have got you know, 13,000 stores, 2 million employees, 1.4 of those, or 1.5 of those, are in the US. You know it's just another level of complexity scale. You know, expectation, even from clients and what they expect and what they define as value, is very different to what I experienced in the UK up until that point. So it definitely helped me get my head around.
Speaker 2:Okay, this is definitely different. There's different layers, different structures and also all those retailers. They work at different speeds and have different levels of maturity and complexity. So it gives you this huge exposure. And, coming back to the UK, you know, after sort of 10 or 11 years not being here, I can bring that experience to the UK. You know, after sort of 10 or 11 years not being here, I can bring that experience to the table and it's actually really insightful for a lot of customers that you know they want to understand. You know, are they? Are they very different to their American counterparts? Is their similarity? You know, are we ahead of them? Are we behind? You know, this is obviously good insight that you can get from all of that sort of stuff. But yeah, to answer your question, it definitely shaped my thought process and just the scale of business. There is just next level basically.
Speaker 1:Yeah, yeah, absolutely so. Frontline XP. Then tell us a bit about the thought behind it. What created the idea? What kind of stuff are you doing?
Speaker 2:Yeah, I'd love to so the kind of I'll come to the sort of pitch in a second but I guess the thing that I saw, especially over the last sort of two to three years you could call it post COVID, I guess is really just kind of the frontline worker being quite underserved, and not just the frontline worker, meaning you know, the store manager, the frontline employee, the colleague, but also the sort of operation side of the business as well. I saw this in the US and see it in the UK now and back here is the operation side of most businesses tends to be quite underserved in terms of their ability to access things like consultants that have depth and experience in the upside. We've seen a lot of the sort of big IT consultants offer project and program management and PMO and these sorts of things, which is all well and good, but it still doesn't deliver the sort of things that an expertise that an ops team really require around forecasting, labor allocation, workforce management, task management, employee experience, helping to drive productivity on the floor. You see a lot of these kind of functions still being left to the ops team to kind of figure it out, and they didn't really get a lot of help in my view. I think there's only a few companies I've come across in my history, you know, rethink being one of them, where you're in that position to really help them and I thought actually I could probably help there. So that was kind of the. But I see frontline work and the frontline worker being a real area of of of change and innovation and excitement. Actually, I think you know there's a lot of talk about, you know, next gen workforce and being demanding and their expectations are shifting and changing. I actually find that sort of stuff really exciting and if we can help clients move into that space and take advantage of, you know, and catch the wave of what's coming, we can actually put them in a really good spot. And I just didn't see anyone doing that really. So I thought this would be a good opportunity to come into that space and help. So that's the kind of genesis of it, I guess.
Speaker 2:In terms of Frontline XP and what we're looking to help with, I guess the best way to describe what we get up to is we help clients improve the profitability and performance of their frontline workforce. So we're very focused on the frontline workforce. Of course, central processes are key to that, but the frontline worker and what they get up to is the key thing for us and we specialize in specifically workforce management, task management and what I'll call experience platforms or colleague ecosystems. But we do have a really broad view of a lot of different technologies that the frontline worker touches. That could be learning and development systems, analytics devices, even you know all these things go into a frontline workers experience and the way that we like to think of you know how we can bring these things together. Technology isn't the only answer and we think that bringing the right combination of technology, business process transformation and frontline worker experiences can achieve the overall outcome. And we still see a lot of clients out there going after technology as the single solve or modifying a process and hoping that will create some sort of transformational outcome, and it really isn't the case. You have to bring those three things together and get them to work in concert and in harmony for it to really make a difference. Bring those three things together and get them to work in concert and in harmony for it to really make a difference and to bring that to life. Really.
Speaker 2:I guess really what we're saying is we take a holistic view of the frontline work and the workforce and how we can bring those things together to solve things. Like you know and these things are typically a front and center for retailers and service businesses but things like lowering their operating costs so looking at planned and unplanned labor, helping them to reduce the cost and impact of turnover and disengagement, which I know is a big thing at the moment and looking at things to improve their overall productivity, reduce performance variances from one store to the next, from one bar and restaurant to the next, and warehousing there's a constant sort of chasing of variances that are across business units. So we can help clients solve those sorts of challenges. And then, second to that, we help clients take, I guess you could say, a bigger swing or a more confident swing at things like reducing complexity across their operation. So we see a lot of applications, devices, information sources out there, not necessarily strung together in the right way. That can actually make work quite difficult for the frontline worker to to get done, also makes it difficult for the central teams to capture data from that and learn anything from it, and causes a bit of tail chasing. So we think, you know, reducing complexity is something that we help clients with, and then a couple of other things enabling AI.
Speaker 2:Of course, you know every client is saying where can I put AI into my frontline? Right, but which tech do I use? I don't want to make a mistake, I don't want to buy the wrong thing and then have to back it out. And also, if I do use AI, where's the ROI going to come? Is it within fiscal? Is it going to cause me a big sort of transformation effort Like where do I begin? Where do I start? You costs. And that's where we can start to look at things like introducing schedule flexibility, changing how the work gets done, how can we help managers make better decisions that make it a less stressful environment and therefore, you know, decisions can be not just of higher quality but also can have a better business outcome and are made more consistently across the business. So we can help them in those sort of two buckets of front and center sort of tactical immediate challenges, as well as help them with their long-term strategy on how to become a more lower cost business but also one that's perhaps more employee centric, with able to leverage AI.
Speaker 1:Basically, yeah, very topical, with all the cost challenges that are around at the moment. From again, we talk about it a lot. You know, all the tax rises, all the people cost rises, all the shipping rises, all the uncertainty in the world that leads to cost. So very, very topical, yeah, ai. So again, I think, on pretty much every podcast we do now there's some talk of AI, but we're going to focus a little bit more in this conversation. So, automation on the front line what type of things are you seeing where AI is coming into play, and is it here now? Is it something that's six months away, 12 months away? Describe the, I suppose, state of the nation.
Speaker 2:Yeah, yeah, good question. So in my view, I mean, I'll state the obvious, I suppose, in that there's been a heavy focus on the information worker thus far when it comes to AI. So CodePilot is a good example of the sort of package or solution out there that's helping people to, you know, interrogate data and make it very sort of conversational and accessible for the most part, but it's really only going to work for a laptop user. So I think it's safe to say that, from a hype cycle point of view, we're very much past that. Now. I think there's a there's a wide belief that AI is here, it's real, it works. It's just about applying it to the right situations to then figure out what benefit you want to use it for, and I think that's relatively sort of true of head office users.
Speaker 2:But when it comes to the sort of and the reason why I talk about information work is I think that what it does, then, and has done as well for clients that I'm speaking to, it's sparking this conversation of, and what's giving me confidence that we're past the hype cycle is they're asking okay, it works for me, but how can I give it to a manager to help them make a better scheduling decision? How can I use AI to serve up an insight that will guide them to do the thing I want them to do? How can I use AI to drive forecast accuracy and reduce the number of people that I need across the overall process? Where can I automate some of that so that we can get more people thinking about and managing outliers and these sorts of things? We see AI come up a lot in the scenario around. Next best action is how can I push the right information to the right person at the right time on the right device to do the thing, to take the action, to speak to the employee, to edit the schedule in the right way? So these are kind of common conversations that I'm having all the time. So that's why I know that we're past the.
Speaker 2:Is this going to be real or not? It's not going to be like the metaverse. You know that probably makes everyone roll their eyes. I think everyone's confident we've moved past that. But in my view, this is where I think you know AI and automation kind of come together and I do see them as very separate actually.
Speaker 2:So automation has been around for the longest and the way that I think of automation, or the best way that I can think of describing it, is that it's a predetermined outcome, it's based on conditions, it's repetitive in nature and automation. Automation is that it can learn, it can remember, it can adapt and it can figure out how to respond based on all of this input. And those inputs could be effectively infinite. Right, a chatbot is probably a crudest version of AI, but it's referencing what it should and shouldn't do. It's referencing different data points so it can make a good decision and provide multiple options, even that are probably all good. Right, and that's what makes it very attractive.
Speaker 2:For how can we present this? Or use AI to present information to a frontline worker or a manager where, instead of kind of letting the manager figure it out, perhaps we can use AI to say, well, here's two or three options based on what's going on. You know, maybe there's some traffic flow coming into the store, maybe the weather is changing. Maybe there's some traffic flow coming into the store, maybe the weather is changing, maybe there's a late delivery coming in. You know all of these things that a manager has to kind of go through and go okay, well, what's my next best action? What should I do now? They typically do one of three things Either do the thing they did before, which probably wasn't particularly good, or business focused. They do nothing, take no action, or they do the easy thing, which is to send someone on a break and hopefully, by the time they come off their break, the delivery will be here and all will be well with the world. What they're not seeing is the impact on sales, the impact on missed opportunity to upsell products, things like this, and it's that kind of somewhat invisible data and also all these other data signals that AI can really kind of bring together and serve up into something that is digestible and useful and actionable for the manager.
Speaker 2:So I think automation has its place, but you typically find it in sort of backend processes, I guess invoice processing, you know this kind of if than else, like I said earlier, those sorts of situations. But a good AI strategy leverages, I think, both of these. So AI can really be kind of front and center just to the customer, and we're seeing that as well, you know, in places like McDonald's and others, where it's, you know, suggesting certain things based on your buying history and loyalty data. But it can also be really useful for the frontline worker from the perspective of, you know, helping them internally as well. You know, for things like HR policy, information, seeking this sort of thing, but also selling product. So you know, for things like HR policy, information, seeking this sort of thing, but also selling product. So again, you know, ai is, I think is going to be, a sort of front and center technology that's going to help an employee be more effective in the moment. So for me, the key questions, you know, to answer the question directly, there's a few customers or businesses that are flirting with it at the moment. I can give some examples of where we're starting to see it play out.
Speaker 2:So AI is not magic. It has to work within a defined workflow. It has to know what good and bad is, what's a good decision, what's a bad decision. To be frank, if you don't know what your managers are doing today, where a manager is being more successful with their decision making than another manager, ai is not going to help you there. You've got to get under the skin of why is there a difference and a variance? What is the data points that the manager is looking at when they're editing someone's schedule, for example? If you don't know that, ai is not going to figure that out for you. It may give you some insights and say, well, here are the differences between those two managers, but what's the motivation behind the schedule? Edit, it won't be able to help you and therefore, you know, training AI and modeling the output that AI can give you won't be much use. But the technology works, know? I think that's the important thing.
Speaker 2:And just to give some example, I guess, of what we're seeing out there in the real world where it's really playing a part, I mean, there's a, an article from starbucks a few weeks ago. Actually, they've got something called green dot assist just for for those in the know or not in the know. Rather, the green dot is what they refer to as their I'll call them regular stores with the green Medusa logo. They differentiate those from their reserve stores, which are their sort of big multi-story experience centers which you may or may not have been to. They're actually pretty, pretty cool.
Speaker 2:But for the barista, the use case coming back to that bit about defined workflow I said earlier the use case is that barista is stressed out because they're dealing with counter workflow people walking in, they're dealing with mobile orders, internet orders, optimizing the order in which to brew each of those coffees based on the type of drink. It is how long it takes to prepare so that they can optimize around delivering a drink within five minutes. That's their goal. They've actually put AI around that workflow, so it's their effectively dynamically tasking on behalf of the baristas. They haven't got to think about it, it's just kind of presented to them hey, here's the next order. It doesn't matter the order in which it was made, online or in the store itself. The brew order is then what's optimized around that. So that's where, in the moment, real time, super, super quick, ai can help make those decisions. That just takes the pressure off the barista, and they've made those decisions thousands and thousands of times. They just don't realize it. So AI has got a really good place to play in that sort of environment.
Speaker 2:But we're also seeing things like Popeyes, taco Bell, other sort of drive-through restaurants as well, use AI to take orders. Again, it's a limited workflow. It's a limited menu. The input is coming from the customer saying please, can I have? You've then got the opportunity to upward sell Do you want to go large? Did you want to drink with that, et cetera. Those things are relatively repeatable, but it does need to respond to the information that's going on at the time. That's why AI, rather than automation, is probably a better fit. So I think we're starting to see it emerge.
Speaker 2:But it really does work well in those kind of closed loop workflows. But as a business, you've got to know what is a good decision. Otherwise, ai will probably make more bad decisions than your managers do, unless you know how to train them and what information they should use to make those decisions. So it's coming, it's out there now, but closed loop workflows definitely works Open-ended. What do you think I should do today? Those type of questions?
Speaker 2:It's not there yet, but that's where we see AI agents, you know, starting to come and play their part in those workflows and having very specific mandates in terms of how they can help a manager make a better decision. So we'll start to see more agents as well be very specifically deployed to to those sort of situations. Hopefully that makes sense. I probably rabbited on a bit there, but it's it's such a broad area picking on one or two and saying is that what is then going to be prevalent across? You know, all of retail is very hard to say, but we're certainly seeing it, you know, play its part in in certain businesses at the moment yeah, and the one thing I suppose, as we've educated ourselves more in in rethink, that surprised me.
Speaker 1:It's a bit like everything, isn't it? The, the marketing of ai will do this, that and the other for you. Great, and you know, I think the reality is people are still trying to find some user cases in retail. If you're playing around on Grok or Gemini or ChatGPT and making cool videos of people cats, skating on Mars in crash helmets, eating ice cream, you know brilliant and they look great and they're, you know, movie quality, aren't they? So I feel sorry for the marketeers out there Retail probably still looking for it. But the point I was coming to was the amount of good data. You need to train some of these things. I don't really know if we've worked with a company yet. That's got it. They've got data, but good, clean, robust data. There's hangovers from lockdown. There's anomalies from X Y. Robust data. There's hangovers from lockdown. There's anomalies from X, y and Z. So that, for me, is the bit that I'm not sure many people have grasped yet. Like anything, ai forecasting algorithms, reports, you're still good data in good results out.
Speaker 2:Yeah, 100%, and I think that's the bit. I said this on a post actually a few weeks ago and it got a few likes. It was put in my head by somebody that I was working with who said you've got to eat your vegetables, which to until now, but you've now got this historic issue with gappy data and it being next to useless. So you've got clients quite rightly saying, right, I want to go, I want to put AI in straight away, and then you're finding that you can't feed it with anything useful and that data cannot be corrected necessarily either. We can perhaps restructure it, refactor it, but it really does drive a direct impact on the results that you get from AI. And if I'd be really honest, you know, some of those early customers that we were rolling Copilot to were saying, oh, this doesn't work, it's rubbish. You know it's giving, it's hallucinating and it's giving me bad data, bad information, and it's because it was drawing on internal documents, things like HR policy documents that you know you could only access. Ones were for sort of 10 years ago or whatever. It was using the information as best as it could to say, well, here is what I think the answer is and people are like but this is hr policy, it's got to be right. It's like yes, that's why you've got to do some homework, got to do some groundwork, got to eat your vegetables, because without that you really don't have anything, and you know it. Also true, on the other end, you know, without sort of process change or behavior change, you won't get anything from ai either, if you're not going to follow through with what it suggests, but getting it to the point where it can suggest something good and useful, and that is, you know, business outcome driven.
Speaker 2:It really goes back to basics. Obviously, my data in good shape, and that's just not necessarily what a client wants to hear when they've got all this excitement of all these scenarios even going back to what I said earlier, they've got 50 scenarios. I want to see where ai can speed this up make a better decision, push the right information to the manager so they act at the right time, like great. But I need to slow you down. The data is not there, so how can we do it? And that's where it's a bit of a reality check. But once that is in place and those structures are there, you're then off to the races. So you know, for clients that want to dabble with AI. You know it's great to build those videos. Like you said, it's a bit of a laugh, but it's hard yards getting AI to really work for you. But it is a big investment not to be understated.
Speaker 1:Yeah, and I'm sure every boardroom probably in the world is conscious they should be doing something with it. I don't know if many people know, as I say now, what they should be doing, but it will be on the agenda for a conversation and if it's not, that's probably a bigger worry. So that's all kind of well and good. We, we help colleagues, we service information to the right people at the right time. We get rid of some of the tasks we can automate and you know my my bot speaks to the british gas bot and works out my new bill and comes back and tells me how much I've saved and if I'm happy with it and all that stuff.
Speaker 1:But what's the impact on the end customer? And then kind of one step back from that. What's the impact on the employee experience? Because you know the news is full of doom and gloom, of interest rates are going to go up again, potentially employments on the rise, which typically then means in retail we end up with less people on the floor. That's counterintuitive with the shrink situation. So there must be an end benefit for customer experience, but hopefully there's also a benefit for employee experience yeah, for sure there is.
Speaker 2:Yeah, and my view on. You know where can ai enhance the employee experience? I mean, making a better decision is one thing. If we take the manager as a good example, if we can remove a lot of the let's call it cognitive overhead, the what is the right decision I need to make at this moment in time, and turn that more into insights, alternatives, options, choices. That's going to help the manager make a better decision. If they certainly if they have a choice of one or two, three things that are all good for the business are also good for, and hopefully this is embedded into how they sort of train the AI.
Speaker 2:But making schedule edits as an example, where it doesn't spend over time but also is congruent with HR policy and scheduling policy, where we don't change someone's schedule on the day that they're supposed to be working, or the day before or within the given week for changing it weeks in advance, you know giving the manager a nudge and saying, okay, if you change the schedule, you know the risk of this person leaving goes up by 20%. Do you really need to change it? Is it really necessary? You've got enough coverage. You should be okay. You still want to. You still want me to change it, you know, and just having those sort of checkpoints there for the manager to go, you know what, it's actually very useful. Actually, you know what? No, it's not worth it. And just having that kind of pause break, that's something that ai is really good for as well. If you can serve the information up in the right way. It means the manager's more focused on their people, they're less stressed about the 50 000 things they have to do when they come in and maybe there's just a little organized list of 10 things because ai is doing the rest of it for them.
Speaker 2:I think that's not just going to help with the stressful side of things, but also, I think, you know, with an external workforce. You know that maybe at the let's call them a frontline worker and hourly worker they look at their manager at the moment and go. They have such a hard life. I'm not sure I want to be sticking around for that. Maybe retail is long-term, is not for me and they. You know we see the turnover at the sort of frontline worker level where people don't want to lead a store or don't want to be a team lead, and I think by having this kind of reforming that that work. It's going to help people see retail, as you know, a longer-term career and where they can lead other people, especially if they don't believe they're going to have a ton of admin to have to take on as well.
Speaker 2:I think for the employee themselves as well. You know, using AI to do things like serving up shifts and offering them up to people and having all of that managed. I think it makes it less draconian than you know than the manager scheduling everyone and having to manage every single change, day off swaps some solicited, some not. It can remove a lot of that pain and make it a bit more democratized, so that employees feel like they have more of a say in how they work when they work, which is obviously a really important thing Even now. It'd be even more important going forward as the Gen Z population starts to make up a bigger proportion of the workforce, of course. So I think AI is going to drive a lot of impact on employees.
Speaker 2:I really do think and I have a strong opinion on this that using it to remove roles on the sales floor is a bad idea. I think it's very hard to grow your business and deliver fantastic service if you have fewer people on the floor to your point about shrink. Those people are your brand. People come to your store because they want an interaction. If you went to an Apple store and it was all automated, I think you'd be a bit miffed about having to hand over 1,500 quid for a phone or a macbook and you serve yourself.
Speaker 2:It's fine at mcdonald's because it's an order taking business. Now, right, you know what you're getting. We've probably all had mcdonald's many times and it's quicker, convenient and you buy into the value that provides. But for a service-based business, which is what effectively retail is, using ai to remove roles as a shortcut to editing the labor model, for example, or driving efficiency purely for business benefit. I think we see a glimpse of that in self-checkout. Um, that I don't particularly enjoy anymore. Selfishly, it's gone so far. The other way now I go into my local asda and there's one man's checkout and 20 self-checkouts yeah, there's limited choice to do anything it's become a you know it's effectively become an obligation.
Speaker 2:Now the choice has been removed, so it's. I think when you get to that point, it just makes it a bit more, you know, uncomfortable. But I think there'll be a lot of benefit for employees if, if retailers and similar businesses employ it for to enhance the service, and they'll find that actually they can leverage the people they have in their store in a slightly different way to be more customer focused, and I think they will actually enjoy that. If you're in retail, you're a people person. There'll always be some people that want to be in retail to then be in the warehouse. Okay, the time for that role is probably disappearing, but it means we can spend more time on service and actually when people are working with people that we can spend more time on service. And actually when people are working with people, that's when they're most interested and excited. And if they get access to services that make them able to balance their work and their personal life schedule flexibility is a good example of that and they know what work they're doing and they know what a good job looks like and they get feedback and they get guided through their day. And for a new employee that's joining the business. They get a curated onboarding experience that is managed through an ai process. That's digital first. I think people want those things and they'll find actually, this is a good place to work. Quite enjoy it. I know what I'm doing, I know what good job looks like and I get feedback and I think those sorts of things are really important and attrition will drop.
Speaker 2:You know where we see employers do some of these things. Their attrition is ridiculously low. We see a couple of those in things. Their attrition is ridiculously low. We see a couple of those in the US where they are employee-centric, you know, and they get the benefit. It's you know. I think businesses just have to have the belief that these things will turn into benefit From a customer point of view. As long as that is passed on, I think they will get the benefit. I do also think as well we've seen this with a few retailers particularly the sort of high-end, sort of luxury fashion end of things which I guess provides a glimpse of what's possible elsewhere is bringing loyalty data to the surface so that clienteling is more natural, you know, knowing that a customer is in front of you, let's say they go to Lidl, lemon or something, and if they're in front of you and they're picking a pair of yoga pants or whatever, if you had some form of AI that could present to you as an employee. Hey, by the way, did you know? I can see that you're buying these pants here. Did you know the top is 20% off? I've only got one left. Do you want me to go get it for you? You know, a customer's probably sitting there saying yeah, I didn't. I didn't realize that.
Speaker 2:This is great, right, customer gets a fantastic experience. You, as the employee, are confident because you've got information in front of you that you can trust. You know exactly where to go get that stock customer fit. You know, and you put all that together and you go. This is just a fantastic experience that's very different from the competitors. Down the road, you know and you put all that together and you go. This is just a fantastic experience. That's very different from the competitors down the road, you know, and when you start bringing in the sort of loyalty data, digital data, omni-channel, if you can bring that information and surface it to the person that's in front of you, they can deliver amazing service and they can do it confidently. It doesn't feel like a horrible upsell. You know where people then start to feel that kind of ick. It can all be very, very natural, you know, if those are the sort of experiences that you want to design. So I think the customer can get an amazing output. They can actually probably get, you know, offers and things that are very unique to them served up by a human. I mean that's where I think AI can really drive a proper impact. And you know you're then going to see in average transaction value, basket size and so on.
Speaker 2:For me, the the outcomes are very obvious, but it has to be deliberately designed that way to, I think, balance the employee experience and the customer experience. It's. It can't all just be about investing the customer, give them everything they want, and then the employee comes like second, third on the list. You know, if the business efficiency comes second, turnover will still remain, people will still be disengaged, and just because you present something at the till, the register or the tablet where you're serving that customer in that yoga pant example I gave well, what if the employee just doesn't care and they don't want to offer that top for 20% off and it's the last one, then you haven't made the sale, you know. That's why all these things have to be threaded together and designed deliberately in balance, because if you don't, what you'll gain in one area of customer experience, you will then lose an employee experience, and of course it's a cycle. So probably convoluted answer, but that's kind of how I think of it.
Speaker 1:No, that makes complete sense, and I think that the key theme there was that you've got to pass the benefit through. So if you're using it as a blunt cost-cutting tool, then clearly employees will suffer and customers will suffer. If you're using it to free up time and maybe there's a bit of cost in there as well, because people people always be conscious, but not the primary driver then you're probably heading in the right direction. So I think we could talk about this for another couple of hours, but we'll pause there. I really appreciate your time. If people want to continue the conversation, find out a little bit more about how you can help them. Where's the best place for them to reach out?
Speaker 2:yeah, good shout. So I'm very active on on linkedin. I love to love to post every day. So, uh, you can hit me up on on linkedin, drop me a direct message. We can connect there. Uh, you can also go through my website, book a book call with me. I'm an open book. We want to help clients, you know, understand the stuff and have a perspective. And actually something we I should have said earlier as well is actually we're independent. Much like yourself, simon, we want the best outcomes for our clients. We won't back a single technology. We're tech agnostic when it comes to that sort of thing. So we'd really love to have conversations around how we can help a client achieve their business outcomes without any sort of bias. So, just hit me up, book a call, pretty available. So so, yeah, happy to discuss the business challenges, how we might be able to help either book a call or drop me an email. Actually, it's robrob at frontlinexpcom perfect.
Speaker 2:Thanks, rob, appreciate your time yeah, thanks a lot, simon cheers.
