WFM Unfiltered | Workforce Management Podcast

The Death of WFM Tools | Jimmy Hosang

• Irina Mateeva • Season 1 • Episode 44

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WFM is dead. At least, that's what Jimmy Hosang thinks - well, the tools, anyway. In this explosive conversation, Jimmy joins Irina on WFM Unfiltered to challenge everything we think we know about workforce management technology. Forget dashboards and legacy software; the AI revolution is already rewriting the rules of contact centre planning, and Jimmy doesn’t hold back.

From his unique perspective as a tech entrepreneur with WFM roots, Jimmy exposes how AI isn’t just disrupting processes - it’s replacing them. He talks openly about what planners need to survive in this new world, why most software vendors are selling snake oil, and how humans still have the edge - but only if we evolve.

You’ll learn why Excel’s days are finally numbered, what it really means when someone says “AI,” and why most operations teams are sleepwalking into a legal and compliance disaster. Jimmy breaks it down in plain English, and Irina isn’t afraid to push back. They dive into the difference between true automation and fake AI, unpack performance management in the age of machine learning, and share real stories of transformation and turmoil.

If you’re in workforce planning, leadership, or on the tech side of CX - this is your wake-up call. Come for the hot takes, stay for the survival strategies.

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Irina:

Hello everyone and welcome to WFM Unfiltered. Today we'll be going to controversial Manchester because my guest, I don't know, we, we were about to do that recording a while ago. and I would like to think that he was scared of me, but sadly he wasn't. Let how this recording will go. So I would like to introduce you to Jimmy. Jimmy, how are you doing?

Jimmy:

I am good. Thank you. I'm good. I was just talking to you, just before we started about, me, me having a weekend on my own with all of my children. So you've got me at a good time because, deprived and I'm a little bit battle wary, so you might land a few punches on me today.

Irina:

So the way that I heard it is you're even using your children as an excuse that I'm.

Jimmy:

Tell you what, I'll use anybody as a human shield, it doesn't matter!

Irina:

Fair. Fair. But before we start, kicking your, butt, I'm sorry, talking about stuff, can you please introduce yourself?

Jimmy:

I can indeed. So I'm Jimmy Hosang, the Founder and CEO of MOJO CX. We are an artificial intelligence platform that, specializes in making every contact center conversation valuable, and we do that in a few different ways. The first is around, guidance and next best action. So what to say, how to say it. So agent assist, but trying to put things into plain language. The second part is around, monitoring those conversations. So using speech and text analytics to make sure that your agents are keeping to the script the right being. closing that feedback loop when things haven't gone quite so well, or when things have gone brilliant to either give them a targeted coaching intervention or give them a digital pat on the back because they're doing a good job. So that sort of harmonic, set of features and a bit of my background as well. So how, did I. contact centers. I've been working in them for about 15 years now. I started off in credit risk, did some pricing, did some marketing, and then my very first, job as a consultant, was, in a capacity planning team in Leeds. And,

Irina:

Oh.

Jimmy:

and then I've been working in kind of contact centers ever since, and I've worked in capacity planning, resource planning, supply. I've did a little bit of real time. I've done co customer insight pieces, and then I've worked in BPO retail and things like that. So hopefully. from a WFM perspective, I don't know, I don't know everything about WFM and it's as much of an art as a science, but hopefully I'm going to be able to, at least hold my own.

Irina:

So we have a traitor?.

Jimmy:

Yeah, I, have, I've, turned on myself, turned on myself. Yeah.

Irina:

Okay, so not only you using your children as an excuse, you are a traitor, but now I, so you own your own company doing ai.

Jimmy:

Yeah, I thought I'd lead off with that. But I think as well, I'm actually, I'm, I've actually, a little bit of a, I'm, a little bit of a naysayer when it comes to artificial intelligence and things like that as well. I think like a lot of people like talk it up and talk it beyond its means. So to a, certain aspect. I'm a little bit of a. I'm a little bit of a naysayer when it comes to it, but actually, when it comes to things like WFM or CRM or just CCaaS, I do think it's got applications that are already pretty solid and, as, as good as a human, at some of those things. But I'm sure we'll come onto that, as we go through the conversation.

Irina:

Let's get right into it. I have read, I believe, that post was maybe a couple of months out already when, you were approaching the topic as AI is gonna replace WFM and basically maybe even agents in the future, and we'll no longer need WFM/planners. Human beings. So take me away. explain to me how this is gonna happen.

Jimmy:

Okay, so first of all, let just explain like my thought process, around some of this. So for a long time, a long time I've been pretty down about AI and what people class as AI and what people class as automation. And was a running joke within my company that. we didn't have AI in our name, and the reason for it is because we were like, if we add AI onto our name, we'll just get more hits. Like it's just a marketing tool. So one ti one day we changed our company to have AI within the title and the, the, hits on the landing page and things like that. And our traffic like increased because of it. So we just believe that. Probably about two years ago I was invited onto a live, a live talk, the Contact Center Network with Gary Gormley. And we were talking, I was talking with a couple of guys, some that have kind of auto QA companies, that do kind of voice ai, but from a more of a consulting point of view. And, we were talking about the applications for artificial intelligence. And look, I said this, it wasn't, and it wasn't wfm, it was software. It was SaaS it's even the stuff that I'm doing. what I said was, why do you need. why do you need Salesforce? If you've got ai, why do you need, why do you need, If you, if, why do you need V****** if you've got an ai? Why do you need a CCaaS platform? Why do you need G***** or A****** C****** N*** C******* O** or whatever? Why do you need all of these things if you've got an ai? And, people looked at me like I'd grown a second head like the other guys, including Garry where like What are you on about But what I said what I said was, and I'll, it's probably best explained through, through the journey of CCaaS. So when, back a hundred odd years ago somebody wanted to make a phone call, they simply picked up a phone. And it went through to an operator, and the operator said who do you want to, who do you want to speak to? I go I want to speak to Irina Hollatz, I want to argue with her about WFM, and they go"Oh, right, Irina" and they'd put you through. And then because phone calls became so popular, proliferation of phone calls, they couldn't employ enough operators to route the calls, a different way of doing it. So that's how we went to telephone networks. So hardwired telephone networks where through numbers you could route people through to different parts. So then there was a proliferation of, hardwired networks. Then, people wanted to reduce the cost of the networks. it was too costly to maintain, so then we needed to move it to fiber optic and we needed to move it to digital. So was it 30 years ago? Maybe slightly longer. But moving forward, we then moved to voiceover internet protocols and it was all digital kind of traffic, digitizing it, moving the. the mud and human labor engineers into data centers, and then you got, then they were building data centers and stuff, so your physical engineers became more of. digital engineers Then that's, my first, foray into kind of, voice was I used to work, for Vodafone in service center, a client, with just engineers, BT engineers, AV via engineers. I was just, it was just surrounded by service, and implementation engineers. So that's, that was my first taste. And then came along. So CCaaS came along because the cost of all of those engineers was so much that we needed to make it simple to route calls around. And therefore, because everything was then digitized, they started to move everything into the cloud. And that's the, that's where we, are today, which is the proliferation of CCaaS. So everybody's now migrating for on-prem solutions cloud. However, my belief is that with ai, the, and sorry, let me just say one more thing. The idea of CCaaS is you can just a web interface, a contact center together through drag and drop with low code with low. of expertise and to get a functioning contact center with high availability. So my belief was, is that with ai, you no longer need that interface. think it's, Going back 120 or yeah. Hundred 20 years to just being able to pick up the phone and going, I wanna to speak to Irina. And it just route you. The only difference being is those operators are not humans. They, and they could do a billion things all at once and Humans like interacting with UX and UIs and having to plump things together. I think it's almost slightly simpler, whereas a human being, a human customer could just pick up the phone and go, I want to speak to, I want to speak to brand A or Brand B or brand C, and it will call them. And then the AI on the other end will just understand that the customers contacted them. Even via an AI and then just route it to, a person without anything in the way. there's not UX or UI necessarily in the way. It's just ai. Then WFM. So if you then take that concept and then plug it into WFM. So much of my working life, wrestling with WFM systems, with like with capacity planning, forecasting, supply side, keeping up to keeping your agents up to date. No one ever does the for uses the forecast in the system. They're always taking it out and doing it in Excel and then plugging it back into it for the, interval profiles. Everybody's take, doing the interview profiles, profiles out the system, plugging it back in skills mappings. So all of the skills issues is all like always different and it's not quite how the system would when everything was. Every time you wanted to redo your shift pattern, it uses Erlang to basically do a mathematical calculation. I've had, situations where, because of the size of the business, because it was all on a p on a, an actual physical piece of tin, to take so long to do the shift patterns that people just used to then take it out of the platform and do the shift patterns manually and then load them back in that.

Irina:

that. weekly so erm

Jimmy:

yeah, to, do like to, for the real time team to do quality of service, because obviously you've had that absence and sickness in the morning. It used to take so long to get through. I think. I think at one point I was working with teams that were planning for 6,000 agents, it was just taking so long because it was on an old underprovision. anyway, and I go through all of this and I'm like, that's just the software. So that's just the software. On top of that, you've then got all of the humans who are trying to have to fight with the software to make it work. just have a different theory. I just think that what if your planning team. Just had an LLM, which you said to her, I want, a forecast with, I want you to take this data from over here, a call, and I want to forecast, and then I want you to just put the data there into, that, and then do that every day or every week or every month. And then tell me the variants. simple. I'm like, then from a resource team, I want you to take that, I want you to look at my budget spreadsheets, and then I want you to work out a budget and then want to tell me my, zero to 12 weeks and then, all of these different things all of the way. Why do you, why do I need, I'm really use the brand, but why do I need V****t? do I need a wfm like, yeah.

Irina:

Here because you're gonna get me in trouble. And,

Jimmy:

then, but I'm just going, I'm just going. The natural step is if I've got all of these digital, digital AI assistance that replicate my best capacity planner, resource planner, realtime planners, HR coaches and things like that. Number one, I even get to the human part of it, which is do I optimize the humans book? Why do I need the WFM? Why do I need the ux? And that's where I got to, that's where I got into trouble with you. That's where I got into trouble with lots of people around say the send this thing.

Irina:

I, will say one thing. First of all, I'm gonna give you a point because one of my biggest irritation is people not understanding the difference between automation and ai. And I feel like lately they're using them interchangeably, like even old traditional WFM systems. Now are using, we have ai. We have ai because they can do some kind of calculations on the second that are automating the process. That's not ai. let's start here. So now that we got that covered, I feel like we are not exactly on the same page when it comes to. What is workforce management? Because you're referring to the tool itself. I'm referring to the team as such to the whole cycle. Whether you're using Excel paper, you are hanging your, schedules on the wall. This is done by workforce management team, As, for the, tools, I do believe they should be enhanced by ai. Absolutely. The thing that currently bothers me with such bold statements is, why do you need WFM tools is many different reasons. First of all, in the major one legislation, there is no current legislation around AI when it comes to, data privacy. Just for example, so go to some very strict regions. Let's use I don't know, Germany for example. I doubt that at the moment you can say, oh, I'm just plugging ai. It's gonna read all of your information and provide with some output, and you'll be fine. They're gonna be probably showing you a middle finger because we know that they have very strict regulations who can see that data. How can it be used for how long? And so on and I feel that when you say that AI is replacing WFM teams, a lot of people tend to get scared and anxious. And now when we're bundling with a lot of layoffs and stuff, this is basically creating anxiety on the market that shouldn't be there.

Jimmy:

let's just do the, let's just split that into 2 a little bit, though.. There's the, let's, say, the productivity gains or the, productivity gains or the accuracy efficiency versus maybe the regulations and the ethics. But let's just do operational overhead. yeah, so from the planning perspective, I'll give you my thoughts on this. I'll probably cross over the regulations my, when we've done analysis before my team, so first of all, my, my company, my team, we're not doing any WFM automation stuff at the moment. I've got this, I have ideas around it, but we are focused mainly on just answering calls and delivering the best customer experience. So I'll just, caveat it with, I'm not, I've not got deep thinking or deep knowledge around this type of stuff. However, I can apply it to something that we do, which is automatic quality assurance. The regulations around, QA obviously is, all calls. Yeah. All calls are, recorded in the UK for quality and monitoring purposes, and we need to check things. Now. What we rubbed up against initially was when we did auto QA was how accurate are you marking the scorecard versus a human, but the, the challenge that we faced, but we faced into was there's a perception that humans do things accurately. Which we don't because we always have bad days. like some of us have had the wives go on holiday for a week and have had to look after the kids. And and then, they have to talk about, stuff on the podcast or got to do like high executive function tasks. when we did a, like for like study, especially, on items that are subjective, did the, agent display empathy? not particularly great at spotted empathetic. You, might be like miles better, somebody else might be miles better. It doesn't matter how much calibration sessions you have in your QA team, there's a huge gap. So what we uncovered was, this is. Maybe slightly controversial again is that your human QA 60 to 70% accurate when you did a proper calibration. So if I do a hundred, so if then I auto QA a hundred percent of the calls, but at 70% accuracy, I am, from an accuracy perspective, I'm at least as level as a human, but I'm getting across like more and more calls. So I'm just gonna loop that back to the reg, the, regulations in Germany in general. Like I think that, I think that I find Germany strange. I, can't quite wrap my head around the concept of, first of all, your, your, first of all your customers being able to opt out of, recordings and personal data. That's fine. the concept that your workers can, say whether or not happy to be coached on. I for me personally, I, look, I grew, I'm, mixed raised, but I grew up in uk. I grew up maybe in this capitalist like ecosystem, but to say that a worker shouldn't have the performance monitors, I, it's quite challenging for me to understand and I'm having to, my company goes into different regions, understand those cultures and whatever. That said though, when it comes to WFM I think that there's lots of benefits, a route to, the workers for having artificial intelligence interacting with them. And that's because, when we're doing some studies around a human interacting with an AI and an employee interacting with an AI for coaching, they actually prefer an AI coach to a human coach because it's not personal. So if you, so if your AI says you've been rubbish at your handling time for payment calls today, you're 30 seconds more than anybody else. Then you go, okay, fine. Whereas if it's, Simon who I've had a, disagreement with, who's my team leader, who've already got who I'm. already a bit, like, annoyed with, then I don't take the, feedback as well as maybe with an ai I think it's maybe the case for, WFM and not all of the WFM interactions, but some of the WFM interactions because we have humans cranking handles all over the operation, has rigidity built into it. Because of humans having to take data out, put data in, we have to lock the plan down 12 weeks in advance because everybody wants to know the shift patterns, blah, blah, blah. Whereas I don't know if you're on six months, six week locks or 12 week locks or shift locks and stuff like that. But, ai. you wanted to change your shift at the moment, you might be scared to call in your re call in your resource planning team or speak to your team manager. Whereas what would a workforce look like if it was more dynamic and it was an AI who would just switch people around and could do it without having to someone to crank the handle? So I do think human in the loop is important, an important first step, but I. A lot of rigidity that's built into planning processes that could be taken away by artificial intelligence and it not caring about how hard the work is to redo the forecast are to move some shifts around. So that's a bit of my view as well.

Irina:

Okay, cool. I'm partially on board with that because I think that there are still to this day a lot of stuff in our teams that are obsolete that we shouldn't be doing. We should be doing better, more efficient things that can be and should be automated even, even if we're not talking about ai. However, for me, it should start and it should end with the planner, and I'm seeing any kind of tech as an enhancement of the skills of a planner, of an agent, of a quality monitor person or whatever, not as a replacement. And I'm having a huge issue right now because you were saying, okay, AI is gonna remove bias, basically. That, that's good. That's great. What if I as an agent, say. I understand, but whatever happened, I need to bypass you and speak to my manager or to the planner because whatever my child fell and I cannot do that shift. And they're saying, oh no. Oops. I'm so sorry. just, let your kid cry. Let it, go on its own in the hospital and you're needed here.

Jimmy:

Where I think my difference is that I the best planners will become hyper valuable. I'm just saying that all of the lower level planners and the people who are cranking the handle, those are the people who I think are most at risk. Because if you enable your best planner to, to have almost unlimited like hands, to do things with, then can optimize their workflows and become like super. super planners who could do loads of different stuff. I worked with a guy, I might give him a name check. In fact, I'm gonna give him a name, check his name's Paul Pritchard. And Paul Pritchard taught me planning. And he, was like Mr. Miagi, he Mr. Miagi, then, he was, was a capacity resource planner. I was, Daniel Sanand he was Mr Miagi, and i, I thought I was like the best, I thought I was the best thing since sliced bread, and he just took me down a peg or two, constantly this was maybe 2010, take a quick note that Mr. Miyagi was very high on empathy and stuff, so I guess your teacher skipped this part with Yeah. No, totally skipped it. Every time I said Oh look, like Ive done this forecast,no, that doesn't matter every time I did like an AHT prediction, no, that doesn't matter. He was like super high level. He could build anything in, in, in Excel and stuff like that. And, it wasn't particularly empathetic, but, he, me, what he taught me things that I know. And there was other, people who taught me like a lot of the softer side. But that said, but if you gave him unlimited capacity to build forecast to, to push data to and from systems because he had a technical Problem, which was he did everything in Excel, but then the Excels had to then be pushed into, whatever WFM system it was. Then we had forecasting models in a different system, in a different system. But if you gave him unlimited capability as one person, then he would be able to, to. and maybe through an interface where he didn't have to code, he could just go, these are the specific things I want you to do. And I know specific layer, we were sat on a team of maybe 16 planners and maybe Paul could have done all of it. Maybe he did 15 years ago, but he can definitely do more of it today. So I, I think I, but I do agree. I agree to a certain extent. I just think your best guys are gonna be more productive.

Irina:

Oh, I, we, are on the same page on this one. what you're referring to and what I'm referring to is administrators that are doing copy paste, manual swapping of shifts and stuff that even with traditional WFM systems, you can do even right now. And that's why I'm saying like, forget about ai. A lot of. Stuff currently on the market should be more efficient. However, what I'm slightly annoyed with is minimizing planners to just the technical or number aspect, because for me, a planner should be much more engaged in the conversations with the different stakeholders, knowing where the business is going, getting that knowledge, thinking, how can we improve the processes, getting other stuff on board, give any sort of suggestions that can help the business. Right, which is not necessarily AI driven part or tech driven or numbers driven part. So this is where I'm having very big reservation on. I see that you're mostly coming from numbers perspective, but that's not all about what planning team are doing.

Jimmy:

It's not, but I, let me, I, but it's it's No, hear me out a second. I think the political way that you, that planning has to nudge its way through the entire process is, one thing, but I've always, my planning from a planning perspective, like when I started planning it was part of finance. So I worked in finance planning teams. It was operational planning capacity resource, but it was, it sat within the finance division. So maybe I do have a different outlook on it versus the operation, the operations, point of view. But I think a lot of the softer side of things, the interfacing into the. First of all, I think the hard numbers are I have a budget that I have to hit and I have number of people that I need on the phone to hit quality service in a day. is the hard numbers. I think the challenge for planners and the guys who I know who are the best. A very, good from a, political point of view and a stakeholder management point of view, but I think that's the nature of, I think that's a, not the nature, it's the byproduct about how we've set up businesses a little bit and the complexity of the businesses, and especially working in the uk like the bureaucracy's involved in some of it, whereas, with the use of AI, automations and ai, I'm using them slightly interchangeably as well because I think the automations sit behind the AI, for me.. What I'm saying is I can envisage a world where you go into a book, a planning session, you go into a planning session, just you Irina as the, like a high, level, super experienced like workforce management specialist. And within that session, you as a planner hook up to a SharePoint site with the, latest, nine plus three or four plus eight budget kind of stuff. You can hook into any information that CFO or the finance guys have, you can be recording the conversation live and you can speak, be speaking to the HR business partners about any feedback that's been getting from the operations and things like that and any issues and stuff like that. And then can take all of that information and you can be asking the LLM and to be creating scenarios for you, in the room in the moment, you're not having to take it away. You're not having to come back. you're actually like on the fly being able to reply with information and conduct analysis and that's that's why. I've said this to people, and people look at me like I've grown a second head. is, why people thought it was crazy two years ago. But I see that's what people are doing now. People are doing it testing, for interviews, for, I think I saw like them using like this type of, this type of technology for, I think it was like un in the un like for disasters and stuff like that. Like how you can take all of the data and, work on it on the fly. And so I still think there is that human element. I just think that at the moment you've got these high level people and then you've got a lot of, you've got high level people, you've got people who are moving into that space. Cranking of the handle, trying to get data into systems. And imagine Irina, imagine if you didn't have the problem of getting it into a system. Imagine if you could just say, I want you to, I want to see my forecast. That's my forecast. That's, I'm comfortable with it. I've looked at the accuracy. I'm comfortable now. Now just put it now, just save it down. I don't need to put, push it into, this software or this software. It's done. It's there, it exists within, layer. Then I can say to my resource planner, and just reading that into a, into the, the AI LLM. And now go and give me what is my best kind of, interval for Monday, Tuesdays, Wednesdays, and things like that. That's fine. Do the accuracy. Forward it to me. Am I happy with it? Yes. Now save it down so you remove some of the friction points that we've got interacting with interfaces as well.

Irina:

I agree with you. I absolutely a hundred percent. I'm hoping we get to this stage be, but this is exactly my position. I need to tell the AI what I need. You need that human element of a planner of a what, whatever function it is to navigate that ai, what it wanted to produce. And it's not much different with any kind of tech. You need a human element behind it to be the driver. And this, when you're saying replacement, because for me, I'm looking at it from the perspective of. People in the team, right? I need a human. this is the same as your, for example, once upon a time when people were calculating on the calculator how much you have to pay them. Now everything is automated. They just scan it and Yeah, exactly. This is what we're gonna replace with people copy pasting shifts. I agree. However, when it comes to. Just planning people and day-to-day operations stuff changes. People come ask stuff constantly. Something is in the way. There needs to be a decision maker for all the changes, and AI can advise you. What if the people are not happy with this decision? It needs to be escalated to someone who is a human decision maker. And that's the issue when, for me, somebody says, we no longer need WFM in general. Okay. We don't need teamlets, we don't need agents, we don't need humans at all. So what do we do then?

Jimmy:

Yeah, so I don't, I think the concept of WFm will, remain even if there's no human agents, you'll still, because workforce management will still be required for managing compute you'll say, say in a world where a human being does, hours a day, I don't know, like five to six hours talk time, however many hours a. Like maybe 80 hours a month or something of talking to customers, that 80 hours will be replaced even in an a, a full AI world will be replaced with 80 hours of compute time. It's 80 hours of an AI like transcribing, like doing things and stuff like that. On top of that, you will still need workforce management. You'll still need resource management. It's managing how much demand do I need at certain bits and optimizing it. So I think, maybe I'm being slightly controversial when I'm going. WFM is dead. Our CRM is dead. how we view the construct of it, and the context of it, is very very different. I think it's very interesting. When I first started thinking of working in capacity planning, but my, the software that I used, which isn't used at all.

Irina:

Please don't trash any more companies on the call!

Jimmy:

No, but the concept, the studies that I was reading was not about, centers. It was about, medical emergency rooms and things like that, and it was showing simulation models of people. To, go around, like to check in and then to go to a e and then to get a scan and all these types of things. So the concept of those types of things I've never thought of before, and I think it's paradigm of what you're managing and who you're managing is different. then if the, human agents are going to reduce, potentially reduce down, which I don't think it necessarily will as quickly as some people think. What I think will happen is, I think there will be more voice, but it's just done by AI I think that once you remove all of the barriers to, for a customer to have a conversation with you, and in fact you make it even easier for a, customer to have a conversation'cause a customer can get ai's to call you, then I think proliferation of conversations will increase dramatically because you're just gonna have like constant conversations between humans, ai's, ai's, and ai's, ai's and humans, like all, all over the place. So I don't necessarily think that there's gonna be this huge pattern change, but. For, workforce management or for resource management, let's call them teams to get across that there will have to be, there will have to be efficiencies gained because you're gonna have to, because the cost will not be able to like, go linearly with the amount of conversations and then. Finally. Yeah, I, think you are, you are right. I'm maybe being a little bit controversial, but I don't believe that, there's going to be zero workforce management. I just believe that the actual like assurance. Auto quality assurance through speech analytics and things has reduced the size QA teams, and now you've got your most attuned people. You don't need, you don't need to go wide because you've got to hit your numbers. You can go specialized and you can get the best person in. I personally believe that for almost every single workforce management discipline, you can have less staff, but higher paid. More specialist and who know what questions to ask and how to tune the machines.

Irina:

Okay. You're not that bad, Jimmy, I think we're

Jimmy:

That's what people say once they get to know me!

Irina:

But it's before they get to know me, they don't like me!

Jimmy:

and then if you know me too well, then you start to hate me again.

Irina:

Yeah, I absolutely fully agree and one of the things that personally gets to me is we know that traditionally contact centers are understaffed. However, we're trying to think of ways to basically make them correctly staff with the people we have and remove the stupid things, the repetitive things that we're doing, and make them do better things and potentially get even higher pay for your specialists. But then seems to be. I think it's all about phrasing and marketing ai. And at the moment we have a lot of AI companies, vendors that are coming with our bullshit solution is gonna help you with this and with this thing.

Jimmy:

On that point though, I think the mix of stuff that you have to do or can do because of AI is, is important. So I see a world where you have full, how you can blend full-time, part-time, gig economy staff. All into the same planning model. But the moment, because it's complex to do all of those different things, maybe like globally running, like global operations, it's quite challenging to mix, blend all of that together. But you've got. If you've got AI supporting planners and supporting WFM teams all of that together, that's what I believe will be the future. It'll be ai, AI agents with gig economy agents, with full-time agents with part-time all blended together. That's what I believe will be the best. But if you think about how people think at the moment, it's got, it's all shit or all sugar. It's all right. So I'm gonna have all humans and then I'm gonna quickly try and get everything to automation. Self-serve. Everybody hates self-serve. Everybody hates chat bots. Everybody hates self-serve. But the human mind in cocorporations can only think of all shit are all sugar. everybody does it for themselves or, we have a white glove, service where you've got humans, but the actual future is a blend you've got and then, but then that. How hard is it to get a CCaaS platform that helps you do with that blend? It's bloody impossible. So that's why do you need a CCaaS when you need, like the inherent flexibility? You can't be reconfiguring stuff all of the time. Number two, like why do you need a CRM when you've got, if you've got gig economy people, you can't, you don't have enough time to train them up on CRMs and things, so how, so why do you need a CRM? Why can't you just capture all of the information and the, and AI just plug, plug it all in, and then send off whatever needs to be sent off. Like, why do you need to train people on systems and things like that? so all of these things make a planner's life harder. Whereas, but AI can make it easier, but to the point where actually then it does start to eat into the resource requirement WFM teams, because like I said, your best play, best people can then configure things in that environment in a much more dynamic manner. And the difference is they ask the right questions.

Irina:

I think you're converting back to WFM. I see the passion coming back to the way that you're speaking about workforce management, but maybe just, and on the note that I feel like many people are using workforce management, teams only for contact centers, where in fact, it's the same for retail, hospitality for, Hospitals, airports, whatever have you. Every single person that is scheduled there to check your passport or to welcome you on the reception of the hospital is a person with the shift that the planner has to create for. And there it might be even more difficult because you don't necessarily have the traffic coming from queues that you can see these numbers and you're basically working based on. Good feeling in a lot of times. yes. So you are saying that workforce management as a role is not that it's gonna become even more important. So I'm happy with that. So I would like to hear any last words of advice or controversial opinion, what have you, how are we ending this episode?

Jimmy:

I think, yeah, I think from my view, I think it's about the best planners having the having the best available information at the fingertips at any given point in time and to be able to dynamically, to dynamically change operations in a very, hyper, skilled environment. and I think to do that, you need the AI and you need the high functioning WFM professionals make that work and passionate, software. I think software, the software side of it will die. But what I am passionate about is humans interacting with each other and in a way that benefits everybody. And I think that this more dynamic approach with WFM, with CCaaS, with CRMs and things like that will enable us to interact with brands and each other, and not be constrained by traditional kind of resource planning models.

Irina:

Okay. I take that one last words and we're wrapping up. Where can my fellow planners find you to, savage you?

Jimmy:

So if you really, really want to take me to task, you can go onto, you can go on to LinkedIn, it's Jimmy Hosang on LinkedIn, or it's Jimmy is Analytics, which is, which is my handle on there. you could also, you could also reach out to the MOJO CX, company page and, contact me via there. it may be filtered by, by, some of my sales and marketing team for, for any swear words.

Irina:

No more trashing Jimmy, no more. Thank you so much, Jimmy, for this conversation. It was better than I expected, but mostly because of the way that you spoke about, workforce management. So thank you for this conversation.

Jimmy:

Thank you.

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Irina Hollatz (Mateeva)

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