From Insights to Execution: The Future of Frontline Productivity with WorkJam

This month on our business productivity podcast, we spoke to Will Eadie, Chief Strategy Officer at WorkJam.
We discussed how Task Management tools are helping drive compliance, productivity and colleague engagement, and looked ahead to when systems will automatically suggest actions, saving even more admin time.

Key takeaways:

Productivity Drives Engagement: Why giving frontline workers clear expectations and streamlined tasks boosts overall job satisfaction and engagement.

The £6.25 Billion Opportunity: Insights from the Rethink Productivity 2026 report, highlighting the massive savings organizations can unlock by managing capacity intelligently.

From Insights to Execution: How AI is moving beyond data-dumping to provide store managers with actual decision support and dynamic task prioritization based on real-time signals like footfall and POS transactions.

Democratizing Tasks: Real-world examples of how digital collaboration platforms allow managers to assign tasks based on skill and availability, keeping operations running smoothly even across differing shift patterns.

The Autonomous Frontline: A look ahead at the next 12 months, predicting a shift toward systems that automatically suggest optimized actions—freeing managers from administrative burdens so they can focus on coaching teams and serving customers.

Event Alert: Catch up with the WorkJam team at the Rethink Forum on September 10th in Birmingham.

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Transcript

Simon 0:06

Welcome to the productivity podcast. Today I am delighted to be speaking again because we spoke about 12 months ago to Will E. Chief Strategy Officer from Work Jam. Hi, Will.

Will 0:17

Hi, good to see you, Simon. Thanks for having me on.

Simon 0:20

No, I'm returning the favor because I say it's about 12 months just at the time of recording that I was on the Yours and the WorkJam podcast, and we we talked about all things insights to execution, and we'll kind of pick up the conversation today. But for those that don't know you, Will, or didn't listen to that first one, do you want to give us a bit of background on yourself and work jam?

Will 0:41

Sure. So I'm Willie D. I'm the chief strategy officer here at WorkJam. I've been with WorkJam since the just since the start of the company about 11 years. But um, Simon, as you know, because you and I have known each other for a very long time, I've been in the HCM, HR Tech, WFM space for far, far too long. I've actually stopped saying how long I've been in it because it just makes me feel old. But um as is as is everything, right? So for 30 plus years, I've been dealing with labor productivity and and labor value and and where we can find productivity and labor standards. And obviously it's why I've always uh been in touch with you. Um and then obviously here at WorkJam, we are focused very heavily on the frontline worker and you know the space where that labor becomes comes to fruition in the frontline. Um so WorkJam is a frontline operations platform that sort of brings all of those different aspects of you know employee self-service, task management, learning and the flow of work, communications, knowledge management all to the front.

Simon 1:39

Perfect. So when we talked 12 months ish ago, it was around this kind of shift about insights to execution. So it's great giving people insight, but actually, how do you get stuff done? And I remember part of the conversation was around productivities back on the agenda for all retail, hospitality, well then any organization, I suppose, really. And it it's still right up there. Number one or number two, I assume, on every boardroom's uh conversation agenda is around cost, which therefore equals productivity efficiency. So it it's been there for a while. What have you seen since we last spoke that means it's still that critical topic?

Will 2:22

Yeah, I think what you know, so when you and I spoke about it 12 months ago, we were kind of talking about coming out of that post-pandemic where everyone was very focused on engagement because they had to be, right? One, employers want to be good employers and they want their teams to be highly engaged. But also, you had to have high engagement because there was hard to find people, right? Everybody had jobs. Unemployment was very, very low and every and and they really needed to go out of their way to make sure people were happy. None of that has gone away. But I think what they learned, my biggest takeaway in the past 12 months is that people are starting to realize that productivity actually can drive engagement. Because when you're actually figuring out how to properly get things done, things done in a frontline organization and a frontline environment at a site or a store, that people, when they know what they're supposed to do, when when they can understand what expectations are being measured against, that actually drives engagement. And I always like to tie to, I I, you know, I always do, but I I just went back and um reread the the Rethink Productivity 2026 report that you guys came out with not too long ago. And I still think that one of the things we're seeing is that as people continue to optimize their frontline operations, they are realizing the amount of um time or productivity or whatever. What I think in your report you you said that they're still wasting the equivalent of almost one working day every week, right? I mean, that's a huge number. So when you can figure out how to orchestrate that front line and drive that productivity, that that those that labor dollars isn't necessarily being cut, it's being reinvested somewhere else, whether it's in technology, whether it's in another person, whether it's in a new process, whether it's in new hardware, whatever it might be. So to drive productivity, I think it ends up being the most important thing for companies to capture both top line growth and and bottom line savings. I mean, is that you kind of agree with what you're seeing?

Simon 4:12

Yeah, yeah, absolutely. Yeah, the report was about, well, it's in pounds, unfortunately, not dollars for you, but six pound 6.25 billion pound opportunity um plays into our kind of six golden rules, which we've talked around on other podcasts. But certainly in there, it's around, you know, typically 26 to 30 hours per week saving in there, you know. So it's almost a day a week per full-time employee is is around that missed opportunity of engagement, driving the right results, etc. So it's huge. And that's just focusing on the UK. So clearly it'll be bigger in the states, bigger across verticals outside retail as well.

Will 4:49

Well, and and I, you know, I love you, you bring into the six golden rules, and I and I I listened to that podcast and I I really uh obviously like that. But I one of the things I love when you read the report is the way you guys sort of have the six golden rules in a wheel, right? Starting from one to six and it goes around. Yep. And and I think you've seen we've just launched um, you know, our fairly big um you know, a fairly big uh vision statement on where we think AI is going in the front line. And I've also sort of visualized it as a wheel where you know you kind of start with with data and what data is being brought in, and then how do you look at that data, and then what do you do with that data, and then how do you execute on what it's done? So I think the way that you guys have mapped those six golden rules actually goes in line with how I think things are going. So one of the big places I think AI is taking this productivity is is this whole concept of insight to action. And I'm sure you've seen this. You speak to so many different leaders. Um, but I was speaking to a CIO at a very large retailer, I don't know, uh, about six months ago. And she said to me, she said, Well, listen, like everyone's coming to me with AI reports. It's great. Yes, AI is so great at getting us data. She's like, but I have a store manager who's maybe only been a store manager for three weeks. She's like, if I just keep inundating him with, hey, here's 3,000 bits of data that come from AI, how do I know that he or she knows what to do with it? He's like, what I'm looking for AI to do is to take all that data, look at historical trends, look at recent trends, and actually give my manager some decision support. Hey, based on these 13 pieces of data, here are some actions you might want to take based on that data, as opposed to just throwing up data from AI. So I think the thing when you talk about like rethinking efficiency, managing capacity intelligently, you know, um unlocking self-potential, uh self-checkout potential, those are all pieces that come from the, hey, we've noticed that footfall has increased by 35% in the past three hours. Maybe now that's time to open the next self-checkout lane, right? Turn it back on because we have to get more throughput. So I think what we're really seeing is that productivity is being tied back, this whole concept of insight to execution. And I can tell you that's what almost all of our customers are really focusing on. How do we figure out, based on KPIs that they might have gotten from working from folks like yourself and rethink to what does that translate? And that's that gets into this whole concept of like task prioritization. So we've just launched a new task prioritization engine. And the goal of that is that you know, companies traditionally know when they should be doing tasks. Like let's take a petrol station, um, you know, for example, and they say, okay, we're going to clean the coffee machine every three hours. And that's fine, except for what happens when you get more footfall in the first hour of being open than you had planned, and now coffee's empty or dirty earlier. So we need to start looking at signals like POS transactions and footfall and say, hey, instead of just doing the coffee every three hours, we should be doing the coffee when these three KPIs meet a standard and then automatically putting that task out. And then we should be able to say, let's measure putting that task out to clean the coffee station against another metric that might actually be more efficient, like, hey, it's it's more important to fix the breakfast, the, you know, the breakfast rolls first because that's going to get us more money. So I think productivity is coming down to data in terms of throughput, both for product and for people, but taking that data and applying it against labor standards and the capacity that they're managing against, both from a demand and from a schedule standpoint. Sorry, I know that's a lot, but I get when what I started thinking about your wheel and how it relates to how I look at AI and the wheel. And I think it all comes together really nicely.

Simon 8:28

Yeah, and it it really hits number two in our wheel, which is managing capacity intelligently. So managing peaks, troughs, and the capacity cap. And it's interesting because when you were talking there, one thing that went through my mind was yeah, it's great around the prioritizing tasks, and you can come up with a logic of this task more important than that one. But I think what you described there is almost prioritizing the tasks by value add to the customer and value add to the business, which isn't probably a typical way we think about it. It's more this needs to be done between eight and nine because we do it when we're quiet.

Will 9:07

I mean, right, like it's almost like I always say we've added this big omni-channel operating model to stores, but in many cases, we're still managing the front line through disconnected tools, right? And and manager, heroic managers. And it's why you see, hey, this store is really good because this is a great manager. This store has the same exact product, the same exact labor budget, and the same exact number of people on the on the roto, but it's not operating as well. Well, it's a new manager or whatever. So when you talk like what you just said, what the real problem is deciding what takes priority. And when you think about it in in against your wheel and capacity planning, it's we have to bring demand and operational signals into the platform. We have to prioritize work by urgency as well as business impact. You have to target it by role, location skills, availability. You got to think about how do we adjust these priorities as conditions change throughout the day. You know, let's I you and I were talking before we went online about obviously the heat wave that that that all of the UK has been seeing. Do you mean I imagine a lot of people had to decide, hey, we better get more orange popsicles out into the front of the merchandising. We should probably stop selling hot soups. I mean, like all these things have to change that might have been different than what you had planned as you were going into that trading period.

Simon 10:22

Yeah, and it and as as the world evolves, it's getting hotter, but certainly the climate in the UK is changing. Obviously, things will evolve with it. So I think it's again using that historic intelligence and then the eye thinking about the future and looking at picking up patterns and trends. And this is quite a big one we talk about here, but even those smaller, minutiae ones of uh you know, competitors doing something differently, therefore it's impacting your traffic or it's impacting your customer patterns. That's that's the bit that you probably know about as a store leader. But actually, back to the conversation with you had with that senior leader, she was really saying, I've got a lot, I'm information rich, but I'm kind of insight actionable, insight poor. And we see that a lot. There's there's a lot of data floating around, there's there's lots of nice insight floating around, but it's that it's that last mile of there's loads of people doing all this work, there's lots of machines turning and processing, but at the front end, how do we simplify that down to make it really easy, whether I've worked there 10 minutes or 10 years, to be doing the right things in the right order for the right reasons?

Will 11:29

I I think that that's exactly it. And I think that, you know, again, if you think we talk about so much about you know how big an impact a manager can have, um, that's where I come into that, like tying it back to that conversation I had with that CIO, right? Like technology should amplify the human capability. Um, since you and I have all you know been in the workforce management space for so many years, right? 20 years ago, when when when sort of optimized workforce management and optimized scheduling became a thing, every great manager in the world, when we first would try to roll out workforce management, would say, you don't know my site as well as I do. So you can't tell me that Becky and and Ralph should be working because I, you know, because I I know when I write the roto myself that that they shouldn't work together. And you're and that's that is true to some extent, right? The manager has some local knowledge. Now, what we proved out over time is that that they that the the optimized schedule almost always put a better schedule out if you allowed the manager to have a tiny bit of tweak to it. And it's the same thing with productivity um applications, right? Like Marks and Spencer is a customer there in the UK of WorkJams and a customer of yours, obviously, you've done a lot of work on. And I think one of the interesting things that you see there is like when they were able to let the manager be part of rolling out tasks to everybody, we talk about democratizing tasks for them, right? The manager was able to go in and say, okay, well, Will is really good at merchandising men's shoes. So I'm gonna give him this level of skill. And now we can automatically assign tasks to Will. I don't have to walk around and wait to assign it to Will. So we've just opened up some manager time and we can do that across. The manager has a role in rating the frontline employee, but then the system is automatically assigning the task based on all those other attributes that we talked about. So I think that becomes a really important role as you bring technology and manager knowledge together.

Simon 13:23

Yeah. And I think you you'll never replace, or hopefully not, the the managers. Maybe they'll manage more than one location, maybe they'll do things differently as kind of cost pressures come in and different, more effective ways of working. But I think it it's fair to say that in the future you will probably as a manager see some of your people less because they'll be more efficient, the processes will be more automated and better. And because of the cost, certainly, certainly in the UK with things like national living wage and some of the other pressures, there will just by default be less people on the floor. So that that communication span has got to be a lot better, has got to be a lot more intuitive and interactive because I I might not see you if we work opposite shifts for maybe two weeks.

Will 14:10

Well, I think you nailed it, right? And just to tie it back again, wait, what one of the things I love about the synergy between your guys' productivity report, that you know, that six golden rules and what WorkJam's doing is you know, your report kind of talks about like the next productivity breakthrough is not going to come from another round of just bluntly cutting labor, right? But it's gonna come from when you do use a platform like WorkJam to orchestrate the front line where we're connecting insights, communication, tasks, learning, all that frontline action. So that do you like you said, so every employee knows what matters when it matters, and they know what sexual, you know, what successful execution looks like. Again, that's that marks, that's the the Marks and Spencer story. Hey, even though you know Jonathan, who's the department manager, isn't in on Tuesday, everything's still getting done. And then in he can still come back on Wednesday and see that it was verified and rate it and make sure that it happens again the next time he's gone. So, or the same thing, like, hey, if Simon and Will, you know, I'm the I'm the morning opening manager and you're you're breaking you're coming on in the afternoon, like we might not even have time to run into each other at the shift change. But there should be a way for me able to digitally leave you some information about what happened, what's going to impact your afternoon. Hey, Simon, here's the trending data that I was given and here's what I did with it. And I think that that's that's increasingly becoming why a collaboration platform is becoming absolutely necessary for people to trade, you know, in an efficient and productive manner.

Simon 15:32

Yeah, I agreed. And if we think forward then, so we spoke 12 months ago, if it was Will and Simon of the future in the next 12 months' time, what what would we be talking about? Do you think where where is it going in this next series?

Will 15:44

I think what in 12 months from now, you and I will be talking about whether or not this vision that I think that we're definitely pushing, and I think I've heard you talk about where we're moving to an autonomous frontline layer. How how how close are we to that? And what I mean by that is like right now, you know, I said I brought you to the, hey, we're getting all these AI reports, and then we're relying on humans to figure out what to do with it. I think now with some of this insight to action that WorkJam and others have have started to bring to fruition, we're giving managers choices. Hey, here's what the data says, here's three things, which one of these three things do you want to do? Press that button. So that's where the manager of up. I think we're eventually going to get to a place, and I would again bring this back to how we saw workforce management, where 12 months from now, hopefully the manager is comfortable enough going, you know what? The system has suggested I do this thing every day for the past year. I have always wanted to be the one making the decision, but I always said yes. So let's just let it happen. And I come back to, you know again, Simon, when we did the first workforce management rollouts, the manager would always change the schedule, right? For six months, he or she would change the schedule. And then we'd go back and show them you really ruined your schedule effectiveness. And they finally just started to trust the schedule. So I think a year from now we're gonna be talking about how AI insights and execution suggestions are gonna become more accepted and that we are moving more to an autonomous model where managers like, you know what? I'd much rather be out serving the customer. I'd much much rather be talking to Will about how I can coach him up in customer service. And that manager, we're actually gonna, we're not gonna see less manager involvement. We're gonna see more manager involvement with employee satisfaction, employee coaching and customer satisfaction, less time worried about if they're the one putting the cans on the shelf themselves.

Simon 17:23

Yeah, no, I I agree. I think as we talked about on the early part of this, the the days of the blunt cost cutting are done. I get people need to manage cost, and there'll be some eloquent ways they can still do it, certainly with the insight and the enhanced data that's presented by lots of organisations. But freeing managers up from expensive shelf filling is critical to drive engagement with colleagues, customers, and then overall performance. But as ever, they only work a certain amount of hours in the week, and most retail outlets, hospitality outlets, convenience are open, way more of that. So it's how you leave that kind of breadcrumb trail so that people can follow you in the right way with the information. So yeah, we'll we'll pick up again in 12 months and see if we were we were right. But I don't at this moment in time, but absolutely far.

Will 18:14

I look forward to it, Simon. Thank you so much.

Simon 18:17

Brilliant. Well, thanks for coming on again, Will. Uh Work Jam are at the Rethink Forum as well on the 10th of September in Birmingham. So over 150 people registered so far. So we'll put that in the show notes so you can register and you can catch up with the team there and continue the conversation. But thanks again, Will. And we'll speak soon.