The Digital Project Manager

How to Know When Your Team Is Truly at Capacity (And When to Hire)

• Galen Low

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Capacity planning can feel like a tug-of-war between sales, delivery teams, and leadership—especially when growth goals collide with a team that already feels stretched. In this episode, Galen Low sits down with Brandon Llewellyn, Head of Delivery at Cirface, to unpack how delivery leaders can use data to diagnose real capacity issues, make smarter resourcing decisions, and avoid the trap of “just squeezing in one more project.”

Brandon shares how his team approaches capacity planning using simple but powerful metrics, why top-down planning often beats granular task estimates, and how productized services, deal size, and role clarity can dramatically change how “busy” a team feels. They also explore how AI is influencing operational efficiency—and what leaders should actually do with the time it frees up.

Resources from this episode:

Galen Low:

What can team and project leaders do when sales wants to sell more, but teams say that they're at capacity?

Brandon Llewellyn:

If your team feels full, but leadership thinks you can do more and your data is telling you that the team's full, well, then you're full and you're gonna close the door and head to new work. The leadership feels like we should take more. The team feels full and the data is showing that we can take more. So then what?

Galen Low:

I wonder if you could talk to me about your flow for planning capacity as well as measuring utilization.

Brandon Llewellyn:

When you track someone's capacity, you need three inputs. You need a person that you're tracking, you need dates or time ranges, and you need work effort score in some way. Problem with that is that you would need to define estimated time and dates on literally every single thing you're doing for a given project. So the question is, how do we solve this? And the answer is by going top down rather than bottom up.

Galen Low:

A lot of organizations now are being asked to justify new hires by explaining why AI can't do the work. How can solid team utilization metrics be packaged in a way that can make the case that actually we need more humans?

Brandon Llewellyn:

There's are not a lot of strategic or creative value that I can see right now. For the most part, the value that AI will provide is—.

Galen Low:

Welcome to The Digital Project Manager Podcast—the show that helps delivery leaders work smarter, deliver smoother, and lead their team with confidence in the age of AI. I'm Galen, and every week we dive into real world strategies, new tools, proven frameworks, and the occasional war story from the project front lines. Whether you're steering massive transformation projects, wrangling AI workflows, or just trying to keep the chaos under control, you're in the right place. Let's get into it. Okay, today we are talking about the capacity conundrum faced by organizations in growth mode and how data can be used to help diagnose team capacity issues and make the case for adding headcount at exactly the right moment. With me today is Brandon Llewellyn, agency operations specialist and Head of Delivery at Cirface. Brandon leads a team of client facing consultant implementing Asana for enterprise organizations like PayPal, CloudFlare, MLB, and the LA Rams. He is responsible for measuring project profitability, balancing team utilization and resourcing, and optimizing delivery processes and workflows. But he doesn't just work behind the scenes, he is also still on the front lines managing several key accounts with some of the biggest Asana rollouts to date in Canada. Brandon, thank you so much for being with me here today.

Brandon Llewellyn:

Yeah, thanks for having me, Galen and happy to be here and looking forward to the conversation.

Galen Low:

I always look forward to our conversations. We were just talking in the green room. Brandon and I go way back to your Parakeeto days. We're always chatting, we're always jamming about ops, we're always jamming about projects. I'm super happy to have you on the show to sort of make some of those conversations and insights. I think that you and I, we can probably zig and zag in our conversation today, but just in case, here's the roadmap that I've sketched out for us. So to start us off, I wanted to tackle like one big burning question that everyone wants to know the answer to, but then I wanna zoom out from that and talk about three things. Firstly, I wanted to talk about how teams can accurately diagnose capacity issues. Then I'd like to talk about what metrics are actually effective at driving the conversation around capacity issues. And then lastly, I'd just like to get your thoughts on like what the future of capacity planning looks like and whether some of the ways your team is leveraging AI changes the capacity equation today and maybe five years from now. How does that sound to you?

Brandon Llewellyn:

Yeah, that's great. Exactly what we had planned. Looking forward to it.

Galen Low:

I thought I'd start us off with just like the big hairy question. I'll take a little running start at it. Overall, like I'd say the consulting space, it's tough right now. Like a lot of consultancies are trying to grow, but the market is a bit soft. So my big hairy question is what can team and project leaders do when sales wants to sell more, but teams say that they're at capacity. Should they enable sales to help grow revenue or should they defend their teams and risk having the business stagnate or maybe even go under and how do they even know for certain that their team is indeed at capacity? Okay. That was like four questions.

Brandon Llewellyn:

Yeah. Well, let me just take it one by one. I've got plenty of thoughts here that I can go through. The first place that my head goes that are little check boxes that you can look at before you actually start to diagnose a problem is to make sure that you, well, I guess taking a look at your data, I would say like. If your team feels full, but leadership thinks you can do more and your data is telling you that the team's full well, then you're full and you're gonna close the door head to new work. Right? So we're good there. And assuming most of the time that's not the case, right? The leadership feels like we should take more. The team feels full and the data is showing that we can take more. So then what the other check box there is time tracking. And so it's like if your team is missing some of their time sheets, if you have poor time sheet compliance, they're putting the work in, but it's not making its way to the time sheets and therefore they feel like they're more busy because they are more busy, but the data is showing they're not that busy. And so those are the two check boxes. If you feel like the data is still like good. The time sheet compliance is strong, which happens most of the time, then you can start to look into, okay, what's the real problem here? Why does the team feel that busy and leadership thinks that they could do more? For the most part, the way that I approach this is to look at your service offerings and to try to understand, okay, well, what could be causing this overwhelm? The first place in my head goes, is. How productize are your services? And so if your producers and your service delivery team roles are doing custom work, it takes a lot more brainpower to handle that. And so what might be a small amount of projects, if they're inherently custom and there's a lot of brainpower going into this stuff, they could feel more busy than they really are. So productizing, you've heard the word before, this means like things like templating your services, strong systems, and removing some of that thinking that needs to happen on the backend. But if you're selling custom work, it's much harder to do. That's one of them. Second one is deal size. And so you know, if you're giving your producers, whether they're designers or consultants, 10 clients or 20 clients, and they're all really small deals. The context switching alone is going to be so difficult to handle. You've got 10 different timelines, 10 different sets of stakeholders, 10 different services you're providing. It's all custom, and you're gonna feel overwhelmed quickly. And so if your deal size are too small or your work is too custom, you're gonna feel like you're more busy than you really are. There's one more, and this is for our small agencies at the too many hats issue. If you have someone that's wearing too many hats, that is inherently another context switching situation where, you know, if you expect someone to be half say, a producer. You should be expecting more like a third of a producer because of the fact that they have this context switching to do so. Those are the three things I've looked at is like if your team feels like they're too busy, but the data is showing they can handle more, try to productize your work, make it less custom, try to up your deal size. So you're doing like, say. Maybe instead of doing 10 small projects, you're doing three big projects. That's three clients. And inherently these are gonna be bigger deals, but generally speaking, a lot less admin, a lot less scheduling. That will help. And then finally, too many hats. Get people in their singular role, in their area of excellence and leave them alone. That's my advice.

Galen Low:

That's actually really cool because I like that you started with like the data bit, right? If the data says no, because in agency world and consultancies, it's a bit squishy and in some ways it is leadership and the owner's role to push a little bit, right? Not to just take something at face value, especially when there's cash on the table. So having that good data hygiene, I love that, but I love how it also goes back to the human brain. Like some of the things you're talking about are like context switching and focus, and I think there's like this tendency to think, oh. We can just slot in one more, three more, seven more small projects, this room in this jar for a few more grains of sand. But what you're saying is that actually it might be better to just make room for a rock and then just like put a big rock in there. The sand is actually toxic because that's the thing that's making people sort of dilute their focus context, which all the time you have more admin, you have more clients. Fundamentally, your team is spread thinner across the same amount of money. Whereas if you could actually increase the deal size, then that actually helps capacity, like that's a really interesting way to look at it. Not just how can we get our folks to do more faster? I appreciate the productization thing, but also the what if we sold it in a different shape? That allows us to earn this money and deliver more value in one go without having to sort of spread it so thinly and we can actually be more efficient by working on a bigger deal. That's really interesting.

Brandon Llewellyn:

I had this thought, it's and I literally just thought of this on the spot and I don't know if this is gonna resonate, but like imagine you've got like a product that's like a chocolate bar. And the chocolate bar. You've got like one kg of chocolate in total, so that could be like a hundred chocolate bars. Or you have one big block of chocolate that is a singular, one KG chocolate bar, let's just say. And if you think about the packaging that comes in most chocolate bars, that is the operational drag that a small chocolate bar would cause your company. So it's the admin work, it's the scheduling, it's the checking the timeline and extending the timeline with a change order. It's the sets of stakeholders. You have to remember their names. And what if they changed their domain? Recently? Recently they were acquired. Now you're getting emails from places you don't know. And all these things are contributing to this overwhelm that your producers could feel. We solved this problem just recently at Surface. The company that I work for and like we sold just one 70 k deal recently, that would make up for about 12 or 13 of these small 5K deals. And the savings alone from one of these sales is monumental compared to the backend team and our consultants in the front. And so, yeah, that's my advice.

Galen Low:

You've got me thinking about my kids' snacks. I'm like, okay, yeah, we buy packs of individually wrapped cookies or whatever to take to school. But when you think about, yeah, every project is having their own wrapper versus a big project in one big sort of box like that is the overhead. That's the sort of admin, that's where some of the, you know, efficiencies can be gained by having one big wrapper around a bigger project. I really do like that. It's funny because I think there's a tendency, at least in my experience for like agency teams to be like, oh, we've sold this big deal, like we must be making so much money. Like the reason why these are more profitable is'cause we just gouge them. Whereas that's actually not the case. The case is they are delivering value equivalent to the budget. You're able to deliver more value and actually teams should feel good about that. Not, you know, worse about that or not feel like they're, you know, in some way gaming the system. Look at these suckers. They spent, you know, $3 million on, you know, seven things that would normally cost whatever. A lot less. We bundled it and there's huge margin, and we're laughing, but actually it's more about like more intelligent sales, more intelligent operations, and ultimately like building deeper relationships with one customer rather than spreading it around to, you know, dozens. I think that's really cool.

Brandon Llewellyn:

I wouldn't fully agree with the fact that like, you know, oh, we're selling this one big deal and this client is carrying the agency's sales or revenues. Let's just say it's more about like, okay, well can we guarantee or what's the expected ROI here? And if that makes sense, then it makes sense and doesn't matter how much it costs, as long as we can provide that amount of value or more, it doesn't matter in my eyes.

Galen Low:

I wonder if we could zoom out a bit, because we know we were talking about data, we're talking about metrics. Man, there is an, at least in my world, there's this ongoing debate about how to measure capacity. And honestly, like so far I feel like no two people feel exactly the same way about it. So I'm just wondering, based on your experience, what capacity metrics actually help delivery teams and which ones just kind of create noise? Like is utilization still a good measure of things?

Brandon Llewellyn:

I have three sets of numbers that I look at, or three kind of numbers that I look at, and that's it. I keep it pretty simple to get the job done for me, and I can't guarantee that all the stuff that I say here today is gonna be applicable to all of your listeners. But I can say this absolutely works for me and for our company, and it may work for you if you're a service-based company as well. First question was like, let's talk about capacity stuff. Then it was like, is utilization a number that is useful anymore? The three numbers that I look at are utilization, estimated time versus actual time, which in other words is project budgets and then capacity and workload tracking. Utilization and capacity tracking are kind of the same thing. It's just that utilization is the actual side, what actually happened. Whereas capacity and workload is kind of like on the planning side, which is like, we're projecting this to look like this. And so I track all three of those things and they all have their own value that it brings to me. And that's basically all I track as the head of delivery. And so, is there one of those or all of 'em that you wanna get into and kinda explain why it's useful and how I track these kinds of things?

Galen Low:

I mean, I would love to get into the utilization and the capacity planning bit. So basically kind of like forecasting capacity, what we'd call sort of resourcing or casting versus utilization. And I'd love to dive into the idea of like utilization as a measure of billable time. But not necessarily a representation of how people are spending their entire time. At least in my experience, it's always been like, you know, hit this, you know, 70, 80% billability. That helps us with our utilization rates and that's how we run our business. But you alluded to it earlier, sometimes folks feel busy. And they're doing something and maybe it's just not billable and maybe it's invisible because we're like, oh, that 20% we don't care about it. We only care about the 80% billability. And then we know we're making money, and if you guys feel busy, you know, kinda your problem, so. Yeah, maybe we can dive into those utilization versus capacity planning. I like it because for you it's like, you know, you're looking at it as a, what we estimate or predict versus what actually happened and then adjusting. So, yeah, I wonder if you could talk to me about your flow for just like planning capacity as well as measuring utilization.

Brandon Llewellyn:

Yeah, sure. I think that sounds good. Let's start with capacity, because that is inherently the first thing that we look at because it's the projected or planning side of things. So I think inherently it only makes sense for us to talk about that to start. So when we talk about capacity, we use Asana for our capacity tracking, and when you check someone's capacity. And I think this is true, whether it's in Asana or whether it's just like elsewhere, is you need three inputs. You need a person that you're tracking. You need dates or time ranges that you're tracking this time in, and you need work effort score in some way. Whether that is percent allocation of a person's time or task count, or the one that we use is estimated time. So inside of Asana, what we'll do is we will have a project where, you know, a producer has been assigned to a project, and from there you have two options. The first option is called bottom up resource planning. And the way this works is it's very detailed, it's very granular, and it's very accurate if done right, and how it works is every single task you need to do on a given project will have all three of those things. Who's doing it? When are they doing it, and how much effort does it take to do that thing? All those things can be bundled up into a nice report that shows people over time and their effort on ongoing projects, and so. If you've got, you know, Sally on a project for 10 hours in this week and then, you know, 15 hours on a different project for the same week, she's got 25 hours going to client work in that given week, and that might be getting close to Sally's capacity, so let's give something else to someone else. That's the general way of looking at bottom up resource planning is having those three inputs, comparing it across time for all your people and being able to shift as needed. Now the problem with that is that you would need to define. Estimated time and dates on literally every single thing you're doing for a given project. And in my opinion, that actually would lead to your reports being unreliable because people aren't gonna follow the process. It's just too cumbersome and burdensome to have that defined bottom up every single time for every single project. And what happens if your estimate changes? So like, usually this call takes an hour, but what if it ticked two? This time, you're gonna have to go in and change that. Otherwise your report's not gonna be fully accurate. So the question is, how do we solve this? The answer is by going top down rather than bottom up. And doing it granular for every single task, we're actually just applying it by role. And so if we have Sally, and we have Brad on a given project and you know, Sally's a designer and Brad is our strategic advisor, let's just say, rather than having like Sally's, you know, task 1, 2, 3, 4, 5, and all the different estimated time on those tasks, we would just have Sally. In a time period, like a duration of the project and her estimated work effort on that project, like 15 hours over the span of a month.

Galen Low:

I'm a huge fan of top down. We used to be bottom up at a lot of the agencies that I worked at and it was overwhelming. And you know, we're trying to plan every second of everyone's day and we're not accounting for things like, you know, bio breaks or context switching or anything like that. I just wanted to come back to the idea about productization because you were saying that Yeah. If you can sort of productize or templatize the work. You know, then it's easier to sell. And folks doing the work, once it's sort of more repeatable, you know, it's less cerebral, it's not as much of a cognitive lift to do the work. And then I know that some folks that I've worked with, and even myself, we'd be like, oh, okay, well now we need to measure how long every task takes. And we would probably gravitate towards bottom up because we wanna know. What the tasks are involved to get the thing done so that we can productize it a bit. And then we know that like if we need to double that, you know, if there's twice as many pages or twice as many graphics or twice as much code, I dunno. And we need to, you know, double that. Can you still productize effectively when you're planning capacity top down? How does that look for you?

Brandon Llewellyn:

Yeah, and I think that's one of the trade-offs is that if you start going down that road of productization and you're starting to define everything at such a granular level like that to make things easy, you may have a harder time tracking your capacity because of the fact that you're gonna have to do that. And I think you can probably find a happy mid-ground between those two things. But there's certainly a trade off that you should be aware of. As long as you're confident in your ability to manage that ongoing, it's still worth it and it's still slightly more reliable and accurate as long as you have good compliance to do a bottom up planning. It's just, it doesn't work for every team.

Galen Low:

That's fair. And I think, you know, when you were even just saying the individual's names, I was like, oh yeah, don't forget, these are individuals. We're not robots. We don't all work at the same efficiency. We don't, you know, work at the same level all day long, you know, eight, 10 hours a day. And as you were explaining to me, I'm like, actually, top down does make a lot of sense, even if you're productizing. Because for me, the origins of productization, like we would do capacity based billing or value based, it's like, well, you're gonna get this much value. Or you're gonna get this many people's time, a percentage of this many people's time. And you know, that's how we would sell it through. Which also means we don't need to know how long each individual task takes and then remeasure it when that task changes. Or we get a do new tool. You know, we're literally counting grains of sand versus saying, you want a beach, you get a beach. You know, like it's staffed by this many people. There's a lifeguard, you know, like you hit the beach and don't even worry about it. And we're not even gonna worry about how much each grain of sand on that beach weighs. Because at the end of the day it won't matter. And then you spend all your time measuring these grains of sand. I do wanna get back into that a little later on, but I also wondered if we could like tilt a little bit into like hiring.'cause I find a lot of the time in my community, folks are, as you say, they're busy. They feel at capacity. The data doesn't show that they're at capacity. The revenue's not, you know, showing that they're hitting their goals in terms of where the agency or other service based organization is at. And I think a lot of folks are being asked to, to a greater degree, justify adding headcount when they're feeling like they're at capacity. And then there's the other complicating factor of AI, and I think a lot of organizations now are being asked to justify new hires by explaining why AI can't do the work. So. I thought I maybe asked, you know, this, about this relationship, like how can solid team utilization metrics be packaged in a way that can make the case that actually we need more humans, we indeed need more humans, not just agents, not just AI. We need more humans to get this work done.

Brandon Llewellyn:

Yeah. I think these topics of like hiring and utilization and using it as a tool to justify or, you know, bring receipts to conversations like this. They're very connected. And so I have thoughts here, like when we talk about utilization, for those of you who are listening and maybe, you know, you've heard this word before, but you're not sure exactly what it means, and it's been defined a million different ways on the internet. Generally what we're looking at here is like how much of our team's time, our producer's time is being spent on. Client work. That's what it goes down to. So if you have someone working for 40 hours a week for you, what percent of that time is being spent on client work in an DL state? And so I guess what you're asking here, Galen, and is like, you know, if we're having a discussion about maybe hiring and the leadership is like, Hey, could we maybe bring AI into the picture? Like how could this look utilization? Let's put it on the back burner for now and just talk about like AI and hiring. And then maybe we can pull that back into how that all works with utilization and why that's important. So my first thought here is that, like, you might have heard this before, so this is not a any groundbreaking take on AI, but as far as like AI and how it works with people and hiring, for the most part, the value that AI will provide is tactical. There's not a lot of strategic or creative value that I can see right now. And don't get me wrong, don't quote me on this,'cause in six months it might be completely different. But current state, again, the real value that AI can provide is. To help your workflows better, to become more efficient, to take care of some of the tactical stuff that you don't want to have to do. But then there's still gonna be a lot of space for humans to be providing the value in the creative space, the strategic space, that kind of space. And so it depends on what kind of role we're talking about hiring for, but justifying hiring with AI, I. Everyone should be willing to adapt in some way to what we're seeing here. And I think like if you're not adapting in some way, you're probably falling behind. But it all depends on the nature of the work that we're talking about.

Galen Low:

I think it's totally fair. If I'm picking out what you're putting down, it's kinda like, AI in its current form has a lot of potential, but presently in its practicality is great for like augmenting or optimizing productivity or efficiency. But not yet at that point where you're like, oh, well yeah, that's okay. We can sell through a million dollar piece of business. But instead of hiring more people to take on that work, even though everyone's busy, we're just going to like, you know, build an agent. We're just going to, you know, vibe code our way into a new team member. To your point, even if that is possible and I know that folks who are working on it right now, you know, working with micro teams to try and feel like, you know, you're working with a giant consultancy, but still operationally they're completely different. Like their DNA is different. The bones are different. Like everything about those teams are different. And you need to adapt to get there. And yeah, I agree with you need to adapt. It's like start adapting now. But I do appreciate that argument that yeah, we're not yet at that point where it's like, okay, cool, well now we don't need to hire another SEO specialist. On this particular project because we're just gonna plug this GPT in and it's gonna be fine. It's actually some of the work is the cerebral strategic work. It's the creative decision making, it's the relationship building. And fundamentally, our teams aren't yet at that point. We have to do the work to build our teams up in such a way that it feels natural, fluid, and efficient to be working as a hybrid team with, you know, AI technology and human technology. I was gonna say, yeah, the brain.

Brandon Llewellyn:

And the way this ties back to utilization, which like I said these are kind of related, is that if we can get to a place where, you know, leveraging AI in your team can enable, say, opening up percentage of hours for your team to use elsewhere, that's where utilization comes in. So imagine a scenario where, you know, a team typically. In 2022, was able to output, say X number in 30 hours of work. Fast forward to 2026, they can do the same output in 20 hours of work. They've got this buffer now of 10 hours. And what do we do with that? And the reason why this matters is because when agency leaders look at numbers like utilization, they're gonna say, okay, well every hour that you're spending on client work, you're earning X number, you're earning $200. USD, let's just say, for which is a very standard rate in our space. For every hour of work that you're bringing in. And so of course if we make an efficiency of 10 more hours by leveraging AI, that person can be 10 hours more efficient or productive. Let's just say for the agency. Here's the thing is that now we're starting to sound robotic and it's like, okay, well work harder so that you can be given more work. And so where do we find that balance? Right? And so that might be a nice segue to talk about like, what does that mean if we're able to enable 10 more hours or a certain percentage of efficiency in your company?

Galen Low:

Actually, let's go there because I, there's three things that I wanna touch on. This is maybe a little off script, but you know, earlier you were talking about capacity planning and utilization. It's kind of like the plan versus actual, and then we're talking about efficiency gains through technology, through AI could be, you know, a 10% efficiency gain. And if 10 people are on the team, does that mean they basically have room to do the job of one more full-time hire? Maybe it doesn't work that way. I'm curious about like, maybe even like the end to end flow. Maybe this is too big of a question, but the way I'm thinking about it is, you know, what do you do when planned capacity doesn't match utilization? You're not like, you know, you're like, okay, yeah, this person, Sally, she's gonna be 80% billable and we're finding that she's not, but she's still working on the same projects that, you know, we had assigned her to. And it's unclear sort of where the time is going and why it's not sort of billable time. And then maybe we could dive into like a bit about. What you do when there's efficiency gains, how to not just pile more work on somebody and whether or not that even makes sense and what to do instead if that's not what makes sense.

Brandon Llewellyn:

Sure. Let's pull it back to yeah the capacity versus utilization. So what do we do? You know, Sally, we've kind of set a target, let's just say, for her utilization. And she's busy, but she's not quite hitting it. And the question is, why? And diagnosing this issue is something that I think most agencies will have to deal with at some point. So there's plenty of ways you can approach this, the first place to go to your estimate. So do we think that what we estimated for, you know, Sally's effort on a given project is this panning out? And this kind of comes back to why I track project budgets and estimate versus actual, that's one of the other metrics that I mentioned there in that list that I provided. And it helps us understand, okay, well we thought this project was gonna be 10 hours and historically it's been 10 hours, but now it's looking like it's more like 15. So what do we do about that? Is that a trend that we want to actually, you know, permanently change in our estimation? And that will impact the backend on how that looks in Sally's utilization once we expect her to be putting 15 rather than 10 into a project. So check in your estimates. If you can't move the estimate, then you're gonna have to change the price of the product, right? And so you're gonna have to actually either make it cheaper or make it more expensive to start to match what that looks like.'cause if you have to do it in 10 hours and you can't change that, then we can't expect Sally to be that much more productive. It's likely you have to change the price. But these conversations are all enabled by the data. And so collecting this information is so important so that you can open up and say, Hey. We thought it was 10, it wasn't. Can we talk about that? Can we understand what was hard about this project? There's other factors like what if Sally's new, or what if this was a PITA client? Like, you know, there's plenty of things there and so do you wanna, may wait for, you know, trends to emerge to make it very clear that this, that a change needs to be made. But that's typically how I go about the diagnosing these kinds of problems.

Galen Low:

Gosh, who was I talking to recently? I feel like it might've been our mutual friend, Marcel Petitpas, and he was saying operations is such a different lens than project management. And even though a lot of folks go from project management into operations, you know, it's a transformation that has to take place. And what I'm thinking about as you're saying that is like I love the sort of data and trends and I feel like, you know, to make a baseball analogy as someone. It doesn't really follow baseball anymore. But you know, the project manager you know, you have your at bat, so you're up there, you're swinging the bat. It's like, you know, you're swinging three times. If three of your projects are like over budget, you're like, oh my gosh, I'm in the doghouse. This business is gonna tank. That's the perspective of the project manager. Whereas when you zoom out, you know, and you're like operations, you're like the manager. The coach, right? You're like, okay, well that's all right. We have other people who got on base. They saw the bat, they hit the ball, they got on base, and that's okay. And in the season. We're still okay. Like we still might make it into the World Series. We might still be okay, even though we won some and we lost some, and you struck out on these games and you hit a home run on this one and like you have to zoom out and look at that data. I found that in my agency days, we'd zoom in, we'd be like, oh my gosh, what's the problem here? Oh gosh. Like Sally's gotta, she's gotta go. Right, right. Like, because then that's gonna fix everything without actually zooming out and looking at the data and looking at the patterns to understand whether, actually, you know what? This might be the thing that is just getting more expensive to do and maybe even looking at our competitors and be like, okay, well, you know, maybe that's just how it's shifting. I wonder if we could like flip it. Maybe we could do the opposite now.'cause we're talking about efficiency gains through technology, through things like AI and that idea that, okay, well if we can get a team to be 10% more efficient, then we can pile 10% more work on them. But then it comes along with a whole bunch of other things. How do you price it? Are you gonna drop the price because you got more efficient at delivering something? What does that look like in your world?

Brandon Llewellyn:

Yeah, and this is such a tough question to answer. I've got so many thoughts here and it really depends, you know, what lens we approach it from. So let me think through this. Like first of all, if you're able to gain 10%, or let's just say 10 hours of efficiencies through great process and more importantly leveraging something like AI, what do we do with that time to we pile the work on What happens if our competitors, like what are they doing? Do we have to lower our prices to get more throughput there? And I have thoughts on all of this, so the first thing is that from the leader perspective, if every other competitor is seeing the same efficiency gains, the market is going to basically tell you that you have to pile more work on. Or lower your price to put the throughput through, because that is the new standard in this space. And so the first thing that I think about is like, that is a very difficult decision to make because you don't wanna fall behind. So it's not like you don't want your team to have a little bit more time to themselves, to take care of themselves, to walk the dog and to, you know, yada, all these kinds of things that are good for your health. It's one of those things we have to be careful because if you fall behind, okay, well then in six months maybe the agency has to make some major changes. Because we didn't jump on that opportunity. So that's one thing I worry about when I see something like that is that we may have to figure out a way to basically pile on more work there. Now, here's the thing is that the way that I think is a little bit more optimistic, I don't like to think like that. And I think it's, you know, it's a very pessimistic view. Do we expect that to happen? I think somewhere in the middle is absolutely achievable, where if you are able to make efficiency gains, you can have the best of both worlds. So say 10 hours is gained across the entire team, that might mean that five of those hours can go towards your health, your team's health, your. Your team building your kind of career progression or your family time or taking care of yourself in other ways and in the other five hours is probably other kinds of projects that get put on your plate or exploratory projects to kind of anticipate where the industry's going and try to get ahead of those kinds of things that can absolutely be used. And that's really the reason that the company that I work for is around, is that our mission is to workplace burnout through intelligent systems, intelligent process, leveraging AI, and we are very cognizant of eating our own dog food and ensuring that all of our team members are well taken care of, that they don't feel like it's a never ending conveyor belt of projects coming on to their lap. And so having some form of efficiency gain to allow for that creative thinking, to allow for that strategic thinking that you inherently will need to have to do because you're leveraging AI can only be healthy for your team and for your company as a whole. So I'm giving you some kinds of different answers here. I'm not telling you which one's the right one. I can see it from both ways. I don't know what the right answer is. Is that resonating with you, Galen?

Galen Low:

Yeah, no, absolutely. And first of all, like I didn't know that about services mission statement. Like I love that. I think it's an amazing way to look at operational efficiency and I think because a lot of folks are like, yeah, operational efficiency, you know, is kind of a ruthless business. It's like, okay, well we're trying to get more done with fewer people. But I like the optimistic lens of the fact that, so first of all, a 10% efficiency gain. It's not something where you can then take Sally and be like, sho into another project and everything's gonna be fine. It's not a big enough, like, it's not like 50%. If we were like, okay, well that cut, you know, the job down by 50%, well now Sally can, you know, do two projects instead of one. Like that kind of makes sense. So 10% is a smaller slice. And then I think you're right in the sense that, you know, businesses, leaders, organizations, teams, they need to make decisions. About what they're gonna do with that increment of efficiency. And I really do like that idea that you could split the difference. You could be, you know, I know a lot of folks, they'd be like, oh, that's a bit woke. Okay, yeah, you get to walk your dog now and your mental wellbeing is going to like make you a better worker. But you know, I think there's science behind that and I think there's a different way to look at that. It's not like. Free time, flex time. Hope you feel good enough to do good work. But like you said, professional development or using that 5% to work on the human stuff, like team efficiencies, workflows, soft skills, and then I like that the other side of it could be like, great, we can use some of this time not to like do more. Like we can't do a whole nother project for the client. Certainly not the big rock that we sold through those like multimillion dollar deals that we've been chasing, but we can use some of that time. You know, you said exploratory projects, and I'm thinking, okay, yeah, well structured internal projects to find another 10% of efficiency gain. Then we take that at least with that difference, like I think that's a really. Optimistic, but also pragmatic way to look at it is that, you know, you had said earlier, especially right now, this doesn't need to be adapting all the time. Like start adapting now. Start planning for the future, now start exploring what that looks like now. And that can't be done off the side of someone's desk when they're already, you know, working 60 hours a week. They get freaked out about losing their job because, you know, their utilization isn't, you know, gonna be as strong one week as it was the other. Like, that's not a great foundation to build a business on. It might adapt under duress. But it would be, at least in my mind, a lot nicer to have it as part of the strategy rather than being so reactionary to be like, oh gosh, we gotta, like, the market is soft. Suddenly we haven't been closing many deals. You have three days to figure out how to shave 10% off your job. Otherwise, you know, we're closing the doors like that's. Unhealthy pressure versus, you know, something more optimistic to be like, yeah, let's grow, let's push forward, let's find better ways of doing things. And yeah, that doesn't necessarily mean that if we get, you know, twice as efficient, we do twice as much work. It could mean other things. It's just how we improve or like that. I wanted to circle back to data. I know that some of my listeners, they're like yeah. You keep having these folks on the show. They're talking about data, cleanliness. It all starts with data. And you know, in their heads they're like, but who's got the time? You know, like, like we'd have to pause our business for six months to a year to like, you know, get our data in order. Because it's so time consuming to sort of organize this data and make sure it's clean and honestly even down to like the time tracking level. Like I know so many folks in my community who are like, oh, can we just please invent a robot that just stands behind me and tracks my time as I work? There's like different devices. There's these multi-sided D you flip 'em over every time you switch tasks. All of them kind of depend on this idea that you start a task and then finish it and then move on. I don't work that way. You know, a little badge shows up in my slack or my email, I go to it. My time is split. So like how can teams gather data? How can they track enough data and communicate about their workload without getting to the point that it like adds so much overhead to even gather that data that it burns out even harder?

Brandon Llewellyn:

First of all, it's, I feel the pain of a PM because if you're a PM listening to this and you're talking about time tracking and like you're probably feeling. Ugh, like I really don't like time track and it's probably the hardest rule to half the time track because you are popping in and out of every project. Two minutes here, a minute and a half here, 47 seconds on this one, and it's like, oh my gosh, this is impossible. And so like, you know, I understand that and empathize with that. I'm no longer a PM, but I felt that pain when I was a PM. But there's one thing that I do know. We need time, data, no matter what. And so the question is how can we make this reasonable data to collect and how can we make the friction of time tracking as frictionless as possible so that people don't stop tracking time and therefore make your data even worse than if they had been tracking it? The way that I think about this is always to simplify, so simplify the expectations you have for what time tracking looks like. Simplify the way that you collect that data and the way that you transform that data into how you look at it on a weekly basis or a monthly basis. So I always come back to is simplify. So what that means is maybe your time checking expectations for your team is only delivery time. You don't care about the internal stuff. You only track client profitability so that you can easily track things like utilization or estimated time versus actual time and the rest of it well. It's just internal time and maybe we want to try that down the road, but let's just remove that friction for now and say just delivery time. Other things, maybe we want to take our increments and say, you don't have to track anything that's under 10 minutes. That's not worth your time to actually log into the tool and type what you did. And so maybe we say it's 30, it's a minimum of 30 minutes, and if you spent a bit of time with a client, call at 30 and then the next time maybe you just like, don't try that time and then eventually you'll probably even out and get close enough and directionally enough to give you an idea of how much time I spend on that project. So upping those increments can absolutely help with removing that friction. And then finally, like going back to not the inputs, but the outputs. When you transform that data, keep it as simple as possible. Don't worry too much about the edge cases, don't worry about PTO or things that matter at scale, but don't change directionally what your reports are telling you. You could. Bring them in, but they might cause more friction, harder to maintain and therefore you're not getting the data you need. So keep things simple where you can, what works for someone else might not work for you. Maybe you need something that's a bit simpler to make it happen, but getting something to start is great. And then building from there is probably a good way to go.

Galen Low:

I really like that. And I also like it because overall that like granularity is important. And then project manager, account manager, business development guy. So like I've I'm seeing it from the three angles and I think a lot of the time people think, oh, productized work.'cause a services agency means, you know, we're gonna be like always profitable because we've, we figured it out, we've cracked the code, we know exactly how long it's gonna take, and now everything is gonna be equally as profitable until the end of time. Which I think is naive. You touched on it earlier, right? It's like you're managing within that pricing model. And so like the edge cases, unless they are a pattern, unless they are a trend, those are the, you know, the swing and a miss within an ocean within an entire season of gameplay. And as long as you're kind of measuring whether or not you come out on top across this portfolio of work, then that's what matters. And what I really like about that, you know, other places that I've worked is like the transparency around that because I've also worked in organizations where that there's a wall between the two Ops is like not telling us that we're doing okay. The pressure is on the PMs to be, you know, delivering the same margin for everything. Even if it's a PITA, you know, client and that never kind of factors in. It's always, you know, we're always getting the stick, but I like that idea that it's like, okay, well yeah, it's important to try and, you know, respect our margins and do the work within estimates, but also life happens. Stuff happens, you know, like there's complexity, there's different things. And I like the idea that there's also a picture, like some kind of information radiator or some kind of calms to be like. You know what, but we're doing okay as an organization. We're doing okay. Like, you know, here's our sort of, you know, operating margin. Here's how we've done over the past season or quarter. And I think that kind of helps a PM mindset. Look at it from a business mindset, which is not just like every at bat must be a home run. It's just overall we need to like support the business. We need this needs to be sustainable.

Brandon Llewellyn:

Yeah. Thinking longevity there I think is the word you're looking for. And I absolutely agree.

Galen Low:

I wonder if we can round out by like talking a little bit about the future. We've touched a little bit on AI. You yourself, you've been building AI power workflows at surface. Those have been adding operational efficiencies that we've been talking about. It's been helping you and your teams deliver more for your enterprise clients. Has that investment of effort helped build a buffer between the teams' current capacity and the company's growth ambitions.

Brandon Llewellyn:

Yeah, but I think this all ties together so perfectly where we are seeing some efficiencies and by leveraging AI. You know, one of the things that I just did just yesterday was I'm planning on heading off for pad leave for two or three weeks, which you're well aware of.

Galen Low:

Congratulations.

Brandon Llewellyn:

Thanks. So excited about that. And a little bit nervous, but on top of that, like one of the things I needed to do while out. Is the team has to be resourced and we have to understand how to resource a project when I'm not here. And what I did was I built an AI teammate inside of Asana, which is a new feature that's not yet been released to the public as surface as partners of Asana. We get access to beta features and we're testing it right now. The Resourcer I built, which is an AI teammate to do just that, has really allowed for efficiencies in the company. And so coming back to your question about. What do we do with that buffer time? Has it created a buffer time? It's kind of what we talked about earlier where it's like, Hey, yeah, a buffer has been created, but what do we do with the rest of that time? We've been trying to use it just the way that we explained where it's like we can probably take on a bit extra work, but we also can have those explore where conversations and we can also understand that. Because so many of these tactical tasks have now been taken off our plate, we're gonna need some more head space for all the strategic and creative thinking that will come into play when as a company like Surface, when we inherently have to create solutions for our clients. And so we're using that buffer to give our brains the space to think. That's essentially what we're using it for right now. So I think it has created a buffer. I'm seeing that currently. I don't know if it's going to continue on that trajectory like I have. I have a feeling that like as of right now, there might be a plateau in some ways, but I might regret saying that, and so don't quote me on that. There might be a plateau in like the value that AI has been providing until we have another jump in what's possible, and so it could be plateauing at that for a little bit. Now that's currently what I'm seeing. Is that a helpful answer, Galen?

Galen Low:

I think so. You know, I was just and again, I haven't done all of the sort of deep research on it, but a colleague shared a, an article earlier today about this idea that the confidence in AI technology actually has dropped for the first time in a couple of years. Even though adoption is, you know, is way higher. I think we're going to see that as well manifests exactly as you said. It's like, okay, yeah, we can find. Small sort of increments and maybe the technology can do a lot of these things that are currently look like they're beyond our reach. But it will take, like the human factor is actually going to create this plateau a little bit, even if the technology's advancing. A, because change management like so much is changing so fast, B, because we actually now need to sit down and figure out where the most like valuable efficiencies are to be found. What I really like about your answer is again, that dog food thing, and I didn't know this about surface really, but you know, you're really living your values there. You are creating enough space where you can have balance in your life and where you can find efficiencies. That doesn't mean you know that we are going to. Take on more little tiny projects and hope that we can maintain quality. Instead, we wanna be able to, you know, service clients with high quality in a way where we're eating our own dog food. We wanna be able to deliver efficiently deliver value. They get more value from it, and your organization gets more value from it as well. And that's kind of really the, like the growth engine, not just sell as much as we possibly can, but almost like. Sell a mindset, a philosophy, a different way to grow that isn't the sort of ruthless model of operational efficiency where you know, we're just slicing jobs. It's actually just gaining more capacity. Coming back to capacity, like increasing the capacity to do more within a project, within an engagement.

Brandon Llewellyn:

And that's what we come back to is if we can create systems for our clients that remove so much of the work about work that improve visibility for everybody who needs to have that visibility, that improves expectations for how to do something, when to do it by, we can have a world where those efficiencies can be seen, and then that buffer that we create is up to us to deal with. And maybe you wanna choose a company that's gonna thank both of you and your clients to make sure that this is the long game for everybody involved.

Galen Low:

Love that. Longevity, the long game comes back again. Brandon, thanks so much for spending the time with me today. I really enjoyed this conversation. It's been a lot of fun. For folks who wanna learn more about you, learn more about Cirface, like where can they go?

Brandon Llewellyn:

Yeah, I'll give you my LinkedIn profile. They can follow me if they wanna learn more about anything to do with Asana's new features, automations, visibility, all that kind of stuff. I post about on the daily about Asana and about delivery leadership. So we're thinking about data, we're thinking about things like leadership. It's all there. And so Popeye, my profile, give it a follow out and maybe you'll find the goodie here and there.

Galen Low:

Awesome. I'll add those links to the show notes. And Brandon, thanks again for coming on the show.

Brandon Llewellyn:

Thanks for having me, Galen.

Galen Low:

Alright folks, that's it for today's episode of The Digital Project Manager Podcast. If you enjoyed this conversation, make sure to subscribe wherever you're listening. And if you want even more tactical insights, case studies and playbooks, create a free account at thedigitalprojectmanager.com/free-account. Until next time, thanks for listening.