The Future-Ready Project Manager Transcript (Part 2)

Segment 3: What does it mean for a Project Manager to focus on Value Delivery Management?

Ross Martin:

Yeah, and that strategic mindset is is the way to go mindset is definitely the answer In the context of a project manager having additional capacity, because you now have an AI-powered project assistant who takes care of all of your mundane tasks, in addition to being strategic, another area that you can focus on is value delivery management. And value delivery management is really more about how the work gets done at your company. as opposed to What what you're doing so It just you know, let's let's talk a little bit about value delivery management Maybe start by explaining a little bit more about what it is and how it's different

Idris Manley:

Sure, sure. Yeah, no, it really is an emerging concept, right? You start talking about like value streams and how we begin to redefine work. So historically, project managers have been very focused on what needs to get done, right? We focus on the deliverables, the tasks, we're very, you know, that's how we measure success. And it's been very important. I spoke earlier in a different segment how that was important because historically the industry has evolved from aerospace and manufacturing and a lot of these sort of more industrial air sort of industries that required that level of discipline. But we're finding that just being able to deliver on tasks and deliverables just isn't enough anymore. And now we need to, as project managers, really understand how we're delivering, how efficiently are we delivering? Are we delivering faster than the competition, that widget? Are the teams, what is the baseline for how we deliver? How can we improve how we deliver year over year, month over month, et cetera? So it really asks us to begin taking accountability for understanding how the team is delivering and how we can continue to drive improvements in that. And to really look at how we deliver in the context of value. And so there are various value streams within a company. There are internal value streams like operations and product manufacturing, product development manufacturing, and there are external. you know, value streams excels and different marketing capabilities and customer sort of facing sort of activities as well. And so really being able to understand all of these various value streams that exist and understand them in the context of projects that you are, you know, defining and managing becomes particularly important.

Ross Martin:

Yeah, absolutely. Once you're freed up from worrying about chasing down tasks and deliverables and the what of the project, one way to really increase your contribution to the company and to the success of the project is looking at the value delivery and the how, as Idris says. So, for example, your engineering team, maybe you're doing a product and you have a product and engineering team, instead of chasing them down and making sure that they're delivering things the way they're supposed to, like you used to do, now that your AI assistant's doing that for you, you're spending time thinking about how they operate as a team. how they interact with each other. You're looking for ways to improve the efficiency of their interactions, to improve the efficiencies of the way that they interface with other parts of the organization. Say, for example, that your product and engineering team needs to be communicating well with product marketing as they're thinking about how customers are gonna be using the new features that they're working on. You as a value delivery focused project manager are now thinking about those things. How are the different departments planning and working together and collaborating? That's the kind of thing that you do in value delivery.

Idris Manley:

Yeah. Yeah. And I just want to reiterate again, I think, you know, KPIs and metrics are critical to this, right? Yeah. It had, you know, you have to be able to measure this, uh, because it's important for you to be able to establish the baselines and to understand how you're progressing or how you're performing or not. And to be able to help set goals that, and you baking those goals into your, your projects so that it's becomes a part of how you are planning and executing and monitoring and controlling against some of those key metrics. And again, I think it's important to understand that this is something that executives may not necessarily proactively approach you with and request, but I guarantee you that they will find value if you as a project manager, you as a PMO leader, able to begin capturing this how insight and you're able to go back to, you know, your head of operations or, you know, your CPO and say, hey, you know, this is how we have performed and this is the goal that I'm setting for the next iteration or for the next cycle. And then you're keeping them abreast of how you are progressing. You know, you will be viewed in a different way than you have if you're just simply In updating them on how you're progressing on the deliverable being complete.

Ross Martin:

Yeah at some of the companies I've had we actually had Dedicated teams though in this case they were within operation focused around continuous improvement and the kinds of people that work there were Six Sigma black belts and also people who had experience with lean or both and And they were looking at the value streams within the different parts of our operations of our company and identifying bottlenecks and other sorts of areas where they could drive efficiencies. And the KPIs were incredibly important on that. So they'd baseline it. They figure out how much it costs to do this particular value stream. And then as they're making improvements, they're measuring to show that ultimately, for example, at the end of the day, the six-month effort resulted in $5 million of efficiencies in the way that that's being done. So as a project manager professional who no longer is required to focus on the what of what you're doing as much as you used to, you could spend time thinking about how all of these things are going. But as Idris is saying, it's absolutely critical that you get a baseline in your metrics and you're checking along the way so you can prove to senior management and to yourself that these things are working.

Idris Manley:

Yeah, the team is improving. And I just want to be clear that I'm not necessarily proposing that you have to become a Six Sigma, or you have to become a lean enthusiast. But I certainly think there's a hybrid, or at least there is a lightweight model that can be incorporated for project managers to be able to incorporate some of those notions and concepts into their day-to-day as a way of looking for opportunities and ways of adding more value.

Ross Martin:

Yeah, fair enough. It really relates a lot to the program or project that you're involved with, or multiple projects, for example, and the teams that you're involved with, as opposed to, say, trying to fix an entire area of operations. But the concepts still hold. So Idris, one of the things that's interesting as well, if you think about this, is we talk about how value delivery management is really a project manager spending time thinking about how to improve the way things are done, right? And traditional project management now powered by AI, your AI assistant is thinking a lot about what is being done. We're delivering these things on these dates, that sort of thing. And in one of the other segments we talked about, Is strategic business outcomes are thinking about why? Why are we doing this investment or this project in the first place? So we've got a why and a how and a what and it's an interesting. It's an interesting way to look at it

Idris Manley:

Yeah, I think I should create some kind of poster or illustration for project managers. I think it would be helpful for all of us to see on a wall, you know, why, how, what, maybe like a triangle or something like that. But yeah, it really is, it's simple. And so as a project manager, if you're trying to understand in the simplest of ways how you know, the introduction of AI as an AI assistant for you can really give you the capacity to think more strategically. I would really sort of simplify it into why, what, and how. And as you said, and then, you know, again, just to reiterate, you know, when you look at the why, it's really understanding the reason why a project is being performed or being initiated to begin with, right? understanding why executives are requesting that this project be budgeted and supported. Why are they investing in this? Why are we even spending resources on this? And the deeper you can understand the why behind that, the more you can add value and define your project in a way that aligns to that. You can track and monitor it in a way that surfaces how the team is progressing against that why or that those business goals and outcome. You know, it just provides an immense amount of value to have that sort of that foresight as you're initiating and managing your project. And then when you talk about the what, obviously I don't think we have to spend a lot of time there. It's what all of us should already understand very well. It's the deliverables, it's the tasks that are required to support actually completing and delivering on the specific project goal, the deliverable.

Ross Martin:

And those still matter. You still need to deliver.

Idris Manley:

They don't go away. They don't go away. They don't go away. You're actually adding more work to your plate in the sense that you're taking on both, not only the responsibility of tasks and deliverables being satisfied, but now you're also taking on the responsibility of business outcomes, understanding business outcomes, and taking on the additional responsibility of how you're getting the work done and how and how you can get the work done more efficiently and more effectively. And the reason why you can take on that additional work is because now you have additional capacity that AI as your partner, as your collaborator, is enabling you to really use that spare capacity in new, more impactful ways. So in that sense, you're really elevating your role in a way that you couldn't have done without AI.

Ross Martin:

It reminds me of a situation at one of the companies.

Idris Manley:

Well, Ross, by the way, you're always being reminded of things.

Ross Martin:

You say stuff and then I go, oh yeah, I remember that. Like if I were in your brain, you know? And even the project name comes to mind. But it reminds me of a situation where I was working on a project and I think I was relatively new at the director level. And a VP of engineering came in and he was going to play the executive sponsor role on this project. And he observed me working in the room with the team and driving towards the business strategic outcome that we're looking for. And later he said, I'm not going to attend these meetings anymore. And I said, why not? He's like, you've got it. He's like, you're representing my views. Let me know if there's any problems or anything you need.

Idris Manley:

So by the way, that's the biggest compliment I can receive from an executive is, you know, is I don't need to attend. I don't need to review. I trust you. So.

Ross Martin:

Yes, you're right. And that's what you're trying to get to as a project manager. You're trying to get to a point where even your executive sponsor feels superfluous on their own sponsoring project. Because you've got it. And that's because you're no longer worried about the what. You will make sure it happens. But it's not your primary focus. You're thinking about the why and the how. But you're still accountable.

Idris Manley:

Oh yeah, that doesn't go away. And or responsible for that what. But yes, you now you have new things on your plate that can offer even greater value than just focusing on the what.

Ross Martin:

Well, and if you're spending 80% of your time worrying about chasing down action items, transcribing meeting notes, and all those other things, you don't have time to think about this stuff. You're tired at the end of the day, and that's all you can do. So again, in the era of AI, having an assistant take care of a lot of this stuff for you, you still have to make sure that whatever your AI assistant is doing is correct. Um, then you now can start to level up and behave. You start thinking as a proxy for your executive about what she or he would be actually worried about. And as they see you acting that way, they're freed up. from worrying about your project to worrying about things above them. Yeah, yeah.

Idris Manley:

Now, when you talk about, you know, still needing to have a level of oversight, you know, over AI, your AI collaborator, I mean, I think it's a really important point, right? Because, again, your role doesn't go away. Someone still needs, you know, at the end of the day, if AI is making a recommendation and you authorize it, you know, your neck is on the line, ultimately, for the decision, right? And so you still have to make sure that you understand the decision, that you're in agreement with what AI is recommending. So there, again, there is a level of oversight and responsibility to make sure that the information it's giving you and the decisions that you are making as a result, that you are still in agreement with. But at least the fundamental work, the work that has to be done to arrive at the insight or the decision that's being done for you, but you still have to make the decision.

Ross Martin:

I think in the current or more recent world of PPM tools and things like that, your tool might be able to show you a bunch of information about the state of your project. And in the era of AI, AI can then take that information and actually make a recommendation to you. Perhaps the recommendation is that the project needs to be pushed back by a month, right? But what you will always need to do is you need to then be the person that A, figures out whether or not you agree. You better dig in and really make sure that what AI is suggesting, you're like, yeah, they came to the right conclusion. That is the right. Now, it's the how. How do I communicate this to the various teams and to my sponsors and to the various executives and functions and areas that are impacted by this? The AI might be able to tell you that it's going to impact them in these ways, but you need to figure out how to communicate it in the most effective way.

Idris Manley:

Yeah, and also you still have to build alignment. Yes, in those teams, right? They may not agree with the conclusions. And so you may still have to sell or to influence the decision making, right? And even to take it a step further, like AI, the suggestions and recommendations that AI gives you may not take into it. to account culture and people and different nuances that you can't just consume data to understand what the best decision is. And so your role as a project manager is to really factor in a lot of these sort of human considerations and to merge that with or to fuse that with the insights that AI is able to provide you and to really come to the right conclusion and the right decision given all of those considerations.

Ross Martin:

I think an interesting thing that will happen in the near few years will be that you may not even want to tell everybody that it was AI who gave you the idea that something like this needs to happen. They may not trust it. It may be that you learn how to trust it. You give it a little bit of oversight and make sure that what it's saying makes sense. And you use it with a little bit of discretion. Or at least you don't go around telling everybody, AI told me how to run my project. I could also see executives actually misunderstanding and thinking that that means that somehow you aren't needed at all and Again that goes back to making sure that you're focused again on on the why and the how More than the what well and the what all at the same time. Yeah

Idris Manley:

And I just want to sort of have a slightly different take on the not sharing AI. If the way that individuals have interacted with chat GPT over the last several months is any indication. Oh, fair enough. People seem to be very comfortable trusting AI. Too much. Too much, actually. And so if on the consumer side, that's any indication. I think in the commercial enterprise space, people become very comfortable with AI very quickly.

Ross Martin:

That's a really good point, Idris. That's a really good point. And I can't tell you how many times I've been in a situation with senior executives who say, I want to make data-driven decisions. And you're right. It may be that it's the exact opposite of what I was saying before, which is instead, if AI based this decision on the data and they believe that the data that you're using is sound, they may actually trust that more than you using your gut.

Idris Manley:

Yeah, or just maybe just a brief level of healthy skepticism that may within a few weeks or maybe even days, even they may go from skeptical or cautious to all in.

Ross Martin:

You're right. You're right. People will convert. It's similar with chat GPT and other generative AI tools where all of us, you know how it is the first time that you ever used it, right? All of us, you're kind of like, well, I don't know how this is going to work. And you say three days later. Exactly. Exactly. every project plan, you know. So now, I am sure all of you have noticed, everything that comes back is not quite production ready for you to share with your bosses. It still requires, you know, the human touch. But that's why you'll still have a job, right?

Idris Manley:

Exactly. That is your value add, is playing that oversight role, being able to help massage what your assistant is offering you to put it into a format, an asset that is consumable and of use to your company.

Ross Martin:

You understand how to communicate messages in the right way. You understand the culture of your company, of the countries you're dealing with. You're right. That part won't go away. But as we said, if all the stuff that you do is what your assistant does, and now you're just free to go home at 2 in the afternoon, That might not work as well.

Idris Manley:

So I think just sort of to close out the discussion, I think when it comes to value delivery management, it's important to really understand that you need to stay locked in on the how. And really understand that with this additional capacity, it provides an immense opportunity for you as a project manager to really dive deep into that how as a way of offering value. I can't imagine a project manager in the era of AI struggling to understand how they can add value. Right? There's so many... They might not be willing to. Well, that's different. Yeah, that's different. But there's so many great opportunities to be able to contribute and make a higher impact. And I would just propose that whatever opportunity you consider, ensure that it's in alignment as closely as possible with business goals and business needs strategically. And if you do that, you can't go wrong. Whether you're focused on, you know, the how or you're focused on the why or a bit of both. If as long as you're aligned to what matters most to the business, you'll be fine.

Segment 4: How Agile Will Finally Achieve its Promise with AI

Ross Martin:

So in the context of a project manager now having an AI project assistant, one of the other things that is going to really open up here is the ability to, as I say, get Agile right. We've found for quite a while now that the promise of agile development, I remember when I first heard about it, it's kind of like, oh, this makes so much sense, the flexibility and all the other good things that come with it, right? But in practice, I've never really seen it work in the purest sense of how it was originally defined. And we think that AI is going to open up that possibility.

Idris Manley:

Yeah, absolutely. I can't tell you the number of times that my team was asked to manage a scrum or to manage some initiative and not being able to offer a predictable sort of schedule based on the product. The executives don't like that very much. Yeah, that doesn't really work very well. And so I think very early on with the introduction of Agile, it was very clear to me that, you know, my teams needed to be able to sort of offer some hybrid approach where they could still sort of plan at a high level conceptually that sort of the longer arc, if you will, in a waterfall manner, while still allowing the teams to function on a day-to-day, iterative basis in an agile manner.

Ross Martin:

Yeah, absolutely. And that's the same thing that happened in my companies as well. We converted the engineering and product teams over to Scrum. And I remember that there was a lot of resistance on that from even some of the engineering folks. You'd think that there would be more embracing of that, but there was some serious skepticism at the time. that this Silicon Valley big tech concept was coming into the next level of companies. And so there's this sense of, okay, now we're agile, but the reality is we also, the same thing within the PMO, and we figured out that outside of the product and engineering teams, everyone else really expected waterfall.

Idris Manley:

You know, I mean, because I mean, it's PMO, we're in the middle, right? So we are in the middle. So you have you have engineers on one side that really have begun to love agility and the freedom and the flexibility gives them because it allows them to be more adaptive to a fast changing, you know, environment and competitive two or three week sprint. they love those. They love being able to not think further ahead than that, which I completely understand. But then on the other hand, as project managers, we have business leaders, we have executive sponsors, you have C-level leaders that really are expecting a certain amount of output, velocity output. They're expecting a certain amount of deliverables to actually be released, product features, et cetera, to be released. And we're having to sort of answer along with maybe the engineering leadership as well as to why teams aren't delivering enough or when they can expect certain things to happen. So sales and marketing can have clarity on when they can set customer expectations on some feature set, et cetera. And so, you know, again, we're in the middle of these two audiences that have very different interests. Nobody was happy. Nobody was happy. And we're here, we're having to sort of bridge the gap here. We're trying to negotiate with engineering leadership to at least give us enough clarity and commit.

Ross Martin:

How many sprints ahead do you think this might be?

Idris Manley:

And can you commit to it? And can you at least... well, you know, confidence levels and et cetera. So I think we were really on the front line of having to force the conversation, or at least to begin thinking about these hybrid sort of designs that have become pretty ubiquitous now, I believe, in a lot of companies in PMO, in having to embrace a hybrid approach to being able to move forward and deliver.

Ross Martin:

Right. But the hard part with the hybrid approach is, as the project manager, again, you're trying to juggle both sides, the structured, predictable side and the flexible, adaptive side. And the way that you take all this information together is, in my case, our team, we were using things like Excel and stuff to try and...

Idris Manley:

Try and pull and then and then you're saying a date to someone and you're like, please please be right It's an interesting point So if you look at all of the you know leading agile tools that are out there today and like in my day You know rally and version one where I think some of the leaders in the industry early on but now you know you have you have you know, you have like Asana, and you have Monday, and you have the JIRA suite. So you have a lot of options. But if you look at that, these tools are really still set up as squarely Agile tools. So when you're scoring, and your story points, and how you're measuring commitments, it's still within the Agile framework. And so this notion of hybrid sort of waterfall-esque ways of being able to track and monitor still really haven't been built fully into a lot of these tools. And so as project managers, you're still left to having your own sort of hybrid sort of hodgepodge way of taking the information that you're getting from your Agile tools, translating it into a Gantt chart of some sort that is not Agile.

Ross Martin:

show that to engineering because they don't want to see that.

Idris Manley:

That's your tool and your data and you're then you're trying to translate that to executives and sponsors and other things that they can understand. So you're really sort of creating this mismatch of using a mismatch of tools and data to try and ultimately to appease all of these different audiences and I think that That leads us to AI and the opportunity that AI actually provides.

Ross Martin:

I think so, yeah. I don't know about you, Idris, but you create something like that Gantt chart and then an executive sees it. It's done. Like now that's the commitment, right? They saw it. It is now the date. And now suddenly you find this date is like everywhere. No, you show it, you own it.

Idris Manley:

Exactly.

Ross Martin:

And what sucks is that you as the PMO leader or the project manager are now Just, like I said, sort of hoping that it all works out.

Idris Manley:

The worst thing is to be asked to share a deck that contains timelines that are still in draft form via email. I go, you know, Idris, can you send me that that that deck that you showed over screen, you know, screen or zoom or and it gets forwarded. And then, you know, yeah, then it gets forwarded. It becomes like, you know, it's too late then. Yeah.

Ross Martin:

But yeah, it's like, oh, great. It's coming out in November. Yeah.

Idris Manley:

Idris is committed. He showed it in a slide.

Ross Martin:

Oh, my. Yeah. So so like you're you're teeing up, I think, is is the interesting thing is We believe that with AI, there's an opportunity here now to finally get hybrid right. The true promise of Agile with the need for a certain amount of predictability and structure for other parts of the organization who don't operate in an Agile manner.

Idris Manley:

Yeah, I think what AI will be able to do sooner than later is to consume all of this different data related to agile and really structure it in a way that it can also understand the constraints or the needs of the executives and really begin to frame naturally how to organize all of these sort of data sources and to ultimately to provide an optimized understanding of what's possible, what's likely, without you as a project manager having to really think a lot about that. And so it will naturally be able to give you data that is organized in a Gantt chart or just gives you new data that's structured in a way that can give you more predictability without necessarily having to crunch the numbers yourself and drop it into an Excel sheet and do all of these sort of creative ways to be able to try and identify and anticipate what's possible. And then in addition to that is going to be able to assess the risk as well. and to be able to offer you greater visibility more proactively with your Scrum teams, your Agile teams, in terms of risks that are possible in ways that would be much more difficult for you to do if you were just trying to read some of these reports and try and assess what the likely outcome is or how teams are actually tracking.

Ross Martin:

Yeah, absolutely. And what AI is incredibly good at, as we all know, is data. And you have lots of it. And there's a lot of data coming out. And even in tools like, say, Asana or Monday, you could take your Agile data and you could try and figure out what your team's velocity of, or maybe if you're doing safe, the multiple Scrum teams or how their velocities are going. But at a certain point, it gets a bit overwhelming, right? Because you're trying to figure out, you know, you're looking at the backlog, you're trying to figure out the velocities, you're trying to figure out how they interact with each other, the various Agile teams, and where that all leads towards the delivery of a significant feature or release of a product. And then there's the ones that aren't even in that tool, like I said, like product marketing, or sales enablement, or any of those other things, customer interactions, all those types of stuff, gets to a point where it's just overwhelming. And that's what AI is gonna really make a difference at here, is that AI will be able to consume all of these things, the people who are working in Agile, the people who aren't working in Agile, the different functions, the constraints, and really be able to bring it together so that, essentially, that the different parts of the organization get to work in their most efficient manner, and it's okay that they're all different, or that they could be different, and it still can work together.

Idris Manley:

AI becomes the glue that allows all of these teams to operate with the project methodology of their choice, and it really sort of links them all together in a way that you as a project manager can maintain visibility and insight into all of the things that matter most. to performing your job, which is, can we deliver as committed or as expected? What are the risks that need to be proactively dealt with? And what is the how? And how are we performing against baselines? And how can we perform even more efficiently and more effectively, increase velocity, and all of those things that's necessary?

Ross Martin:

Absolutely. And to make something that was actually impossible to get your arms around relatively easy to get your arms around, frees you up to focus again on how the team's operating, why are we delivering this, and how are we doing on our metrics and KPIs towards the business outcome that this entire project is here for in the first place. And figuring out how to make tweaks and changes and adjustments along the way, driving through the risks, that's what your job's gonna be.