Episode Transcript
[00:00:00] Speaker A: We had a choice. We could pause the transformation until funding returned, timing indefinite, or we could redesign the transformation itself. So we stopped asking kind of the questions around what kind of technology do we need to invest in? Where do we need to put our money? That was no longer a question for us. We then started looking at, okay, how do we redesign with the tools that we have available to us?
Hi, this is Josh Burson.
[00:00:27] Speaker B: Welcome to the what Works podcast where
[00:00:30] Speaker A: Josh Burson Company analysts talk with innovative HR and business leaders about what's really working in talent, technology and the future of work.
[00:00:41] Speaker C: Hello everyone and welcome to the what Works podcast. I'm Julia Burson, Director of Research at the Josh Burson Company and today's episode highlights a story from one of our 2026 HR Pacesetter Award winners. Scott Seneca Polytechnic Seneca Polytechnic is a public college based in the Greater Toronto area in Canada offering a wide range of career focused programs. This conversation is with Diana Mouhand, Executive Director of Transformation and Change at Seneca. Diana is a Transformation specialist and trusted advisor specializing in over a decade of organizational strategy, AI adoption and the future of work. With a career spanning Deloitte Carney and executive leadership roles, we talk about the HR Transformation journey Seneca has been on over the past few years, the role that AI has played, and how her team has maintained agility while navigating unexpected
[00:01:32] Speaker B: changes along the way.
[00:01:34] Speaker C: We hope you enjoy.
[00:01:36] Speaker B: Diana. Welcome to the what Works podcast.
[00:01:39] Speaker A: Thank you so much, Julia, for having me.
[00:01:41] Speaker B: Absolutely. And congratulations again to you and your team on on the recent HR Pacesetter Award. I'm so excited to dive into your HR Transformation story today.
But before we do that, just to kick us off, can you share maybe a little bit more about the HR team at Seneca Polytechnic and specifically what your transformation team works on?
[00:02:03] Speaker A: So we're a small but mighty team at Seneca Polytechnic. My transformation team is comprised of many different COEs and our focus is to innovate and to be kind of that innovation hub for the HR team as well as for the organization.
And so we look at everything from learning and development, HR technology, HR analytics. We have a change management team, a process redesigning team, and we look at how do we make things make work better. And so that's our focus across the Transformation Team, but more so across HR as well.
[00:02:38] Speaker B: I absolutely love that. I think we could all use an innovation team that's constantly thinking about how do we make work better? And speaking of which, so I know your team has been on a transformation journey over the past couple of years and there was an initial start to that transformation. So maybe you can walk us through what kind of started your transformation journey. And then what happened along the way that prompted you to pivot your path
[00:03:06] Speaker A: a little bit, so to navigate an increasingly unpredictable environment, our HR team, like many HR organizations, we had already started on a transformation journey, starting with our operating model. And then as we entered the post pandemic era, we had a highly operational, reactionary manual and siloed function. At the same time, we were facing seismic shifts in digitalization, in increasing student and employee expectations, in new ways of working, working in changing government regulation.
And so we really had to fundamentally change how HR operated. And at the core of that transformation was our technology and how we invested in technology to support service delivery for our employees and leaders and scale our HR services.
And so with that, we were really excited about taking on this journey. But then, in the middle of that journey and transformation, higher education in Canada, the sector was hit by huge regulatory changes that created a structural deficit across the industry.
And so we suddenly had to face the fact that the very investment that was core to our transformation strategy suddenly disappeared.
So our challenge became, how do you create and sustain a transformation journey without the resources that you initially counted on? And that traditional path that you typically take in order to change an operating model and service delivery that was no longer an option?
[00:04:50] Speaker B: What a journey. It sounds like you began with kind of these big goals and expectations around technology transformation. And then something unexpected happened. And what I think is really unique about your journey is that rather than saying, let's halt or press pause or continue later, let's figure out how we can continue on this path. But we need to do some things differently. I'd love to hear what changed and how were you able to pivot such that you could continue your transformation amid some of the disruption that was happening to the industry?
[00:05:23] Speaker A: That's a great question. So you're right. We had a choice.
We could pause the transformation until funding returned, timing indefinite, or we could redesign the transformation itself. And so we decided we made a really thoughtful choice to continue and stay true to our vision. But we really had to be challenging ourselves to think creatively about the path to get to that transformation vision. And that too quickly. And so we stopped asking kind of the questions around what kind of technology do we need to invest in? Where do we need to put our money? That was no longer a question for us. We then started looking at, okay, how do we redesign with the tools that we have available to us? How do we redesign without such large funding requirements? How do you. How do we redesign without the perfect team and situation?
And so that fundamentally changed our approach in how we looked at the transformation.
At the same time, this little thing called artificial intelligence started popping up everywhere and sounded like the key to our journey without these massive tech investments.
So, moreover, when we were looking at this concept of AI, the organization itself wanted to be AI ready, wanted to be the frontier firm in this AI native world. And so we had to figure out how to utilize AI effectively as well. It became a priority.
[00:06:49] Speaker B: And what great timing. That AI all of a sudden entered kind of everyone's radar and became an opportunity to actually be a part of that pivot for you.
Now, I know that your AI and HR journey began with this foundation of really building trust and capability on the team, because this technology was new for everyone. Right. How did you actually assess and then start to build that trust within the hr. Org at Seneca so that people could actually start to use these tools, feel comfortable with them, trust them, and then reinvent how work gets done?
[00:07:25] Speaker A: Yes. So honestly, Julia, we listened. We took the time to really understand where everybody was on their AI journey, because so many of us are in such different spaces. Some are still trying to figure out at that time what even a prompt was, or what does artificial intelligence mean? And then on the other end, you have people who are actually experimenting with this thing. And so we really took the time to understand, okay, where are you with your trust with AI? How much have you learned about AI? How much do you feel confident in using it within the workspace? And by listening to that, we were able to quickly see that I think it was 25% or 30% of our team actually truly trusted AI and to utilize it within the workspace. And so we had to make some significant shifts in trust and empowerment to actually have them utilize it more effectively.
And one of the biggest learnings, as I had throughout this journey, is trust isn't just telling people, don't be afraid, it's here. Don't be afraid to seize it. Trust is actually built on acknowledging the concerns that they have and being super vulnerable in that journey with them. When AI entered the conversation for us, many of our HR colleagues immediately wondered whether their jobs would be impacted, whether they would be left behind, which is very. It made sense when you think about the capabilities of this technology.
So we made sure not to ignore those emotions and actually talk about them openly. We talked about things like, you know, human judgment would remain with the employee, with the specialist, with the human. We talked about how there's A responsibility and accountability that continues to be with the leader, ultimately focusing on how agency is preserved with the employee.
So that was a huge conversation and topic with the team. And then we also did things like bring the leadership team together to understand it more deeply, experiment together, co create together everything from use cases, as well as principles for how we utilize AI. We came up with that together so that we could kind of co create and build that up together.
[00:09:36] Speaker B: I love that you started with listening. That's such an important component to just really understand where your team is at in terms of readiness. And that you found that the relative trust wasn't super high to begin with, but that gave you an opportunity and a place to build from. And then rather than focusing on just pure reassurance, it's like, here's what we know, here's what we want to preserve from the human side and here's how this technology can support us in that. So I love that.
And so it sounds like. And from what I know, you've come up with a lot of really creative use cases for AI within the HR function.
So I'd love to hear a little bit more about what your team came up with. What have you seen as some of those most valuable AI use cases for your team now?
[00:10:20] Speaker A: Yeah, what's interesting is some of our best use cases didn't come from our leadership team. It came from folks from all over every level. Today we're using AI across things like workforce planning, organizational design, job architecture, change management, even compensation analysis. We are trying to find business use cases for this technology that can really support us. And I think the biggest kind of excitement from this technology is seeing how it can take this mundane, everyday operational work, automate it to the extent possible with the oversight of people and experts, and actually focus on the next level of thinking. As Josh Burson would say, it's that human and super manager. Right. So we're really looking at opportunities to leverage AI for that purpose.
And so one example that we're really excited about and has helped us tremendously is we've actually created Personas for change management where we have taken high level, at the thematic level, organizational data, to help us build Personas around certain archetypes within our organization and use that to test ideas and priorities and see where we could improve our deliverables and products and services.
And we use that as kind of the first line of testing. And it's been phenomenal. It's been so helpful in helping us navigate different kind of complexities and conversations. And so those are some of the examples of how we've used AI in our space, in our world.
[00:11:55] Speaker B: Really cool, Diana, thanks for sharing those. And I love the Persona example because one of the great things about AI is it enables this personalization at scale.
And so what I feel like you were able to do is here's how we can better tailor our solutions, our communications to all of these different audiences that we know exist in our workforce. Let's use AI to help us do that in a much more efficient way, which is fantastic. And one of the other cool things that you've done, and we get a lot of questions about this, is that because you've built these agents across the team and you have actually embedded them into your HR org chart and, and we get a lot of questions around how do we represent a team or how do we decide who's responsible for what when you've got these human agent hybrid teams? So what prompted that, that integration of the agents into the org chart and how has that supported your team in better understanding roles and responsibilities?
[00:12:54] Speaker A: That particular topic is always a bit controversial. Should we include them in our orchard? How much should we humanize them?
That topic kind of always comes up and we always have this debate about it. But we, we did this on purpose with a lot of intention. It's more than just symbolic, right? We added these agents and integrated them into our org chart for a few reasons. One, it creates clarity and ownership around who owns these agents, who's responsible for their works, who's the agent boss.
It also adds a layer of governance to say, okay, this is how we're organizing ourselves. This is where the agents are playing a role.
Are the workflows that are actually being represented on the org chart that are being done by our AI agents.
Every agent has a purpose, an owner, a defined responsibility.
We're also even thinking about how we create performance management and reviews for these agents so that we can sustain continuous improvement, we can sustain the quality of the output, and we can also showcase the skills of the manager. So supporting that agent and how they've developed this agent to improve and do more. So we've really been thoughtful about including these agents as part of the orchard because of these reasons. The concept of agent bosses within the orchard as well, we've been really thoughtful about what does that mean for people when they start utilizing AI.
We don't want HR professionals to just be simply like users of chatbots. We want them to be responsible for training, for monitoring the outputs, for continuously improving the agents. We have to rethink expectations of early career professionals coming in and having to act like managers suddenly right out of school. Right. That shift has fundamentally changed how we think about the usage of AI. It's not a traditional automation. It's something that's really integrated in how we work and how we manage this thing, not only today, but into the future. And so that's why we decided to utilize the org chart concept as a way of creating that ownership, clarity and governance.
[00:15:02] Speaker B: Yeah. And that makes a lot of sense. And I think the controversial element of it is, are we overly personifying these agents? But the things that you've mentioned about the importance of managing an agent, being responsible for its performance, governance, what's the job that the agent's doing, Those are questions organizations need to answer. It sounds like you've really created that clarity through the way that you've embedded these agents in your team.
[00:15:27] Speaker A: I think that personification argument is more nuanced than the way it was probably presented in some of the research.
We need to give it a name so that we can effectively think about how we work with it. And I think that's so important. We're not saying it's an executive, we're saying that it is maybe an analyst, an intern, a coordinator, so that we understand, okay, we still have accountability and agency for what it produces.
And so that's been really important as we think about how we even position it within the teams. Right. Like, how do you relate to it?
So, yes, I agree with you. I think it's very nuanced and there's actually importance in it being on the org chart.
[00:16:10] Speaker B: I think your story really exemplifies agility in the age of AI and amid transformation. And so what results have you seen? Where are you at in your journey today?
What are you proud of?
[00:16:22] Speaker A: I love talking about this because the team has worked so hard to get to this point.
And honestly, it's been twofold. So the first was just being able to take away some of that monotonous work for the team so that they can work on higher value activities, things that excite them, things that drive their capability and interest.
And two is figuring out how we utilize that capacity to build increasing and more value add partnerships with the business, how we increase our ability to innovate for the business.
I'll give you a few examples. Operationally, more than 90% of our employee interactions have moved onto our ServiceNow platform. That was not the case four years ago. We were on email, phone, fax, you can name a channel. We were probably on it. And it was really difficult to manage today, having that centralized point, we're able to better manage. We have average response times dropping from nearly two weeks for less than 24 hours, which is phenomenal. We've refreshed more than 100 knowledge articles so that we can dramatically improve user experience and self service.
We've also looked at data governance and quality to improve our data and ability to analyze and make decisions better. We've supported trust and empowerment in AI across the HR team.
And then the strategic shift is even more important. We have our HRBPs focusing on relationships, we have more time advising rather than transacting. And we have leaders with better workforce insights, better conversations about their business and we're still early in the journey, especially with AI as most leaders are, but we are feeling super excited about how we can support the institution in a more meaningful way into the the future.
[00:18:10] Speaker B: Diana, to close us out today, what would be one lesson learned or piece of advice that you might share with another HR leader that's embarking on a transformation journey or maybe has had to pivot or is using AI to try to pave their own path here?
[00:18:24] Speaker A: The most important thing we did before the AI frenzy happened was focusing on our fundamentals.
So things like data governance, process, we design, knowledge management, understanding and straightening those things up so that they were really wonderful blocks to launch off of that was super critical. And also AI is driven on that, right? So it's driven on good data, it's driven on good process, it's driven on good knowledge. And so being able to clear up those things first, it sounds really simple. But being able to do that will give you leaps and bounds into your AI journey as well as your OP model journey. Because then you can start thinking about how work flows, how data flows, how do you get closer to the leader of the business and so much more. And so that was really important for us to take on before we even entered the AI conversation.
[00:19:19] Speaker B: Fantastic piece of advice. Strong foundation is everything. Diana, thank you so much for joining us today. This was a great conversation and hope you have a great rest of your day.
[00:19:30] Speaker A: Thank you Julia.
