Subscribe
Share
Share
Embed
The WorkOps Podcast is your weekly conversation with HR leaders and People Ops practitioners doing the real work.
In every episode we dig into one story. A process that went sideways, a system that just didn't work, and what someone actually did about it. Packed with practical lessons you'll want to bring back to your team. Whether you're supporting 500 employees or 5,000, this is how the best People leaders are building for what comes next.
William & Jeet | May 13
===
Speaker 2: [00:00:00] they had spent, I wanna say, twenty-plus hours in calibration the previous cycle. ~Um- ~Wow I'd say driven by high value around fairness, high value around, ~um,~ honestly investing in people, so the intentions were actually really good.
And- ~Right ~... how we actually did that was just a slog. ~Like, ~20 hours- Yeah ... talking is really hard. ~Um, ~and ~so, uh, ~that was the problem, was, okay, how do we take this thing that has historically been really hard,
Welcome to the Work Ops podcast. In every episode, we dig into one story, a process that went sideways, a system that just didn't work, and what someone actually did about it. It's packed with practical lessons that you'll want to bring straight back to your team. This podcast is brought to you by Kinfolk, the AI service desk built for HR.
I'm your host, Jeet Mukherjee, and with that, let's dive in.
Speaker: Hey, everybody. Today, I am joined by William West, VP of People at Wrapbook. William, thanks so [00:01:00] much for joining us today. Before we jump into things, can you tell us a little bit about yourself and how did you choose HR?
Speaker 2: Hey. Yeah, ~nice to, ~nice to see you. ~So, uh, ~I'm based in Seattle. I have been here 17 years this summer.
~Uh- ~Wow ... I've got two little girls who I celebrated birthdays, ~uh,~ this last few weeks, actually. ~So, uh, ~now- Happy birthday ... and nine. Yeah, it's been a lot of parties. ~Um- ~And originally from Nashville, grew up in the Southeast, and then made my way to the Northwest. ~Um, ~I... on the HR side of things, I finished undergrad and then grad school at a very wonderful time to look for work, which was 2008, 2009, which meant, ~uh,~ I knew I wanted to do- Wow
something that had impact, but I didn't know ~kind of ~the what and where. Was interviewing at a nonprofit. It was a leader who had formerly been in tech, in HR for 20-plus years, saw something and said, "You should try this," and then I did. Fast-forward six [00:02:00] months as a recent grad school grad, I was leading HR for that nonprofit.
And then- Congrats ... everything-- ~I mean, sort of. ~Made a bunch of mistakes. ~Um, ~but really from there, it was, ~uh,~ I'd say a lot of learning, a lot of trial by error, but within different environments. So went from, ~uh,~ a nonprofit to a chocolate company, eventually into tech, ~uh- ~Okay ... with Tableau that was, ~uh,~ rapidly growing at the time.
Was there actually then seven and a half years. And then post-Salesforce acquisition found I love startups, I love building, and so spent the last, ~uh,~ four and a half years or so, ~uh,~ building in startups.
Speaker: Wow, what a journey. How is-- Before we dive into your story, how is HR different, if at all, between a chocolate place and a nonprofit and a tech company and something that's been acquired?
Speaker 2: Yeah. ~Uh, ~that's a great question. I will say, one, I was a one-person show there, so that just fundamentally meant- Yeah ... I was doing a little bit of [00:03:00] everything in previous life, whereas now I have the great benefit of a team. ~Uh, ~I'll say the biggest difference is pace. At the end of the day, ~the,~ the rate of change, particularly within tech, has been so high, and then, ~I mean, ~the last 12, six to 12 months has, ~uh,~ if you've been thinking it'd get faster, ~it,~ it has.
~Um- ~Yeah ~Uh, ~but the, I'd say pace is one of the biggest one. The complexity is different. I'll say, ~uh,~ in the other two environments, there was a lot of human complexity. ~Um- Right ~... just people, ~you know, ~you're really close to people and the things that are going on in their lives, and so there's, ~uh,~ a lot more of ~sort of ~that dynamic at play.
Whereas within tech in particular, it's a lot more ~sort of ~like a system as a whole, and how do you orchestrate the system toward ~like, uh, ~an end state or end goal or end result. And ~so, um, ~it-- that, that change in transition's also been pretty fun.
Speaker 3: I
Speaker: bet. So since we are talking about systems and processes, William, ~um,~ of course, on this podcast we talk about a particular process or system, ~um,~ [00:04:00] that didn't quite work out ~or, ~or was dysfunctional.
~Um, ~what's your story today?
Speaker 2: Yeah. So I-- There are so many. ~Uh- ~So I've worked only for a period of time. ~Uh, ~I also have found that I love going to organizations where that's the thing, like where there is a process- ~Mm-hmm ~... a thing that's been painful, and- You like pain ... how do you redeem it and, ~uh,~ make it better for people?
~Uh, ~so the one that I thought of was around calibration process and- Okay ... ~uh, ~particularly how that's been, ~uh,~ particularly at Wrapbook, ~um,~ but in some ways it's been everywhere. Okay. ~Well, ~
Speaker: talk us through it. ~Um, when, ~when didn't it work? Yeah. And what went wrong?
Speaker 2: So I joined Wrapbook about two years ago, ~um,~ and we're about two hundred and fifty people.
~The, ~the process I'd say was fairly traditional in that, ~uh,~ you, around review time, you get a bunch of ratings. You then wanna make sure that there is fair and equitable application of that rating. And so the, I'd say, the most common way of then solving that has been get people in a room. And so that's really what [00:05:00] calibration has been.
Mostly by department, talk through by level, and for many teams, it either can be super political, super long, or just a waste of time- Yeah ... because you are there just to ~sort of ~check the box to say that you did, and then you get out of the meeting and people still, ~you know, ~feel the way that they feel about ratings.
And ~so, uh, ~when I joined Wrapbook, particularly within, ~uh,~ our largest teams, which is our engineering product design teams, they had spent, I wanna say, twenty-plus hours in calibration the previous cycle. ~Um- ~Wow I'd say driven by high value around fairness, high value around, ~um,~ honestly investing in people, so the intentions were actually really good.
And- ~Right ~... how we actually did that was just a slog. ~Like, ~20 hours- Yeah ... talking is really hard. ~Um, ~and ~so, uh, ~that was the problem, was, okay, how do we take this thing that has historically been really hard, taken a lot of time, but that we also really care about and [00:06:00] we wanna do right, and how do we create efficiency while not losing, ~uh,~ quality and sort of the richness that comes from that conversation?
And- Yeah. ~So I'm happy to keep going. You want me to keep going? Keep going. Yeah. Yeah. All right. ~so what we did. ~So, uh, ~I think in many ways that's where we started, which is, okay, what are we trying to do here? Which is we want to, ~uh,~ first and foremost, make sure that the outcomes that we have, which are the ratings, are fair and that they, you know- Yeah
we're using the same measuring stick for similar roles to evaluate people. And, ~uh, and, ~and the secondary goal was, okay, how do we make that as efficient as possible, ~uh,~ in the process? And so what we did was break down the problem then very simply. ~You know, ~we had a bunch of data, ~so, you know, ~people write reviews before that.
~Um, ~we also have a culture of a lot of, ~like,~ reading in order to get, ~uh,~ to ~sort of ~help elicit thoughts. And so what we actually did was instead of, we cut out what is often the most time-intensive part of the meeting, which is people explaining the person. ~You know, ~if you've been in a calibration [00:07:00] meeting, you know- Yeah
there's some people that are really good with sticking to that one- to two-minute timer, and the other people that they spend 10 minutes telling you everything that person had done, and then we're supposed to talk about them afterward. And so what we did was we, ~uh,~ we shortened that period to actually now everyone is reading.
We're actually gonna read three people at once in a similar role at a similar rating, and then let that guide the conversation. So ~that was, ~that was, I'd say, in its simplest form, the way that we ~sort of ~retooled that. ~Um, ~and then we worked our way through all of the people. So it went from, ~uh,~ again, a, what I'd say it was like a 20 hour mostly listen to people monologue on their people to then- ~Mm-hmm~
actually shifting the burden of conversation away from just listening to the explanation this person had, to rather to understanding the foundations of what they were representing, and then we can actually talk about it and talk about the person and let it be much more question driven rather than, ~uh,~ explanation driven.
~Um- Right. ~We went from then, I'd say, 20 [00:08:00] hours, I think it was probably more than 20 hours, but 20 plus hours, ~uh,~ to I think like we ended up like six, ~uh- ~Wow ... the first year. ~Um, ~and It-- everyone left calibration
Speaker: feeling good, believe it or not. ~It, ~it sounds like you actually went from not doing calibration and just talking to actually doing calibration because you actually talked about the framework and why are we positioning someone ~in this, ~in this particular way versus another.
Speaker 2: Totally.
Speaker: I
Speaker 2: think the other thing which ended up being, I don't know if it was unintended or just really strategic, but we didn't say it out loud, which was- ... we-- ~what, ~what one of the reasons why it was-- there was so much time being spent was that we were both calibrating and talking about development. ~Mm.~
And those often can happen together, and the amount of time and the context that you need to do that I think are very different. And so the other thing that we did was actually then intentionally separate those out. So [00:09:00] calibration is about ratings. The fact that this person is awesome and we want to high five and celebrate them, great, not this time.
~Like, ~are they- Nice ... meeting this definition for this rating? Do we have alignment on that? Great, let's move on. And then we've, we pulled in using a similar model, ~um, we, ~we started then talent reviews on an off cycle with that same- Yeah ... intention. ~So, uh, ~with or with the intention rather, not the same intention, but the intention rather, let's talk about the more qualitative.
So we're actually not gonna talk about ratings at all. ~Um, ~we might use those as like directionally, but we're gonna talk much more qualitatively about the growth and development. And- Sure ... that also then took-- it, it reverted the pressure from what we were trying to do, which was really do everything in this one meeting because this is our time, to, you know- Yes
we have time set aside to do these different things. And again, we're gonna use some prep work to help make sure they're as efficient as possible.
Speaker: That sounds great. ~I mean, it's, ~it's interesting, right? Because everything is so connected that for the human brain not to want to make those jumps and fill up that entire [00:10:00] twenty hours, it's actually really hard.
So to bring that down from twenty to six hours ~is, ~is pretty amazing. And were you seeing, before you made the shift, any kind of, ~uh,~ reactions or implications for the folks that were receiving the ratings after spending those twenty hours? 'Cause it sounds like people were coming out and there still wasn't much clarity.
So I'm guessing maybe the folks that were getting the ratings were also unclear about, why am I being rated that way? Was that the case ~or, ~or not really?
Speaker 2: Yes. ~I think, ~I think in some ways that's, that is ~the, ~the perpetual challenge of being in, ~uh,~ a manager and/or- Yes ... a HR leader, is that you're trying to bring clarity, and you only have so many, like so much control over the dials that get you there.
~Um, ~and I will say ~the, ~the more focused that we've gotten, ~uh,~ we've cut out the noise that managers need to sort through to then be able to articulate that. I'll say to your point of everything's interconnected, it can't just be that either, and that's one of the things- ~Mm-hmm ~... that I think we're continually investing in, which is how do we [00:11:00] then equip leaders to be able to have those conversations?
Because calibration is one input, where you got the data right is another input. ~Like ~there's a host of these inputs that, ~um,~ we have to get right. We have to enable managers on hard conversations as an example, or development positive conversations. Like all of that comes together. So I'd say it, it helps, but on its own it was never gonna solve the thing.
It was, I'd say, a- an important input in a stream of inputs to get us there.
Speaker: Yeah. And so it sounds like it didn't happen overnight. It sounds like it happened over a series of weeks, months. How long did this transformation take?
Speaker 2: I'll say so when I-- It was really, I'd say two cycles is really how we got there.
So the first- ~Mm ... I, ~I have made, it's ~kind of ~just worked out, I wanna say three companies now where I've joined right before a review cycle, and it ends up also being an engagement cycle happening at the same time. And so- Yeah ... what that has meant is that I'm facilitating calibration [00:12:00] meetings in my first or second week.
~Um- ~Yes ... and so I think that was the same here. This was maybe my fourth week was the first one, so I had a little bit of context, ~uh,~ but not a ton. ~Um, ~and so yeah, the first time it was very much a, okay, let's take this thing that we had historically done, and there had been a little bit of pre-work, but it was very conversational, and okay, how do we just get it down into something that's gonna be palatable?
And then there's somebody on my team, then ~it was, ~it was then the next cycle, somebody on my team came in and was like, ~"Well,~ hold on. We did this in a spreadsheet. What if we did it in a deck that's much more conducive to actually reading?" ~Um, ~rather than, ~you know, ~I don't know if you've been in a spreadsheet where- Yes
everyone is trying to filter and somebody doesn't do their own filter, and all of a sudden you can't find your... Yeah. ~So, uh, ~and so that, ~you know, ~there's been a healthy evolution that's both actually saved the prep because there's also been- Yeah ... part on our part, ~um,~ to then the actually the presentation, which has been through a deck.
I'll [00:13:00] say, ~you know, ~on that, AI has helped dramatically with all of that, ~uh,~ because- I bet ... now the work that has been, let's say, like manual pulling into different sheets, ~uh,~ are things that You know, we've been able to experiment with, so I won't say we've nailed, but we are finding plenty of applications where AI can help, and I'm excited to see how that continues to go too.
That's awesome.
Speaker: ~I, ~I'd love to dive a bit more into the AI piece, ~uh, in a little, ~in a little bit. Yeah. ~Um, ~but before we do that, I'm curious to hear-- It was great to hear that, ~uh,~ it was actually someone on your team who said, "Hey, we can improve this. We don't have to be on these sheets anymore. Maybe just a ~simple, ~simple thing of tweaking the presentation, ~um,~ is gonna make things more effective."
Did you find that in this process ~of, ~of doing it the old way to the newer way, going from 20 hours to six hours, was there also a internal team mindset shift that you had to make? Or was it also primarily ~on the, ~on the receivers, on the manager side that it was like, "Hey, let's do things differently"?
Speaker 2: Yeah.
I would say I have-- [00:14:00] In overall at Wrapbook, I had the benefit of the first hire that I made was a business partner, and then was able to add another to that role and team. And therefore, in doing, didn't have, ~uh, you know, ~we got to set the direction for how we do it out of the gate. And so- Yes ... and how we do it, meaning we do it one way and it will need to evolve with w- At the end goal, ~you know, ~me as somebody who grew up as a business partner, like that's the world that I ~kind of ~was raised ~in, ~in a lot of ways, ~um,~ taking very much a business first mindset and what's the thing that's gonna deliver the most value for the business?
Yeah. Let's understand where they are, and that has in a lot of ways been how I've hired since I've been here. ~And, ~and so fortunately, internally, great. ~Like ~what's gonna, what's gonna get the best end result? It, there wasn't a ton of convincing within our team that we needed to change how we do it, because we didn't like sitting in 20 hours of meetings any more than the business did.
~Um- ~Yeah. ~Uh, ~so th-that part fortunately [00:15:00] was,
Speaker: ~uh- ~Nice ...
Speaker 2: ~uh, ~not a barrier to overcome.
Speaker: ~And, ~and I imagine ~the, ~the folks who were involved in this, the managers, they must have been super open to this, 'cause the fact that you're not asking them to sit in 20 hours of meetings anymore, that must have been godsend for them.
I imagine there was no resistance there too, right?
Speaker 2: I have not met a manager who when you say you have less time in a meeting- ... ~uh, ~particularly if HR are involved, that they're not gonna be excited. ~Um- ~Good. So I, ~a-I mean, ~they're-- I say that and, so very much ~so. ~And, ~um,~ the thing that drove the time investment before still was this really deep desire to, ~um,~ make sure we were being fair.
And so- Yeah ... ~um, ~which is a value that I personally really hold, ~uh,~ tight. And so Ensuring that we were, ~uh,~ not only focused on efficiency, but also talking about ~like, ~"Hey, here's how I actually think we'll get better results," ~uh- Right ~... people, ~uh,~ so that you'll be better equipped, ~um,~ that I'd say helped a lot with the change management part of it, ~uh,~ because everyone cares about efficiency, and I think we [00:16:00] all show up ~to work, ~to work with people because we also care about the people.
And so how do we also tap into that, I think ~was, ~was important- Yeah ... and then same in many ways continues to be.
Speaker: Yeah. ~And I, ~and I think, ~um,~ that's a nice segue into what you were saying about AI, because actually there's been so much narrative around we're gonna use AI to be more efficient, and ~there's a, ~there's a lot of that, move faster, do more.
But actually, there's also an argument to be had of we can use AI to not just go faster, but be better and deliver more effective, higher quality, ~um,~ deliverables, as well as allowing us to focus more on the human side of things and the relationship side of things. So I'm kinda curious to hear your thoughts.
H- have you also ~kind of ~experienced that in the way that you're starting to inject AI into areas, and how have you helped people both within your team and within the business to adopt AI?
Speaker 2: Yeah. So I say ~on the, ~on the first one, I... Fundamental believer in the power of AI and how you can [00:17:00] take work that is painful today, not dissimilar to calibration, and- Yeah
~uh, ~just make it better and easier. And I think that, ~uh,~ AI as a technology and all its applications have seen ways that it does that. ~Um, and, ~and I think the for what is really important. It often gets lost. ~You know, ~I think, ~uh,~ efficiency absolutely matters. I think that we all would love to work efficient- more efficiently because- Yeah
either that means we don't have to work as hard and we can spend more time doing things that matter to us, if that's ~sort of ~the orientation of your life. Or within the context of work, we can not have to do the things that are as hard and do the things that really give us energy or have higher impact.
And ~so, um, ~I would say I fundamentally believe, particularly in the context of people, that AI is best positioned to help us then, ~uh,~ invest more in human connection and make those human connections stronger because I both at a individual, corporate level, and then, ~you know, I, ~I won't go into ~like ~two philoso-philosophies in the world.
~Like, ~we all need more connection [00:18:00] in the world, and that we're better as humans when we do. And so- Yes ... ~uh, ~I-- my continual hope and expectation with AI is that it is enhancing human connection, not detracting from it. ~Um- ~Right ... that requires a lot of intentionality. But I'll say, ~like ~a great example, and this will ~kind of ~get to the second part, which is we recently-- So Ashby is the ATS that we use internally.
We moved to it, ~uh,~ about ~like ~a little, ~like ~two and a half years ago. ~Um, ~have been really pleased with it, and they have an embedded AI notetaker in the system. And this is, I think, ~a,~ a simple but great example of where AI can help enhance human connection. So-
Speaker 3: ~Mm ~...
Speaker 2: I now have a notetaker that is on my call, on my interview, which by nature of not needing to focus on capturing every word that someone said or key points- Yeah
that someone said, I can actually just have a really good conversation and create a connection with this candidate, which I think increasingly is [00:19:00] important in a world where, ~uh,~ really good people, ~uh,~ are harder to find, and you have to have that, what's that "something else" to get them. Yes. And I really believe that within the context of recruiting, ~like ~the connection that you create, ~uh,~ is a really important ingredient to that.
And so great example of here's this technology that by nature of automating that thing, like taking notes in a meeting- Yeah ... that you can refer back to. ~Um, ~now I can actually just have a conversation with you. ~Um, ~and so that's in many ways the framing of our team. I'll say like overall- On AI, ~we're,~ we're on the journey.
I think everyone says they feel behind. We're in the same boat, ~uh,~ which is- ~Mm-hmm ~... we feel behind, and also are making really intentional investments, both at an individual, ~like, you know,~ we've given pretty free access to the range of tools, whether that be ChatGPT or Claude. ~Um, ~and at-- ~you know, ~encourage people with whether that be trainings or just ~sort of ~like consistent messaging on think about ways that you can use these tools, whether it's to streamline comms, help with [00:20:00] data analysis.
That's been one. Two, ~you know, ~the natural evolutio-evolution has then been on workflows and where can we look at automating workflows. Some of that is through, ~you know, ~building something of your own via Claude. In other ways, it's bringing in other tools or point solutions that can help you, ~uh,~ automate, like offboarding/onboarding is a great one within the people world.
~Um, ~and then the last part is then just looking at some of our foundational systems and making sure that they are, ~uh,~ gonna enable us to, ~uh,~ both automate those workflows, but also create an experience ~on the, ~on the employee-facing side that is consistent with the messaging that we have overall as a company, which is that we wanna, ~um,~ again, ~like ~automate away the things that are really painful and hard and make really- Yeah
great experiences that are connective, ~uh,~ on the things that really matter.
Speaker: There's a lot there, and I wanna talk to you for way more than the time that we have about that. ~Um, ~but just to ~kind of ~summarize, and maybe we can dig into some of those things you mentioned. ~I mean, ~clearly, there's a thread of good employee experience and connection across everything that [00:21:00] you're doing, which is amazing to hear.
And I wanna talk to you ~a, ~a little bit about, ~um,~ connection in recruitment and the candidate experience in a little while in the age of AI, and that's one piece. The second thing, it sounded like, ~uh,~ the idea that everybody should be using AI and you're allowing people to experiment and have, ~uh,~ access to all these different great tools, ~um,~ I'd love to then dig into who is leading the charge, if it is anybody, or does it sit with HR?
Does it sit with IT? Is it more democratized? ~Um, ~that's one area. ~Uh, ~and then the other great thing you said there was, ~um,~ that you're starting from like ~the, ~the workflow itself. So you're not starting from, "Hey, we need a tool," or, "We don't need a tool." And then it sounds like for you guys, it's not like a build or buy, but it's more like what's gonna be ~the, ~the fastest and the most elegant and efficient way to solve the problem.
Sometimes it's gonna be build with Claude, sometimes it's gonna be buy. Yeah. So those are the three areas. Let's see how far we can get , and then I do wanna come back to calibration and how you're using AI in calibration. So one question on the, ~um,~ the [00:22:00] candidate experience. Have you so far come across-- I've been hearing these stories about, ~um- ~These AI avatars turning up and you gotta hold up-- you gotta ask them to hold up fingers in front of their face to, to let you know that they're real or that they're the person that they are.
I'm hoping you haven't experienced this ~or, ~or are you also facing this in your hiring process?
Speaker 2: We-- I would say it has been sparse but true, which is we have had, I wanna say a handful of the- Oh, you have? ... ~the, ~the name on the Zoom doesn't match the name of the resume- Okay ... or, ~uh,~ the face doesn't match what was on LinkedIn or whatnot.
So it is, it has happened, I think fortunately, and I'm happy for my TA team that it's not been ~their, ~their consistent experience. I did see the three-finger video actually the other day, 'cause it's gotten better. Like ~the, ~the video's- ... been getting better and better. ~Um- ~Yeah ... but it's, it has not been common, though it has existed.
Speaker: Okay, gotcha. So ~you're, ~you're not seeing a world where AI from the recruitment side and AI from the candidate [00:23:00] side, it's just one AI talking to another. ~I, ~I don't see that happening. Do you see that happening or is that a-
Speaker 2: I, ~you know, I, ~I see-- I know a number of companies are experimenting with that intake being one where- ~Right~
~um, ~it is AI. I'll say we-- ~I mean, ~we've, we have experimented with videos ~like, you know, the, ~the first submission- ~Mm-hmm ~... or, ~uh, like the, ~the initial submission, just the resume or, ~you know, ~for the small set of people that we select for a screen, have them submit a video. ~Um, ~and I think with the increased technology, that may be something that is AI, but I-- The, a world where AI is speaking to AI in an interview, ~I,~ I think we've lost the plot a little bit there.
~Um- ~Totally. I couldn't agree more ... there's a world where, yes, let's make sure that things are more efficient, and I think there's st- there's plenty- Yeah ... of opportunity within the recruiting process to do that. ~Uh, ~and you can do that before you talk to a person, in my mind. ~Like, ~that is where you can actually- Right
invest quite a bit. And then you can be more thoughtful on talking to the right people. ~Um, ~but- Yes ... the number of times where I find so [00:24:00] much value and, ~you know, I, ~I end up taking ~like ~one role a month, ~uh,~ one role a quarter or so where, that I recruit for. ~Um, ~some of it is for load balancing. Also just a great way for me to stay connected to- Yes
that part of work. And every single time, though, I find value in those conversations—those first conversations- Yeah ... even if it's 20, because you round out your rec, ~like ~make sure you're hiring the right person. ~Like, ~I think there's a ton of value in that, and so I think it is a place- Yeah ... where if we can make it a more efficient, great, but not at the- Totally
not at the detriment of human to human.
Speaker: Yes, agreed. ~I mean, ~I have been on calls waiting for other folks to join, and everybody's note-takers have joined, so it's been like me and ~like ~three note-takers until people join. ~Um, ~but yes, I don't think ~we're, ~we're also heading to a world, if anything, it's gonna, it's gonna make people actually do more manual, authentic conversations.
~Um- ~I hope ... and that's gonna be the differentiator, right? And so given that we are talking more about the human side of things, and given where AI is now, ~it's, it's,~ it's a workforce conversation. It's not a tooling conversation. And therefore, [00:25:00] for you guys, remind me what is your headcount, and then for that type of organization, who is leading the charge to encourage the use of AI within the business?
Speaker 2: Yep. So we're about 400 people- ~Mm-hmm ... uh, ~today. We-- The answer to that is in, ~uh,~ I'd say in some ways would be what I would answer in any organization, which is, ~uh,~ we've taken a very democratic like approach. It's been fairly well spread, ~um,~ but it's been our leaders, ~you know, ~our- Yeah ... CEO has very much been ~sort of ~the ~like ~the voice of, in helpfully pushing everyone on this is important and, ~uh,~ we likely need to move faster than we think.
~Um, ~and though the what it means is so different depending on your org that I find that if it's only one person or one group that is driving it, that the lack of contextualization can make the people that may be the late [00:26:00] adopters just dismiss altogether. And in some ways that's happening anyway. But, ~uh, you know,~ in, in an ideal world, we're getting as many people on the bus with all the context that they have that we want to be here and we're driving it forward.
And I think that the people who have the most context who are then helping them not just adopt AI, but rather- ~Mm ~... adopt this new technology in a really intentional way that's gonna drive things forward, ~um,~ is really important. So for engineering, that means something different than operations, than finance- Yeah
and what. I will say I-- the and there is, as we continue to scale, how do we make sure that we are centralizing the right things like governance and there needs to be some consistent tooling as people are building their own micro app or whatnot, ~like ~where do we host it? ~Like, ~that's all ~we're, ~we're in the midst of, and I think having- Yeah
someone, ~uh,~ who is leading and driving that, which, ~um,~ for us ends up being ~sort of ~more on like the engineering IT part is- Yes ... really important. But I-- for any sort of big [00:27:00] change, I'm a big believer in the power of, ~um,~ leaders in their context being the champions, ~uh,~ 'cause I think you get adoption a lot faster than if it was centrally owned otherwise.
Speaker: Totally. ~And, and before we hit record, I think we were talking about how in some companies HR ends up being the, the function of the department that, uh, does lead the transformation itself. Yeah. Um, how do you, how do you see the, the function's role,~ or if I was to ask more, a more lofty question, responsibility in this transition, ~uh,~ as people think about AI?
Speaker 2: Yeah. I-- So I do think that like HR plays a massive role in any sort of change within an organization, this being- ~Mm ~... probably the biggest in many of our lifetimes from a technology standpoint. ~Um, ~and so I see our role as a few-fold. One, in making sure that the why is really clear. I think it's really easy to get, ~uh,~ to get excited on the what and what we can deliver, and as humans, we care about why.
~Um, ~and I think HR is specifically positioned to help, ~uh,~ flesh out and articulate the why and why it matters to people, and how do we appropriately both bring them along and also ~like ~draw a stake and make sure that, ~uh,~ when decision is a [00:28:00] decision that it's clear. ~Um, ~and, ~you know, ~stacking is.
I think en-- we can play a helpful role in that sort of a generalized enablement on what it can mean. ~Um, ~and then third, in particular, which is where I'd say we're, ~uh,~ have ~like ~a fair amount of energy now is just around mentoring and the people. ~So, you know, as, ~as you're getting to a place where we have-- we've made a decision on direction, we're making our investments, then ~getting, ~getting the right people, getting the best people who are, ~uh- ~Yeah
gonna help you on that journey and, ~you know, ~shift from being a follower to a leader, I think is where we can play a really important role in evolving ~how we, ~how we evaluate that
Speaker: too. Amazing. So let's bring us back to your story. Now, in the age of AI, ~um,~ you brought it down from twenty hours to six hours.
What's the next number of hour reduction that you're looking at? And is that even possible? Are you using AI in order to get to that- Yep ... ~uh, ~now? I
Speaker 2: don't-- The short answer is, I don't know. I don't know if we necessarily need less time. ~Mm-hmm. ~It's gonna be continuing to make [00:29:00] sure ~that, ~that we're using them the best ways possible.
~Um, ~I'll say how we-- I don't have an answer for how AI yet, and where we will- ~Mm-hmm ~... experiment is we have all of this data, we have increasing number of data as more one-on-ones are being recorded and all of that. ~Right. ~And so how do we then take all of these inputs, make them consumable, palatable, understandable to then ensure we're driving the right conversation?
So I could see a world where before it's essentially a readout of, "Here's where they're great, here's where they can grow, here's the rating, and here's why." Using AI to help generate a, like what's the question that we should be asking based on the rubric, based on what everyone else- Nice ... has rated for that, as an example.
And ~so, um, ~I- taking it from a mostly, "Here's some information," in a conversation, but making sure, like, how might we use AI to have-- make sure we're having the right conversation and that the quality of those conversations are even better. So that's ~sort of... ~That's at least directionally where I think it will be really helpful.
~Um, ~but with anything, we'll experiment. ~We'll, ~we'll try something. I like that. Cycle, get a bunch of [00:30:00] feedback, and then iterate from there.
Speaker: That's the way to go. William, thanks so much. Before we wrap up, any final thoughts you wanna leave, ~uh,~ listeners with who might be in the middle of a process optimization, ~um,~ with AI in the mix?
~Yeah. None. None. ~
Speaker 2: ~Um. I was about to say, "Do you wanna say anything?" ~
Speaker 3: ~No. ~
Speaker 2: ~Um, my children will say, "You asked me a question, and..." Yeah. Uh, I, ~I would say you will always feel behind or like you could do more, and rather than that be something that holds you back, I think understanding that we're all in the same place, which is- Yeah
we all can do more, and you're not alone, and leaning into that, being open. ~You know, ~I'd say, ~like,~ vulnerability is a gift that actually then brings other people out of the woodwork to then learn with you. ~Yeah, ~yeah. ~Um, ~and so I think just accepting that you're behind, that's okay, which then opens you up more to learning, has been the biggest, ~uh,~ I'd say gift for myself in the last six months, and it takes me from a place of feeling stressed or ashamed or whatnot to like, "Great.
We all gotta learn. Let's go."
Speaker: Love it. I feel like, ~um,~ on the topic of opening up, after listening to this, some folks might [00:31:00] wanna reach out to you. Is LinkedIn the right place to give you a quick DM on, "Hey, how are you doing this piece?" Or what would you recommend?
Speaker 2: LinkedIn is great.
Speaker: Yeah. Love to talk to you.
Amazing. Great. Thank you so much for joining us, William, on the WorkOps podcast, and to everyone listening, see you on the next one.