Welcome back to VOICES w/ Amy Butchko SAIC's Director of Talent Acquisition Solutions. This is the final episode of this 5 part binge-able series. We pick up the conversation around a debate in HR about augmentation vs. robots enjoy.
- Augmentation over Robots
- Building Recruitment Teams
- Wage inequity solutions
- Moving Fast and Breaking Shit!
TRANSCRIPTION SPONSORED BY: Disability Solutions partners with our clients to build best-in-class inclusion programs and reach qualified, talented individuals with disabilities of every skill, education, and experience level.
BINGE all 5 episodes with Amy
Where I just kind of imploded and just quit being effective at my job, because I was just like my attitude tanked. And I mean, just all the things that can happen when someone is burnt out, you know, you say the wrong thing in the wrong room.
Voices INTRO (18s):
Voices. We hear them every day. Some voices like mine are smooth and comforting, while on the other hand, the Chad and Cheese podcast is like listening to a Nickelback album, you'd rather stab yourself in the ears with an ice pick. Anyway, y'all now listening to Voices a podcast series from Chad and Cheese that features the most important and influential voices within the recruitment industry. Try not to fuck it up, boys.
It's Chad again, welcome back to voices with Amy Butchko SAIC's, Director of Talent Acquisition Solutions. This is the final episode of this five-part bingeable series. We pick up the conversation around a debate in HR about augmentation versus robots. Enjoy.
Joel (1m 12s):
Your opinion on the robots is obviously pretty clear from this interview. Curious about your thoughts on if you're bearish on automation, where are you on augmentation? In other words, creating tools that help enhance a human being's ability to do something quicker, faster, more, you know, more, I dunno, deeper where they're going. Like I always think of a lot of the sourcing tools, the Seek Outs and the Hired tools, their success has been built on augmentation. So instead of you having to go out and search Google or whatever search engines, like they bring all the candidates into one place. So where are you on augmentation in the future of that?
Amy (1m 49s):
Bullish on augmentation, because it works. I mean, it works! So, let's break that down into like, what does that actually mean in the job? So back in the day, if you were a sourcer, which I was, you know, you had to know how to write a Boolean code string into your, you know, into whatever, you know, the kajillion browsers that you can, you know, use to go find your specialized people to do the stuff that you gotta do. And, you know, because Google does one thing and the other, you know, and they all do different things to keep you in their walled garden and keep search and their algorithm working their way.
Amy (2m 29s):
Right? So you had to know how all those different things worked and how to code your search. Just so, the software does that for you now. And it has completely transformed how efficient sourcing can be. You know, another example of where augmentation is effective is text messaging. So used to be, if you wanted to send text message, I'd pick up my phone, open my app, put your number, in type you a note, and wait for you to respond. Now I can do that at scale, I can send kajillions of text messages, to kajillions of people who have opted in to my system.
Joel (3m 13s):
That doesn't sound spammy at all.
Amy (3m 15s):
Well we don't actually do it because the kinds of candidates that we work with.
Joel (3m 17s):
I know I'm giving you shit. But when you say a kajillion that's a lot, but I guess,
Amy (3m 21s):
But it's augmentation, but I could do it.
Joel (3m 24s):
Amy (3m 24s):
And you know, and what we were talking about before with the chatbot thing I'm telling you, you can't do it. I'm gonna tell you what, like, that's probably not gonna work. This you could do it.
Joel (3m 35s):
So yay on terminate or no on Terminator. Yay. On Robocop. That's no Schwartzenegger, we're going Robocop.
Amy (3m 41s):
Robocop is the answer.
Joel (3m 43s):
I like it. We like to funnel everything to the eighties Amy, when we understand stuff.
Amy (3m 47s):
I don't understand anything before or after.
sfx (3m 50s):
Joel (3m 51s):
Oh shit, she just earned a second applause. Way to go Amy.
Chad (3m 57s):
Joel (3m 58s):
Any pro '80s commentary gets an applause.
Chad (3m 60s):
So yeah. Now we've got to get into you know, the, shall we play a game kind of scenario. So the algorithms are generally trained off of humans, which are biased. Right? But yet we expect the algorithms not to be biased. Well, how have you seen just the conversation go around matching biased in the different algorithms that are out there for organizations like yours to find better quality candidates and not be a bunch of old white dudes.
Amy (4m 37s):
We don't use a lot of that.
Chad (4m 39s):
Okay. Is that because of the perspective, bias or what?
Amy (4m 43s):
Yeah. The potential for, you know, so I work in an environment that is very focused on like information security. And so one of the components of information security is identity. So anything that potentially breaches the identity of the individual is going to be questioned in our world. The search that we do is pretty careful, and we have a lot, we have humans doing it. So do we use the tools? Yes. Do we rely on those tools to handle every component of that search? No we do not.
Chad (5m 22s):
Right. So augmentation. Back to augmentation then?
Amy (5m 25s):
Yes, definitely back to augmentation.
Joel (5m 28s):
We briefly talked about scaling, scaling a company in terms of talent acquisition in a post pandemic world. Obviously there are new challenges in that. Have you, have you given much thought to that and how people should sort of rethink building an organization quickly in a post pandemic world, is, do things change much or do they change a lot or somewhere in the middle?
Amy (5m 51s):
Yeah, that's a good question. And I haven't thought about it specific to post pandemic, probably because I think talent acquisition to me, but to me, talent acquisition has always felt like a place where people come and go and it's, you know, COVID was a time when not a lot of people came or went, if you were, if you had a job, you could keep your job. If you can, you know, if your company downsized your recruiting department, then you know, I know that that was a gosh, the spring of 2020 was rough for a lot of people. And for us, we were able to retain and keep chugging along.
Amy (6m 35s):
Government contracting was pretty stable. So post pandemic, we have started to see an uptick in turnover, just like everyone else. And you know, some of that may have been, as I discussed, pent up, you know, might've left last year was thinking about making a change, blah, blah, blah. And some of it is because, you know, compensation is, you know, some of the offers are really good. I have been hearing things, you know, from some of my peers out there that are making me wonder, shouldn't my phone be ringing? I'm like, wait a minute. Cause there's some pretty nice and pretty sweet deals.
Amy (7m 16s):
But I think that for me, in terms of building a team and growing a team, we started this team three years ago and started kind of scaling it up around 2018. And now the team is much larger than it was, but that it feels to me right now, more like that building phase when we were starting from scratch. And it was like, wow, you know, I'm going to be interviewing all the time. I've gotta be always, you know, making sure that I'm taking care of my people that are here and, you know, and we do have a good emphasis here on what is our quality of work-life balance?
Amy (7m 58s):
What is the, you know, is it, how are we treating each other? How, what is the burnout level? How are we taking care of ourselves? And, you know, bringing that wellbeing work. So I think, you know, I think that that last part is new post COVID where that mindfulness of being human, that we're human, that part is kind of new, but the rest of it, you know, the, the growth and building something is familiar to me.
Chad (8m 27s):
When it comes to wage in