September 24, 2024 • 46 mins
Join host James Mackey and Daniel Chait, CEO of Greenhouse as they discuss skill-based hiring, emphasizing the shift from traditional qualifications to assessing candidates based on their capabilities. They highlight the benefits of this approach, such as broader talent pools and internal career development. They also explore the consolidation of recruiting tech, noting the trend towards all-in-one solutions and strategic partnerships. AI's role in talent acquisition is debated, with a focus on its potential to enhance job descriptions and interview processes, while acknowledging regulatory and bias risks.
0:00 Skill-based hiring
9:39 The evolution of job skills
15:13 Evolving buyer needs in recruiting tech
21:30 Strategic partnerships in recruiting tech
28:54 LinkedIn integration and AI in recruiting
34:11 AI filtering in recruiting tech
37:21 The Future of recruiting technology
44:29 Machine Learning for evaluation in recruiting
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Our host James Mackey
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
Hello, welcome to the Breakthrough Hiring Show.
I'm your host, james Mackey.
We are joined with Daniel Chetoday.
Daniel, welcome back.
Thanks great to be here.
Looking forward to it yeah, metoo.
So we have a few topics fortoday.
We're gonna discuss skill-basedhiring, recruiting, budgets and
consolidation in the talentacquisition tech space, and then
we're gonna get into AI usecases for talent acquisition.
We're gonna talk about the mostsought after use cases.
(00:23):
We're going to talk about theuse cases that may be more or
less so technically feasible,risks associated with different
use cases, and also maybe justbrainstorm a little bit on what
AI's use cases are essentiallyjust going to become table
stakes.
But then also, what does thefuture look like?
What types of issues are peoplegoing to try to tackle over the
(00:45):
next couple of years?
Speaker 2 (00:46):
Awesome.
It's going to be a lot of fun.
Looking forward to it.
Speaker 1 (00:48):
Yeah, yeah, me too.
So I guess let's just startwith skill-based hiring.
You mentioned that this issomething that's top of mind for
a lot of people right now.
Could you provide maybe we'lljust start with a definition of
skill-based hiring and then wecould just riff back and forth
on that for a little bit.
Speaker 2 (01:04):
Yeah, great question, because it's one of those
jargon words that people throwaround and what do you really
mean by it?
And are we doing it, or is itthe future or whatever?
The way I think about it isvery simple.
It's hiring people based onyour assessment of their
capabilities, as opposed tobased on a set of qualifications
or on, maybe, like a degree ora college that they've gone to
(01:27):
or a place that they've worked,which is the traditional look at
their resume.
And we want to hire people fromquote good companies or from
quote good universities, and Ithink people have started to
wake up to the idea that noteveryone who worked at Facebook
is the same.
Not everyone who is awesome atthe skills you need for the job
(01:49):
went to an Ivy League university, and so if you're going to hire
the best people for yourcompany, you need to think about
how do you assess what thoseskills really are, and then how
do you separate that out fromwhat's on their background,
which may or may not reflectthat perfectly at all.
Speaker 1 (02:05):
Yeah, and so when you talk about how to assess the
skills that they have right, thetransferable skills, is there a
specific method that yourecommend to customers in terms
of a cover?
Is it as simple as just likejotting down a list of different
things that they're doing intheir current role and then
(02:25):
trying to find match, differentparallels, stuff like that, I
mean yeah, look at a high level.
Speaker 2 (02:30):
It's about assessment and it's about identifying,
like you say, here are theskills that we need in this role
and here are the differentassessments we're going to run
to identify who has those skillsand to rate them on those
skills.
Obviously, depending on what theskill is, you're going to use a
different technique If you'relooking for a programmer versus
if you're looking for anaccountant versus if you're
(02:50):
looking for a delivery driver,you're going to do a different
assessment, obviously, but themethodology, the approach, is
the same, which is like what arethose key skills that you need
and then match up the rightassessment to it all.
I think the great opportunitiesthat you have are number one,
you can attract a much broaderand more diverse group of talent
for the same roles, becauseyou're not fishing in the same
(03:10):
pond as everyone else.
Number two is, you can find newcareer paths for people within
your organization, as opposed tohaving to take on the cost
expense and risk of goingoutside, because you might have
people in your, for example, atGreenhouse, in our SDR
department, our kind ofentry-level sales roles that
have gone on to roles inprogramming and software
development and QA and customerservice, and other areas,
(03:35):
because you don't just look atwhat job title they've had, but
you can look at what the skillsare that they bring to the table
, and so I think it gives you anumber of advantages.
But it takes some doing and ittakes some.
It takes really, first andforemost, an intentionality and
a commitment on the part of theorganization that you're going
to look past the headlines onthe resume and you're going to
get over your hangups aboutcertain companies and certain
(03:57):
schools and you're going to geton with finding the right people
for the job.
Speaker 1 (04:02):
Yeah, and I think also probably some of the some
of it comes down to trying toanalyze which roles it makes
more sense to do this with.
Of course, there's going to besome roles in which that
transferable skill, if they'redoing something else necessarily
isn't going to be as relevantor doable.
It's like certain finance roles, for instance, or just
(04:23):
different, more maybe technicalsenior positions that require
the subject matter expertise.
But I think that's alsosomewhat intuitive, right, Like
when you're looking at the typesof roles in the organization
that this would work for, maybemore so like individual
contributor roles or no, I don'tmean that it's only individual
contributors.
Speaker 2 (04:40):
I just hired a CFO, for example, who, while he has
many years of CFO experience, healso worked in the past as a
strategy consultant, and so thatgives him certain skills that
he's exercised in the past thatare very relevant to this job.
Obviously, there's other skillslike that you really can't
learn on the fly, that you haveto already bring to the table if
you're going to have that job,going to have that job, and so
(05:05):
there obviously are certainbackground markers that one
needs, or qualifications thatone needs for certain jobs.
To your point, if you're goingto be a CFO at a company at our
scale, for example, you have tohave a track record of being a
successful CFO at scale.
You have to have worked incertain software industry and
things like that.
But other parts of many jobs,including that one, are very
much a transferable skill thatyou can pick up in other areas.
And so I think when you'relooking at most roles that
(05:27):
you're hiring for, you probablyhave the opportunity to identify
some or all of the skills thatyou need and find people who
bring those skills inside andoutside your organization, as
opposed to just looking at thekind of background markers that
they have.
And I think the pandemic era wasreally a big change in mindset
for a lot of people because allof a sudden kind of remote work
(05:50):
was everywhere and the officedissipated into work from home
and so everybody's just adifferent zoom box on your
screen and it opened people'seyes up to the fact that hang on
a sec, if I don't even have tobe in the same room as you to
get work done like maybe mybeliefs about where you used to
work are also don't even have tobe in the same room as you to
get work done, maybe my beliefsabout where you used to work
also don't necessarily hold up.
And I think it opened up a lotof people's Because you get the
great resignation you had, tonsof people moving and changing
(06:11):
jobs and rethinking lots ofthings, and so I think that
created the conditions underwhich we're now seeing
skills-based hiring take on amore central role in how
companies hire.
Speaker 1 (06:20):
Yeah, I think so and I think to some extent to people
that are in talent acquisitionhave always tried to broaden the
qualification requirementsright, maybe bias too far in the
other direction to some extent,but so it's.
I feel like it's.
If you come from a recruitingbackground, it's.
This is a little bit moreintuitive of a concept.
(06:41):
So the reality is there was, ofcourse, a middle ground and
just in the early days ofstarting Secure Vision, we
working on a lot of salesopenings and the qualification.
It was closer to 10 years ago.
There was still a big push forcollege degrees and that was
something that was, andsometimes like specific types of
degrees and from certain typesof schools, and it was just, it
(07:04):
was a little interesting andeven if somebody had a great
quota, accomplishments orreferences, it was there was
like these hard requirements.
Another one that I thought wasa little bit overkill was the.
It was there was a huge demandto have people that come
servicing the same industry, soa salesperson that was selling a
SaaS product to a specific typeof, maybe a company that has
(07:29):
customers in real estate or justvery nuanced things, and some
cases I think that kind of stuffmight be relevant If it's a
really technical cybersecurityproduct, I don't know, but
generally speaking it's like thetransferable skills of, but
(07:51):
generally speaking it's like thetransferable skills of okay,
has this person sold enterpriseSaaS products, like a similar
sales length deal cycle?
Speaker 2 (07:54):
Yeah, can you do discovery calls, can you take
good notes, can you do the righttype of follow-ups, and
probably, if you can sell a 300KACV SaaS product to, for
example, real estate, you couldprobably also sell that same
product or a similar product toa different industry.
Speaker 1 (08:09):
Yeah, I don't know.
I just think that a lot offolks over-index how difficult
selling to their customer baseis.
And sales is hard.
It's not necessarily because ofthe types of customers you're
selling to.
It can be, but I think weover-index, a lot of folks
over-index on that.
And the other thing that, likethe one hangout specifically to
stuff like that is they're likewell, it just takes so much time
(08:31):
for someone to learn what we'redoing in this.
You want people that areadaptable and, quite honestly,
you do need somebody that has,in some of these roles, maybe a
fair amount of raw intelligence.
The right person should be ableto figure it out.
Speaker 2 (08:49):
That's right and look , I think it's.
Also it reflects a reallyoutdated mindset about what's
available today to learn and howeasy that is.
Versus when I began my careerin the 90s, it was like, oh,
that person has a Rolodex.
To take your example one stepfurther, that person brings a
Rolodex in the real estateindustry.
That's really helpful Because,like you, didn't have any other
way to get those people.
So if you wanted to sell tothat industry and you had a
(09:10):
salesperson that knew the top100 accounts and had their phone
numbers, that was really anasset.
Today, needless to say, all thatinformation is out there.
I don't need that Rolodex,quote unquote.
I have the same 700 millionLinkedIn profiles access that
you do, and that's on the groundkind of knowledge of, like how
to get ahold of someone or howto learn about a particular
(09:32):
industry.
You had the World BookEncyclopedia.
It was like a shelf full of 20books.
That was all the knowledge youwere supposed to have and beyond
that, it was in people's heads.
Now there's so much availableinformation, there's classes
online, there's so much abilityto connect with other people,
and so I just think the wholenotion of learning on the job is
(09:53):
way different than it was halfa career ago and I think in
hiring we're just starting tocome to terms with what that
means and the fact of what atransferable skill is, I think
is a lot broader than it used tobe.
Speaker 1 (10:04):
For that reason, yeah , and I think honestly, I was
recommending skill-based hiringbefore I even really knew that
was the term for it.
I mean, that was typically whatI was going for.
I think that one way that I putit I did I would post about
this on LinkedIn and it seemedto get a lot of traction or
resonate with a lot of people isthere's I feel like there's,
(10:27):
and not only can you doskill-based hiring and that
makes sense, but in factsometimes you can get more
ambitious, hardworking people ifthey haven't done everything
you're hiring them for.
So I would say, like, hire forsome roles, it makes sense to
hire somebody who's done 70% ofthe job, and it's the 30% they
(10:48):
haven't done.
The 30% they haven't done iswhy they're going to accept your
offer.
It's that growth right that and,honestly, many of the best I
don't know if all, but many ofthe best employees that I've
hired at secure vision and I'vehelped my customers hire are
folks that that haven't done ahundred percent.
They've done 70 of it and 30 30that they haven't done and
(11:08):
that's just like a roughestimate.
I don't have like data per se,it's just my own experience,
what I've seen.
I try to get people to have afoundational understanding but
there's stuff that they haven'tdone and I it just never
concerned me too much.
There's different roles, likefor a cfo I I want them to have
done everything that I need tohave done.
Speaker 2 (11:25):
I don't want them you should know how to.
You should know how to likepresent to a board and, yeah,
financials to the company andstuff for sure, yeah.
Speaker 1 (11:32):
Yeah, that's like the strategic person that's
supposed to be, like way betterthan you at a specific, very
strategic function.
That's like very high risk ifit's done wrong.
And but for a lot of jobs, yeah, like sales roles, recruiting
roles, even a lot of programming.
Speaker 2 (11:46):
There's an empathy on programming.
Can you learn a new programminglanguage or a different
database or a differentarchitecture?
Absolutely.
Do you have the kind offundamentals and I think you'll
see that in a greenhousescorecard that a customer of
ours will put together.
Here's the kind of must-have,non-negotiables that they can't
learn on the job.
Here's the sort of nice-to-haveIt'd be great if they brought
it to the table.
And then here's some growthopportunities and it's a great
(12:09):
way to think about, as you say,what's the?
Not only how are we assessingthat person, but what open space
are we giving that person inthis job to grow and learn,
which is a big part of whypeople take jobs.
So I think and to your pointthat you made earlier, I
remember when I first heard thisjargon of skills based hiring,
I was thinking like, yeah, duh,obviously you hire people that
are good at the job you'rehiring for.
(12:30):
But it took me a minute to learnthat there's a whole other
philosophy that people havearound credential-based hiring,
and so you just look at thesemarkers on their resume of what
companies they've worked at,what schools they go to, what
degree do they have, and forsome of us, it's really obvious
that you should look at theskills, but there's a whole
group of people that are stillnot there yet.
Yeah, and I think too.
Speaker 1 (12:50):
There's a whole group of people that are still not
there yet.
Yeah, and I think too it's.
There's that nuance ofunderstanding when credentials
really matter and specialization, like when we're going to a
doctor, we want somebody who'sspecializing in that very small,
specific thing like your ankle,somebody who's like focusing on
one specific little thing, butthat's just there's.
There needs to be thisawareness that there's different
(13:11):
approaches and when to use oneor the other is the point.
Yeah, I think, just for us itprobably just comes very
intuitively, just as a result ofour life experiences in this
space, but it's certainly not,it will admit, a lot fewer
companies and leadership teamsthat are driving hard on some of
(13:35):
the things we were talkingabout in terms of the
credentials and whatnot.
Speaker 2 (13:38):
They're more so, yeah , what it means, though, and
then maybe we can.
Maybe this is maybe an offseton this topic, but I think the
last thing I would say is whatit means is, as an organization,
if you're going to make thisshift, you have to be good at
assessment.
You actually have to be able todevelop some conviction
internally that you've figuredout this person and you know
what their skills are, becauseyou're not going to just rely on
(14:00):
the credential, and that can behard.
It's.
The first question you ask iswhere we started this
conversation.
To bring a full circle.
So how do you know if I'm hiring, say, a programmer or a
salesperson, to take some ofthose examples?
How do I know that they havethe required skills?
And that can be a process wherethere's some change management
involved.
You got to roll this out toyour hiring managers and to your
(14:20):
interviewers and let them knowhere's the way we assess these
people.
Here's what a good answer.
Give them a rubric.
Here's what a good answer lookslike.
Here's an okay answer it lookslike, so that they can come away
from those meetings with someconfidence that they've actually
done a good job assessing thoseparticular skills.
And so the prize is high.
If you get that, then you havethose abilities that we talked
about.
But it can be some changemanagement and it can be some
(14:41):
work to get the organizationthere.
Speaker 1 (14:43):
Yeah, I think so.
For some of the programmingroles too, we've just had
companies simply do technicalevaluations on okay, we really
need somebody to know thislanguage.
But if they know this, thesecouple of things, then we know
they can pick up X, y and Z, andso the primary evaluation is on
the foundational stuff thatthey know is super important,
and then they know okay, if thecandidate aces these things,
(15:06):
then we might be able to asksome broader technical questions
about hey, so in this project,how would you think about
solving X, y and Z?
And you can understand somemore behavioral and technical
like acumen.
But that's usually just afairly straightforward way of
determination.
I think it's the hiringmanager's understanding of the
role makes a big differencethere too.
(15:27):
Okay, what's really the hardstuff to learn?
And assuming that theyunderstand more of a skill-based
hiring approach or they value askill-based approach, I should
say Yep, cool, yeah, I thinkthat's a good stopping point for
that topic, and then we canmove on to recruiting budgets
and consolidations episodes orwhatnot, and I have this has
(15:54):
been a common theme withrecruiting tech leaders that I'm
talking with in particular whenit comes to their product
roadmaps and how they'rethinking about the future.
They're looking at ways toessentially get stickier, offer
different products, thinkingmore of a product suite approach
to their solution.
I'm seeing a lot more peopletalk about acquisitions, looking
at different startups that canmake their product suite more
(16:16):
comprehensive or have a workflowthat goes from end to end for
the hiring process, and there'sjust a lot of thought and
consideration in terms of howcompanies are thinking about
positioning and offeringdifferent products, and then, of
course, that's influenceddirectly by how companies are
buying.
So this shift is happening.
Companies are looking forall-in-one solutions.
(16:39):
It's just interesting nowbecause it just seems like
that's almost like across theboard right now.
Speaker 2 (16:47):
Yeah, absolutely so.
Just to start with, on thisit's a great topic that you
raised.
Just to start with, we're nowin the third year of this kind
of elevated interest rate focuson profitability versus growth
across the board.
This is not about hiring orrecruiting tech.
Every company, especially everySaaS company, is feeling this.
Every B2B seller is in some wayor another grappling with their
(17:10):
buyers, having an elevated levelof scrutiny around every
purchase, looking to save money,looking to be more efficient,
and it's very much become thenorm in any kind of technical
sales environment, save for avery small number that seem to
be immune to the laws of gravity.
But for most of us out thereselling technology, whoever you
are, to businesses, you'refeeling this pinch, and you have
(17:31):
been now for going on threeyears, and so start with that.
Then you zoom into what'shappening in our little
neighborhood and, to your point,our buyers are often hiring
less recruiters themselves tohandle more candidates and, at
the same which we'll talk aboutthe more candidates thing when
we get to the AI stuff and, atthe same time, having less
(17:54):
resources available, having lesstools, having less automation,
wanting to simplify, wanting toconsolidate, wanting to buy
fewer things from fewer vendors,spend less money, have it all
be more efficient, and so thoseare great goals for teams to
have as a vendor.
It creates challenges andcreates opportunities, and so I
think it's an interesting momentof transformation within
(18:15):
recruiting tech right now.
Speaker 1 (18:17):
Yeah, definitely.
It's really interesting to seethe different strategies and I'm
wondering too it's like from abuyer position it's looking at
what are the primary use casesthat they're considering with
different product suites.
I think, yeah, again, I'mseeing this shift of there's
yeah, there's products atdifferent parts of the workflow
(18:38):
that are plugging in andintegrating with tools like
greenhouse, for instance.
I'm starting to see, okay, thecategory leaders of all those
different parts of the workfloware now just purchasing startups
that can provide, like, theadditional parts of the workflow
for this all in one, and so I'mjust curious is there anything
you could share in terms of whenyou're speaking with customers
(19:00):
or prospects or when your teamis?
Are there key pieces offunctionality that they're
looking for, maybe outside ofthe applicant tracking system or
the hiring operating system?
Rather that you do, what otheruse cases are they pressuring
you guys, or are they reallyasking you about right now?
Speaker 2 (19:20):
Yeah, I think you said it.
It's this idea that you havethis applicant tracking system,
and then you had all these otherpoint solutions that you were
going to do to be the best ateverything.
And now they're saying, okay,but the truth of the matter is I
have to have an applicanttracking system.
If I'm doing anything, I need aplace where the candidates can
come from my website, I can movethem through a process and
ultimately disposition them.
(19:40):
That's the must-have.
Now, how do I enhance thatfunctionality to get what I need
without sprawling around andtaking up all these budgets that
I don't have and complexifyingmy stack with a bunch of tools?
And so they're coming tovendors like us and saying what
do you got?
And so for us it's you justlook at the investments that
(20:01):
we've made and the products thatwe've launched.
It tells the story.
It's, first of all, somesourcing tools so you can do
more of your sourcing nativelyin in greenhouse, Whether that's
hey, I've got a candidate, Iwant to look up their email
address, and I don't have to buythird-party technology, I can
do that right in Greenhouse.
I want to send them a cadenceof emails and get them
outreached as a prospect andultimately recruit them into
(20:22):
being an applicant in a hiringprocess, Whether it's internal
mobility and posting internaljobs on a company job board,
whether it's more sophisticatedtools for scheduling and
logistics and like the candidateexperience side of it, where I
think just the basic calendaringbecomes difficult.
I think certainly reporting andanalytics is an area where we've
(20:45):
released tons and tons of newfeatures dashboards,
visualizations, scheduleautomatically, schedule, reports
that can go to hiring managers,like all the stuff.
So you don't have to havegreenhouse and a reporting tool
and visualization and businessintelligence software.
You can do it all right withinthe product.
Those are some of the main usecases.
(21:05):
But we're seeing evene-signature.
We just bundled an e-signaturetool with Adobe eSign texting.
We're now in market with theability to bring in a
third-party texting tool fromGrayscale and bring that in
under greenhouse as like onepurchase, one buyer, one throat
to choke, one order form, and sowe've really been the system of
(21:26):
consolidation of recruitingtools in those ways and at the
same time as I say it's aninteresting moment of
transformation because I thinkwhat you're seeing from the
recruiting lens is it'sconsolidating around the ATS and
so our customers are buyingmore and more of that stuff just
from us.
But when you zoom out, you'vegot like Oracle or Workday or
whomever, saying oh we're theall-in-one tool and you should
(21:48):
get it all from us.
And success factors Okay, We'vegot a recruiting tool and so
you don't even need thegreenhouse and all that stack,
you can just get it all from theworkday.
And so the everyone looks attheir own universe through that
lens and it's interesting to seewhere the lines are actually
going to end up being drawn.
Speaker 1 (22:02):
Yeah Well, I think also you've made a really
interesting point about thee-signature solution, where it's
you're just basicallyco-selling be the right term.
You're not like you didn'tacquire them or they didn't,
it's just vice versa, yeah.
Yeah, or the vice versa, rather.
But you guys, it's justessentially, if they purchase
(22:22):
through Adobe, they can purchaseyou at the same time, or vice
versa, essentially.
Speaker 2 (22:27):
Yeah, so basically Greenhouse comes with a bunch of
credits, signatures, so yousave money.
Basically what it is.
Our customers typically arehaving to go to market and buy a
third party call it, whetherit's Adobe or DocuSign or
HelloSign or all these othertools, and that can cost
thousands of dollars.
Speaker 1 (22:46):
Yeah.
Speaker 2 (22:46):
And instead now you get a number of e-signatures
with Greenhouse.
You don't have to buy anything,you don't have to have a third
party, anything, it's just there.
It doesn't cost any extra money.
And then if you go over and youend up signing like hundreds
and hundreds of more documents,you can pay per unit but you're
still saving a bunch of money.
So that's an example of it's asimpler purchase from the
customer standpoint, Securitypurchasing, IT are all satisfied
(23:09):
and it costs a lot of money.
Speaker 1 (23:11):
Yeah, that's also, in a way, that's really nice too
right, because you're not justeven if you do an acquisition,
then it's like everythingbecomes your problem in terms of
the product and makingeverything work.
So this is it allows people to,in a sense, stay in their own
lane but provide that, thatshared functionality.
So I'm wondering, like, ifwe're going to see even more of
(23:37):
that.
I think I've just I've seensome other companies.
They're just basically tryingto acquire, like crazy, to build
this entire end-to-end workflow.
So I am seeing a couplecompanies do that too.
Speaker 2 (23:43):
So it's, just it's interesting.
Speaker 1 (23:45):
How do you like, is there a way that you decide?
I'm just really curious aboutthis, honestly, yeah, you decide
whether you're going to acquirea product, a point product or
partner with a company likeadobe.
How do you?
Yeah, we call it.
Speaker 2 (24:02):
It's literally that it's like build by partner.
Okay, this is the solution wewant to be able to offer.
What's the path?
Build by partner and pros andcons to each.
To your point, some of it hasto do with is this a technology
that we can differentiate andbuild our own?
E-signature was pretty clearlyan area where it was like nope,
that's been done.
(24:22):
Yeah, that's fine, we're notgoing to build a better, more
reliable e-signatureinfrastructure than Adobe.
That's too big of an admission.
And so it's widely acceptedamong the customers and it's
very mature technology andthat's a great way for us to
bundle it and include it, andwe've done that with background
check tools.
We've done that with all kindsof stuff.
On the other end of thespectrum, when we did our
(24:43):
approach to sourcing, when wedid our approach to onboarding,
we decided to make acquisitionsbecause we identified companies
who we thought really solved theproblem nicely, really had
built good technology, was verycompatible with what we had.
That was essentially what wewould want to build, but already
built, and so it was just like,hey, we could build it
ourselves or we can make theacquisition and you're two years
(25:06):
ahead of the game, which is aspeed to market thing.
So often, if you're in thatquestion of buy versus build, it
comes down to is the rightcompany or product available on
the market when you want it in away that gets you to market
quicker and that the economicsmake sense?
The partnership is reallyinteresting because on
partnering we have a huge numberof partners we have 500, some
(25:29):
technology partners and ourcustomers use a ton of that
stuff Our customers on averageuse like a dozen partners, and
so they enjoy a lot of that.
But when do we decide to saywe're going to do a more
targeted, more strategicpartnership?
A go-to-market like we've donewith, say, grayscale or Pave or
Adobe or Checkr or on and on iswhen we have an opportunity to
(25:51):
create a win, meaning a benefitfor the customer.
A benefit for the customer, abenefit for the partner and a
benefit for us all.
Through these partnerships wecan add value, we can make the
buying process easier, we cansave you money, we can put it
all together under one umbrella,we can deliver it more
efficiently.
That's a great win.
And so we look for thoseopportunities and increasingly
(26:11):
we're now a one-stop shop forrecruiting technology through
those kind of more strategicgo-to-market partnerships like
that.
Speaker 1 (26:19):
Understood, and so my assumption would be that, in
addition to an applicanttracking system and I'm curious
if you could validate this oryour thoughts I would assume
sourcing would be the next mostvaluable, the next biggest value
proposition.
Is that accurate?
Speaker 2 (26:39):
Yeah, sourcing is where a lot of the money is for
sure, especially historicallyright, because companies would
spend a huge amount of dollarson everything from LinkedIn to
ZipRecruiter to Indeed, to Seek,to staffing firms and
recruiting agencies and on.
So there's a huge amount ofdollars there.
The issue for us the reasonthat those dollars go to those
(27:02):
places is because those placesoffer access to candidates that
you can't otherwise get, and thequestion that our customers
have is are they spending thatmoney efficiently?
Are they aiming their dollar atthe right source?
Are they getting the right bangfor the buck, and is it
strategically aligned with thetype of hiring they're trying to
do, or are they actuallyspending it somewhere that they
(27:24):
could be spending it moreefficiently?
So those are the kinds ofquestions our customers are
looking to answer.
Speaker 1 (27:28):
So one of the things, too, you mentioned is that
you're talking about doing moresourcing natively within
Greenhouse.
How does that work withLinkedIn?
What is that workflow?
Speaker 2 (27:38):
Yeah, so again, we're not going to replace LinkedIn.
You're never going to have.
Linkedin has basicallyeveryone's professional profile
online.
It's like this one-of-a-kindasset in the world.
It's fantastic.
Many of our customers, most ofour customers, use it, and so
the question is, how do we helpthem use it better?
How do we take advantage ofthat connectivity?
So there's a program calledLinkedIn Recruiter System
(27:59):
Connect.
We've been longtime leaders inthat space.
We've got a fantasticintegration.
You can send in-mails, which isLinkedIn's kind of proprietary
messaging system, to a candidatethrough LinkedIn.
It shows up in Greenhouse intheir activity feed and vice
versa.
So it's like a really nicelyintegrated experience as a
recruiter.
You don't have to worry aboutdata being out of sync between
(28:23):
those two.
I know, if I come across yourLinkedIn profile, that you're
already in my Greenhousedatabase and vice versa, so that
all works great.
There's a financial component toit that's quite separate.
Like customers today, they buytheir LinkedIn seats from
LinkedIn.
They buy their greenhouse fromus, then they go in and they
enter the program keys and thenthe tool gets connected up and
(28:45):
we aren't involved in that atall.
We definitely hear a lot fromour customers that they're
starting to feel like LinkedIn'sa bit pricey and they worry
where does this go from here?
Like, how much?
How many more years are wegoing to keep giving so much
money to LinkedIn for access tothat database?
When?
What more are we getting out ofit?
And so I think we're startingto see some pressure from
(29:07):
customers on LinkedIn to becauseit's so expensive.
Speaker 1 (29:11):
Yeah, I am seeing that as well.
I'm seeing that as well.
I'm seeing that as well, and Ithink LinkedIn's pricing
strategies is interesting andthey've really stuck to their
guns.
Right, they're sticking totheir guns.
They're really not budging.
Speaker 2 (29:23):
And God bless them.
I have a lot of, I have a lotof respect for them.
I've worked, we were veryclosely with LinkedIn, and they
do occupy this really uniquespace in the ecosystem where
they can command that sort ofpremium, monopoly pricing.
And so they do, and they'regood at it, and so you hear this
pressure, but you don't yet seeanyone leaving it because you
still can't get away from itfully, and so I'm just more
(29:44):
saying it as observers, like Iwonder where that heads, I
wonder how long they're able tomaintain that or what the
pressures may end up being.
Speaker 1 (29:50):
I don't know.
I think people are looking at alot more data sources and
looking at using differentsourcing technology, and also
there's this feeling too that insome cases, in-mails might be a
little oversaturated.
Anyway, that's a whole nothercreate an opportunity if and I'm
(30:13):
not sure I would want to seemore data on that specifically
to the extent that emails orwhatever, just different data
sources, different outreachstrategies, could potentially
increase response rates and thenallow you to bring down the
number of linkedin licenses youhave.
So you have a more, a bettersplit between in mail and email
(30:34):
yeah, I think, and ultimatelynot to just say it's about
LinkedIn.
Speaker 2 (30:38):
It's about more than that.
But, excuse me, ultimately,maybe where we can leave this
topic is, I think, for acustomer with a budget
constraint and this mandate totry to be more efficient and
consolidate systems.
What they're asking us is notjust about oh, can you compare
greenhouse to another ATS andsay, okay, I'm paying 23 grand
(31:00):
for greenhouse and I got a pitchfrom another ATS for 18 grand?
There's $5,000 in there.
No, but you're probablyspending like 200 grand on
recruiter agency fees andLinkedIn seats and indeed, ads.
And like, how do I affect thatoverall budget?
How do I use your tools to bemuch more efficient and don't
worry about the ATS budget,which is like 3%, 4% of my
(31:23):
budget, but all my sourcing fees, and that's where I think you
talk about consolidation ofbudget.
Like I had a conversation with acustomer around that very topic
.
It's like let's show you theoverall business case.
If you come on to Greenhouse,how do you actually spend a
whole lot less money?
How do you take a zero out ofthat bill?
And then the ATS is like a dropin the bucket compared to where
the real dollars are, and sowe're seeing a lot of that
(31:45):
pressure on those companies inthat space too.
Speaker 1 (31:52):
And I think we have a lot to say about how customers
can do better.
Yeah, I think that it also is amind shift for the customer to
for companies that are buying toreally think about this budget
consolidation, because they havetheir separate budget line
items and it's been done acertain way for a very long time
and getting them to rethink isparticularly coming in.
As an existing vendor that'sexpanding services, it's you're
starting to get them like oh, wedon't just do this, like we can
also package it with this, thisand overall, like the pricing
(32:14):
is a lot more competitive.
Right, it's interesting.
Yeah, let's move into ai, and Ithink we've had a couple of
prior conversations on ai andtalent acquisition, I think
primarily concerning more liketop of funnel activity,
particularly when it comes tonumber of applicants and how
companies are leveraging ai forresume matching and and
(32:34):
potentially qualifying toleveraging AI for resume
matching and potentiallyqualifying to some extent based
on resumes and whatnot.
But I'm curious are there any?
Let's just go through a quickupdate on the use cases that you
see are in the most demand andthe use cases that are like the
most technically feasible, likethey're the ones that people are
really using right now, andthen we could just maybe move on
from that into okay, what's thefuture really going to look
(32:57):
like?
Speaker 2 (32:57):
Yeah, yeah, so it's a great question.
Look, the one hot buttonquestion here is using AI as
like a matching algorithm at thetop of the funnel to weed out
or select in who gets to thehiring manager.
And the reason I say it's a hotbutton issue is I was just
having a chat on LinkedIn.
It happens almost every week.
Someone raises this questionlike the ATS is filtering me out
(33:20):
.
Right, there's an AI in the ATSand when I apply to jobs like
I'm not getting through and theAI hates me, and then me and all
the other ATS companies jump onthe thread and we're like we
don't do that.
That's not how our product works.
We don't use AI in a filteringcapacity and a matching the top
of funnel capacity and likecandidates are persistently
(33:41):
worried, that's what's happeningand I think there's reasons for
it, very understandable.
But that's always a big hotbutton issue, both because it's
the thing that candidates keepworrying about because they're
not getting through and theyassume it must be that the
machine is unfairly filteringthem out, and on the other side,
the customers keep asking forthat feature, like they actually
(34:02):
want it, until they realizewhat the risks are and they
realize, oh, got it.
So there's regulation arounduse of AI and hiring decisions.
That places us at regulatoryrisk.
There's bias there's provenbias in these algorithms that
jeopardize our ability toactually find the right talent.
These algorithms routinelymistake facts confidently
(34:24):
so-called hallucinations.
There's a lot of problems withthat, but it's the number one
thing people want is they'reawash in candidates and help me
filter it down, and we don't dothat.
And yet it's the one thing thatcandidates keep over and over
imagining is in the way of themand their dream job.
It's a bad situation.
Speaker 1 (34:38):
This is not going to be a perfect analogy, but I
think it's going to make senseto folks.
There are so many other ways interms of how ML is leveraged and
not even ML, but that we usetechnology to filter.
I think everybody likes thefact that their inbox filters
out or is able to put togetherpriority messages versus spam.
Nobody these days wants to livewithout that feature, so it's
(35:00):
just like this thing is.
The reality is it's it hurt.
It could be an emotionallypainful thing when you're not
picked for a job, and I thinkthe reality is people are not
going to like it, whether it's aperson reviewing it or a
technology, but the reality isthat the technology is going to
get to a point where it'sevaluating the profiles more
(35:20):
accurately than a human will.
Now there's risks, right, andthere's risks I think you had
mentioned before, like of itcompounding or whatnot, and
everything you said about thehallucination is true and
there's these issues, but in myopinion, this is just going to
be how it's done, like you wouldhope so, and you would hope so,
and you would think so.
Speaker 2 (35:39):
So I think it's a smart bet to say it'll get there
.
It's very much not there now,yeah, and so the whole question
is what can we do?
What can we do now?
And there's a lot of stuff tosay there.
We should talk about that, andthen how will we know when it is
the right time or to whatdegree can we bring, can we
invite AI into the loop on humandecision-making, and what's the
(36:03):
right way to do that and what'sthe path there.
So to me, those are thequestions we have to pay
attention to.
Speaker 1 (36:09):
Yeah, yeah.
I think that a lot of peopleare talking about resume
matching.
I think there's companies nowthat are getting more into
screening calls.
To me, I don't see any reasonwhy phone screens in the even
over the next few years arereally necessary to be had with
recruiters.
In my opinion, I, I, I justdon't, I just don't see it.
(36:32):
I really don't because Becauseat the end of the day, it's like
people First of all schedulingphone screens with a recruiter
when you have a full-time jobit's not easy, it's not easy and
the ability to just use asystem to get the information
that you need quickly and submitthe stuff that you need to
submit, I think is a betterexperience, a better candidate
(36:54):
experience.
To some extent, I think it'slike a bit of a mental shift for
companies and for candidates.
But I think we're going to getto the point where people are
going to actually see a hugebenefit to not having to speak
to that recruiter on the phonescreen.
At the end of the day, too,they probably want to speak to
the hiring manager, but theydon't necessarily want to speak
(37:14):
to a recruiter, and there's somany examples of industries
where you needed a salesperson,for instance, like, think about
like stockbrokers, right, andnow you could just do trades
online all by yourself, and Ithink it's like that's the
direction we're going to.
So I also think that for me,like phone screens, I think it's
going to be table stakes thatstuff is done through large
(37:36):
language models.
Like I don't see any reason whyit wouldn't?
Speaker 2 (37:40):
It's an interesting point.
I think you're probably right.
I think it's probably a safebet.
That is where it's headed.
I may not be as optimistic asyou sound about how good that's
going to be.
I think you're right, that isprobably that could happen.
But I think, if anyone's everspent time with the chatbot at
their airline or the phonecompany, I don't think anybody
loves it and I think it'sobviously more efficient and
(38:04):
there's good reasons why thosecompanies do those things.
But I do think it comes at thecost of the experience to the
end user and I think in thiscase, when you talk about
candidate experience, it'sabsolutely true that the ability
to do the interview on yourterms, on your schedule, at
night or off hours is a bigbenefit.
But I think people struggle toget the same feeling out of
talking to a computer that theyget out of talking to a person
(38:25):
and I just worry there'ssomething lost in that process.
Speaker 1 (38:29):
I think there's a balancing act and I also feel
like it's going to be a gradualshift.
And I also feel like it's goingto be a gradual shift, yeah,
but I think it's like thinkabout how many phone screens
where you qualify somebody outin the first five, 10 minutes,
like whether, and even if it'son the JD about anything related
to salary or experience orcommute or whatever else.
(38:49):
There's just so many thingswhere it's just like why did
everybody take their timescheduling yeah, manually and
putting stuff into the system,doing a reschedule, take time
away from work or things I thinkyou'd be working on other stuff
and it's there's.
That is just a hugeinefficiency in the process and
it also that's expands the timeit takes to hire.
(39:11):
Just doing this coordinationand qualification, that is not.
I don't think it requires a lotof mental force.
Speaker 2 (39:16):
I think a lot of the workflows and processes
absolutely can be highlyautomated without losing a whole
lot.
I think the phone interviewsand kind of the interactions
will get to your point, will getautomated eventually, largely
because of the kind of brutallogic of the efficiency of it
and just like that mathoverwhelms any other concern.
(39:37):
I don't think it comes at zerocost.
I think it comes at the cost ofsomething getting lost in terms
of the experience and we're alljust going to have to live with
it.
I don't know, Can I use a?
Can I use a four letter word onthis podcast?
Speaker 1 (39:45):
Yeah, of course.
Speaker 2 (39:47):
The term is in shitification, right.
You've heard heard that inother contexts.
It's this relentless focus onefficiency that works really
well, but it comes at the costof making so many of the
experiences we go through inlife just worse.
Speaker 1 (40:05):
And.
Speaker 2 (40:05):
I think it'll probably happen in phone screens
too.
Yeah, I agree with you thatit's performing.
At the same time, I thinkthere's tons of ways where AI is
already and can continue tomake things much better.
So I think I go to the otherend of the process.
When you're just kicking off ajob today, most recruiters and
hiring managers are sitting downand writing a job description
and thinking about interviewquestions to do and thinking
about what goes on thescorecards and how that whole
(40:26):
process is going to work, andthey don't do it very well.
It takes too long, the contentisn't very good, there's no
continuous learning, there's acomplete lack of consistency,
and I think there's a world inwhich AI really helping solve
those problems and makeeverything much better, because
you're probably not the firstperson to write a job
description for a data scienceexpert or an accountant or a
(40:49):
sales development representative, and so when you go sit down at
Greenhouse in the future tohire that person, my vision is
that Greenhouse can be a lotsmarter at partnering with you
on how do you write that jobdescription, even what do you
call it?
What do you pay that person?
What should you assess for?
How many interview stagesshould you have?
Who on your team should dowhich of the interviews?
All of the things can be mademuch better with the amount of
(41:13):
data that we have and the amountof intelligence that we can
apply to that data.
So I do think there's a ton ofpromise in making things better
through AI and machine learningthat we're actively pursuing.
Speaker 1 (41:23):
Yeah, absolutely.
Do you have a hard stop in twominutes, or can we run a little
over, because I have questions?
Speaker 2 (41:28):
I do.
Unfortunately, I'm going tohave to run.
Speaker 1 (41:29):
Okay, yeah.
So I think what you're talkingabout is like taking role
requirements from hiringmanagers and then basically
creating, maybe even doing somelike automated prompts to do,
ask follow up questions, to puttogether a job description.
Like that stuff is happening.
I think from there it's alsothere's some cool interview note
takers.
That's pretty basic stuff.
If there's a way to train thatto where it's like showing, if
(41:51):
that can help companies evaluateconsistently right, Because we
might write different types ofnotes for different candidates
and if there's a way toconsistently extract the
information so that you can havea more accurate comparison,
that's interesting.
Speaker 2 (42:07):
Yeah and look.
I think ultimately, the promisefor a SaaS tool is not about
greenhouses, not about ATSs, notabout hiring any SaaS company
today.
I think the promise that youhave of the role that your
product can play vis-a-vis thecustomer is tremendous.
It used to be that the computerscreen was like a form and the
user would fill in the form andhit save and store it in the
(42:29):
computer and that was what thecomputer did and, like the first
version of Greenhouse was likea nice version of that when.
And that was what the computerdid, and like the first version
of Greenhouse was like a niceversion of that when we are now
and where it's going.
I think for SaaS businesses ofall types is your product can
play these two really importantroles for your customer it can
be a concierge and it can be acoach.
A concierge is someone who doesstuff for you, makes your life
(42:50):
easier.
You give it a simple request.
It intuits what you really mean, helps you do it more
efficiently and better than youcould on your own.
And a coach they give youfeedback, they look over your
shoulder, they make you do itbetter, they help elevate your
game.
And I think SaaS tools armedwith tons of data and with AI
and machine learning, can playthose two roles much more
effectively.
(43:10):
I think if you think about thefuture of where AI is headed in
SaaS, it's in playing those tworoles better.
Speaker 1 (43:16):
Last thing I'll say.
It's interesting, though, isthat it seems that you think, in
a sense, that help withevaluation is actually a more
realistic use case and tell meif I'm wrong more realistic use
case for ML than actuallymatching in an early stage
qualification, which is a mentalmind F.
I would not use that word, butit's just that's interesting to
(43:39):
me.
Did I say that?
Speaker 2 (43:41):
Yeah, because I think , in my formulation of it, it's
there with you and it's helpingyou do your job better, either
by taking stuff off your plateor by helping you imagine or do
things in a more elevated way,versus putting the person out of
the loop and replacing you witha machine which I just think
can go South in a number ofdifferent ways, some of which,
(44:03):
as we talked about, areinevitable and are just going to
make things more efficient, butworse, and other ways are like
ah, they may be still risky andmay create more problems than
they solve, and so it may takelonger to get there but yeah,
yeah, that makes a lot of sense.
Speaker 1 (44:19):
So this is a lot of fun, daniel, thanks for coming
back on the show and sharing allof your insights with us.
Always a pleasure, greatconversation.
Thank you, all right, thank youBye.
Hello, welcome to the Breakthrough Hiring Show.
I'm your host, james Mackey.
We are joined with Daniel Chetoday.
Daniel, welcome back.
Thanks great to be here.
Looking forward to it yeah, metoo.
So we have a few topics fortoday.
We're gonna discuss skill-basedhiring, recruiting, budgets and
consolidation in the talentacquisition tech space, and then
we're gonna get into AI usecases for talent acquisition.
We're gonna talk about the mostsought after use cases.
(00:23):
We're going to talk about theuse cases that may be more or
less so technically feasible,risks associated with different
use cases, and also maybe justbrainstorm a little bit on what
AI's use cases are essentiallyjust going to become table
stakes.
But then also, what does thefuture look like?
What types of issues are peoplegoing to try to tackle over the
(00:45):
next couple of years?
Speaker 2 (00:46):
Awesome.
It's going to be a lot of fun.
Looking forward to it.
Speaker 1 (00:48):
Yeah, yeah, me too.
So I guess let's just startwith skill-based hiring.
You mentioned that this issomething that's top of mind for
a lot of people right now.
Could you provide maybe we'lljust start with a definition of
skill-based hiring and then wecould just riff back and forth
on that for a little bit.
Speaker 2 (01:04):
Yeah, great question, because it's one of those
jargon words that people throwaround and what do you really
mean by it?
And are we doing it, or is itthe future or whatever?
The way I think about it isvery simple.
It's hiring people based onyour assessment of their
capabilities, as opposed tobased on a set of qualifications
or on, maybe, like a degree ora college that they've gone to
(01:27):
or a place that they've worked,which is the traditional look at
their resume.
And we want to hire people fromquote good companies or from
quote good universities, and Ithink people have started to
wake up to the idea that noteveryone who worked at Facebook
is the same.
Not everyone who is awesome atthe skills you need for the job
(01:49):
went to an Ivy League university, and so if you're going to hire
the best people for yourcompany, you need to think about
how do you assess what thoseskills really are, and then how
do you separate that out fromwhat's on their background,
which may or may not reflectthat perfectly at all.
Speaker 1 (02:05):
Yeah, and so when you talk about how to assess the
skills that they have right, thetransferable skills, is there a
specific method that yourecommend to customers in terms
of a cover?
Is it as simple as just likejotting down a list of different
things that they're doing intheir current role and then
(02:25):
trying to find match, differentparallels, stuff like that, I
mean yeah, look at a high level.
Speaker 2 (02:30):
It's about assessment and it's about identifying,
like you say, here are theskills that we need in this role
and here are the differentassessments we're going to run
to identify who has those skillsand to rate them on those
skills.
Obviously, depending on what theskill is, you're going to use a
different technique If you'relooking for a programmer versus
if you're looking for anaccountant versus if you're
(02:50):
looking for a delivery driver,you're going to do a different
assessment, obviously, but themethodology, the approach, is
the same, which is like what arethose key skills that you need
and then match up the rightassessment to it all.
I think the great opportunitiesthat you have are number one,
you can attract a much broaderand more diverse group of talent
for the same roles, becauseyou're not fishing in the same
(03:10):
pond as everyone else.
Number two is, you can find newcareer paths for people within
your organization, as opposed tohaving to take on the cost
expense and risk of goingoutside, because you might have
people in your, for example, atGreenhouse, in our SDR
department, our kind ofentry-level sales roles that
have gone on to roles inprogramming and software
development and QA and customerservice, and other areas,
(03:35):
because you don't just look atwhat job title they've had, but
you can look at what the skillsare that they bring to the table
, and so I think it gives you anumber of advantages.
But it takes some doing and ittakes some.
It takes really, first andforemost, an intentionality and
a commitment on the part of theorganization that you're going
to look past the headlines onthe resume and you're going to
get over your hangups aboutcertain companies and certain
(03:57):
schools and you're going to geton with finding the right people
for the job.
Speaker 1 (04:02):
Yeah, and I think also probably some of the some
of it comes down to trying toanalyze which roles it makes
more sense to do this with.
Of course, there's going to besome roles in which that
transferable skill, if they'redoing something else necessarily
isn't going to be as relevantor doable.
It's like certain finance roles, for instance, or just
(04:23):
different, more maybe technicalsenior positions that require
the subject matter expertise.
But I think that's alsosomewhat intuitive, right, Like
when you're looking at the typesof roles in the organization
that this would work for, maybemore so like individual
contributor roles or no, I don'tmean that it's only individual
contributors.
Speaker 2 (04:40):
I just hired a CFO, for example, who, while he has
many years of CFO experience, healso worked in the past as a
strategy consultant, and so thatgives him certain skills that
he's exercised in the past thatare very relevant to this job.
Obviously, there's other skillslike that you really can't
learn on the fly, that you haveto already bring to the table if
you're going to have that job,going to have that job, and so
(05:05):
there obviously are certainbackground markers that one
needs, or qualifications thatone needs for certain jobs.
To your point, if you're goingto be a CFO at a company at our
scale, for example, you have tohave a track record of being a
successful CFO at scale.
You have to have worked incertain software industry and
things like that.
But other parts of many jobs,including that one, are very
much a transferable skill thatyou can pick up in other areas.
And so I think when you'relooking at most roles that
(05:27):
you're hiring for, you probablyhave the opportunity to identify
some or all of the skills thatyou need and find people who
bring those skills inside andoutside your organization, as
opposed to just looking at thekind of background markers that
they have.
And I think the pandemic era wasreally a big change in mindset
for a lot of people because allof a sudden kind of remote work
(05:50):
was everywhere and the officedissipated into work from home
and so everybody's just adifferent zoom box on your
screen and it opened people'seyes up to the fact that hang on
a sec, if I don't even have tobe in the same room as you to
get work done like maybe mybeliefs about where you used to
work are also don't even have tobe in the same room as you to
get work done, maybe my beliefsabout where you used to work
also don't necessarily hold up.
And I think it opened up a lotof people's Because you get the
great resignation you had, tonsof people moving and changing
(06:11):
jobs and rethinking lots ofthings, and so I think that
created the conditions underwhich we're now seeing
skills-based hiring take on amore central role in how
companies hire.
Speaker 1 (06:20):
Yeah, I think so and I think to some extent to people
that are in talent acquisitionhave always tried to broaden the
qualification requirementsright, maybe bias too far in the
other direction to some extent,but so it's.
I feel like it's.
If you come from a recruitingbackground, it's.
This is a little bit moreintuitive of a concept.
(06:41):
So the reality is there was, ofcourse, a middle ground and
just in the early days ofstarting Secure Vision, we
working on a lot of salesopenings and the qualification.
It was closer to 10 years ago.
There was still a big push forcollege degrees and that was
something that was, andsometimes like specific types of
degrees and from certain typesof schools, and it was just, it
(07:04):
was a little interesting andeven if somebody had a great
quota, accomplishments orreferences, it was there was
like these hard requirements.
Another one that I thought wasa little bit overkill was the.
It was there was a huge demandto have people that come
servicing the same industry, soa salesperson that was selling a
SaaS product to a specific typeof, maybe a company that has
(07:29):
customers in real estate or justvery nuanced things, and some
cases I think that kind of stuffmight be relevant If it's a
really technical cybersecurityproduct, I don't know, but
generally speaking it's like thetransferable skills of, but
(07:51):
generally speaking it's like thetransferable skills of okay,
has this person sold enterpriseSaaS products, like a similar
sales length deal cycle?
Speaker 2 (07:54):
Yeah, can you do discovery calls, can you take
good notes, can you do the righttype of follow-ups, and
probably, if you can sell a 300KACV SaaS product to, for
example, real estate, you couldprobably also sell that same
product or a similar product toa different industry.
Speaker 1 (08:09):
Yeah, I don't know.
I just think that a lot offolks over-index how difficult
selling to their customer baseis.
And sales is hard.
It's not necessarily because ofthe types of customers you're
selling to.
It can be, but I think weover-index, a lot of folks
over-index on that.
And the other thing that, likethe one hangout specifically to
stuff like that is they're likewell, it just takes so much time
(08:31):
for someone to learn what we'redoing in this.
You want people that areadaptable and, quite honestly,
you do need somebody that has,in some of these roles, maybe a
fair amount of raw intelligence.
The right person should be ableto figure it out.
Speaker 2 (08:49):
That's right and look , I think it's.
Also it reflects a reallyoutdated mindset about what's
available today to learn and howeasy that is.
Versus when I began my careerin the 90s, it was like, oh,
that person has a Rolodex.
To take your example one stepfurther, that person brings a
Rolodex in the real estateindustry.
That's really helpful Because,like you, didn't have any other
way to get those people.
So if you wanted to sell tothat industry and you had a
(09:10):
salesperson that knew the top100 accounts and had their phone
numbers, that was really anasset.
Today, needless to say, all thatinformation is out there.
I don't need that Rolodex,quote unquote.
I have the same 700 millionLinkedIn profiles access that
you do, and that's on the groundkind of knowledge of, like how
to get ahold of someone or howto learn about a particular
(09:32):
industry.
You had the World BookEncyclopedia.
It was like a shelf full of 20books.
That was all the knowledge youwere supposed to have and beyond
that, it was in people's heads.
Now there's so much availableinformation, there's classes
online, there's so much abilityto connect with other people,
and so I just think the wholenotion of learning on the job is
(09:53):
way different than it was halfa career ago and I think in
hiring we're just starting tocome to terms with what that
means and the fact of what atransferable skill is, I think
is a lot broader than it used tobe.
Speaker 1 (10:04):
For that reason, yeah , and I think honestly, I was
recommending skill-based hiringbefore I even really knew that
was the term for it.
I mean, that was typically whatI was going for.
I think that one way that I putit I did I would post about
this on LinkedIn and it seemedto get a lot of traction or
resonate with a lot of people isthere's I feel like there's,
(10:27):
and not only can you doskill-based hiring and that
makes sense, but in factsometimes you can get more
ambitious, hardworking people ifthey haven't done everything
you're hiring them for.
So I would say, like, hire forsome roles, it makes sense to
hire somebody who's done 70% ofthe job, and it's the 30% they
(10:48):
haven't done.
The 30% they haven't done iswhy they're going to accept your
offer.
It's that growth right that and,honestly, many of the best I
don't know if all, but many ofthe best employees that I've
hired at secure vision and I'vehelped my customers hire are
folks that that haven't done ahundred percent.
They've done 70 of it and 30 30that they haven't done and
(11:08):
that's just like a roughestimate.
I don't have like data per se,it's just my own experience,
what I've seen.
I try to get people to have afoundational understanding but
there's stuff that they haven'tdone and I it just never
concerned me too much.
There's different roles, likefor a cfo I I want them to have
done everything that I need tohave done.
Speaker 2 (11:25):
I don't want them you should know how to.
You should know how to likepresent to a board and, yeah,
financials to the company andstuff for sure, yeah.
Speaker 1 (11:32):
Yeah, that's like the strategic person that's
supposed to be, like way betterthan you at a specific, very
strategic function.
That's like very high risk ifit's done wrong.
And but for a lot of jobs, yeah, like sales roles, recruiting
roles, even a lot of programming.
Speaker 2 (11:46):
There's an empathy on programming.
Can you learn a new programminglanguage or a different
database or a differentarchitecture?
Absolutely.
Do you have the kind offundamentals and I think you'll
see that in a greenhousescorecard that a customer of
ours will put together.
Here's the kind of must-have,non-negotiables that they can't
learn on the job.
Here's the sort of nice-to-haveIt'd be great if they brought
it to the table.
And then here's some growthopportunities and it's a great
(12:09):
way to think about, as you say,what's the?
Not only how are we assessingthat person, but what open space
are we giving that person inthis job to grow and learn,
which is a big part of whypeople take jobs.
So I think and to your pointthat you made earlier, I
remember when I first heard thisjargon of skills based hiring,
I was thinking like, yeah, duh,obviously you hire people that
are good at the job you'rehiring for.
(12:30):
But it took me a minute to learnthat there's a whole other
philosophy that people havearound credential-based hiring,
and so you just look at thesemarkers on their resume of what
companies they've worked at,what schools they go to, what
degree do they have, and forsome of us, it's really obvious
that you should look at theskills, but there's a whole
group of people that are stillnot there yet.
Yeah, and I think too.
Speaker 1 (12:50):
There's a whole group of people that are still not
there yet.
Yeah, and I think too it's.
There's that nuance ofunderstanding when credentials
really matter and specialization, like when we're going to a
doctor, we want somebody who'sspecializing in that very small,
specific thing like your ankle,somebody who's like focusing on
one specific little thing, butthat's just there's.
There needs to be thisawareness that there's different
(13:11):
approaches and when to use oneor the other is the point.
Yeah, I think, just for us itprobably just comes very
intuitively, just as a result ofour life experiences in this
space, but it's certainly not,it will admit, a lot fewer
companies and leadership teamsthat are driving hard on some of
(13:35):
the things we were talkingabout in terms of the
credentials and whatnot.
Speaker 2 (13:38):
They're more so, yeah , what it means, though, and
then maybe we can.
Maybe this is maybe an offseton this topic, but I think the
last thing I would say is whatit means is, as an organization,
if you're going to make thisshift, you have to be good at
assessment.
You actually have to be able todevelop some conviction
internally that you've figuredout this person and you know
what their skills are, becauseyou're not going to just rely on
(14:00):
the credential, and that can behard.
It's.
The first question you ask iswhere we started this
conversation.
To bring a full circle.
So how do you know if I'm hiring, say, a programmer or a
salesperson, to take some ofthose examples?
How do I know that they havethe required skills?
And that can be a process wherethere's some change management
involved.
You got to roll this out toyour hiring managers and to your
(14:20):
interviewers and let them knowhere's the way we assess these
people.
Here's what a good answer.
Give them a rubric.
Here's what a good answer lookslike.
Here's an okay answer it lookslike, so that they can come away
from those meetings with someconfidence that they've actually
done a good job assessing thoseparticular skills.
And so the prize is high.
If you get that, then you havethose abilities that we talked
about.
But it can be some changemanagement and it can be some
(14:41):
work to get the organizationthere.
Speaker 1 (14:43):
Yeah, I think so.
For some of the programmingroles too, we've just had
companies simply do technicalevaluations on okay, we really
need somebody to know thislanguage.
But if they know this, thesecouple of things, then we know
they can pick up X, y and Z, andso the primary evaluation is on
the foundational stuff thatthey know is super important,
and then they know okay, if thecandidate aces these things,
(15:06):
then we might be able to asksome broader technical questions
about hey, so in this project,how would you think about
solving X, y and Z?
And you can understand somemore behavioral and technical
like acumen.
But that's usually just afairly straightforward way of
determination.
I think it's the hiringmanager's understanding of the
role makes a big differencethere too.
(15:27):
Okay, what's really the hardstuff to learn?
And assuming that theyunderstand more of a skill-based
hiring approach or they value askill-based approach, I should
say Yep, cool, yeah, I thinkthat's a good stopping point for
that topic, and then we canmove on to recruiting budgets
and consolidations episodes orwhatnot, and I have this has
(15:54):
been a common theme withrecruiting tech leaders that I'm
talking with in particular whenit comes to their product
roadmaps and how they'rethinking about the future.
They're looking at ways toessentially get stickier, offer
different products, thinkingmore of a product suite approach
to their solution.
I'm seeing a lot more peopletalk about acquisitions, looking
at different startups that canmake their product suite more
(16:16):
comprehensive or have a workflowthat goes from end to end for
the hiring process, and there'sjust a lot of thought and
consideration in terms of howcompanies are thinking about
positioning and offeringdifferent products, and then, of
course, that's influenceddirectly by how companies are
buying.
So this shift is happening.
Companies are looking forall-in-one solutions.
(16:39):
It's just interesting nowbecause it just seems like
that's almost like across theboard right now.
Speaker 2 (16:47):
Yeah, absolutely so.
Just to start with, on thisit's a great topic that you
raised.
Just to start with, we're nowin the third year of this kind
of elevated interest rate focuson profitability versus growth
across the board.
This is not about hiring orrecruiting tech.
Every company, especially everySaaS company, is feeling this.
Every B2B seller is in some wayor another grappling with their
(17:10):
buyers, having an elevated levelof scrutiny around every
purchase, looking to save money,looking to be more efficient,
and it's very much become thenorm in any kind of technical
sales environment, save for avery small number that seem to
be immune to the laws of gravity.
But for most of us out thereselling technology, whoever you
are, to businesses, you'refeeling this pinch, and you have
(17:31):
been now for going on threeyears, and so start with that.
Then you zoom into what'shappening in our little
neighborhood and, to your point,our buyers are often hiring
less recruiters themselves tohandle more candidates and, at
the same which we'll talk aboutthe more candidates thing when
we get to the AI stuff and, atthe same time, having less
(17:54):
resources available, having lesstools, having less automation,
wanting to simplify, wanting toconsolidate, wanting to buy
fewer things from fewer vendors,spend less money, have it all
be more efficient, and so thoseare great goals for teams to
have as a vendor.
It creates challenges andcreates opportunities, and so I
think it's an interesting momentof transformation within
(18:15):
recruiting tech right now.
Speaker 1 (18:17):
Yeah, definitely.
It's really interesting to seethe different strategies and I'm
wondering too it's like from abuyer position it's looking at
what are the primary use casesthat they're considering with
different product suites.
I think, yeah, again, I'mseeing this shift of there's
yeah, there's products atdifferent parts of the workflow
(18:38):
that are plugging in andintegrating with tools like
greenhouse, for instance.
I'm starting to see, okay, thecategory leaders of all those
different parts of the workfloware now just purchasing startups
that can provide, like, theadditional parts of the workflow
for this all in one, and so I'mjust curious is there anything
you could share in terms of whenyou're speaking with customers
(19:00):
or prospects or when your teamis?
Are there key pieces offunctionality that they're
looking for, maybe outside ofthe applicant tracking system or
the hiring operating system?
Rather that you do, what otheruse cases are they pressuring
you guys, or are they reallyasking you about right now?
Speaker 2 (19:20):
Yeah, I think you said it.
It's this idea that you havethis applicant tracking system,
and then you had all these otherpoint solutions that you were
going to do to be the best ateverything.
And now they're saying, okay,but the truth of the matter is I
have to have an applicanttracking system.
If I'm doing anything, I need aplace where the candidates can
come from my website, I can movethem through a process and
ultimately disposition them.
(19:40):
That's the must-have.
Now, how do I enhance thatfunctionality to get what I need
without sprawling around andtaking up all these budgets that
I don't have and complexifyingmy stack with a bunch of tools?
And so they're coming tovendors like us and saying what
do you got?
And so for us it's you justlook at the investments that
(20:01):
we've made and the products thatwe've launched.
It tells the story.
It's, first of all, somesourcing tools so you can do
more of your sourcing nativelyin in greenhouse, Whether that's
hey, I've got a candidate, Iwant to look up their email
address, and I don't have to buythird-party technology, I can
do that right in Greenhouse.
I want to send them a cadenceof emails and get them
outreached as a prospect andultimately recruit them into
(20:22):
being an applicant in a hiringprocess, Whether it's internal
mobility and posting internaljobs on a company job board,
whether it's more sophisticatedtools for scheduling and
logistics and like the candidateexperience side of it, where I
think just the basic calendaringbecomes difficult.
I think certainly reporting andanalytics is an area where we've
(20:45):
released tons and tons of newfeatures dashboards,
visualizations, scheduleautomatically, schedule, reports
that can go to hiring managers,like all the stuff.
So you don't have to havegreenhouse and a reporting tool
and visualization and businessintelligence software.
You can do it all right withinthe product.
Those are some of the main usecases.
(21:05):
But we're seeing evene-signature.
We just bundled an e-signaturetool with Adobe eSign texting.
We're now in market with theability to bring in a
third-party texting tool fromGrayscale and bring that in
under greenhouse as like onepurchase, one buyer, one throat
to choke, one order form, and sowe've really been the system of
(21:26):
consolidation of recruitingtools in those ways and at the
same time as I say it's aninteresting moment of
transformation because I thinkwhat you're seeing from the
recruiting lens is it'sconsolidating around the ATS and
so our customers are buyingmore and more of that stuff just
from us.
But when you zoom out, you'vegot like Oracle or Workday or
whomever, saying oh we're theall-in-one tool and you should
(21:48):
get it all from us.
And success factors Okay, We'vegot a recruiting tool and so
you don't even need thegreenhouse and all that stack,
you can just get it all from theworkday.
And so the everyone looks attheir own universe through that
lens and it's interesting to seewhere the lines are actually
going to end up being drawn.
Speaker 1 (22:02):
Yeah Well, I think also you've made a really
interesting point about thee-signature solution, where it's
you're just basicallyco-selling be the right term.
You're not like you didn'tacquire them or they didn't,
it's just vice versa, yeah.
Yeah, or the vice versa, rather.
But you guys, it's justessentially, if they purchase
(22:22):
through Adobe, they can purchaseyou at the same time, or vice
versa, essentially.
Speaker 2 (22:27):
Yeah, so basically Greenhouse comes with a bunch of
credits, signatures, so yousave money.
Basically what it is.
Our customers typically arehaving to go to market and buy a
third party call it, whetherit's Adobe or DocuSign or
HelloSign or all these othertools, and that can cost
thousands of dollars.
Speaker 1 (22:46):
Yeah.
Speaker 2 (22:46):
And instead now you get a number of e-signatures
with Greenhouse.
You don't have to buy anything,you don't have to have a third
party, anything, it's just there.
It doesn't cost any extra money.
And then if you go over and youend up signing like hundreds
and hundreds of more documents,you can pay per unit but you're
still saving a bunch of money.
So that's an example of it's asimpler purchase from the
customer standpoint, Securitypurchasing, IT are all satisfied
(23:09):
and it costs a lot of money.
Speaker 1 (23:11):
Yeah, that's also, in a way, that's really nice too
right, because you're not justeven if you do an acquisition,
then it's like everythingbecomes your problem in terms of
the product and makingeverything work.
So this is it allows people to,in a sense, stay in their own
lane but provide that, thatshared functionality.
So I'm wondering, like, ifwe're going to see even more of
(23:37):
that.
I think I've just I've seensome other companies.
They're just basically tryingto acquire, like crazy, to build
this entire end-to-end workflow.
So I am seeing a couplecompanies do that too.
Speaker 2 (23:43):
So it's, just it's interesting.
Speaker 1 (23:45):
How do you like, is there a way that you decide?
I'm just really curious aboutthis, honestly, yeah, you decide
whether you're going to acquirea product, a point product or
partner with a company likeadobe.
How do you?
Yeah, we call it.
Speaker 2 (24:02):
It's literally that it's like build by partner.
Okay, this is the solution wewant to be able to offer.
What's the path?
Build by partner and pros andcons to each.
To your point, some of it hasto do with is this a technology
that we can differentiate andbuild our own?
E-signature was pretty clearlyan area where it was like nope,
that's been done.
(24:22):
Yeah, that's fine, we're notgoing to build a better, more
reliable e-signatureinfrastructure than Adobe.
That's too big of an admission.
And so it's widely acceptedamong the customers and it's
very mature technology andthat's a great way for us to
bundle it and include it, andwe've done that with background
check tools.
We've done that with all kindsof stuff.
On the other end of thespectrum, when we did our
(24:43):
approach to sourcing, when wedid our approach to onboarding,
we decided to make acquisitionsbecause we identified companies
who we thought really solved theproblem nicely, really had
built good technology, was verycompatible with what we had.
That was essentially what wewould want to build, but already
built, and so it was just like,hey, we could build it
ourselves or we can make theacquisition and you're two years
(25:06):
ahead of the game, which is aspeed to market thing.
So often, if you're in thatquestion of buy versus build, it
comes down to is the rightcompany or product available on
the market when you want it in away that gets you to market
quicker and that the economicsmake sense?
The partnership is reallyinteresting because on
partnering we have a huge numberof partners we have 500, some
(25:29):
technology partners and ourcustomers use a ton of that
stuff Our customers on averageuse like a dozen partners, and
so they enjoy a lot of that.
But when do we decide to saywe're going to do a more
targeted, more strategicpartnership?
A go-to-market like we've donewith, say, grayscale or Pave or
Adobe or Checkr or on and on iswhen we have an opportunity to
(25:51):
create a win, meaning a benefitfor the customer.
A benefit for the customer, abenefit for the partner and a
benefit for us all.
Through these partnerships wecan add value, we can make the
buying process easier, we cansave you money, we can put it
all together under one umbrella,we can deliver it more
efficiently.
That's a great win.
And so we look for thoseopportunities and increasingly
(26:11):
we're now a one-stop shop forrecruiting technology through
those kind of more strategicgo-to-market partnerships like
that.
Speaker 1 (26:19):
Understood, and so my assumption would be that, in
addition to an applicanttracking system and I'm curious
if you could validate this oryour thoughts I would assume
sourcing would be the next mostvaluable, the next biggest value
proposition.
Is that accurate?
Speaker 2 (26:39):
Yeah, sourcing is where a lot of the money is for
sure, especially historicallyright, because companies would
spend a huge amount of dollarson everything from LinkedIn to
ZipRecruiter to Indeed, to Seek,to staffing firms and
recruiting agencies and on.
So there's a huge amount ofdollars there.
The issue for us the reasonthat those dollars go to those
(27:02):
places is because those placesoffer access to candidates that
you can't otherwise get, and thequestion that our customers
have is are they spending thatmoney efficiently?
Are they aiming their dollar atthe right source?
Are they getting the right bangfor the buck, and is it
strategically aligned with thetype of hiring they're trying to
do, or are they actuallyspending it somewhere that they
(27:24):
could be spending it moreefficiently?
So those are the kinds ofquestions our customers are
looking to answer.
Speaker 1 (27:28):
So one of the things, too, you mentioned is that
you're talking about doing moresourcing natively within
Greenhouse.
How does that work withLinkedIn?
What is that workflow?
Speaker 2 (27:38):
Yeah, so again, we're not going to replace LinkedIn.
You're never going to have.
Linkedin has basicallyeveryone's professional profile
online.
It's like this one-of-a-kindasset in the world.
It's fantastic.
Many of our customers, most ofour customers, use it, and so
the question is, how do we helpthem use it better?
How do we take advantage ofthat connectivity?
So there's a program calledLinkedIn Recruiter System
(27:59):
Connect.
We've been longtime leaders inthat space.
We've got a fantasticintegration.
You can send in-mails, which isLinkedIn's kind of proprietary
messaging system, to a candidatethrough LinkedIn.
It shows up in Greenhouse intheir activity feed and vice
versa.
So it's like a really nicelyintegrated experience as a
recruiter.
You don't have to worry aboutdata being out of sync between
(28:23):
those two.
I know, if I come across yourLinkedIn profile, that you're
already in my Greenhousedatabase and vice versa, so that
all works great.
There's a financial component toit that's quite separate.
Like customers today, they buytheir LinkedIn seats from
LinkedIn.
They buy their greenhouse fromus, then they go in and they
enter the program keys and thenthe tool gets connected up and
(28:45):
we aren't involved in that atall.
We definitely hear a lot fromour customers that they're
starting to feel like LinkedIn'sa bit pricey and they worry
where does this go from here?
Like, how much?
How many more years are wegoing to keep giving so much
money to LinkedIn for access tothat database?
When?
What more are we getting out ofit?
And so I think we're startingto see some pressure from
(29:07):
customers on LinkedIn to becauseit's so expensive.
Speaker 1 (29:11):
Yeah, I am seeing that as well.
I'm seeing that as well.
I'm seeing that as well, and Ithink LinkedIn's pricing
strategies is interesting andthey've really stuck to their
guns.
Right, they're sticking totheir guns.
They're really not budging.
Speaker 2 (29:23):
And God bless them.
I have a lot of, I have a lotof respect for them.
I've worked, we were veryclosely with LinkedIn, and they
do occupy this really uniquespace in the ecosystem where
they can command that sort ofpremium, monopoly pricing.
And so they do, and they'regood at it, and so you hear this
pressure, but you don't yet seeanyone leaving it because you
still can't get away from itfully, and so I'm just more
(29:44):
saying it as observers, like Iwonder where that heads, I
wonder how long they're able tomaintain that or what the
pressures may end up being.
Speaker 1 (29:50):
I don't know.
I think people are looking at alot more data sources and
looking at using differentsourcing technology, and also
there's this feeling too that insome cases, in-mails might be a
little oversaturated.
Anyway, that's a whole nothercreate an opportunity if and I'm
(30:13):
not sure I would want to seemore data on that specifically
to the extent that emails orwhatever, just different data
sources, different outreachstrategies, could potentially
increase response rates and thenallow you to bring down the
number of linkedin licenses youhave.
So you have a more, a bettersplit between in mail and email
(30:34):
yeah, I think, and ultimatelynot to just say it's about
LinkedIn.
Speaker 2 (30:38):
It's about more than that.
But, excuse me, ultimately,maybe where we can leave this
topic is, I think, for acustomer with a budget
constraint and this mandate totry to be more efficient and
consolidate systems.
What they're asking us is notjust about oh, can you compare
greenhouse to another ATS andsay, okay, I'm paying 23 grand
(31:00):
for greenhouse and I got a pitchfrom another ATS for 18 grand?
There's $5,000 in there.
No, but you're probablyspending like 200 grand on
recruiter agency fees andLinkedIn seats and indeed, ads.
And like, how do I affect thatoverall budget?
How do I use your tools to bemuch more efficient and don't
worry about the ATS budget,which is like 3%, 4% of my
(31:23):
budget, but all my sourcing fees, and that's where I think you
talk about consolidation ofbudget.
Like I had a conversation with acustomer around that very topic
.
It's like let's show you theoverall business case.
If you come on to Greenhouse,how do you actually spend a
whole lot less money?
How do you take a zero out ofthat bill?
And then the ATS is like a dropin the bucket compared to where
the real dollars are, and sowe're seeing a lot of that
(31:45):
pressure on those companies inthat space too.
Speaker 1 (31:52):
And I think we have a lot to say about how customers
can do better.
Yeah, I think that it also is amind shift for the customer to
for companies that are buying toreally think about this budget
consolidation, because they havetheir separate budget line
items and it's been done acertain way for a very long time
and getting them to rethink isparticularly coming in.
As an existing vendor that'sexpanding services, it's you're
starting to get them like oh, wedon't just do this, like we can
also package it with this, thisand overall, like the pricing
(32:14):
is a lot more competitive.
Right, it's interesting.
Yeah, let's move into ai, and Ithink we've had a couple of
prior conversations on ai andtalent acquisition, I think
primarily concerning more liketop of funnel activity,
particularly when it comes tonumber of applicants and how
companies are leveraging ai forresume matching and and
(32:34):
potentially qualifying toleveraging AI for resume
matching and potentiallyqualifying to some extent based
on resumes and whatnot.
But I'm curious are there any?
Let's just go through a quickupdate on the use cases that you
see are in the most demand andthe use cases that are like the
most technically feasible, likethey're the ones that people are
really using right now, andthen we could just maybe move on
from that into okay, what's thefuture really going to look
(32:57):
like?
Speaker 2 (32:57):
Yeah, yeah, so it's a great question.
Look, the one hot buttonquestion here is using AI as
like a matching algorithm at thetop of the funnel to weed out
or select in who gets to thehiring manager.
And the reason I say it's a hotbutton issue is I was just
having a chat on LinkedIn.
It happens almost every week.
Someone raises this questionlike the ATS is filtering me out
(33:20):
.
Right, there's an AI in the ATSand when I apply to jobs like
I'm not getting through and theAI hates me, and then me and all
the other ATS companies jump onthe thread and we're like we
don't do that.
That's not how our product works.
We don't use AI in a filteringcapacity and a matching the top
of funnel capacity and likecandidates are persistently
(33:41):
worried, that's what's happeningand I think there's reasons for
it, very understandable.
But that's always a big hotbutton issue, both because it's
the thing that candidates keepworrying about because they're
not getting through and theyassume it must be that the
machine is unfairly filteringthem out, and on the other side,
the customers keep asking forthat feature, like they actually
(34:02):
want it, until they realizewhat the risks are and they
realize, oh, got it.
So there's regulation arounduse of AI and hiring decisions.
That places us at regulatoryrisk.
There's bias there's provenbias in these algorithms that
jeopardize our ability toactually find the right talent.
These algorithms routinelymistake facts confidently
(34:24):
so-called hallucinations.
There's a lot of problems withthat, but it's the number one
thing people want is they'reawash in candidates and help me
filter it down, and we don't dothat.
And yet it's the one thing thatcandidates keep over and over
imagining is in the way of themand their dream job.
It's a bad situation.
Speaker 1 (34:38):
This is not going to be a perfect analogy, but I
think it's going to make senseto folks.
There are so many other ways interms of how ML is leveraged and
not even ML, but that we usetechnology to filter.
I think everybody likes thefact that their inbox filters
out or is able to put togetherpriority messages versus spam.
Nobody these days wants to livewithout that feature, so it's
(35:00):
just like this thing is.
The reality is it's it hurt.
It could be an emotionallypainful thing when you're not
picked for a job, and I thinkthe reality is people are not
going to like it, whether it's aperson reviewing it or a
technology, but the reality isthat the technology is going to
get to a point where it'sevaluating the profiles more
(35:20):
accurately than a human will.
Now there's risks, right, andthere's risks I think you had
mentioned before, like of itcompounding or whatnot, and
everything you said about thehallucination is true and
there's these issues, but in myopinion, this is just going to
be how it's done, like you wouldhope so, and you would hope so,
and you would think so.
Speaker 2 (35:39):
So I think it's a smart bet to say it'll get there
.
It's very much not there now,yeah, and so the whole question
is what can we do?
What can we do now?
And there's a lot of stuff tosay there.
We should talk about that, andthen how will we know when it is
the right time or to whatdegree can we bring, can we
invite AI into the loop on humandecision-making, and what's the
(36:03):
right way to do that and what'sthe path there.
So to me, those are thequestions we have to pay
attention to.
Speaker 1 (36:09):
Yeah, yeah.
I think that a lot of peopleare talking about resume
matching.
I think there's companies nowthat are getting more into
screening calls.
To me, I don't see any reasonwhy phone screens in the even
over the next few years arereally necessary to be had with
recruiters.
In my opinion, I, I, I justdon't, I just don't see it.
(36:32):
I really don't because Becauseat the end of the day, it's like
people First of all schedulingphone screens with a recruiter
when you have a full-time jobit's not easy, it's not easy and
the ability to just use asystem to get the information
that you need quickly and submitthe stuff that you need to
submit, I think is a betterexperience, a better candidate
(36:54):
experience.
To some extent, I think it'slike a bit of a mental shift for
companies and for candidates.
But I think we're going to getto the point where people are
going to actually see a hugebenefit to not having to speak
to that recruiter on the phonescreen.
At the end of the day, too,they probably want to speak to
the hiring manager, but theydon't necessarily want to speak
(37:14):
to a recruiter, and there's somany examples of industries
where you needed a salesperson,for instance, like, think about
like stockbrokers, right, andnow you could just do trades
online all by yourself, and Ithink it's like that's the
direction we're going to.
So I also think that for me,like phone screens, I think it's
going to be table stakes thatstuff is done through large
(37:36):
language models.
Like I don't see any reason whyit wouldn't?
Speaker 2 (37:40):
It's an interesting point.
I think you're probably right.
I think it's probably a safebet.
That is where it's headed.
I may not be as optimistic asyou sound about how good that's
going to be.
I think you're right, that isprobably that could happen.
But I think, if anyone's everspent time with the chatbot at
their airline or the phonecompany, I don't think anybody
loves it and I think it'sobviously more efficient and
(38:04):
there's good reasons why thosecompanies do those things.
But I do think it comes at thecost of the experience to the
end user and I think in thiscase, when you talk about
candidate experience, it'sabsolutely true that the ability
to do the interview on yourterms, on your schedule, at
night or off hours is a bigbenefit.
But I think people struggle toget the same feeling out of
talking to a computer that theyget out of talking to a person
(38:25):
and I just worry there'ssomething lost in that process.
Speaker 1 (38:29):
I think there's a balancing act and I also feel
like it's going to be a gradualshift.
And I also feel like it's goingto be a gradual shift, yeah,
but I think it's like thinkabout how many phone screens
where you qualify somebody outin the first five, 10 minutes,
like whether, and even if it'son the JD about anything related
to salary or experience orcommute or whatever else.
(38:49):
There's just so many thingswhere it's just like why did
everybody take their timescheduling yeah, manually and
putting stuff into the system,doing a reschedule, take time
away from work or things I thinkyou'd be working on other stuff
and it's there's.
That is just a hugeinefficiency in the process and
it also that's expands the timeit takes to hire.
(39:11):
Just doing this coordinationand qualification, that is not.
I don't think it requires a lotof mental force.
Speaker 2 (39:16):
I think a lot of the workflows and processes
absolutely can be highlyautomated without losing a whole
lot.
I think the phone interviewsand kind of the interactions
will get to your point, will getautomated eventually, largely
because of the kind of brutallogic of the efficiency of it
and just like that mathoverwhelms any other concern.
(39:37):
I don't think it comes at zerocost.
I think it comes at the cost ofsomething getting lost in terms
of the experience and we're alljust going to have to live with
it.
I don't know, Can I use a?
Can I use a four letter word onthis podcast?
Speaker 1 (39:45):
Yeah, of course.
Speaker 2 (39:47):
The term is in shitification, right.
You've heard heard that inother contexts.
It's this relentless focus onefficiency that works really
well, but it comes at the costof making so many of the
experiences we go through inlife just worse.
Speaker 1 (40:05):
And.
Speaker 2 (40:05):
I think it'll probably happen in phone screens
too.
Yeah, I agree with you thatit's performing.
At the same time, I thinkthere's tons of ways where AI is
already and can continue tomake things much better.
So I think I go to the otherend of the process.
When you're just kicking off ajob today, most recruiters and
hiring managers are sitting downand writing a job description
and thinking about interviewquestions to do and thinking
about what goes on thescorecards and how that whole
(40:26):
process is going to work, andthey don't do it very well.
It takes too long, the contentisn't very good, there's no
continuous learning, there's acomplete lack of consistency,
and I think there's a world inwhich AI really helping solve
those problems and makeeverything much better, because
you're probably not the firstperson to write a job
description for a data scienceexpert or an accountant or a
(40:49):
sales development representative, and so when you go sit down at
Greenhouse in the future tohire that person, my vision is
that Greenhouse can be a lotsmarter at partnering with you
on how do you write that jobdescription, even what do you
call it?
What do you pay that person?
What should you assess for?
How many interview stagesshould you have?
Who on your team should dowhich of the interviews?
All of the things can be mademuch better with the amount of
(41:13):
data that we have and the amountof intelligence that we can
apply to that data.
So I do think there's a ton ofpromise in making things better
through AI and machine learningthat we're actively pursuing.
Speaker 1 (41:23):
Yeah, absolutely.
Do you have a hard stop in twominutes, or can we run a little
over, because I have questions?
Speaker 2 (41:28):
I do.
Unfortunately, I'm going tohave to run.
Speaker 1 (41:29):
Okay, yeah.
So I think what you're talkingabout is like taking role
requirements from hiringmanagers and then basically
creating, maybe even doing somelike automated prompts to do,
ask follow up questions, to puttogether a job description.
Like that stuff is happening.
I think from there it's alsothere's some cool interview note
takers.
That's pretty basic stuff.
If there's a way to train thatto where it's like showing, if
(41:51):
that can help companies evaluateconsistently right, Because we
might write different types ofnotes for different candidates
and if there's a way toconsistently extract the
information so that you can havea more accurate comparison,
that's interesting.
Speaker 2 (42:07):
Yeah and look.
I think ultimately, the promisefor a SaaS tool is not about
greenhouses, not about ATSs, notabout hiring any SaaS company
today.
I think the promise that youhave of the role that your
product can play vis-a-vis thecustomer is tremendous.
It used to be that the computerscreen was like a form and the
user would fill in the form andhit save and store it in the
(42:29):
computer and that was what thecomputer did and, like the first
version of Greenhouse was likea nice version of that when.
And that was what the computerdid, and like the first version
of Greenhouse was like a niceversion of that when we are now
and where it's going.
I think for SaaS businesses ofall types is your product can
play these two really importantroles for your customer it can
be a concierge and it can be acoach.
A concierge is someone who doesstuff for you, makes your life
(42:50):
easier.
You give it a simple request.
It intuits what you really mean, helps you do it more
efficiently and better than youcould on your own.
And a coach they give youfeedback, they look over your
shoulder, they make you do itbetter, they help elevate your
game.
And I think SaaS tools armedwith tons of data and with AI
and machine learning, can playthose two roles much more
effectively.
(43:10):
I think if you think about thefuture of where AI is headed in
SaaS, it's in playing those tworoles better.
Speaker 1 (43:16):
Last thing I'll say.
It's interesting, though, isthat it seems that you think, in
a sense, that help withevaluation is actually a more
realistic use case and tell meif I'm wrong more realistic use
case for ML than actuallymatching in an early stage
qualification, which is a mentalmind F.
I would not use that word, butit's just that's interesting to
(43:39):
me.
Did I say that?
Speaker 2 (43:41):
Yeah, because I think , in my formulation of it, it's
there with you and it's helpingyou do your job better, either
by taking stuff off your plateor by helping you imagine or do
things in a more elevated way,versus putting the person out of
the loop and replacing you witha machine which I just think
can go South in a number ofdifferent ways, some of which,
(44:03):
as we talked about, areinevitable and are just going to
make things more efficient, butworse, and other ways are like
ah, they may be still risky andmay create more problems than
they solve, and so it may takelonger to get there but yeah,
yeah, that makes a lot of sense.
Speaker 1 (44:19):
So this is a lot of fun, daniel, thanks for coming
back on the show and sharing allof your insights with us.
Always a pleasure, greatconversation.
Thank you, all right, thank youBye.
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