[00:00:00] Alright, I want to talk to you for a moment about retaining and developing your workforce.
[00:00:05] It's hard.
[00:00:06] Recruiting is hard.
[00:00:07] Retaining top employees is hard.
[00:00:09] Then you've got onboarding, payroll, benefits, time and labor management.
[00:00:13] You need to take care of your workforce and you can only do this successfully if you
[00:00:18] commit to transforming your employee experience.
[00:00:21] This is where ISoft comes in.
[00:00:23] They empower you to be successful.
[00:00:26] We've seen it with a number of companies that we've worked with and this is why we
[00:00:30] partner with them here at WorkDefined.
[00:00:32] We trust them and you should too.
[00:00:35] Check them out at isofthcm.com.
[00:00:48] Hey, this is William Tinkup and Ryan Leary and you are watching and hopefully listening
[00:00:53] to the Use Case Podcast.
[00:00:55] Today we have David on From Talent Neuron and we're going to be learning all about
[00:00:59] the use case, business case for why people choose talent neuron.
[00:01:04] David, how are you doing today?
[00:01:06] Great. Thank you, sir. How are you doing?
[00:01:07] I'm doing well. Ryan, how are you doing?
[00:01:09] Oh, I'm fantastic, man.
[00:01:10] We've got David on.
[00:01:11] We're going to talk talent neuron and we're going to get smart.
[00:01:14] Here we go.
[00:01:15] Here we go.
[00:01:15] David, would you do us a favor and introduce yourself?
[00:01:19] Sure.
[00:01:20] David Wilkins.
[00:01:21] I am our Chief Product and Marketing Officer here at Talent Neuron.
[00:01:24] I've been in the HCM space now for, I guess, sad to say over 30 years.
[00:01:29] No, no, no, no, no, no.
[00:01:30] Oh, wow.
[00:01:31] We don't use yours.
[00:01:32] We don't use yours.
[00:01:32] We just dated himself.
[00:01:34] So in 1953 I joined.
[00:01:37] After I worked on the atomic bomb.
[00:01:40] Yeah, so true story, guys.
[00:01:42] I was in a board call a couple weeks ago and noted when I started my career
[00:01:46] and said that I had been in this space about 24 years.
[00:01:49] Right.
[00:01:50] And then one of our board members, in fact, our chairman of the board said,
[00:01:53] David, I think your math is wrong.
[00:01:55] It's actually like 34 years.
[00:01:58] That was a disheartening moment.
[00:02:00] I must say to lose 10 years like that.
[00:02:02] No, I delete my LinkedIn profile only goes back to 20 years.
[00:02:07] OK, good.
[00:02:08] So I deleted everything below 20.
[00:02:10] And in 2025 it'll go to 2005.
[00:02:14] I'll always only have a rolling 20.
[00:02:17] I'll always.
[00:02:19] This guy just never ages.
[00:02:21] Never ages?
[00:02:22] Like no, you know what?
[00:02:24] I love that you put product and marketing together.
[00:02:27] How did that?
[00:02:27] How did that?
[00:02:28] Because a lot of companies don't.
[00:02:29] They product over here, marketing over there, sales over here.
[00:02:32] How did you all agree on putting those two things together?
[00:02:36] Yeah, I think I've kind of bounced around between the two
[00:02:39] over a lot of my career.
[00:02:41] So I've run marketing a few times, product a few times,
[00:02:44] been a chief strategy officer, been a general manager
[00:02:46] a couple times of product lines within SAS.
[00:02:50] So when we were constructing this,
[00:02:52] I came in last October to talent neuron.
[00:02:54] Julie, who's the CEO, actually had a real similar background
[00:02:57] to me where she's been in product, been in marketing,
[00:02:59] been a head of strategy and obviously run as a CEO
[00:03:02] a lot of companies.
[00:03:04] So she and I both really similarly, I think, see that
[00:03:07] when you do marketing at the high enough level,
[00:03:09] then you have to know the market, you have to know competitors,
[00:03:11] you have to know the needs of your clients,
[00:03:12] you have to know where the space is going.
[00:03:14] And if you do a product at a high enough level,
[00:03:16] you have to know all that
[00:03:17] and you have to know where the product should go
[00:03:19] and how to shape strategic direction.
[00:03:22] So at the right level of strategy,
[00:03:23] they kind of start to overlap a lot in meaningful ways.
[00:03:27] And given the space that we're in is a little bit
[00:03:30] still kind of being built out, it's a little category creation.
[00:03:33] Kind of makes sense to kind of ram it all together
[00:03:35] and think about it holistically.
[00:03:37] I love it because it's not a lot of this,
[00:03:40] the claiming that product people are saying,
[00:03:42] marketing doesn't get it.
[00:03:44] Marketing says, product people, they're crazy.
[00:03:46] Now I just look at the mirror and just yell at myself.
[00:03:48] That's exactly right.
[00:03:49] Only if marketing would send me the right people.
[00:03:53] That's how it works.
[00:03:55] That's how it works.
[00:03:55] So I know we're going to jump in the product,
[00:03:57] but before we do that, David, do you find,
[00:04:01] because the setup, the structure you have here
[00:04:03] is interesting to me and I prefer it this way myself.
[00:04:06] Do you find that when the roles are separated,
[00:04:11] there is a clash and less things get done?
[00:04:14] Yeah, I do think that.
[00:04:16] And often in scenarios where I've been ahead of marketing
[00:04:20] but not had a product, I've often found myself
[00:04:23] in a position where I feel like I have a better handle
[00:04:26] on what we should be doing based on market understanding
[00:04:28] and the competitive landscape.
[00:04:30] Because you think about the resources that a good marketing
[00:04:33] leader has access to.
[00:04:35] Analysts, folks like you guys as major influencers
[00:04:38] in a space, client conversations, events.
[00:04:42] There's a ton of signal that comes in through marketing.
[00:04:45] And if you're properly ingesting that signal
[00:04:47] and get a point of view about what should happen,
[00:04:50] sometimes you're in some ways more informed
[00:04:52] even than the product team.
[00:04:54] And so if you have to then filter all of your ideas
[00:04:56] into the product team and hope they understand it all,
[00:04:59] then it can slow things down and create friction points.
[00:05:03] And then similarly on the product side,
[00:05:05] when I've had product but not marketing,
[00:05:08] there's often technology constraints and limitations
[00:05:11] and things you got to work around
[00:05:12] that other folks aren't aware of.
[00:05:14] When you have that whole picture in one view,
[00:05:17] it allows you to juke and weave in ways
[00:05:20] that is more flexible, more nimble, more responsive
[00:05:23] and yet still achieve the ultimate end game.
[00:05:26] Who owns testers?
[00:05:29] So we have a CRO function.
[00:05:32] So Catherine Evans on our team runs that
[00:05:34] and she owns that whole from an AE
[00:05:38] like existing customers as well as new customer segmentation.
[00:05:41] So much support, everything.
[00:05:42] Yeah.
[00:05:42] And then we have a slightly separate function
[00:05:44] where we have customer success as well
[00:05:46] and those teams work in concert with the account or nurse.
[00:05:50] Yeah, so it's a pretty sophisticated model
[00:05:54] but it gives us a pretty good...
[00:05:56] And we all work obviously very closely together
[00:05:58] to try to understand client needs
[00:05:59] and how things are evolving, etc.
[00:06:01] So what is talent neuron and what problem do we solve?
[00:06:06] Yeah.
[00:06:08] So first, I'm still new enough that I remain in awe
[00:06:11] a little bit of what this company does
[00:06:13] and how it does it.
[00:06:14] I think for those of us who've been in the space a little while,
[00:06:17] it's kind of a little bit of a wish fulfillment for me
[00:06:20] in that it's a massive big data AI machine learning based company.
[00:06:26] And what we do is we ingest all kinds of demand signal
[00:06:30] in the form of job posts on a global basis,
[00:06:33] supply data about the available people in a given market
[00:06:37] and then cost data from variety of sources
[00:06:40] including what gets published into job posts.
[00:06:42] And we're basically gathering all of that kind of information
[00:06:46] for 40 countries in the world,
[00:06:48] representing collectively about 90% of the world's GDP
[00:06:52] where we know talent demand, talent supply and talent cost.
[00:06:57] Things like skills, things like the employee value proposition,
[00:07:02] things like where are people hiring?
[00:07:05] What skills are they hiring for in different locations?
[00:07:08] Who's hiring for what talent?
[00:07:10] And all of that enables us to basically take all that raw data
[00:07:14] and through AI machine learning, we can distill all that into signal
[00:07:18] and actually make sense of it in ways that companies can then do things like
[00:07:22] play in their next location based on available talent today
[00:07:26] and what that talent's going to look like a few years out.
[00:07:29] Do things like if I could hire an Austin or Boston or Bangalore,
[00:07:34] what's the mix of demand versus supply
[00:07:37] and what's the cost of it
[00:07:38] and where is the most likely place I'm going to be successful
[00:07:41] in bringing that talent together?
[00:07:43] Maybe I want to understand what my competitors are doing
[00:07:46] as they're thinking about AI and machine learning skills.
[00:07:49] What roles are they putting those skills in?
[00:07:51] Where in the world are they hiring for that stuff?
[00:07:53] Where should I be looking based on what my competitors are doing
[00:07:56] and am I doing things in a way that's inconsistent with market?
[00:08:00] We can look at the way that skills are being asked for
[00:08:03] inside of the 1.5 million job posts we get per day across the world
[00:08:08] and we can say, hey, these are new skills.
[00:08:11] These are emerging or growing skills.
[00:08:14] These skills are core that are asked for all the time for this kind of role
[00:08:18] and maybe these skills used to be core
[00:08:20] but now they're not being asked for as frequently.
[00:08:22] So something's changing.
[00:08:23] The skills of all things, it's declining,
[00:08:26] it's becoming assumed that you just have that skill
[00:08:29] and so it gives us an ability to then say things like,
[00:08:31] well, today you're hiring for this kind of person
[00:08:34] but the market, when they hire for this same role,
[00:08:38] they're looking for this and you're no longer keeping up with.
[00:08:41] Yeah, this is how you compare, right?
[00:08:43] So all of that collectively gives folks like intelligence to know
[00:08:47] not just what's going on inside my business
[00:08:49] but what's going on in my competitor landscape inside the market,
[00:08:52] what's evolving, what's changing, what's available
[00:08:55] and how can I make better strategic decisions around all of that
[00:08:58] to basically future proof or de-risk my strategy going forward?
[00:09:03] Two questions here, take them any way you want.
[00:09:07] So one is who are we selling to?
[00:09:09] Who's the company?
[00:09:11] What's your target, your ICP?
[00:09:12] And then second to that, you've answered it somewhat here already
[00:09:19] but I want to use a different word trigger.
[00:09:21] What's the trigger point for that customer,
[00:09:24] a potential customer to say,
[00:09:26] All right, I need a solution here.
[00:09:28] I need to solve this problem.
[00:09:29] So we know the problem that you solved
[00:09:31] but what's that trigger point that you find a norm may come to?
[00:09:35] Yeah, so the target demo for us historically has been
[00:09:39] what I would call the Fortune 2000.
[00:09:41] So organizations that typically have a multinational footprint
[00:09:45] of some kind, often multi-regional.
[00:09:47] Some of our companies that we support are in literally
[00:09:50] like 110 countries in the world, right there everywhere
[00:09:53] and they're struggling with, how do I solve for where do I hire?
[00:09:59] So it's a very strategic high level TA challenge.
[00:10:02] So if I can hire in any of 110 locations,
[00:10:06] what's my best strategy to do wage arbitrage
[00:10:09] or to look at skill availability, speed of hire,
[00:10:12] competitiveness, that type of thing.
[00:10:15] Where can I go find pockets of talent
[00:10:17] that I otherwise don't know exist
[00:10:19] right and discover inequities in the market
[00:10:22] that I can exploit either cost or talent availability.
[00:10:25] And so the other key use case beyond strategic TA
[00:10:28] is really what I would call workforce planning.
[00:10:31] I know strategic workforce planning has kind of got like a
[00:10:33] that's here obviously it's one of those words
[00:10:35] that people have talked about for 20 years
[00:10:37] and no one's figured out.
[00:10:38] I don't wish that but in this case,
[00:10:41] like a lot of what our clients do squarely fall into that bucket
[00:10:44] like location planning or like skills analysis
[00:10:47] build versus buy versus bought frameworks
[00:10:50] comparing internal capabilities to what the market
[00:10:53] is looking for to see where my Delta's exist.
[00:10:56] So there I wouldn't say it's full blown strategic workforce planning
[00:11:01] but there's very significant substantial pieces of it
[00:11:04] that clients are trying to solve for within the framework.
[00:11:07] So people analytics teams,
[00:11:08] folks who are on strategic workforce planning
[00:11:12] talent intelligence, business transformation, talent intelligence
[00:11:15] it's those kind of things where they're looking for
[00:11:18] an understanding of markets and the talent in them
[00:11:21] writ large to support strategic planning and strategic thinking.
[00:11:25] Do you all know about the kids?
[00:11:27] Yeah, yeah.
[00:11:28] You all know about the kids.
[00:11:29] We do.
[00:11:29] I mean, especially now that they're giving it away.
[00:11:32] So everybody and their brother is looking for cost savings
[00:11:36] nowadays right?
[00:11:37] I understand.
[00:11:37] But yeah, I know there are folks who see that as an alternate.
[00:11:41] They don't have all three.
[00:11:43] If I remember right.
[00:11:44] Yeah.
[00:11:44] They do the supply and demand but they don't have comp.
[00:11:48] Yeah.
[00:11:48] And the other piece that we often hear from clients is,
[00:11:51] you know, it's all self reported right?
[00:11:53] So one of the things that we've probably ourselves on is,
[00:11:55] you know, we're getting our data from governmental sources,
[00:11:58] NGOs like trade unions like census data from various
[00:12:02] government entities.
[00:12:03] Hard data.
[00:12:04] Supplement.
[00:12:04] Yeah, hard data.
[00:12:05] We do supplement that with social data, right?
[00:12:07] Because why wouldn't you write as a secondary data source but
[00:12:10] so not a primary.
[00:12:12] Yeah.
[00:12:13] And then from a demand perspective, they're only aware of the
[00:12:15] demand they're aware of.
[00:12:17] We're speaking from millions and millions of company websites
[00:12:20] directly also from the big job boards.
[00:12:23] We dedupe it all.
[00:12:24] So it's just a bigger data set to make more informed
[00:12:26] decisions against.
[00:12:28] Which is absolutely great.
[00:12:29] Let me ask because there has been products in the past
[00:12:32] that have that have been supplied demand.
[00:12:35] But I love the three prong, you know, of basically
[00:12:38] mix again cost or comp into this.
[00:12:42] What's the workflow for people?
[00:12:45] So we understand the market that you're going after.
[00:12:47] Do they need to see this in their ATS?
[00:12:50] Or is it a standalone?
[00:12:52] Like where do they see this data?
[00:12:54] Yeah, yeah.
[00:12:55] So there's a couple of different scenarios right?
[00:12:58] So if you think about something like hiring analysis,
[00:13:00] some of that can happen externally where I'm looking at
[00:13:03] the availability of talent in a market.
[00:13:05] Right.
[00:13:05] I'm really thinking strategically where should I go.
[00:13:08] But you're right, William.
[00:13:09] I mean like the logical place that you'd eventually want to see
[00:13:11] that stuff is inside your ATS or CRM.
[00:13:14] We're starting to explore those relationships.
[00:13:17] If you weren't aware, we were previously held by Gartner
[00:13:21] for a long, long time.
[00:13:23] We broke away about a year and a half ago now.
[00:13:26] Gartner because their Gartner didn't typically engage
[00:13:29] in a lot of those partner kind of relationships.
[00:13:31] Right.
[00:13:31] So we're starting that journey now.
[00:13:34] We actually just built a relationship with Beemory.
[00:13:37] It will specifically allow you to take some of our data,
[00:13:40] not all of it, but relevant pieces around like talent supply,
[00:13:44] demand, hiring difficulty and bring that into the talent
[00:13:47] calibration process directly inside the Beemory interface.
[00:13:52] And now we're exploring really other interesting things
[00:13:54] we could do together to even look at like competitiveness,
[00:13:59] what who the competitors are in the space, location
[00:14:01] optionality and things like that to try to embed
[00:14:04] some of that intelligence into your calibration
[00:14:07] and decision-making process at the point of building out the rec.
[00:14:11] So we're starting that journey, I would say William,
[00:14:13] and I think that's the right way to think about it.
[00:14:15] For other things like competitive analysis,
[00:14:17] general skills analysis of a market or a role,
[00:14:21] things like location analysis as I'm planning
[00:14:24] where my next center of excellence will be
[00:14:25] or my next office or my next factory.
[00:14:28] Many of those are standalone sort of planning decisions
[00:14:30] which can exist outside the flow over typical HRAS.
[00:14:33] Right. But that said, we are exploring additional partnerships,
[00:14:37] folks like one model workday trying to figure out how our data
[00:14:40] and where our data fits in their back-end data structures.
[00:14:44] Who are you selling to in the organizations?
[00:14:48] Are we selling to talent leaders?
[00:14:50] Are we at the CHRO level?
[00:14:53] What we're exactly all?
[00:14:54] Yeah, it's varied. So CHRO is for sure heads of TA,
[00:15:00] regional heads of TA if the company's big enough.
[00:15:02] Many of our clients are.
[00:15:05] It might also be head of people analytics,
[00:15:07] head of talent intelligence.
[00:15:09] It could potentially be someone in charge of digital transformation
[00:15:12] or business transformation who's looking at this dataset
[00:15:16] as a supporting data play and making those decisions.
[00:15:21] But that's pretty much the universe in which we're typically operating.
[00:15:25] I'm going to add probably the COO and the CFO at some point
[00:15:29] because the COO is usually in charge of a next plant and stability.
[00:15:35] And the CFO cares deeply about cost.
[00:15:38] Occasionally it might be someone in charge of location planning
[00:15:40] for that same reason.
[00:15:42] They have rental data, they have governmental regulatory data.
[00:15:47] They don't have talent data.
[00:15:48] But they don't know.
[00:15:49] I can't tell you how many times people have come to us
[00:15:51] after they put a plant somewhere.
[00:15:53] You're right. How are people?
[00:15:54] Yeah. Great. It was really cost effective
[00:15:56] to build there but I can't stop it.
[00:15:57] So now what?
[00:15:58] You got really tree property and that's fantastic.
[00:16:04] We've got not too far from you David.
[00:16:06] We've got a... it's out in farmland.
[00:16:10] Close enough that it's commutable but not really commutable.
[00:16:14] But there are some big healthcare companies out there.
[00:16:17] And they can't staff it.
[00:16:19] They just can't staff it because coming from either direction...
[00:16:23] Because they're going to use talent newer on.
[00:16:25] That's why.
[00:16:25] You're going through cities to get to the farmland.
[00:16:28] And it's just... it's too much of a commute on the way back.
[00:16:32] And it's ridiculous and I don't think they actually plan for that.
[00:16:36] They just said cheap, we're getting incentives.
[00:16:39] Big facility, we can do this.
[00:16:42] And that's it.
[00:16:43] It only takes a few of those before someone says,
[00:16:46] hey maybe we should look at talent next time.
[00:16:47] Yeah.
[00:16:49] Well, there's a guy in Dallas that I've known for a long time
[00:16:53] and that's what he does for Whole Foods.
[00:16:56] And he does site planning.
[00:16:58] He does this for several big companies.
[00:17:00] And grocery, retail, all the hourly stuff.
[00:17:05] They need to know where to put their next little place.
[00:17:08] Okay, but they've got ways to do the demographics of the buyer
[00:17:13] and all that stuff.
[00:17:14] They've got some tools that do all that stuff.
[00:17:16] They don't have talent.
[00:17:17] Right.
[00:17:18] And I think what gets really interesting about that William is like,
[00:17:20] if you know some of the demographics of the area, you might think you know.
[00:17:25] But here's where things get hairy.
[00:17:26] Who else is hiring for that same talent?
[00:17:28] That's right.
[00:17:29] Right.
[00:17:29] And one of the things that we do in our competitive module
[00:17:32] is it's not just go identify your known obvious competitors
[00:17:35] who are your business competitors.
[00:17:36] Right.
[00:17:37] But at a role level, who else is posting for the same kind of talent
[00:17:42] in the same locations you are?
[00:17:44] So who are your talent competitors?
[00:17:47] Yeah, that gets messy in the hourly market
[00:17:49] because the person that's applying to Walmart is also applying to AT&T and Taco Bell
[00:17:57] and Starbucks.
[00:17:58] So it's not like they're only applying to fast food restaurants.
[00:18:04] Then Amazon Fulfillment Center pops in and they still get it.
[00:18:07] You're done.
[00:18:07] You're done, buddy.
[00:18:08] Right?
[00:18:08] Yeah.
[00:18:09] Yeah, it's so true.
[00:18:11] Right?
[00:18:11] I mean, I was working at healthcare source for a while
[00:18:13] and we were supporting things like long-term care facilities
[00:18:17] and with talent strategies, nursing homes, assisted living.
[00:18:22] And God forbid an Amazon Fulfillment Center opened up nearby or a UPS.
[00:18:27] All those people are getting paid $13 an hour to be a CNA.
[00:18:30] It can now be a $17 an hour factory worker
[00:18:33] and it would just pull the lifeblood out of the company.
[00:18:36] And so now I'm here, I can actually see all that.
[00:18:38] Like for any company, I can see who else are you fighting for
[00:18:41] for the same kind of talent and what's that competitive concentration
[00:18:45] and the drain that it's putting on your location strategy?
[00:18:49] Right?
[00:18:49] It's fascinating what you can do now.
[00:18:51] Where do you find most companies are struggling at this level?
[00:18:57] So they're complex enough that they need you, right?
[00:18:59] They're large enough that they know they need you.
[00:19:01] They bring you in.
[00:19:04] Are they struggling?
[00:19:05] Once they get the information, what's that next step for them?
[00:19:08] Are you recommending or helping them at that point?
[00:19:10] They're on their own.
[00:19:11] Where are they struggling?
[00:19:13] So there's a couple of things.
[00:19:14] I'll start with the shifting nature of what people are trying to solve for,
[00:19:18] which is fascinating to me.
[00:19:20] And then I'll talk a little bit about how we're bridging that gap, Ryan,
[00:19:22] because it's not even as sophisticated as the clients are that we support,
[00:19:26] they still need help sometimes for what they do with analysis.
[00:19:30] So the first thing I'll share with you guys that I think is crazy,
[00:19:33] I guess not unexpected, with all the changes that the world's been through
[00:19:37] over the last five years, right?
[00:19:40] With global pandemic war, like, you know,
[00:19:43] recession, bounce back from recession, supply chain disruption.
[00:19:47] Oh my God, AI everybody.
[00:19:49] Let's do AI.
[00:19:50] Social revolution.
[00:19:52] Just a few things, right?
[00:19:55] Minor things.
[00:19:55] Minor things, right?
[00:19:56] So everybody in their brother is now like,
[00:19:58] hey, where are we today relative to where we need to be?
[00:20:03] And where are we relative to where the competitors are
[00:20:05] and where the market is?
[00:20:07] So there is a very, very high level of scrutiny right now
[00:20:10] pretty high percentage of our clients and prospects coming in
[00:20:13] to understand what talent and skills do I have now
[00:20:17] and where the hell are they in the world?
[00:20:19] And what talent and skills do I need to get where I'm trying to go
[00:20:23] and how far off am I?
[00:20:25] And depending on how far off I am, what's,
[00:20:27] am I going to build it?
[00:20:28] Am I going to buy it?
[00:20:29] Am I going to automate it away?
[00:20:31] And if I am going to buy it, where am I buying it?
[00:20:34] And where can I find it?
[00:20:35] And at what cost?
[00:20:36] And then the FOMO and the FOMO that's running parallel to that
[00:20:40] is what the hell is everybody else doing?
[00:20:42] Bingo.
[00:20:43] Bingo.
[00:20:43] And you know, what are my competitors doing around AI?
[00:20:48] Where are they putting those skills?
[00:20:49] Where are they hiring for those skills?
[00:20:51] How are they thinking about this problem?
[00:20:53] And am I thinking about it the right,
[00:20:55] where am I relative to them?
[00:20:56] And what, and that's just one small example
[00:20:58] like you could say the same thing about other critical roles,
[00:21:02] right?
[00:21:02] So that's been a big shifting nature of asks in the last year
[00:21:06] or so, Ryan.
[00:21:08] But then the follow on is like, okay, great.
[00:21:10] So now we've done this analysis.
[00:21:11] We know what your gap is.
[00:21:12] Here's the percentage of this role that's going to be automated.
[00:21:15] Here's the percentage of this role that you can find easily
[00:21:17] in the market.
[00:21:18] But this other part you would have built.
[00:21:20] So then it's the whole, well, what's your build by strategy?
[00:21:24] How should you be thinking about internal mobility?
[00:21:26] How should you be implementing?
[00:21:28] And you know, it's sometimes it's silly things.
[00:21:29] Like we were dealing with one of our clients
[00:21:32] who was looking for markers.
[00:21:33] And one of the constraints that we're putting on it
[00:21:35] was well, they need to have B2B experience.
[00:21:38] Right?
[00:21:39] Which because that's super relevant.
[00:21:42] We were able to show them if you take that B2B skill set
[00:21:45] off the table and that B2B experience,
[00:21:47] you're available talent pool triples.
[00:21:49] And then why don't you just put a little training program
[00:21:52] together about what's different between B2C and B2B.
[00:21:55] And then you just opened up three acts
[00:21:56] the talent available to you.
[00:21:58] And then you can train them on the gap, right?
[00:22:00] But that kind of think hybrid, think, you know, blended.
[00:22:05] Don't just think TA.
[00:22:06] Don't just think talent development.
[00:22:08] How are you going to bring these things together
[00:22:10] to build the talent that you need for the future?
[00:22:12] We're providing a lot of strategic consulting
[00:22:14] and support for that as a separate function.
[00:22:17] So we run it all through our normal, you know, platform.
[00:22:21] But then we can engage in specific strategic consulting
[00:22:24] engagements to support clients in that way.
[00:22:27] We can also try and do like research projects
[00:22:29] like bespoke.
[00:22:31] So I mentioned word of 40 countries, you know,
[00:22:33] if you want, you want to report on Bolivia,
[00:22:35] we don't that's not in the platform,
[00:22:36] but our research team can go and do that for you.
[00:22:39] Or discover manufacturing talent in Bangladesh,
[00:22:42] for example, right?
[00:22:43] And then build out a report of talent availability
[00:22:46] and that type of thing.
[00:22:47] Typically we include a certain number of reports
[00:22:49] in your contract so that you can go beyond
[00:22:53] what's natively in the platform
[00:22:54] and do secondary and tertiary analysis
[00:22:57] with support from our research team as well.
[00:22:59] I want to ask a couple of my sites questions real quick.
[00:23:03] We'll start off with your most recent favorite customer story
[00:23:06] without disclosing names.
[00:23:08] We don't need to know their name,
[00:23:09] but like something that was before talent neuron
[00:23:13] and after talent neuron.
[00:23:16] And so what what story do you got for us?
[00:23:18] Actually, I think one of the best ones is that
[00:23:20] is the one I started to relate, which was
[00:23:23] one of our clients was really at an impasse
[00:23:28] about their inability to hire a sufficient number of marketing folks
[00:23:34] given the geographies in which they were operating.
[00:23:37] And we were able to show them with data
[00:23:40] what was available in the market, why it was so constrained,
[00:23:44] why the nature of their approach to the problem
[00:23:48] was the root cause of the problem.
[00:23:50] It wasn't just throwing money at it.
[00:23:52] Yeah, right?
[00:23:53] How about think differently?
[00:23:55] You're spending this amount of money on recruiting
[00:23:59] to go get these very specialized people
[00:24:02] when if you choose to get less specialized people,
[00:24:05] you open your talent supply
[00:24:06] and then you can use those same dollars
[00:24:08] you were spending there on a training program.
[00:24:11] And now you're not like solving that problem
[00:24:15] at a point in time through herculean effort.
[00:24:19] You're building capability
[00:24:21] and you're building a deep systemic ability
[00:24:24] to be successful over time
[00:24:26] by fundamentally changing the dynamics of the problem.
[00:24:29] And that's only possible when you have the visibility
[00:24:32] into that external data
[00:24:33] and the way that external data is interacting
[00:24:35] with your strategy to drive the outcome
[00:24:38] that was happening, right?
[00:24:39] So that's a super simple example, but other ones
[00:24:43] that I think are really interesting
[00:24:44] are all the stuff we're doing lately
[00:24:46] with internal skill like identification versus external
[00:24:51] and mobility and recommendations on build versus buy.
[00:24:55] But even some of those basic, basic things
[00:24:57] are still really useful to companies
[00:24:59] as they're trying to sort through
[00:25:01] just how to be successful
[00:25:02] in a very difficult challenging labor market.
[00:25:05] So I don't know if you can answer this.
[00:25:07] I'm gonna put it out there
[00:25:09] because you just you're here
[00:25:11] what last year, right?
[00:25:12] The year?
[00:25:13] Yeah, I came in October.
[00:25:14] So in October?
[00:25:15] Okay. So we remember Talon Oron from a long time back.
[00:25:22] What's that evolution look like?
[00:25:24] So somebody like me, for example,
[00:25:26] or that I was in corporate at the time
[00:25:28] long time ago, I have a vision of what Talon Oron was
[00:25:32] or what the capability was.
[00:25:35] What is that?
[00:25:35] I mean with obvious, there's obvious changes
[00:25:38] and evolution that happened.
[00:25:40] Yeah.
[00:25:40] What are those big changes through the last
[00:25:43] six, seven, eight years that people need to be aware of?
[00:25:48] Wow. That's a great question.
[00:25:50] So I guess the first thing I'd say
[00:25:52] is we're way easier to do business with than we were before.
[00:25:55] In the past, we sold,
[00:25:57] the only way we sold was as the full platform.
[00:26:00] Right.
[00:26:00] You had to buy regions of country data at a pop.
[00:26:05] We didn't have a strategic consulting arm
[00:26:07] in the way we do today.
[00:26:09] So we've broken a lot of that apart, Ryan.
[00:26:11] So now we broke it into modules.
[00:26:13] So there's a hiring analysis module.
[00:26:15] There's a location analysis module.
[00:26:17] There's a skills analysis module, right?
[00:26:19] So we're allowing people to sort of buy in
[00:26:21] against the key problems they're currently facing
[00:26:24] and the specifics of what they're solving for,
[00:26:26] which has brought the average price point down pretty
[00:26:29] considerably to make it more accessible,
[00:26:31] more to mid-market or larger market players.
[00:26:34] But also frankly, to find cost advantage
[00:26:36] even among large players
[00:26:37] who were previously getting charged
[00:26:39] for the whole dang platform and not only using.
[00:26:42] So we've price adjusted a lot of people to get them
[00:26:45] to something that is reasonable
[00:26:46] and makes sense for their usage pattern, right?
[00:26:48] We also changed from a very heavy dependence license-wise
[00:26:52] on your license or price-wise on your licenses.
[00:26:56] We've minimized that so that people can more democratize
[00:26:59] access and make it more widely available in the business.
[00:27:02] So it's more priced now by the module
[00:27:04] and by the country coverage.
[00:27:06] The actual cost per license,
[00:27:08] we want to minimize that so people can spread that out a lot, right?
[00:27:11] And then the last thing was going from global
[00:27:13] or very regional coverages to mix and match specific countries
[00:27:18] because each business is different.
[00:27:20] They're in different parts of the world.
[00:27:22] It was too limiting.
[00:27:23] So that's a massive change in the whole go-to market
[00:27:25] which has made us able to better tailor
[00:27:30] what people have bought against their actual needs, right?
[00:27:33] The other big thing is the availability
[00:27:34] of strategic consulting.
[00:27:36] So previously that was sort of handled
[00:27:38] when we were under Gartner by the Gartner Analyst Team.
[00:27:41] When we separated, there really wasn't anything
[00:27:44] that sort of filled that gap of like,
[00:27:45] okay, I got all this analysis, what do I do?
[00:27:48] Or how do I teach my team to be better data storytellers
[00:27:52] or to better communicate HR and talent issues through data?
[00:27:56] Like we can do that kind of consulting too
[00:27:58] because that's what we live and breathe every day.
[00:28:00] Or we could take you through a whole build-by analysis
[00:28:03] globally for a region, for a location, for a role,
[00:28:06] for a set of roles, for a job family.
[00:28:08] So we can go really, really big or pretty narrow
[00:28:11] to specific things.
[00:28:13] And then I think the last thing I'd say
[00:28:15] that's another major, major shift is,
[00:28:20] you know, I think that we saw opportunities
[00:28:22] when we separated to really double down
[00:28:25] on our global data coverage.
[00:28:27] You know, we were in a lot of countries before
[00:28:30] we weren't as diligent maybe as we should have been
[00:28:33] about having all three of those pillars,
[00:28:35] the supply, demand and salary in all those locations.
[00:28:38] We've put a massive effort forth this year
[00:28:41] to make sure that across all 40 countries,
[00:28:44] not only do we have all three of those data points,
[00:28:46] but they're refreshed and updated
[00:28:48] and have a recency to them.
[00:28:50] India for example, we've updated salary there
[00:28:52] three times this year because there's wage inflation
[00:28:55] going on.
[00:28:56] And so what we had six months ago was inaccurate today.
[00:28:58] Right. And so we're taking a much more proactive approach
[00:29:02] to data freshness and ensuring that what's there is like up to date.
[00:29:06] Right. So those are probably the biggest changes.
[00:29:09] You know, what you're going to see next year
[00:29:11] is we're starting to really double down
[00:29:14] in that universe of strategic workforce planning,
[00:29:16] you know, scenario driven stuff,
[00:29:18] what if analysis really serious.
[00:29:21] Yes. Yeah.
[00:29:22] More playful kind of things that allow you to take
[00:29:25] an internal data with external data
[00:29:27] and then model some stuff to see what's my best.
[00:29:30] Yeah, what's my best finance?
[00:29:31] Finance will love that, especially in the M&A folks.
[00:29:35] They'll love that because then they can,
[00:29:36] they have a sandbox.
[00:29:38] They can then look at that and see what they have.
[00:29:41] Well, I think, you know, I think what's happening,
[00:29:43] what's happening, William, is I think companies are,
[00:29:46] you know, 15 years ago when some of this technology first
[00:29:49] really started emerging at scale,
[00:29:51] you know, it was people were in awe.
[00:29:53] Like, what do you mean I can get like,
[00:29:56] you know, salary posts for like 20 countries in the world
[00:29:59] all at once and analyze that and see what that means
[00:30:02] and use AI to distill signal
[00:30:05] from what is otherwise just an unstructured job post.
[00:30:07] Right?
[00:30:08] I think people were just amazed
[00:30:10] that you could do any of that, right?
[00:30:12] But now as we've gotten more sophisticated with data,
[00:30:15] as large language models have come out,
[00:30:17] you know, people are asking way more sophisticated questions.
[00:30:19] Like, hey, based on signal
[00:30:22] and what you see my competitors hiring for
[00:30:25] and what job titles and what skills and where in the world
[00:30:28] and what's the difference in the new hiring rate
[00:30:31] versus their previous organic rate,
[00:30:34] is that something I should pay attention to?
[00:30:36] Like, can you just tell me if I give you a list of competitors
[00:30:40] who were making moves that I should be interested in diagnosing, right?
[00:30:44] Like, that's kind of the next level of this stuff
[00:30:47] is like turning this stuff into insights
[00:30:50] and triggers and actionable moments
[00:30:54] where someone can go, oh, wait a second, what's going on there?
[00:30:57] And cross the board, that's where we're moving now
[00:31:00] and that's where the space is starting to move
[00:31:02] is to move beyond just having the data
[00:31:04] to really making sense of it and deriving insights from it.
[00:31:07] You know?
[00:31:08] So for the audience's edification,
[00:31:11] what do we call ourselves?
[00:31:12] You might have already said it, but I want to make sure...
[00:31:15] You mean the company name?
[00:31:17] Yeah, yeah, talent.
[00:31:19] Talent?
[00:31:19] Or Ron?
[00:31:20] I got it.
[00:31:22] That was fantastic.
[00:31:24] I love that.
[00:31:24] What's that?
[00:31:25] That's going to be the opener to the...
[00:31:27] What do we call ourselves?
[00:31:28] Talent or...
[00:31:28] Noron.
[00:31:29] Thanks.
[00:31:30] I scheduled the show, I'm pretty much like...
[00:31:34] No, the...
[00:31:35] Drugs Mike walks off stage.
[00:31:37] Category.
[00:31:39] Because it could be a hiring intelligence,
[00:31:41] it could be talent and intelligence.
[00:31:42] What's the category-ish?
[00:31:45] Thanks, Ron.
[00:31:46] Yeah, I think the broad category has been called talent and intelligence.
[00:31:52] I think that's a...
[00:31:53] Candidly, I think William, that's not the best term for the space, right?
[00:31:56] Because I think Vizier or Cruncher or HR Workbench,
[00:32:01] I mean they're all doing talent and intelligence too,
[00:32:03] but it's inside your company data, right?
[00:32:05] So I think it's some combination of external talent and intelligence
[00:32:10] or market talent and intelligence.
[00:32:12] It's something along those lines.
[00:32:14] I think...
[00:32:15] Would you go as nichey as hiring?
[00:32:17] Hiring intelligence?
[00:32:19] I don't think so, because I think some of what we're opining on is when not to hire
[00:32:24] and when you should build or when you should automate or...
[00:32:29] The reason I asked the question wasn't just to learn the company name, was
[00:32:36] what questions if they haven't bought this before?
[00:32:40] Let's say it's talent and intelligence,
[00:32:41] keep it simple for the audience.
[00:32:43] Sure, sure.
[00:32:44] What questions should they be asking in the buying process?
[00:32:48] Because like you mentioned things like data recency and things like that.
[00:32:54] What should they be asking because they've never...
[00:32:56] Let's say they've never bought this.
[00:32:58] What should they be asking you?
[00:33:00] At the root, the interesting thing about the space is like there's sort of two
[00:33:05] root things that both have to be good to have a good solution.
[00:33:10] One is data quality, right?
[00:33:12] Really understanding where is this data coming from?
[00:33:15] Per my comments earlier, I liked LinkedIn.
[00:33:17] It's a great solution, but it's all self-reported.
[00:33:20] So if you're looking for statistically valid, defensible data, it's a little sketch.
[00:33:26] Right?
[00:33:27] So making sure that people are pulling in governmental sources, NGOs, trade unions,
[00:33:32] banging that up against a Ddupe model and that you have really deep statistical analysis
[00:33:38] and AI tools to get all that right so that when you do say something about something,
[00:33:43] you know that you have high degrees of confidence in it or at least as high as you can.
[00:33:47] The other thing I'd say related to that, William, that is also really important
[00:33:52] is you want a vendor who's transparent about what they know and don't know.
[00:33:57] Right?
[00:33:57] Right.
[00:33:58] There are places in the world where we can't get that same level of data quality
[00:34:03] not because for want of trying on our part because it doesn't exist.
[00:34:06] There isn't an NGO.
[00:34:07] There isn't a governmental entity.
[00:34:09] We're doing the research ourselves and compiling it,
[00:34:12] and then basing it on surveys in some cases.
[00:34:15] Right?
[00:34:15] That has less statistical certainty than when we can cross validate against five other sources.
[00:34:22] Right?
[00:34:22] And so we're very open about that and transparent because at the end of the day,
[00:34:27] our clients are making multi-million dollar decisions on these data points
[00:34:31] and you don't want to make a decision on something with its...
[00:34:35] No.
[00:34:35] We are falsely implying a level of precision or quality that may not be present.
[00:34:40] We at least want them to know with eyes open what they're basing these decisions on.
[00:34:44] Which then in some cases leads them to do secondary checks or tertiary checks
[00:34:48] and makes them do additional diligence rather than just rely on us.
[00:34:52] Right?
[00:34:53] So I think all of that is really important.
[00:34:55] And I think the second thing that's really, really important is
[00:34:59] what then can I do with the data?
[00:35:01] What insights can I derive?
[00:35:03] How do I use that data successfully?
[00:35:05] Is it easy to access?
[00:35:06] Is it easy to make sense of?
[00:35:08] Can I manipulate it in different ways?
[00:35:11] And then I think if there's a third thing, the third thing would be given that a lot of
[00:35:15] companies are still beginning to develop maturity in this area.
[00:35:18] Can I get an assist per Ryan's comment earlier?
[00:35:22] Can you guys help me when I'm stuck or I need extra hands or I'm timeline constrained
[00:35:29] or I'm looking, they're looking for analysis that I can't complete on my own.
[00:35:32] It's too much.
[00:35:33] Like can the vendor step in and help you with that in a way that once they're done,
[00:35:38] they hand it over to you and you can continue on on your own.
[00:35:40] And you haven't then manufactured a dependence forever on a third party consultancy.
[00:35:45] Right?
[00:35:46] Where when the conversation or demo and the sales process, do you find that
[00:35:52] prospects get to this point in that demo?
[00:35:55] And they're just like, yes.
[00:35:58] This is the solution.
[00:36:00] The aha moment?
[00:36:01] Yeah.
[00:36:01] The aha moment.
[00:36:02] I think what I've seen the lights go on is when you can take somebody from that first question
[00:36:09] that they ask and then chain them three levels deep to three other things they never
[00:36:14] thought to ask that'll be critical to their success.
[00:36:17] Right.
[00:36:17] So as an example, the thing that we're hearing is everywhere, as I'm sure you guys
[00:36:22] are hearing it everywhere.
[00:36:23] How do I find AI talent?
[00:36:24] Where do I find AI talent?
[00:36:26] What should I pay for it?
[00:36:27] What are my competitors doing?
[00:36:28] So we can start with, here's what's going on with your competitors.
[00:36:32] Here's what they're hiring this talent.
[00:36:33] These are the kind of skills they're looking for.
[00:36:35] These are the tools that they're looking for, which is also super interesting to
[00:36:40] folks usually right?
[00:36:41] Where in the world are they doing that?
[00:36:43] Which then leads to okay, if that's where that's happening, what's like
[00:36:49] what skills should I be looking for in those areas?
[00:36:53] What skills exist in those areas?
[00:36:56] And from a location standpoint, am I present there?
[00:36:59] What skills am I looking for?
[00:37:01] Am I looking for those same skills?
[00:37:03] So now we're branching from what are my competitors to doing to what am I
[00:37:07] currently doing?
[00:37:08] Right.
[00:37:09] Right.
[00:37:09] And then we go okay great.
[00:37:10] I definitely want to hire those skills in Bangalore.
[00:37:13] Who else is hiring in Bangalore right now?
[00:37:16] And now with our latest launch of our new module, our Employee Value Proposition
[00:37:19] Module, we can even tell you in Bangalore, foreign AI role,
[00:37:24] what are the EVPs that they're pitching?
[00:37:27] Oh cool.
[00:37:28] Right.
[00:37:28] So now I can see, I can go from this very high level of like what's going on
[00:37:33] competitively down to what's in the job posts in Bangalore, foreign AI
[00:37:39] engineer for my three main talent competitors in that location and how
[00:37:44] does my EVP stack up?
[00:37:46] And from there I can even drill into the specific examples in the job posts
[00:37:50] and see the specific job posts.
[00:37:53] So Ryan, that's when people you know they have to click, they're like whoa,
[00:37:56] I can go from like this global competitive view all the way down to
[00:38:00] the specific job post that collectively informed all of that.
[00:38:04] They forgot the original question.
[00:38:06] Yeah because now we're answering right, because now we're answering okay
[00:38:11] because your real question isn't what are my competitors doing?
[00:38:14] It's going to be how do I out-compete my competitors for those same talents?
[00:38:17] Right.
[00:38:18] And so we can show them like what you're really asking is this,
[00:38:21] so let's tell you how to get there and then we can show them that whole
[00:38:24] path through the different modules and how they interconnect to deliver
[00:38:27] that kind of insight right?
[00:38:28] That's usually when people go whoa okay, I got it now.
[00:38:32] Yeah.
[00:38:32] So last question for me is what's success for you for the rest of the year?
[00:38:39] Like what do you want to be by 25 and then maybe by this time next year?
[00:38:44] Like what's where are we trying to be?
[00:38:47] Yeah so right now we're in the midst of launching our first generative AI chat bot
[00:38:53] which is super exciting.
[00:38:54] It's in closed beta with clients, it'll be launched in all availability by end of year.
[00:38:59] That's basically like a chat GPT type of interface.
[00:39:02] We've been really thoughtful about the design.
[00:39:05] It's no IPs going out publicly.
[00:39:06] There's no ability for it to hallucinate in the way it's been built
[00:39:10] but it basically allows you to interrogate the system but with a very natural
[00:39:15] chat GPT type of experience right?
[00:39:18] So that's pretty cool.
[00:39:19] We're excited to get that launched.
[00:39:21] We're also launching a candidate profile capability where once you've done your
[00:39:26] hiring analysis and we've set up where in the world is the right place for you to go
[00:39:30] find data engineers for example and we say okay it's Bangalore or it's you know Seattle
[00:39:36] and we can say well who in Seattle is available?
[00:39:38] What's that talent pool look like and even begin to surface names
[00:39:42] for you to then add to a sourcing tool or something in those lines.
[00:39:46] So we're moving beyond just the pure analysis to closer to action ability right?
[00:39:51] And that's the second thing I'd say William is over time what you're going to see from us
[00:39:54] is we're going to be making that move from just having the data to like
[00:40:00] making it much more actionable scenario driven, what if driven.
[00:40:05] A big thing we're going to do next year is really double down on our competitive
[00:40:07] intelligence module.
[00:40:09] It's already pretty robust but we think we can do things like
[00:40:12] expose what tools people are hiring for which could be really interesting to CTOs and CIOs.
[00:40:19] Now that so many countries and so many states are now starting to publish salary
[00:40:24] data in job posts we think we can do things where we could expose maybe not
[00:40:29] what they're really paying but what they say they're going to pay.
[00:40:31] So you can compare that to what you say you're going to pay and then combine that with our EVP
[00:40:36] data and even tell you what bonus is also part of that artist user part of that.
[00:40:41] You know they have a pet insurance benefit like we can give you like that whole nuanced picture
[00:40:47] not of what they're generally doing but what they did yesterday.
[00:40:50] Right what did your competitor put in a job post yesterday right?
[00:40:54] So we think some of that will be really interesting competitively.
[00:40:56] So what that's what you're going to see from us is really kind of more
[00:41:00] making sense of the data and delivering more actionable insights
[00:41:04] and allowing for more scenario driven planning and that type of thing.
[00:41:08] So two things from me pet insurance again has come up David like every other episode
[00:41:17] pet insurance is coming out.
[00:41:18] Absolutely oh my gosh.
[00:41:19] And this started back a couple years ago we were doing a live show and the first
[00:41:25] guest was nationwide and it was pet insurance.
[00:41:30] I didn't know what to talk.
[00:41:32] Right.
[00:41:32] You got this brother.
[00:41:33] Ryan's head almost exploded because the lady sat down she pushed her card over
[00:41:38] and she goes I'd really like to talk about pet insurance so I'm like all right let's go.
[00:41:42] Not sure how we're doing this but let's.
[00:41:45] Right I looked at Ryan and I thought he had an aneurysm.
[00:41:48] Like I understand the valley.
[00:41:52] I get right but I'm like an hour on how are we going to do that a long time.
[00:41:56] Yeah yeah yeah yeah were you successful you know 100% he can talk about anything he could
[00:42:02] talk about the pain on your wall and take it down.
[00:42:05] Yeah it was fantastic.
[00:42:08] Sorry final question from me David is how far out is talent nor I'm thinking what are you
[00:42:13] planning for are you looking just next year in a year I mean are you 10 years down the line
[00:42:18] where are you guys at in terms of planning how far out do you think.
[00:42:23] Yeah so I'm so I personally think in three year increments I think candidly much beyond that is
[00:42:28] the world's going to change too much you know and and the CEO shares my worldview about that so
[00:42:36] you know I the way I would describe it Ryan is like in the next six months we have very clear
[00:42:42] very well laid out plans with clear milestones timelines etc.
[00:42:47] The next six month chunk is typically very directionally on point and we know the sort
[00:42:54] of the shape of it after that we sort of move to the next year right and that year is sort of a
[00:42:59] directional like let's plan a flag here this might mean M&A this might mean organic build
[00:43:05] right these are the kind of partnerships we'd want to chase right.
[00:43:09] Yeah it gets fuzzier.
[00:43:10] Yeah it gets a little fuzzier but like you know the north star for us
[00:43:14] is this notion of making things actionable and intelligent more intelligent in the actual display
[00:43:22] of the information and the insights it delivers so you will continue to see us make more and more
[00:43:29] sense of the data we have but also layer and other data points that would increase the
[00:43:35] level of contextual understanding and insight that you can derive from the data so that's
[00:43:41] north star there will be specific juxtapos and weaves will make along the way but we will
[00:43:46] be breaking out of just being a pure talent intelligence here's some data right into a much
[00:43:52] more actionable place you know really for the next six months and beyond.
[00:43:57] Josh Mike walks off stage David so great to talk to you.
[00:44:02] We should have had more discussions over the years because I get smarter every time I
[00:44:08] talk to you so just thanks for coming on the show thanks for educating the audience and
[00:44:12] good luck to everything you do with talent you're on.
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