Harnessing Big Data and AI for Strategic Workforce Planning with Talent Neuron

[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.