Schmidt List · 2026-05-11 · 38 min
Key moments - from our scoring
Substance score
51 / 100
Five dimensions, 20 points each
Curtis built Mustard Hub after experiencing severe turnover in his education business and discovering that existing engagement software was designed for enterprises and didn't work for small businesses. Rather than selling directly to employers, Mustard Hub integrates into platforms that companies already use - ATS, payroll, compliance, and vertical SaaS - to generate behavioral signals those systems were never designed to capture. The core insight: modern workforce platforms excel at recording transactions (hires, terminations, payroll runs) but miss the upstream behavioral indicators that predict churn, like disengagement patterns or sentiment shifts that precede resignations. Mustard Hub fills this gap through gamified engagement indices, sentiment inputs, and AI-powered predictive insights that identify flight risks and quantify the financial impact of employee exits. Curtis uses concrete numbers to illustrate the problem: SHRM estimates hiring costs at $4,500 per employee plus $1,000-$1,400 in onboarding, totaling roughly $7,200 per churn event. At a 2,500-person mid-market retail company churning at 80%, that's a $14 million annual burden. His first customer was his kid's preschool, and after implementing the system in his own operations, turnover dropped 80 percentage points while top-line revenue grew 42.5% in year one.
Mustard Hub is behavioral infrastructure that embeds into existing workforce platforms (ATS, payroll, compliance, vertical SaaS) to generate continuous behavioral signals about employee engagement, sentiment, and participation patterns. It uses gamified engagement indices and sentiment inputs to predict attrition early, outputting AI-powered insights identifying flight-risk employees and quantifying the financial impact of potential exits.
Most engagement software was built on an enterprise model and has been retrofitted for small businesses through feature-gating and pricing, but this doesn't align with how SMBs operate their P&Ls and manage their organizations. Curtis found that all existing solutions were ineffective for small business realities.
SHRM estimates recruiting costs at $4,500 per employee, plus $1,000-$1,400 in onboarding and productivity loss (new employees operate at 20-25% efficiency for the first four weeks), totaling approximately $7,200 per churn event. At a 2,500-person company with 80% turnover, this creates a $14 million annual churn burden.
After implementing Mustard Hub in his flagship education organization, turnover dropped 80 percentage points and top-line revenue grew 42.5% in year one. He then rolled out the system portfolio-wide and saw the same results everywhere.
Modern workforce platforms are designed to capture transactions (hires, terminations, hours, payroll) but miss the upstream behavioral signals - disengagement, sentiment shifts, participation drops - that predict attrition. By the time those behaviors show up as transactions, it's too late to intervene. Mustard Hub fills this gap.
Our reviewer’s read on each dimension, with quotes from the episode.
The episode contains a few genuinely useful structural insights - particularly the framing that HR systems capture transactions but are blind to upstream behavioral signals, and the distinction between metadata-level participation patterns versus content-level surveillance. However, the second half degrades into standard leadership platitudes ('invest in your people,' 'do a lot of listening') and the density of novel ideas per minute is moderate at best.
the disengagement that precedes a resignation or somebody quitting, right, the sentiment shift that precedes that no show all the participation dropped, et cetera. So by the time that those things show up in transactions, it's generally too late to act on them
engagement software kind of came in vogue what fifteen years ago, iship, and it was built for the enterprise model right out of the gate
The 'behavioral workforce intelligence' category framing and the metadata-vs-content-level data distinction are legitimately fresh angles; the critique that engagement software was enterprise-born and never genuinely re-architected for SMBs is a real observation. But the episode's conclusion retreats to recycled takes on listening and humility, and the 'rising tide lifts all boats' philosophy is well-worn.
Behavioral workforce intelligence is a category that really didn't exist five years ago because the infrastructure to generate signal at scale embedded inside platforms and employers use didn't exist
The data that predicts disengagement and sort of voluntary attrition is what I consider metadata level and not content level. In other words, I'm not reading your your messages, but I can tell your participation patterns
Curtis is a credible practitioner who built, scaled, and exited real businesses before productizing an internal tool - he is not a career podcast guest or thought leader. However, Mustard Hub is an early-stage startup and his domain background is music education rather than HR tech, which slightly limits the depth of expertise on display.
I founded an education company about two decades ago that I scaled across the country. I built a roll up portfolio in the space, and I exited all those ventures very early in twenty twenty five just to focus on Mustard Hub
we vetted a lot of different types of engagement softwares, most of which, in fact all of which were built on an enterprise model trying to sell to small businesses
The episode includes concrete churn-cost math walked out in real time - recruiting, onboarding, and productivity-ramp figures from SHRM, arriving at ~$7,200 per churned employee and ~$14M annual burden for a 2,500-person company at 80% turnover - plus the guest's own reported results of 80-point turnover reduction and 42.5% top-line growth. Deductions for the loose 'some statistic out there' ROI claim and some hand-waving about integration architecture.
SARM estimates the cost of hire at roughly forty five hundred employee. That's simply for recruiting. Right. You tack on another thousand to fourteen hundred dollars in in onboarding costs
at a twenty five hundred person mid market company that's churning at eighty percent...that's putting your your burden, your your churn burden it close to fourteen million a year
The host brings relevant personal experience and asks a few probing questions - notably the 'eating your own dog food' follow-up and the 'tools don't fix culture' challenge - but never pushes back on unverified claims (the 80-point turnover drop, the 42.5% revenue figure) and allows the conversation to drift into product pitch territory without redirecting. Questions frequently meander before landing.
tools don't fix culture, And how does your tool increase that engagement? Because the thing is is, I've had that experience where I'm like, we're going to bring in this thing that's going to help with engagement, but nobody engages
However, you eating your own dog food as they say in Silicon Valley, right, like? How how what have you learned about being a better manager and a better leader running an organization that helps people be better managers and better.
Computed from the transcript - who did the talking, and the words that came up most.
In this episode of Schmidt List, Kurt welcomes a special guest, Curtis, founder and CEO of Mustard Hub, to discuss the challenges and opportunities in managing frontline and distributed workforces. Curtis shares his journey from jazz musician and educator to tech entrepreneur, revealing how the pain points of high turnover and the limitations of traditional engagement software inspired him to build a new kind of behavioral workforce intelligence platform.
Transcribed and scored by The B2B Podcast Index.
1 - >
Speaker 1: It's funny. It's that old thing, right, You have to 2 - > spend money to make money. And while it sounds so 3 - > trivial and so old school, the reality is is that 4 - > investing in your people will pay you back. 5 - >
Speaker 2: Running an agency doesn't have to feel like juggling flaming chainsaws. 6 - > At Schmidt Consulting Group, we help you ditch the chaos, 7 - > land more clients, and even enjoy running your business again. 8 - > No fluff, no bs, just strategies that actually work. Check 9 - > us out at Schmidt Consulting Dot Group because your agency 10 - > deserves better. 11 - >
Speaker 3: Today's guest is Curtis, founder of Mustard Hub, a visionary 12 - > transforming how businesses understand and lead frontline teams. Tune in 13 - > as Curtis shares insights on how to beat employee turnover 14 - > and build stronger, smarter organizations. 15 - >
Speaker 4: All right, everyone, welcome to shmid List. I'm your hos KIRCHMD. 16 - > I'm so happy you're here joining me this week. I've 17 - > got a very special guest, my new bestie, Curtis. 18 - >
Speaker 5: Because of a great name. 19 - >
Speaker 1: By the way, Curtis, say hello, Hello, thank you, thanks 20 - > for having me here today. Kurt, I did notice that 21 - > you spell your name wrong with. 22 - >
Speaker 4: Now it's actually the correct way as well. O what 23 - > I understand, we can agree to disagree. 24 - >
Speaker 5: There. There you go. Yeah, well, I appreciate you having 25 - > me here on the show. 26 - >
Speaker 1: I am I'm the founder and CEO of Mustard Hub, 27 - > and really the simplest way I guess to describe what 28 - > it is that we do. 29 - >
Speaker 5: We make the behavior of. 30 - >
Speaker 1: Frontline and distributed workforces very visible to the people responsible 31 - > for leading them. 32 - >
Speaker 5: And we can get into more about what that means 33 - > in a. 34 - >
Speaker 1: Bit, but I think in a succinct way, that's kind 35 - > of what we do a little bit about my background. 36 - > Early in my career, I spent fifteen years on the 37 - > Jests or Get playing and teaching music. I founded an 38 - > education company about two decades ago that I scaled across 39 - > the country. I built a roll up portfolio in the space, 40 - > and I exited all those ventures very early in twenty 41 - > twenty five just to focus on Mustard Hub, which we'd 42 - > been building for about two years at that point. 43 - >
Speaker 4: So that brings us, that brings us to today. All right, 44 - > And so what was the driving force with starting this? 45 - > Was it you saw a gap or you had a passion. 46 - > Both will tell me more about that. 47 - >
Speaker 5: Both. So our workforce that. 48 - >
Speaker 1: We had been leading musicians, teachers, folks in the education space. 49 - > It grew considerably over the years, and we suffered from 50 - > i'd say, what a pretty typical picture of turnover looked 51 - > like in most frontline industries, and then right around co 52 - > when COVID, When COVID hit, it forced us to rethink 53 - > our people strategy, how we went about hiring people, how 54 - > we went about interacting with them on a daily basis, 55 - > just our general people ops and we I mean to 56 - > your to your question, yes, I mean I do have 57 - > a general passion for leadership and working with people. I'm 58 - > a people person, I feel like, but also I think 59 - > most of my leadership decisions are driven by the people 60 - > that we work with. I know that they're always going 61 - > to be the backbone, right of any organization that you're 62 - > you're runnings, and in an organization with so many frontline workers, right, 63 - > they are the face of your of your business. 64 - >
Speaker 5: Yeah. 65 - >
Speaker 1: So COVID brought a lot of challenges and we really 66 - > wanted to reinvest in our people as we were measuring performance. 67 - > It probably comes as no surprise that those those those educators, 68 - > those those staff members that we worked with who stayed 69 - > longer right, wound up doing that much better for the organization. 70 - > The organization thrives right as our turnover went down and 71 - > the more or turnover went up, not over. Not only 72 - > were we turning staff members, but client relationships also disintegrated 73 - > rather quickly. 74 - >
Speaker 5: So and it's not like that in. 75 - >
Speaker 1: Every high turnover industry, right, I mean, but the cupcake 76 - > shop folks aren't necessarily going to stop going there simply 77 - > because the person at the cashier doesn't work there anymore. Right, 78 - > But in organizations with really high touch staff and customer relationships, 79 - > it can often mean. 80 - >
Speaker 5: Whether or not a customer six or own. 81 - >
Speaker 1: So we actually we vetted a lot of different types 82 - > of engagement softwares, most of which, in fact all of 83 - > which were built on an enterprise. 84 - >
Speaker 5: Model trying to sell to small businesses. 85 - >
Speaker 1: In fact, it's still that's all it is now, right, 86 - > I Mean, engagement software kind of came in vogue what 87 - > fifteen years ago, iship, and it was built for the 88 - > enterprise model right out of the gate. And now it's 89 - > become fairly commoditized, and every entrant is essentially buildings similar 90 - > software and competing on price maybe or they're feature flagging 91 - > and how they gate them right to sell to the 92 - > small business customer, and it simply doesn't work for the 93 - > small business realities and how they govern their p and ls. 94 - >
Speaker 5: It just doesn't. 95 - >
Speaker 1: And as much as we vetted all of the existing 96 - > software on the market to better engage our people, we 97 - > really discovered that this would be something that we can 98 - > be It would be more effective if we just built 99 - > it internally and it didn't have it also didn't have 100 - > to be pretty. We could build it into our system, right, 101 - > and so we did that. We built it on top 102 - > of proprietary software we already owned, and then it gave 103 - > us the ability also to measure data points in a 104 - > variety of different ways we never would have been able 105 - > to do with some third party out of the box right. 106 - >
Speaker 5: The software system. So we did that. 107 - >
Speaker 1: After year one, our turnover dropped eighty percentage points. 108 - >
Speaker 5: Top line grew about forty two and a half percent 109 - > in year one. 110 - >
Speaker 1: So a lot of the bets that we made, like 111 - > it's not like it was cheap, right, but we made 112 - > a big. 113 - >
Speaker 5: Bet on our people, and it really paid off. 114 - >
Speaker 1: And so after I mean we started that in our 115 - > in our flagship ORG and then we rolled it out 116 - > portfolio wide right in the in the roll up that 117 - > I had, and we had the same results everywhere. So 118 - > at that point in time, I made the decision to 119 - > productize it. And that the irony here, and I do 120 - > feel it is a bit It is a bit ironic. 121 - > Is it wasn't necessarily intended for to spin off to 122 - > be its own thing for mass consumption. The goal that 123 - > I had was to just give it to all my competitors. 124 - > The reason why is that I'm very much a firm 125 - > believer of if others in my space are doing well, 126 - > then I'm doing well because it makes the space look good. 127 - > If others in my space are doing terribly, that's essentially 128 - > going to turn off customers entirely to the right to 129 - > the whole category. 130 - >
Speaker 5: And so I had a great real people attitude. 131 - >
Speaker 1: I right, a rising tide, right, and that's generally my attitude. 132 - > And I had good relationships with most of my competitors, 133 - > and from time to time we talk, we'd interact, we'd 134 - > go grab a beer together if we were local, and 135 - > we'd try to help each other out. And I built 136 - > this as a standalone so that they could use it 137 - > and have a similar experience right where there could even 138 - > potentially be some portability right for the earned value that 139 - > some of these folks would have on our platform. There 140 - > was a little bit of a novel idea. 141 - >
Speaker 5: Right at the time, this idea of portability, but that 142 - > was essentially the reason why. 143 - >
Speaker 1: Why I productize it my first and I'll shut up 144 - > here in a second. Although my first customer out of 145 - > the gate was my kid's preschool because about a couple 146 - > of weeks, literally a couple of weeks before we launched it, 147 - > they lost another teacher. So I went to the owner 148 - > and we just had a real discussion and I said, hey, look, 149 - > I don't know if I can help you here. 150 - >
Speaker 5: I mean, we're sticking around. 151 - >
Speaker 1: We love this place and we love the people here, 152 - > and I know you do too. I built this thing 153 - > and it could be helpful for you. They jumped on 154 - > two weeks later and they've been using it ever since. 155 - >
Speaker 4: Still, that's awesome, And I have so many questions for you, Curtis, 156 - > because as a business owner in the past, when I 157 - > had a large team and things, we just like you mentioned, 158 - > we installed lots of engagement things right, and there was 159 - > everything from more enterprise version looking things to basically some 160 - > version of like a Tamagatchi hr like like little slack 161 - > bots and things that did stuff. And I think one 162 - > of the biggest challenges was, again, there's something I bring 163 - > up a lot. The audience will probably be sick of 164 - > me saying this, but tools don't fix culture, And how 165 - > does your tool increase that engagement? Because the thing is is, 166 - > I've had that experience where I'm like, we're going to 167 - > bring in this thing that's going to help with engagement, 168 - > but nobody engages. 169 - >
Speaker 5: With it, right, Well, so what's your approach there? 170 - >
Speaker 1: No, I appreciate you bringing that up, And probably the 171 - > way I would start to answer this question is with 172 - > some reframing around what it is that mustard Hub is. 173 - > Sure the story originates from an engagement like that's part 174 - > of the origin story, but Mustardhub itself is embedded behavioral. 175 - >
Speaker 5: Infrastructure for the workforce. So we don't sell software to employers. 176 - >
Speaker 1: We integrate inside platforms that they already use ats, payroll compliance, 177 - > vertical SaaS and were built to generate this continuous behavioral 178 - > signal that those systems were never designed to produce, so 179 - > to sort of double click on that. Workforce platforms today 180 - > are built to capture transactions and they do a phenomenal 181 - > job of it, right, hires, terminations hours, payroll runs, compliance events. 182 - > They're very good at that. But what they don't see 183 - > is the behavior that drives those events, right, the behavior 184 - > upstream that drives those outcomes, and like the disengagement that 185 - > precedes a resignation or somebody quitting, right, the sentiment shift 186 - > that precedes that no show all the participation dropped, et cetera. 187 - > So by the time that those things show up in transactions, 188 - > it's generally too late to act on them. And what 189 - > Mustardhub does. We embedd inside these platforms and we fill 190 - > that gap. We can use engagement in different types of 191 - > engagement indices when in some gamified reinforcements some sentiment inputs, 192 - > et cetera, to create sustained behavioral interaction, That interaction generates signal. 193 - > The signal predicts attrition early enough to intervene. And so 194 - > that's essentially where we live is in generating this signal. 195 - > Our primary output is AI predictive insights. Who's a flight 196 - > risk and when right, what's their risk trajectory and index 197 - > and quantified the financial impact of that exit. And so 198 - > again origin story is in engagement, but Mustard Hub is 199 - > built as infrastructure and that infrastructures in these systems to 200 - > generate those that signal that they were never designed to produce. 201 - >
Speaker 5: Got it? 202 - >
Speaker 4: And so why why does someone need this? 203 - >
Speaker 5: I mean? Is it? 204 - >
Speaker 4: This kind of goes back to like, I mean, the 205 - > question I want to ask you is like, what are 206 - > the common mistakes you're seeing people make in these management 207 - > and these people management things? And does and does this 208 - > help them? But is there a specific problem that people 209 - > have or is it is it the same problem? Is 210 - > it a multitude of problem? Like what is it when yeah, 211 - > they are like, yes, I need this. 212 - >
Speaker 1: Well, I think Kurt I would probably call it a 213 - > one trillion dollar problem, Right, that's what That's what charn 214 - > is costing ussmbs every year. 215 - >
Speaker 5: I would say so. 216 - >
Speaker 1: SARM estimates the cost of hire at roughly forty five 217 - > hundred employee. 218 - >
Speaker 5: That's simply for recruiting. 219 - >
Speaker 1: Right. You tack on another thousand to fourteen hundred dollars 220 - > in in onboarding costs, and then with your loss of 221 - > productivity generally employees are only about twenty operating in about 222 - > twenty five percent efficiency for generally the first four weeks. 223 - >
Speaker 5: Right, that's a sort of a. 224 - >
Speaker 1: Measured estimate right, Yeah, you're looking at about seventy two 225 - > hundred dollars all in for the cost of an individual 226 - > employee churning. Now, in some high turnover industries, your cost 227 - > of recruiting is arguably half right, So okay, so forty 228 - > five hundred dollars. And if you're operating a business with 229 - > fifty people, with one thousand people, with twenty five hundred people, right, 230 - > SMB means different things to different people. You can quantify 231 - > that financial impact, and that becomes incredibly painful. 232 - >
Speaker 5: So at a. 233 - >
Speaker 1: Twenty five hundred person mid market company that's churning at 234 - > eighty percent, right, there's a lot of mid market retail 235 - > out there with majority frontline and distributed workforces that are 236 - > operating at roughly eighty percent turnover. Well, if you have 237 - > twenty five hundred people and you're losing two thousand of 238 - > them a year, that's putting your your burden, your your 239 - > churn burden it close to fourteen million a year. I mean, 240 - > walking through the math like that kind of forces it 241 - > into your face how painful that is. And I think 242 - > that you asked, what are they doing wrong? Are they 243 - > doing something wrong? Well, yes and no, But it depends 244 - > on a lot of factors. I mean that the micro smalls, 245 - > more franchise style businesses, a lot of them are led 246 - > by former employees who felt like they could make a 247 - > better cupcake, right, they start their own business, they have 248 - > very little experience leading people or leading organizations. That doesn't 249 - > make them bad managers, it just makes them inexperienced managers, right. 250 - > And when operators lack the people experience, your first instinct 251 - > is to cut things to make your margins look better, right, 252 - > rather than investing in your people. 253 - >
Speaker 5: Right. 254 - >
Speaker 1: Who are the ones that are essentially the face of 255 - > your business right? 256 - >
Speaker 5: Right? 257 - >
Speaker 1: So a lot of it could be management, could be training, 258 - > could be onboarding, could be a lot of different things, 259 - > could be the engagement. 260 - >
Speaker 5: Right. 261 - >
Speaker 1: So that's kind of hard to give a blanket statement about. 262 - > But I think that the problem that we recognized in 263 - > the market, right is, again, these systems that we use 264 - > every day, they are very good at recording transactions, and 265 - > that's what they were built to do. It's not any 266 - > kind of efficiency on their part, it's simply a structural 267 - > limitation of theirs that there's zero visibility into the behaviors 268 - > upstream that. 269 - >
Speaker 5: Affect those outcomes. 270 - >
Speaker 1: And so what we decided to do, and this was 271 - > a pivot right a couple of years ago, is to 272 - > create that infrastructure for those platforms so that they can 273 - > help these managers, employees, operators and give them operator ready data, information, 274 - > analytics and insights that they can act on. 275 - >
Speaker 4: So, how do you determine which platforms you integrate with? 276 - > Is it based on like how are you making those decisions? 277 - >
Speaker 5: I think that right now, we're. 278 - >
Speaker 1: We are still in that phase where we've obviously had 279 - > HR and HR adjacent platforms I think tend to be 280 - > the most likely I think of targets for us, right, 281 - > But what I think that as we as we look 282 - > at different segments, we maybe are talking about different products. 283 - > For example, we have different ways to integrate and embed 284 - > our system, everything from really simple partner links and sso 285 - > to white labeled infrastructure to embedded API, right and with 286 - > larger hcms that may have certain elements that our infrastructure has. 287 - > Maybe the goal isn't necessarily to white label a system, 288 - > but to use that pure embedded API, that infrastructure where 289 - > we can ingest data and processes through our AI models 290 - > and then provide the output, right that they can render 291 - > is one option, right, but you look to other organizations 292 - > who lack significant engagement capabilities and want to white label 293 - > the whole entire thing so that they can own that 294 - > under their brand and so ATS compliance, payroll, HRIS systems, 295 - > fullcm ecosystems, et cetera really make great candidates for those 296 - > types of things. 297 - >
Speaker 5: Yeah, others like workforce sas and or workforce ops and 298 - > and vertical sas may. 299 - >
Speaker 1: Maybe sometimes lack engineering power right to do that, and 300 - > so we have lower lift, lower resource like partner link 301 - > in Sso that makes it really simple and really easy 302 - > to do. 303 - >
Speaker 4: Yeah, I get that. So who's the user of this? 304 - >
Speaker 5: Is it? 305 - >
Speaker 4: Like you mentioned, if it's a twenty person place, it's 306 - > probably the founder, right. But is the majority of the 307 - > people you're working with have a dedicated HR. 308 - >
Speaker 5: Yeah, that's a good question. It very much varies. 309 - >
Speaker 1: So I'd say probably a lot of the sub seventy 310 - > five person sub one hundred person teams there's an operator. 311 - > There could be a dedicated HR practitioner. Oftentimes it could 312 - > be someone in an OPS role who also owns that 313 - > HR responsibility. They're the ones going to be responsible for 314 - > setting it up. But it's very much a flywheel, right, 315 - > Like a lot of engagement software the infrastructure side of it. 316 - >
Speaker 5: Right. Once you get that. 317 - >
Speaker 1: Going, I mean it generally runs itself. 318 - >
Speaker 5: You have folks interacting on the platform. 319 - >
Speaker 1: Once your systems are connected, right, we're able to pull 320 - > in data from a variety of sources. 321 - >
Speaker 5: Right. 322 - >
Speaker 1: So it's not like most engagement software that require continuous 323 - > usage on a daily basis in order to be effective 324 - > and to be able to provide really like robust predictive insights. 325 - >
Speaker 5: The interaction can be. 326 - >
Speaker 1: Episodic, while the insights and signal that we're generating is perpetual. 327 - >
Speaker 5: Right. 328 - >
Speaker 1: So that's actually one of the really nice things about 329 - > it is that. 330 - >
Speaker 5: It matters. 331 - >
Speaker 1: It relies less on heavy team activity, right, in order 332 - > to produce that continuous. 333 - >
Speaker 5: Does that make sense? It makes sense? 334 - >
Speaker 4: Well, that kind of goes back to my question about 335 - > like how do you get people to engage with the software, 336 - > And it sounds like it doesn't need like a big 337 - > oh now this is part of your daily job is 338 - > exactly is to answer. 339 - >
Speaker 5: How are you feeling questioned today? You know exactly it doesn't. 340 - >
Speaker 1: And just to go a step further, right, if there's 341 - > an HCM platform that embeds the API infrastructure, that that's 342 - > pure infrastructure, right, you're not really even white labeling the 343 - > part of the engagement infrastructure that's just data flows right 344 - > bi directionally. So when in some cases there may not 345 - > even be an engagement platform to engage with, right depend 346 - > depending on depending on how the platform chooses to chooses 347 - > to integrate with us. So, but yes, I mean there 348 - > is a there is some some engagement infrastructure there. There 349 - > are a lot of ways that on that platform that 350 - > teams can can interact with each other that can generate 351 - > a lot of signal, but it's not necessarily required on 352 - > a daily. 353 - >
Speaker 5: Basis in order to be extremely effective. 354 - >
Speaker 4: Okay, So, however, you eating your own dog food as 355 - > they say in Silicon Valley, right, like? How how what 356 - > have you learned about being a better manager and a 357 - > better leader running an organization that helps people be better 358 - > managers and better. 359 - >
Speaker 5: What we do? 360 - >
Speaker 1: We use it every day and it becomes less what's 361 - > the word I'm looking for? It feels less chore like, Right, 362 - > The more that you do it, it becomes a lot 363 - > of fun and we really enjoy it. I will say 364 - > that the interesting thing what helped me become a better manager. 365 - > I'll preface this by saying I am I am not 366 - > a data scientist. That is not my it's not my 367 - > domain of expertise. However, as I work with these incredibly talented, 368 - > very technical team members that I that I work with 369 - > every day, we're working to improve these systems. 370 - >
Speaker 5: And we're forced to. 371 - >
Speaker 1: Really evaluate right because again we we we generate predictive insights, 372 - > you know, right, and and we quantify what that financial 373 - > impact will be, right and what we can do about 374 - > it right recommendations, recommended actions right for for different different folks, 375 - > And so it forces us to really critically evaluate the 376 - > efficacy of each and every output that we see and 377 - > measure it against. 378 - >
Speaker 5: Our our own behaviors, our own intuition. 379 - >
Speaker 1: We have real conversations with folks about this right because 380 - > we're building it. But then we also start to see right, 381 - > these insights that it will yield. So I can sit 382 - > down with Luca or Serge, Alex, Yvonne, any of these 383 - > folks and look at these insights and say, this is 384 - > what it's telling me, how. 385 - >
Speaker 5: Do you feel about that? 386 - >
Speaker 1: And it's forced me to really look at and evaluate 387 - > how I'm doing what I'm doing in a little bit 388 - > of a different way. You might imagine a manager might 389 - > look at some of these things and take it at 390 - > face value. Well, that's great because the software has been 391 - > created for them, But I'm actually the one building it, 392 - > so I have to look at it through a different 393 - > sort of more critical lens. 394 - >
Speaker 4: Right, Yeah, and how do you do that? I mean, 395 - > how what does that process look like for you? 396 - >
Speaker 5: I'm still learning, Kurt. 397 - >
Speaker 1: I'll be the first to tell you that I don't 398 - > have it figured out. It's it's a nascent space. Behavioral 399 - > workforce intelligence is a category that really didn't exist five 400 - > years ago because the infrastructure to generate signal at scale 401 - > embedded inside platforms and employers use didn't exist. And we're 402 - > building this category. It forces us to rethink a lot 403 - > of different things. One of our core values is burn 404 - > the box. Right, What does that mean? Well, a lot 405 - > of times we tend to think inside of a box, 406 - > and so the whole goal here is to not even 407 - > think outside of the box. Is to imagine that a 408 - > box just never existed in the first place. 409 - >
Speaker 5: Ah. 410 - >
Speaker 1: Sure, right, And so this this idea of behavioral workforce intelligence, right, 411 - > the continuous capture and structure of post higher employee behavior 412 - > into some predictive signal when and measuring the event that 413 - > the behaviors that happen between events. Right, Yeah, it's a 414 - > it's a shift in thinking from reactive to predictive. 415 - >
Speaker 5: Right. 416 - >
Speaker 1: Obviously it's capable. We have this capability now with with AI. 417 - > And so to your question, how do you do that? 418 - > I think we're learning every day. I'm learning new things 419 - > about my team every day, learning how to have conversations 420 - > I'd never thought i'd have before. And the conversations are 421 - > genuinely they're they're genuinely led by curiosity and exploration. In 422 - > a lot of HR, you are, you're often having a 423 - > conversation about something that happened past tense and it gets difference, right, 424 - > is that you walk into HR when someone said something, 425 - > or someone did something, or you need time off, or 426 - > something happened, right, Yeah, very reactive. BWI tells you what's 427 - > about to happen while there's still time to do something 428 - > about it. And so this is where it gets really 429 - > really interesting. And so when I have the answer to 430 - > that question you asked, I'll make sure to come back 431 - > and you next episode. 432 - >
Speaker 4: Well, there's lots of books out there people try to 433 - > answer that question. Right, that's the next question I was 434 - > going to ask you. I mean, what sort of activities 435 - > and things are you do you do to what sort 436 - > of mindset for you to be a better leader and manager? 437 - >
Speaker 3: What? 438 - >
Speaker 5: Well, how do you approach it? What's your philosophy? 439 - >
Speaker 1: Well, software engagement Software in a vacuum by itself is 440 - > not going to improve relationships, right, It takes people. 441 - >
Speaker 5: Software is there to augment, right, It's there. 442 - >
Speaker 1: To help facilitate some interactions. My team is fairly small, 443 - > and it's important that I do one on one time 444 - > with all of them, but either weekly or bi weekly, 445 - > and that's really valuable time to get really personal perspective 446 - > on not just things that we're doing inside of the organization, right, 447 - > but the interactions between everybody and how things can be 448 - > improved right or frankly what we're doing right. Also getting 449 - > that validation from a lot of the folks, right, and 450 - > even what they feel like they can improve on or 451 - > do differently, or what they want to bring to the table. 452 - > I work with some incredibly, incredibly smart people and we 453 - > really try to push these values that we have. And 454 - > what's nice is you start to see everybody being an 455 - > idea person, right, even though some for some folks it's 456 - > not maybe they don't consider it their strongest asset, right, 457 - > but you put everybody in this position to have a voice, right, 458 - > to feel that sense of belonging and to contribute. Right, 459 - > No one is just clocking in and clocking out, right, 460 - > We're all sort of contributing. 461 - >
Speaker 5: To the greater good. 462 - >
Speaker 1: And if one person is not pulling in the direction 463 - > that they need to, the whole thing doesn't work. And 464 - > I think it's instilling that mentality that in order for 465 - > this to function and move forward, everybody has to pull 466 - > in the same direction and has to do their part, 467 - > and when one person doesn't, it all falls apart. And 468 - > I think when your team, when all of your team 469 - > embodies that right and it feels that sense of responsibility, 470 - > amazing things can happen and we're able to make magic 471 - > happen that and that's another one of our of our 472 - > big things, right, and we all, I think we all 473 - > take that that kind of ownership that you can move buttons. 474 - >
Speaker 4: The greatest skill I think I had as a manager 475 - > was just curiousosity, you know, And that was enough to 476 - > get me through my early years as a manager, because 477 - > I was really bad at it. I got better at it. 478 - > But that's the thing is, like they the story goes right, 479 - > like people forget jobs. People forget projects, but you never 480 - > forget your manager. 481 - >
Speaker 1: It's it's true, and it's not an exact science. I 482 - > know that people will look to their leaders and their 483 - > managers for answers, but I also think that one of 484 - > the things that managers and leaders can do to earn 485 - > the most respect is demonstrate humility and when you don't know, 486 - > being honest about that, right, you know, is going to 487 - > do wonders for the respect that your team gives you 488 - > because you're just not you're not just bullshitting people. 489 - >
Speaker 5: Yeah, right, you might allow to say that you're hopefully 490 - > that's okay. 491 - >
Speaker 4: You're right, it's not for kids. But I would say, 492 - > with that in mind, do you see do you see 493 - > what what's coming? Because of like you said, like this 494 - > this tool helps predict some of these things. Is there 495 - > commonality like what people should be looking out for? Are 496 - > there trends? Is it different for every place? Like what 497 - > has the last couple of years taught you? 498 - >
Speaker 1: That's a good question, and yes there's trends. Yes, it's 499 - > taught me a lot of things. Yeah, I think that 500 - > it's it's a really interesting age that I think we 501 - > are running into. Right, We're not really crawling or walking 502 - > into it. I think we're at a full on sprint 503 - > when we talk about behavioral intelligence. I think a critical 504 - > distinction I should make is it we're not really talking 505 - > about workforce surveillance. Sure, and it's important, I think to 506 - > bring up this distort. You're not the panaere of VHRS. 507 - > That's not on your website. No, I mean it's out 508 - > there and there's a lot of discussion about it. I 509 - > just in fact, I wrote an article not that long 510 - > ago about workforce surveillance and what that looks like compared 511 - > to analytics. 512 - >
Speaker 5: For example, when you ask what's coming down the. 513 - >
Speaker 1: Pike, Yeah, there's a fair amount of software that's being 514 - > developed to surveil the workforce. And I think that privacy 515 - > concerns are real and legitimate, so important topic to discuss. 516 - > I think it's important to focus on what signal actually is. 517 - >
Speaker 5: Right. 518 - >
Speaker 1: The data that predicts disengagement and sort of voluntary attrition 519 - > is what I consider metadata level and not content level. 520 - > In other words, I'm not reading your your messages, but 521 - > I can tell your participation patterns, like how often someone's 522 - > engaging with something, right. I can also read transactional data 523 - > that already exists right in these HR systems, how often 524 - > you change managers, if you ever get pay raises or. 525 - >
Speaker 5: Not, how often you take your PTO? Right. 526 - >
Speaker 1: These things that data can read and that they can process, 527 - > along with more meta data level participation patterns and engagement drift, 528 - > the connection topology that the who interacts with things, and 529 - > how often and how that web changes over time. These 530 - > are things that don't really invade people's privacy. Reading your 531 - > Slack messages will invade your privacy. We don't do that, right, 532 - > and so, but that software does exist. So it's interesting 533 - > that you ask that question because I think ultimately it 534 - > brings up the conversation of what responsible insights actually mean. 535 - > And again, we're we're sprinting into this new age where 536 - > a lot of things are possible. 537 - >
Speaker 5: Yeah, and you know, so those are some things that 538 - > I'm saying that. It's very interesting. 539 - >
Speaker 1: Everybody's looking to adopt AI in different ways. Everybody is 540 - > you know, you're here a leader. I'm sure you probably 541 - > hear this all the time, right. Leaders will come to 542 - > you saying, I want AI in my system. Okay, well 543 - > what do you. 544 - >
Speaker 5: Want it to do? I don't know, I just want it. 545 - > Everybody else has it? We need yeah, right, so. 546 - >
Speaker 4: Yeah, we want AI when you want it, Now, what 547 - > do you want it to do? 548 - >
Speaker 5: We don't know? 549 - >
Speaker 1: Yeah, exactly, exactly, yes, So that's the These are obviously 550 - > things that I that I think are important to discuss, 551 - > you know, how data is used, if it's used for 552 - > people versus being used on people. You know, I think 553 - > that those are the big count of stations that kind 554 - > of need to be happening. Now, yeah, I would agree. 555 - >
Speaker 4: So if you had some advice for managers leaders today 556 - > after the last few years of doing this, what would 557 - > you tell. 558 - >
Speaker 1: Them, Well, my advice to the operators who are running 559 - > the businesses might be different from the those Yeah, we'll 560 - > give me both the platforms themselves that are helping the 561 - > people running the businesses. But it's not easy to see 562 - > around corners and unless you have some really helpful software 563 - > that you know, or infrastructure that can help facilitate things 564 - > like that. Doing things the old fashioned way means doing 565 - > a lot of listening, a lot of patients and a 566 - > lot of listening. 567 - >
Speaker 5: And my I mean that that it's a it's a 568 - > it's a small thing, but it's a big thing. 569 - >
Speaker 1: Right. Listening means so many different things from how you 570 - > run your business to what somebody might need in their 571 - > personal life or so that there's a variety of things 572 - > that I think operators and business owners beyond. I think 573 - > that things stretch beyond the numbers that you see on 574 - > the page right. 575 - >
Speaker 5: On your P and L yep. 576 - >
Speaker 1: And one thing that I learned, I think from running 577 - > all those businesses is that it's funny. It's that old thing, right, 578 - > you have to spend money to make money. And while 579 - > it sounds so trivial and so old school, the reality 580 - > is is that investing in your people will pay you back. 581 - > I think there's some statistic out there, maybe from Sherm 582 - > it was like for every dollar you invest in your people, 583 - > it pays you back for And that's not a joke. 584 - > I mean that is a for real thing, and I 585 - > think where everybody is trying to cut there's an argument 586 - > for investing in your people in some different ways. 587 - >
Speaker 3: Right. 588 - >
Speaker 5: That doesn't mean. 589 - >
Speaker 1: That that people sometimes downsizing is a necessary evil. I'm 590 - > not going to sit here and say that people shouldn't 591 - > or can't do that, and you should always be hiring 592 - > more and invest more of your people. 593 - >
Speaker 4: Know. 594 - >
Speaker 1: What I'm saying is is that there is a place 595 - > to be investing in your people right and in your workforce, 596 - > and I think when done properly, those things are going 597 - > to pay significant dividends. And generationally, we all have different needs, 598 - > the millennials, boomers who are still in the workforce. 599 - >
Speaker 5: Gen X left myself out of that one. 600 - >
Speaker 1: We all need different things, and I think that that's 601 - > where a lot of the listening comes in. There isn't 602 - > really a one size fits all for everyone. And those 603 - > great managers and those great operators, the people that you 604 - > remember right, like you pointed out, those are the folks 605 - > that listen intently and really want to do right by 606 - > their people. And so that's really kind of the best 607 - > advice that I can give them. 608 - >
Speaker 5: I love it. I think it's very sound advice. 609 - >
Speaker 4: So well, Curtis, I want to thank you for taking 610 - > the time on a busy day join me if I 611 - > want to get in touch with you, if I want 612 - > to learn more about the product, if I want to 613 - > connect with you. 614 - >
Speaker 5: Where's a good place to go? Awesome? I love that. Yes, 615 - > and thank you Kurt for having me here. 616 - >
Speaker 1: You can visit mustard hub dot com to learn more 617 - > about mustard Hub. You can find us on LinkedIn as well. 618 - > We're on substack at Behavioral Workforce Intelligence dot SUBSEAC dot com. 619 - > Feel free to reach out to us. You can reach 620 - > out to me directly Curtis at Mustard hub dot com 621 - > and yeah, we'd love to hear from everybody and interact 622 - > in the public sphere. 623 - >
Speaker 5: Awesome. 624 - >
Speaker 4: Well, thanks again, Curtis. I really appreciate it. 625 - >
Speaker 5: Appreciate you. 626 - >
Speaker 6: Thanks for listening to schmid list. If you found this 627 - > episode useful, a quick review goes a long way. To 628 - > learn more about the work Kurt does helping businesses grow 629 - > with more clarity and profit, visit Schmidt Consulting dot group. 630 - > Have a great week.
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