Chason Hecht, CEO of Retensa, discusses employee retention strategies, emphasizing the importance of understanding workforce data to address employee turnover. He introduces three laws of retention, highlighting the need for organizations to focus on retaining high performers and understanding the changing dynamics of employer-employee relationships. Hecht also stresses the importance of data in predicting turnover and improving employee experiences.
Chason Hecht, CEO of Retensa, discusses employee retention strategies, emphasizing the importance of understanding workforce data to address employee turnover. He introduces three laws of retention, highlighting the need for organizations to focus on retaining high performers and understanding the changing dynamics of employer-employee relationships. Hecht also stresses the importance of data in predicting turnover and improving employee experiences.
Takeaways
Title Options
Sound bites
"Retention is crucial for success." "Data predicts employee turnover." "High performers drive growth." "Turnover is a symptom, not a problem." "Focus on root causes of turnover." "Employer relationships are evolving." "Predictive analytics enhance retention." "Understand workforce data for success." "Retain high performers for growth." "Retention laws guide effective management."
Chapters
Michael Bernzweig (00:00.205)
Welcome to Software Spotlight, recorded live from Software Oasis AI Summit. Today's episode features Chasen Hecht, founder of Retensa, revealing the science behind employee retention, his founding story, and some real world Q &A on strategic AI transformation. Discover how consultants help top organizations keep their best talent and why retention is your competitive edge. Listen for exclusive insights.
and your invitation to connect at our next summit. Michael Bernsweig, your host and the founder of Software Oasis. Joining us this week, have Chason Hecht, the founder of Retensa. And Chason has actually taken a few minutes out before his presentation to join us on this podcast live. And I really appreciate you taking a few minutes out, Chason. Great to be here. Great dialogue, incredible topics.
for this conversation as good as I've ever seen. So thank you so much. Fantastic. You know, just for any listeners that may not be familiar with Chason or Retensa, he is a popular keynote speaker. You may have heard him at conferences all the way from Adobe to the United Nations, delivering insights from all parts of the world, from Kentucky all the way to Kuala Lumpur. So with that, Chason, we're honored to have you on the event today.
If you could share with us a little bit about your journey prior to starting Retensa, which I know is you're to have to dig through the memory banks because that's, that's quite a few years ago, myself, but it gets cloudy fast. really does. But there's, there was a discrete moment, certainly that was the spark for the organization a hundred percent. I had worked in a family business. The family business was.
actually manufacturing textiles on the west side of Manhattan, something that we don't really do much of anymore in Manhattan. And then I went to work for a construction company and I then was at an IT, a global IT consulting firm. And the spark occurred when we were actually relocating offices. And I was at the time in charge of IT, WAN land, architecture, infrastructure, the kinds of, you know, connecting from New York to London for projects. More years ago than I
Michael Bernzweig (02:26.895)
you know, care to share. That was actually a lot harder than pushing buttons. And so we're relocating anyway, and I was a part of that relocation. And we pulled the office manager, kind of like the local HR manager's desk away from her wall to move it over. And someone brought me over an envelope, an envelope, giant envelope, full of hundreds of papers. And I opened that envelope and what I found were 300 employee surveys.
And my employee survey that I had taken, I had never done an employee survey before. And I was so impressed. I was so thrilled when I got it. was like, this is amazing. This company is like leaning into the employee experience and what's important to them. It was really a warm and fuzzy moment when I filled it out until I discovered that it had fallen behind her desk and she never sent them in. And I standing there with two other people and all of us were silent, completely stunned that.
The New York office, the largest by far, in the organization with tremendous revenue and 450 employees, lost the entire voice back to the organization. That survey had closed months earlier. And at that point I realized that number one, we should probably not be using paper. That seems inefficient. There's probably a better way to do this using technology. And just how much easier it was if we knew, if there was some connection to
what people thought and felt at an organization. At that point, I didn't know what I would call it. I didn't know what it would be. I didn't know we'd be in 59 countries and 22 languages when I made that technology to predict why people joined Stainly. But I knew that better way was out there and I wanted to know it. didn't want to experience the feeling of being completely ignored and the people I was standing next to didn't feel heard ever again.
So here we are in the year 2025 and obviously Retensa is vibrant, a global organization at this point and you've obviously become a leader in the space. Can you share with me a little bit about the challenge that Retensa solves for your clients? What does that look like? How are you helping? Yeah, absolutely. Well, if you have employees, you have employee issues, right? And there's breakdowns in
Michael Bernzweig (04:49.699)
that employee experience. And oftentimes the manager, the leader, the director of a division department, they can no longer have their finger on the pulse of what's happening every day with developers, with sales, marketing, operations team. This is just impossible to now. And so the problem we solve is unlocking the insights that's hidden in that workforce, in that experience, and then translating it into real world solutions.
based on the industry, based on the culture. What you do at a construction company to motivate and engage staff is not what you do at your accounting firm, and it's not what you do at your high-tech operations. Knowing why people join, stay, and leave the motivational drivers allows us to then act and respond to exactly what that experience is. In the context of our culture, our industry, our company size, the 200-person organization,
You know, in the 200,000 person organization and we have clients across the spectrum. They operate under totally different scaffolding of change and implementation. yeah, once one doesn't work, you know, when works, what works over there doesn't work someplace else. So knowing what they need and what to do about it. That's it. Yeah. Having the right, the right focus and visibility across so many organizations and data. mean, obviously understanding of the common data points, but.
Really looking forward to the presentation coming up in just a little bit. know you have to get prepared for that coming up after for anyone that is excited about it. We'll have that Q and a session. So people can ask all those questions that they may not have heard during the presentation itself and any other things that come to mind. So that'll be a lot of fun. And for anybody that is new to the spotlight podcast series each week, we have.
founders and on the episodes, you'll actually hear, if you were at the live event, you'll hear answers to your questions that were raised at the live event. So it's a fun way to interact on any of our podcasts over, over the events and kind of tying it all together. So I will get everybody onto the presentation. Thanks. Okay. I hope everyone's having a great time at the event. We've had a packed day with a lot of education and learning. Our next speaker is Chason Hecht.
Michael Bernzweig (07:11.526)
He's an advocate and innovator of employee retention strategies and the founder and CEO of Retensa. With predictive analytics software used by organizations in 59 countries and 22 languages, Retensa unlocks the insights hidden in workforce data to address the social and financial impact of employee turnover. What common question kicks off your research on employee retention? If you're running a
business or a department or division, there's probably a question that comes up at some point or some version of how long is Kevin going to stay or maybe it's some version of, can we get another developer or possibly you're asking something like, you know, when will our next employee or salesperson or QA developer quit? This, if it hasn't crossed your mind, probably will.
at some point in the near future when that great developer or QA or Kevin does quit. And this is a reality of the modern workplace, right? The realities of the modern workplace are that we can't expect and we don't plan for perpetual employment. so understanding what is governing these choices, these motivational behaviors is the science of employee retention. How people join, stay and leave an organization is something that we've studied for
25 years and this is actually our 25th anniversary and I'm happy to say that I've distilled 25 years of insights into three laws and a whole lot of postulates and Interpretations and theories but I can tell you there are three laws of employer retention and that's what I'm going to share with you today That's what anyone who's in this conversation is going to hear and understand is at the very least if you're trying to motivate engage retain high performers in your
division, unit, team, or company. Then it's important to know that these three laws exist. Whether you believe them or not, gravity happens. I might disagree with gravity, but that doesn't mean I'm gonna fly. And these laws happen. These laws are real. As real as the speed of light, as real as every other law of nature, here are the three laws of retention that are gonna be helpful in your organization. Now, there's a lot more to it than just these three, but as a fundamental good starting point.
Michael Bernzweig (09:39.268)
Also to recognize, what is it that is employee retention? When we're talking about retaining employees, what do we mean by that? Very simply, the definition to use to consider is the people that I want to be in my organization want to be in my organization. Whether that's my team, my department, if I'm just a division manager, people I want here want to be here. That simple definition really can carry us through years of talent management theory and approaches and organizational behavior. And let's keep in mind that
The people you don't want there, that's the first people to stop catering to. It's the first people you don't want to retain. By all accounts, I'm probably the world's most recognized retention expert. I'm the first one to tell you, you don't retain everyone. And we know actually 87 % of high performers have thought about leaving because of a low performer. So really a key starting point is to recognize that retention by definition is who you want in the organization. You're not helping them or you. Keeping people who shouldn't be there, who don't want to be there any longer.
How is the employer-employee relationship always changing? We just leveled up. If you were with us on the first one, that was pretty straightforward. This has got some nuance. And what are we talking about when we say it's always changing how it's changing? That means that you, as an individual manager, director, leader, or executive, cannot predict how the ideal employer relationship looks tomorrow. There's a finite number of points in that employee-employee relationship.
and how you manage each of those points from pre-recruitment to post-separation really matters. But you as a leader can't possibly know what to do next. And that informs really not a sense of disempowerment, but it activates hopefully, wait, I need to grab tools that can tell me, help me understand how that employee-employer experience is ideal. What the needs, wants, and expectations were of an employee.
five years ago, let alone 10 or 15 years ago. And in some cases, in some industries, five months ago is different than what it is today. Give up the ghost of trying to chase the idea that you and someone else or your HR team are gonna figure this out on their own. That's impossible, right? We're not gonna figure out the weather looking up. We have to have tools in place because this law is inevitable. It's always changing how it's changing. All outcomes of that employee firm relationship can be predicted with data and time.
Michael Bernzweig (12:03.878)
These are your two variables. Can you get enough data across enough time that you can answer anything you want to know about your workforce? And one tactic for doing that is understanding your blind spots across the employee life cycle and filling in blanks. So this is the employee life cycle. There's eight stages. Just consider from upper left is sort of pre-recruitment all the way around to separation. And outside of the pedals here of these eight stages is
are a set of instruments, tools that you might be able to use to avoid bond spots. You might be using applicant surveys or candidate reference surveys. You might be doing some kind of a new hire survey or a quality of hire. Maybe you do safe workplace or benefits, but filling in the blanks to avoid not knowing why people join, say, and leave your organization is critical to reducing the feedback loop of understanding of there's a change in that expectation. There's a change in what people want and what we're given.
That's what I'm talking about. people want this now? Well, can we give that? And if not, we gotta be real. Well, we don't do that. That's not what we're gonna give. But for people who want what we got, let's find them. Let's find the people who want what we're good at. And that means you have to ask these questions constantly to understand what are we good at? Are we still good at this? Are we great at this? That's the card to play in campus recruiting. That's the card to play in the interview at the end of a high performer. Here's what we've got. Here's what we can offer.
I'm not talking about comp and benefits. I'm talking about the culture, the experience. Are you looking for that? Is that interesting? Because I can promise we're going to give that to you. I can't promise what else, but we'll give you this. And making those promises and delivering on those promises strengthens the psychological contract between that prospect, between the current employees and your organizations. So recognizing it's always changing how it's changing, and you need tools, you need instruments to understand it. That's critical to addressing the second law.
of retention. Third law is that turnover is a symptom, not a problem. What are the three laws that you've distilled from your experience? So let's talk about those three laws that govern the entire conversation about your workforce. First law is simply the one with the best talent. If you don't have high performing employees, then someone else does. Someone else has gotten the best marketing or sales or delivery.
Michael Bernzweig (14:27.654)
or support or customer success because they're out there. Now that's not to say that you still can't achieve, you still can't get ahead. But if we're not recognizing that, the game that we're all playing, if we manage a team above 10 and under about thousand employees is really just getting the best people in the best positions using their strengths to achieve those outcomes. That is the game we're all playing. Under 10 employees, by the way, for anyone who's listening or is here, that's a different set of influences.
So recognize that this is applicable to a startup, but very different laws are at work at a startup. So if you're under 10 employees, probably another set of rules that you need to get to. When you're over about a thousand employees, you're starting to get affected by macroeconomic conditions and geopolitical situations. Over a thousand employees. That 10 to 1000 employee range of again, your team, your department, your division, your company. The game you're playing is getting the best people to do their best work.
I was working at an IT firm before founding Ritenzo, over 10,000 employees. They replaced 3,500 people a year. It took hundreds of people per day to feed that machine. Prior to that, I worked at a construction company that was 100 % total. I was actually promoted in three weeks because I didn't know that I could quit. And in both of those cases, right, they were chasing the talent, but the cost of that replacement
was insurmountable in the case of the construction company and just was massive, you know, in the case of the IT global consulting firm. I come from a family business where nobody quit. And it was that juxtaposition that it occurred to me that really this is the same game we're all playing because if I have, it is only my employees that are going to market the products that are going to deliver the services that are going to innovate me out of whatever problem or situation that I've got right now. So rule number one, retention law number one, the best talent wins.
What's the current state of talent and turnover across industries? What's the current state of talent right now? Well, in the very near future, something to keep in mind. And we're having this conversation in October of 2025. The laws are evergreen. They last forever. But this slide, this can change in a week and a month, but by most accounts, we're going to see turnover increase in some industries with higher foreign born workers, hospitality, restaurant construction. If you're in healthcare, retail or food service, you're still going to see turnover increase or at least continue unabated.
Michael Bernzweig (16:49.638)
They'll decrease in professional services, finance and insurance, and a few other markets where it's less affected and where, and certainly in real estate, where it's a little bit softer. So just recognize, I might hold onto my team a little bit longer if I'm in real estate, finance, insurance, professional services, but I'm gonna continue to have challenges in some of these other industries. We're also seeing that labor trends are currently being affected by fewer job openings. So we've moved from job hopping
which hit its peak in 2022 and 2023 in most industries. Really a 70 year peak by the way of more turnover than ever. Now we're looking at something called job hugging. You're gonna see people staying longer because there's not enough, a lot of other opportunities. The flip side of that is I've probably got to manage my people and my experience and the morale a little differently because that doesn't mean they don't want to quit. They just can't find a place. And what has happened in
Again, 25 years, we've seen every boom and bust, every ebb and flow, every great recession and economic return. People, the pent up demand and interest to leave can sometimes release very quickly in an organization. had a company come to me once, 40 people quit in 10 days, 40 people quit. This was only a few hundred employee organization. And what happened was over the course of months, competitor was setting up plans to pull everyone over.
and they were incentivizing the people they got to commit to grab somebody else. This is real, it happens. And I hope it hasn't happened to you, but just the organic attrition that occurs is enough to undermine your ability to be on time, to hit deadlines, and to anything. Government downsizing and the shutdown that's occurring right now inevitably has an impact on labor forces and other things that will continue to create volatility in the workplace, but it is a soft job demand.
which means it's a slightly shifted employer advantage. So that's the state of talent. How you're going to get them is going to make a difference in the degree to which you can deflect any increase in job demand and people will stay. Which brings us to the second law, which is the employer relationship is changing and it's always changing how it's changing. Why do you say turnover is only a symptom, not the real problem? No employer has a turnover problem.
Michael Bernzweig (19:10.866)
You actually have a connectedness problem. have appreciation problems. have productivity problems because high performers don't want to be unproductive. High performers don't want to fail very often before they're out of here. And so if you set up onboarding and orientation to be a struggle, to be a high bar that reasonable people can't overcome, or they're not achieving success, you got to be careful because of high performance women. So by focusing on the symptom though, as many organizations do and not the problem, turnover returns, right? It's a good chance that your back pain is not caused in the back.
It didn't start there. It started maybe in the bed, right? That's too soft. Or with the shoes that don't fit and they throw off the back or you're sitting all day. Well, the problem is actually the chair, the bed, the shoes that caused that back pain. And turnover is the same. Looking at the root causes is going to help to inform what we can do about it. Stop solving turnover as your problem and look deeper to understand what's at the root of
So how accurate do you want your return on prediction to be? Can you share how predictive analytics and data help organizations improve retention? Well, that's perfectly correlated to how much information you gather. And ultimately, if you gather enough information, you can produce insights of understanding where your red zones are when you gather more data, data like geographic, location, proximity from work, market data. Then you start gathering
more information around demographic, okay, like who works here? And we start gathering, what about our organization is influential? We can predict turnover over 90 % within the next 90 days. I can tell you who's gonna quit in an organization anywhere in 59 countries and 22 languages, because we collect the data that's needed to be accurate. And if you don't have this data, you're guessing, and guessing is expensive. So I hope this has been helpful.
As you move up the data chain and understanding and capturing employee experiences and predicting turnover ultimately, it's about using instruments at your disposal where you can reach out and understand the employee experience across the employee life cycle. Don't fight the three laws of retention. This is what they are. And instead work with it with tools and technologies to understand why people will join, stay and leave your organization. Thank you so much. hope this has helped. Talk to you soon. Chason.
Michael Bernzweig (21:35.056)
Thanks so much. think a lot of the executives who are in the audience will take quite a bit from that presentation. We're really looking forward after this. We'll have the Q and a session coming up. So jot down all your questions, pop them into the Q and a and Chasonwill be answering those live in just a bit. Thank you. As we head into the Q and a, we'll now hear from three software Oasis community experts, Matt Bailey over at SiteLogic.
Chason Hecht over at Retensa. And finally, Daniel Alfvahn with Alfvahn Consulting. All experts in the Software Oasis community that provide guidance to many of the world's top leading organizations. So let's dive right in. Hopefully everyone's having a fun time at the event today. We have several of the speakers that you've heard over the course of the last hour or so.
I really wanted to bring this event, uh, all the way full circle for everybody. I know we have a ton of questions that came in. We're going to do our best to get to as many as we can, although we only have just a few minutes, but let's do this. So what I want to do is start off with a question that came in several times in several different ways for Matt. So let me, let me start there, Matt.
One of the questions that came in, and I'm sure you hear this every day. How do you turn a substantial slide data dump that may be handed to you into something that executives will actually act on? every presentation you should go into starts with three questions. Number one, who's your audience? And I always like to laugh at this because marketers forget their own.
dog food or take their o we identify audiences, we create persuasive media for ou But we forget to do it information. So who are y are they measured? What's we present our content in needs it and needs it to m second thing after we kno do want them to do? Wh
Michael Bernzweig (23:53.084)
Do need to make a decision? Do we need to confirm something? Do we need to change? So with that in mind, that should then dictate the type of data you bring and the tone that you will present it. If you just do those three things, you will be on your way to instead of, you know, 30 slides with a 30 second discussion, three slides with a 30 minute discussion, and you'll be to making decisions. And I won't even tell you the person that submitted the question first.
how many slides they were talking about, but it had three digits. is my conservative estimate. But yeah, I hear a CEO say, when I would just want to buff board, I just create 100 slide deck. And I know no one will ask any questions that that's it's sometimes I think just creating that many slides as a way of just quelling any, any talk. Yes, you don't want any discussion. That's the problem. Yeah, don't ask me about any of these slides.
Too funny. Well, the other question that came in actually for Chason. So as long as you're, you're right there, I will throw this out to you. And, you know, a lot of employees are in key positions, different, different parts of the organization. So are there some red flags that management can look at that are predictors that, that
employees may leave within that first year or within a very short initial period that they should kind of like red herrings that they should be looking for. Yeah, absolutely. The key thing is to establish a baseline of typical behavior and then the degree to which this varies from that baseline of normal. and one of the ways to do that is to start asking questions early on. So, you're bringing somebody into an organization, you making
high five, six figures, maybe, you know, currently it takes six months or a year before a formal sort of structured dialogue occurs. That's way too late for those red flags to emerge and to be seen. So two things to keep in mind. One is start asking early and ask often. Once every two year employee survey is long since dead, the idea that we're going to somehow ask 80 questions of all our employees, you know, every 24 months, the things that happen in that inter-institutional time.
Michael Bernzweig (26:16.988)
You know, massive loss, problems, chaos, or successes that get overlooked. So we want to have many conversations more often, much shallower dialogue. That's how you create a structured predictive model for red flag interpretation in terms of tactically, just managers, like keeping your eye out. this person less communicative than they were before? Are they less engaged in the dialogue in the day to day? Is there lower levels of enthusiasm, excitement, or exuberance towards future planning? Are they hedging their.
Leaning in to projects that are forward looking. Those are some classic symptoms for the professional worker that they're not actually leaning in because they're taking interviews somewhere else. I love it. And I know you shared in your presentation that it's so important to have the right, right people on the bus, shall we say, obviously you want to have the best of the best in your organization. And that's really the way it's your differentiator. mean, there is so many different.
strategies that you can employ, but your people are by and far the number one asset that you in your organization. And I can't tell you, you know, when my, my, organization that I sold about three years ago, over 30 years, how many vendors came in and walked through our warehouse and would say, you know, I've, I've been to many warehouses over the years, but you could eat off the floor in this place. What's, what's going on?
And, know, it's because every single employee was 100 % committed to what we were doing. the end of the day, if you're shipping thousands and thousands of packages every day as a leader, you can't be everywhere. You can't be doing everything. You have to have people that are 100 % committed. So I think that that's a big, big deal. Now, Daniel, I know that bringing aboard clients for a lot of organizations is really what you were speaking about in your presentation.
Quite a few consulting companies in the audience today and quite a few SaaS organizations. we had some pretty spicy questions, but I'm going to give you the best of the best. So one was asking, with all of these AI tools that are coming out and enhancing LinkedIn strategy, where does an organization even begin and what should and shouldn't they employ in their tech stack?
Michael Bernzweig (28:36.635)
This comes up a lot and I'd to differentiate the organization and the individual, the executive. We always have a wishful thinking that it will be a dictate like top down, the CEO will mention A, B and C and everyone will march and do this. But there is a whole spectrum and we should allow each leader and each employee to pick what they think is right for them to represent the organization.
Simplest test you could reply to AI or any other question really is three simple questions. Say you have AI suggest that you perform that action. It could be changing like tweaking your LinkedIn content or anything like that. Change the question to whatever you want. A, do you like it when you read it? Does it resonate with you? Yes or no? If it does, we can move to the second question. People who know you, when they see you perform that action.
Will they nod in yes and say, yes, this is Michael's style. These are the words you use. Or they go, what was this guy thinking about? I know him is always A, why do I see B? So the first question was whether you like it. The second question, do people who know you approve? And the third and last question, the clients you were mentioning, the clients who want to enroll, is this attractive to them? Does it repel them or is it neutral? If you have three affirmative answers,
then you should do it, whether it's AI or anything else. Now, Matt, one of the things that you kind of covered in your presentation that drew a few questions, you spoke about, and I don't know if you mentioned it explicitly, but the law of data intentionality. And I guess what people were trying to understand is how do they apply it to their teams' reports, you know, in terms of all of that. It comes back to the question.
What's the question you're trying to answer? What's the purpose of the meeting? What's what action do we want them to take? And when you identify that now you purposefully go out and find data that will this. So for example, Google analytics is a great example of non intentional data. Google analytics gathers everything that goes on on a website. And regardless of what company you are,
Michael Bernzweig (30:54.072)
multinational, small, medium-sized business manufacturing, you get the same reports in the same layout in the same data tables. They're all the same. They're same location. So that is low intentionality. It's we get everything and we rethink everybody. High intentionality says, you know, I'm only going to go get graph or this piece of data because it's specific to the question I'm trying to answer. And those sources of data may be in three, four places.
And then intentionality of showing the data of reporting the data means that I just don't copy and paste those graphs into a chart. I analyze them. I come up with a way to show Lee what this data means, what the correlations are. And I create something new rather than copying and pasting and making my audience do the work of analysis. I do the analysis intent that the law of intentionality is now that I know the big question, I go get the data that answers the question.
And then I intentionally manipulate the data to present it in a way that enables people to figure out what you're showing them within two to five seconds. Because if you put a data chart on a slide, no one's going to listen the next 15 seconds. They're all trying to decode the data. And so they were saying, yeah. you're trying to make it easy for people to just look at it and understand what they're saying. And I was wondering, as you were saying, Google analytics, if you were talking about.
GA three or GA four, because I remember that whole transition. was, it was just, yes. Yes. I do not like GA four. I have used different options. I pay for analytics now because it's worth it. Yeah. No, absolutely. They, they, they had a rocky transition there, you know, and it's so interesting. think a lot of, lot of organizations and a lot of people doing presentations. mean, let's face it. People are not, you know, it's not their.
first job, it's an acquired skill. It's not something that, that, that's an aid or, or born and learning how to present effectively, communicating effectively and how to take data and, you know, present it so that you can achieve the outcomes and the, you know, that, that you're looking for or, or help people to understand what's really going on. think that's, that's half of half of the challenge. that's really good. Yeah. I love the way you presented that in your.
Michael Bernzweig (33:19.238)
your presentation. that was great. And Chason, another question that came in for you. So I'll throw it out at this point. One of the numbers that you throw out in your presentation, I'm not sure if it was exactly or something on the idea of 90 % accuracy. And a few individuals said, what the heck? How is that possible? Can you dive into that for us? I think we have a lot of analytical minds here and a lot of people that are wondering.
Yeah, absolutely. In the path that we got to predictive, we've been adopting and using more and more mature models. So the most technical side of the conversation, I'm happy to engage in direct dialogue and it's exciting to have it. But there are predictive tools that have been around for decades. The earliest being linear regression, which you add up kind of a number of patterns.
and they point towards something. And then in the evolution, including AI and machine learning technologies, can add more and more variables that influence the employee experience that will determine whether or not an individual is predisposed to stay or to quit. Now, the most common one that was around for 20 or 25 years, for instance, is like distance from that warehouse, Michael. There was probably a correlation between how far I worked from your warehouse and how long I stayed. That was an early...
discovery in, uh, you know, uh, talent science that, you know, if someone's 55 minutes away, they're not going to be here for very long. Right. And the, and the person who lives across the street, we've got a good chance. So if you take the most simplest formula and with one variable, that's it. Well, let's multiply all the variables around that individual. So you economic education, also success level, the manager, all of a sudden we have more variables. You start compounding those variables and you get a better model.
Now let's add local market. So what's happening in that local marketplace? More variables. What's happening in the region? What's happening in the industry? And all of a sudden you have a stack of about 160 variables that are influencing the employee experience every day. And when you use modern machine learning and technologies, you're able to build a profile composite and algorithm for each organization that says these are the variables that are happening at Burnswig Co. And what's happening at Burnswig Co. is totally different.
Michael Bernzweig (35:41.465)
you know, then Alfonica and at Alfonica, they might even be an accounting firm. They might even be actually in the same city, but because the leadership style is so different variables that occur and emerge inside the organization and the experiences can have wildly different effects. And a single manager leaving could have a wildly different effect, positive or negative. So the idea is fundamentally no human, no
Daniel, Matt or Michael can consider all the variables happening on their shop floor or in their pit or on the construction site or in the office. And you need technology to wrap together and to begin to map and predict and see the influencers, the detract, the gravity, we call it, the attractors and detractors on that employee experience. I hope that any of that made sense, Michael. Absolutely. And I think, you know, for me, you know, numbers and statistics and modeling is
very, very exciting because as all of us know, you you can really predict quite a bit as long as you have enough data. And that is really, really very, very interesting. And probably one of the reasons that the only course I enjoyed with math in college was statistics. you know, and served you well. You're prescient to consider that and you would get a job tomorrow at just about anywhere.
Well, it's the language of business, think. you know, obviously with anything, any type of, whether it's, you know, something like you're doing or fraud analysis or you name it, having enough data points, you know, for an algorithm. Your pattern recognition is what we're looking for. And the tools to do that have evolved from, again, the early stages to correlate basic correlation.
to extreme boosted trees. I'm sort of in a Bayesian wrapper. You have this model inside of a model, given the influences that are driving change inside of the organization or around it. It gets exciting. It is fascinating. And luckily I have people far smarter than I, lots of degrees that help us do this. No one person can build and support. Yeah. You're supposed to do that. Daniel, this next question that came in, I'm not sure if you have your crystal ball, but I thought it was an interesting one. They were asking,
Michael Bernzweig (37:55.173)
Do you see sitting where you said, you know, you've been doing the LinkedIn thing for as long as anyone. think you've been there longer than anybody at LinkedIn as far as LinkedIn. What do you see in terms of B2B relationship building changing with the advent of AI? What do you, what do you see as the biggest shift in this relationship building paradigm? Perhaps what happened with AI the day we have this chat.
is that it's a great leveling mechanism. Because any one of us could now produce high quality content that would have taken a huge budget and a lot of resources five years ago. The SaaS revolution is one strong element that changed that and enables small firms to offer services. But now basically what you could do with any free version of AI could be probably comparable to what the largest corporations in
corporate America would have produced five years ago with committees and budgets and in six months. And now you can have a 30 seconds video that would go viral. So how do we manage to take advantage of this? This is almost the wild west phase. You can pick anything you like. So the limit is no longer technological. It's our head. What do we want to do with this gift? We've been given a gift. Do we only use it for automation and smartly spamming people?
Or do we use it to something else? love it. I love it. Well, I see, I see that clock ticking away. You know, the types of individuals that you see on this call are representative of the software Oasis community, an amazing group of executives within the community. And it's a lot more than just these types of events for anybody that would like to reach out to any of the experts in the community.
giant orange button at the top of the site. Everyone has full access at no cost to reach out to any of the experts in the community for further engagement and all of that. Click that button and you'll be able to schedule a meeting. Any which way, I really appreciate Matt, Daniel, Chase. I really appreciate everybody taking the time out of your busy days to join us, not only on the event.
Michael Bernzweig (40:15.919)
but on this Q &A session as well. So thank you so much for your time. Thank you. Absolutely. Pleasure. Thanks for joining us this week for Software Spotlight, recorded live from the Software Oasis AI Summit. If today's insights help you grow your business or inspire your next move, don't miss the chance to connect live with founders and executives from leading global brands at our next event. Reserve your free pass by tapping the green button at the top of softwareoasis.com.
or use the link in our show notes. See you at the summit where top consultants, founders and innovators lead conversations that shape the future.