AI Isn’t the Problem. Culture Is. - Ian Heller

AI isn’t the barrier in distribution.

Culture is.

In this episode of Confessions Beyond the Food, Nancy sits down with Ian Heller — AI expert and Chief Strategy Officer at Distribution Strategy Group — to explore what’s really slowing adoption across foodservice, sales, and manufacturing.

They unpack:

• Why this AI shift is fundamentally different from past technology cycles
• The growing gap between leadership urgency and frontline skepticism
• How AI challenges the traditional identity of the sales rep
• The fears reps don’t openly admit — from exposure to irrelevance
• Why “AI isn’t accurate” may be more about control than data
• The leadership mistakes that stall real adoption
• How culture quietly overrides strategy inside organizations

This conversation goes beyond technology — into trust, identity, and the uncomfortable truths shaping the future of distribution.

Learn more about Applied AI for Distributors here: https://appliedaifordistributors.com/speakers/

Transcript

Welcome And What We Unpack

SPEAKER_00 0:00

Welcome to Confessions Beyond the Food. I'm your host, Nancy Redwin. Let's dig in and get inspired. On our last episode of Confessions Beyond the Food, I had a conversation about AI and the future of food service sales. And it ended with a confession. But what I've been thinking about since isn't the technology, it's the reaction to it. Because knowing what AI can do and actually changing how we work are two very different things. And if I'm being honest, I'm not sure this industry believes it yet. In this episode, I sit down with Ian Heller, an expert in AI and chief strategy officer at distribution strategy group. Ian has spent over 30 years in distribution from operations to executive leadership. We talk about culture, resistance, and what's really holding this industry back. So let's jump in. Hey guys, welcome back to Confessions Beyond the Food. We're so excited to have you today, and we're so excited to have Ian in the studio. Welcome, Ian.

SPEAKER_01 1:08

Hi Nancy. Thank you. I'm delighted to be here.

A Math Failure That Changed Everything

SPEAKER_00 1:11

We're so excited to learn more about AI and to bridge the previous episode. If you haven't checked it out, please listen to it. It's really cool. But Ian's gonna bring it all together for us and land it. Um so excited to do that. We're gonna do something a little different, be a little crazy today. Um, we're gonna start with Ian's confession because as you guys know, if you've listened to any of our shows, is you have to confess something. So, Ian, tell us your confession.

SPEAKER_01 1:41

Yeah, so boy, this was, you know, this is a tough one, Nancy. I had to think about what I was willing to admit. Um, so uh what I came up with was in the first half of my career, uh roughly, I was terrible at math. So I was in, I grew up thinking I was like horrible at math. And in fact, um I mean I flunked algebra two in high school. That's how bad it was. And then I got to graduate school. My I got my dream school, and my very first class in this executive program was financial accounting. And I was like, oh my gosh, I'm gonna flunk out before I even start in this program. And uh the professor, Thomas Lease, handed out this form in advance because he wanted to know who was good at math and who wasn't, so he could direct the hard questions at the people who knew math, which I thought was kind of a nice thing for those of us who were bad at math. And I wrote on the form, I am the worst math student you will ever teach in your career. That's how bad I thought I was. And so uh he didn't comment on it then, but I took the class and I wound up uh getting a B in the class and I got an A on his take-home final. And so he's handing back our tests, and as he's handing mine back, he stops and he said, I thought you said that you would be the worst math teacher I've ever had, but you got a B in my class and my final, I've had many people do worse than that. And I said, Yeah, I know, but you said your take-home final should take two hours and it took me 12. And he said, Ah, I think I see the problem. Like, yeah, me too, I'm bad at math. And he goes, No, you're not. He said, You think that math is about doing the calculations, and you may struggle with that, which is why it took you so long. The more important thing is you did the right calculations, you chose the right calculations to do, and that's why you got an A on the test. He said, Ian, in the rest of your career, in your companies and in your partnerships, there are going to be people around you who are good at the calculations. So as you go through the rest of your graduate school program, when you go through statistics and managerial accounting, don't worry about the fact that you struggle with the calculations. Instead, learn which math, which formulas, which calculations to apply in what circumstances and what the outcomes mean, and have somebody else help you with the calculations. Because they're do being good at doing the calculations is much less important than understanding the concepts behind when you use certain kinds of math and what the outcomes mean. And it absolutely transformed math for me. And I went from avoiding, I mean, I'd be reading a white paper or some kind of analysis. So if there was a table of numbers, I'd skip it. I wouldn't even look at it, right? And then instead, because of the way Professor Elise framed this to me, I began understanding that, you know what? I can understand the concepts behind the math, which math to use when and what the outcomes mean. It doesn't matter if I'm not good at the calculations, because I will have somebody else who can do that for me. And it completely transformed my career. And suddenly I was able to read financial statements and I was able to engage with material that was more quantitatively oriented. And then a funny thing began to happen, which is that I actually got better at doing the calculations. And I realized the way my brain worked was I need to understand the context of the numbers that I was doing in order to focus my brain around the calculations themselves. And it completely changed my career. That little one-minute conversation that I had with him and taking that class completely transformed the way I think about myself in math, and it completely transformed my career. Um, and so I confess at one time I was truly horrible at math. And thanks to Thomas Lees, I learned I wasn't as bad as I thought, and that there was a way around it.

SPEAKER_00 5:15

Wow, that's such great insight. My son is actually in tutoring right now, and he struggles with the word problems. And she was like, just think about it. Think about like, does that would that would that answer make sense? You know? And so the way that you frame math, I think, is in using your common sense. And I I love that. Um, I love it when people can speak into you and um give you confidence and and show you like how to navigate that. And there are people good that can do the calculations. And I think this is such a great confession because it really ties into what we're talking about today is AI, is we don't have to know. I I'm I'm just guessing maybe this is where we might land. So you don't even have to know everything about it, but you need to know where you can apply it. Maybe. I don't know.

SPEAKER_01 6:06

I actually hadn't thought about that. I think that's a brilliant insight, Nancy. Uh that's right. You don't have to understand how AI works, you have to understand what it can do and how to use it properly.

Why AI Is Not Just Another Shift

SPEAKER_00 6:15

Right. So let's jump into this on the AI side. So um, is this moment with AI different from past tech tech shifts?

SPEAKER_01 6:26

Yes. And there are really four reasons behind that. First of all, AI is the first technology ever invented that ultimately is going to be, and in many ways already is, smarter than humans themselves. Okay, and this has big implications because you know, when people talk about, hey, AI is going to create jobs just like it's going to destroy jobs, well, that's you know, that's always been the history of technology. The difference now is you could argue that AI is actually going to take those new jobs that it creates because it's more capable than human beings and at so many things. So I think it may have a harder impact on the job market than people are expecting. Secondly, it's so broad. I mean, e-commerce was pretty broad, and just even though it was focused around commerce and about search and about research, it transformed the world. Well, AI is much broader. It's more like electricity, right? It's more like the invention of fire or the invention of electricity. It it is you know, the there have been recent studies that say that 80% of the U.S. workforce has at least 10% of their tasks exposed right now. And if you've used Claude Co-work, which I use to organize my inbox and make presentations for me and do research, I asked it to research 94 distribution stocks the other day, and it came back with an in-depth six-tab spreadsheet and it calculated all their financial ratios, done excerpts about their AI strategies, and it was incredible. I mean, it would have taken me a week to do that work, and it did it in half an hour. Um, third, the adoption speed is so fast because the rate at which it's going to move through society, the rate at which it is moving through society, is just much faster than any previous technology. You can't ignore it. And then uh fourth, the fundamental difference between AI and other technologies is it's the first technology that improves on its own. It actually is a learning technology. Every other technology, you know, you had to you had to wait for humans to upgrade it. So the example I give is, you know, my wife has a SUV and it has a bunch of technology built in to keep you a certain distance from the car in front of you and to keep you in your lane. And to, you know, it's got, of course, cruise control and uh uh collision protection, all that stuff. But it doesn't get any better at that on its own. I mean, yeah, yeah, you have to take it to the dealer and they upgrade the system, maybe, but it doesn't get better at that. Autonomous vehicles do learn and get better on their own. And so right now we're at a point where AI is starting to improve recursively. So there AI is improving AI, which means the shackles are off and waiting for humans to upgrade it. So as rapidly as we've seen these LLMs like ChatGPT and Claude improve, it's about to become almost a vertical line of improvement where it's it's improving at such a fast rate that it's almost beyond our ability to understand it. Um they're already doing things that the that their inventors don't understand. Um so I think just this, you know, the pace of change, the fact that it's self-improving, the fact that it's gonna take many of the jobs that it creates, uh, and the fact that it's so sweeping make it different than any preceding technology.

From Skepticism To Urgency

SPEAKER_00 9:24

So when you speak at conferences, do you sense this urgency of this change or skepticism?

SPEAKER_01 9:31

There was a lot of skepticism at the beginning. I think I'm beginning to see more of it be about urgency. Um so we just did our 2025 state of AI and distribution survey, and we found that 88% of distributors are citing productivity and efficiency as their primary driver for AI adoption. I mean, I think they get it. You know, the the skepticism tends to be one or two levels down. I mean, in part because if you're in an executive leadership role, you're being pushed by your board to adopt AI. In fact, you could argue to an unhealthy degree because there are certain tasks that regular technologies can solve or that other alternative technol approaches can solve, and people are adopting AI approaches anyway, right? Um, so I think it's the skepticism that was healthy in 2023 has become dangerous in 2026. I mean, the the technology is moving so rapidly, as I said, that you know, rather than if you're asking the question, should we adopt AI, you're really behind. You should be already adopting it and asking about what you can do with it next.

SPEAKER_00 10:31

So when it comes to a sales rep, I mean that's what I do as a sales rep, um so does AI threaten the identity of the sales rep?

SPEAKER_01 10:42

Yeah, but it depends on the sales rep and the nature of the work that they do, right? So if your differentiating characteristic as a sales rep is you're the answer person, and that's you know, hey, I know the products, I know the pricing, I know what's in stock. Well, AI is going to it is eroding that value proposition because AI agents in particular are going to be able to do all of that better than most people can. Um, but I think there's an identity that AI doesn't really threaten, and that's if you're truly a business advisor where you understand the customer's operations and uh you can see problems the customer hasn't seen coming, uh, then you're more valuable with AI, not less, because AI can give you better intelligence to work with. You know, right now, um you can go into Claude and say, hey, I'm about to have a sales call with so-and-so at such and such a company. Tell me everything you can about it. And you're gonna go in better prepared or better armed to provide value than you ever have been before. In fact, when we met at Mofsi, I laid out you know, three diverging paths, right? Outside sales, manufacturers reps, and inside sales. I think the disruption timeline is different for each, but the direction is the same. That the transactional part of the relationship is going away. Uh there's still the strategic part. Um, and so if your identity is built on transactions and being an information source, yeah, you should feel threatened. If you're highly about business advising and about relationships, I think you've got a lot more time.

SPEAKER_00 12:07

Yeah, order takers, beware.

SPEAKER_01 12:10

Right.

Resistance Is Often Fear Of Exposure

SPEAKER_00 12:12

So is resistance about technology or fear of exposure?

SPEAKER_01 12:17

Uh it's almost always about exposure. I mean, I think you know, it's it's socially acceptable to object to the technology, but I think it's really about exposure. You know, so if you think about what um an AI enhanced CRM does, you know, it'll show you which accounts are profitable, which ones are not. It's really great identifying patterns that even techno regular technologies are find hard to spot and humans really struggle with. So you can see you know, buying patterns and measure wallet share, identify at-risk accounts, and uh it will help raise certain customers that you need to pay attention to um before they call you with a complaint. Uh, but it also means you can't hide anymore, right? If you've been coasting on a few big relationships and ignoring the rest of your territory, AI is gonna make that visible to your boss. Um, so when someone says I don't trust the data, or AI doesn't understand my customers, listen carefully because sometimes that's a legitimate data quality concern. Because one of the things that's still true of AI is it's garbage in, garbage out. If your data is no good, your output won't be any good. But a lot of times when people point, you know, have those kinds of objections objections, they're uncomfortable because AI is revealing how successful they are with across their territory and defining how they spend their time.

SPEAKER_00 13:34

So what fears do reps rarely admit out loud?

SPEAKER_01 13:38

Um, first of all, I love salespeople. So I you know, I want to be careful I don't sound like I'm being too critical because I think really great salespeople are extraordinarily difficult to find and incredibly valuable to an organization. But they're still human beings and they're not perfect. And, you know, I think a common thing in distribution sales is accounts or account reps have more customers than they can really manage. And I think AI makes that apparent. It's gonna reveal that you don't know as much about your accounts as you think you do or as as you pretend to. Um, and so if you run an AI analysis on a territory, it's gonna show opportunities that you just missed and it's gonna identify risks you didn't risks you didn't see. That's why you should be doing that analysis before the company does it, right? So so you're using the AI tools, they're not being used against you. Um second, your relationships might not in every case be as valuable as you thought. Um if you know if a customer is ordering products on a on a scheduled basis and AI can automate that, well, you don't really need the rep to do that. Um but I think the biggest risk is reps who are reacting in fear to the technology and they're thinking, oh, I'm not sure I can learn this. You know, so if you're in your 40s or 50s and you think you can't make the transition, I would just tell you that I'm 62 um and I find it the most fascinating and and interesting technology I've ever come across. If I can learn it, you can too. But you do have to jump into it and spend the time.

SPEAKER_00 15:08

So one thing I hear a lot out there is in different industries, and I've just been asking a ton of people around me lately, you know, what what is your hesitation and about AI? And I always get AI isn't accurate. Yeah. So are we holding AI to a higher standard than human instinct?

Accuracy Doubts Control And Hallucinations

SPEAKER_01 15:30

We we hold all technology to a higher standard than humans, right? I think we accept a certain amount of fallibility in humans. I mean, look at the accident rate for autonomous vehicles. I mean, statistically, they're wildly safer than human drivers. They don't have road rage and they don't drive drunk and they uh tend to follow the laws and the speed limit, and they don't drive fast because they're in a you know they're late for work. So they're much safer, and the stats prove that. But they're not perfect. And so every now and then you'll see autonomous car wreck and you know, somebody dies, and all the comments are this is why I'll never trust an autonomous vehicle, right? So it doesn't really make sense, but that's how people are wired. They don't they don't forgive technology mistakes like they do human mistakes. And I think you have to watch out, right? I mean, I I had a I was interacting with uh Gemini yesterday, the Google product, and I asked it about a certain physicist that I was reading about, and it said, you know, and he died of uh of an illness uh or died of uh complications after surgery. And I wrote back and I said, I thought he was murdered. And it said, Oops, you're right, he was murdered. Like, well, how do you get that wrong? I mean, that's um, and uh uh so it does make mistakes, and in some ways, Gemini is more accurate than the others because it's tied to Google, and so it actually uses Google in its search to try to verify facts, but it messed that up. Um, and so I think you can't just take it at face value. And look, here's the other thing. When it makes stuff up, these this is called these are called hallucinations, right? And some of it is because they really don't have sufficient programming in there to say that it's okay to say I don't know in response to a prompt. Um, but they're gonna get past this, right? In my in my view, the hallucinations are probably gonna come to a stop or to an end or mostly come to an end. Uh, but I think, yeah, the answer to your question is we're less tolerant of mistakes in in AI and technology in general. Um, and they still hallucinate and you still need to verify important things. Like I didn't just take that spreadsheet that I talked about earlier and publish the results from it. You know, it's like I mean, I appreciate having it, but I gotta go in and double check it, right? And I did find a math error, by the way. It's it looked it read a it read a dollar number as a percent, and it had given me some incorrect ratios. And I read them, I'm like, okay, I don't think that's right. When I went and checked in that spreadsheet, it had some things wrong.

SPEAKER_00 17:46

Quick pause to thank W3Sales for sponsoring this episode. If you're looking for inspiration in food service, from the details that shape the space to the products that elevate the experience, W3Sales new online catalog is built just for that. Explore and shop anytime at W3Salesonline.com. So um is distress of AI about accuracy or about control?

SPEAKER_01 18:11

Well, I think the accuracy becomes an excuse for discomfort about control. Right? And I I've seen this before. If you present data to salespeople and there's if there's a couple things wrong with it, they disqualify the whole data set. I think you know there's just a general level of skepticism. Um But you know, I I think I I I think that it's mostly about law, about about the threat to losing control, but it gets framed as accuracy.

SPEAKER_00 18:40

So um transitioning to leadership and some of their blind spots. Um, what do leaders consistently get wrong with introducing AI?

SPEAKER_01 18:49

Yeah, uh AI is management infrastructure. It's it's a whole new way of organizing your company and getting work done. And it often is treated as a technology project instead, right? And so it's so sweeping and so broad, Nancy, that it should not be uh the sole domain of your IT department. The everybody needs to understand the capabilities in their role. So whether you work in accounts receivable or marketing or operations or or warehouse management or fleet management or purchasing or product management, you name it, you should be mastering AI skills relative to your job. Um, and a lot of people aren't, you know, kind of waiting for the that AI project to roll or that AI project or roll out from IT. Um, so I think that's one thing. I think the second um I'm hearing a lot of leaders say we're gonna implement AI, but we're not gonna reduce headcount except through attrition. In fact, I wrote a column about this called the AI attrition myth. Well, here's the problem: two-thirds of people who leave jobs go to other jobs. There's a third that retire, they quit to go to school or take care of a family member. Two-thirds of people who leave a job go to another job. Well, if all these companies at the same time say, we're not gonna lay anybody off, we're just gonna let attrition take care of it, that's gonna run out of steam really fast. Because if no one's hiring, because you know, the other side of the coin of we're only gonna lose people through attrition means I'm not gonna add people to my company, right? So there's this hiring freeze, that's the other part of that. So if everybody's relying on that strategy at the same time, there's not gonna be enough new jobs created for anybody to leave for. There's not gonna be any attrition. And so I think this notion that we're not gonna ever fire anybody because of AI, sometimes it's disingenuous. Sometimes people just don't understand the dynamics, the broader dynamics in the math. But I would be very careful about saying that because I think you may be in a position where you're bored saying you're gonna get 10% productivity gains from AI every year, um, and you find you that you can't do it without layoffs.

SPEAKER_00 21:00

So can a culture resist change even when leadership says they support it?

SPEAKER_01 21:07

Yeah, uh all the time. Um, you know, and a lot of times the break is not between the CEO and the workforce directly, it's between the CEO and the person who's in the interim, right? So you may have a strong-willed VP of sales, for example, um, and you know, the this everybody just heard the CEO at an annual meeting say, we're an AI forward company, we're investing in digital transformation, or whatever the technology is, and then afterwards the VP of sales goes back and says, Look, I just want you guys to focus on hitting your numbers. Um, and you keep you know, the comp plan doesn't change, the KPIs don't change, and the culture winds up eating the strategy. You know, because culture isn't what you say it is, it what's getting it's what gets rewarded, uh, who gets promoted, you know, and if your reward recognized. This revenue, no matter how it's generated, and you're telling people the old ways still work, uh, and you're and you're tolerating people not using your CRM and you're telling people digital adoption is optional. Um, you know, culture culture change requires change of the incentive structure, not just the messaging.

Culture Incentives And KPI Reality

SPEAKER_00 22:16

That's such a good point, is that if we as leaders, because I came back and from listening to you, Ian, and I was so pumped up. And I told, you know, sales, we're gonna start doing this. And um, you know, inside, I want you guys to look at how we can be efficient. And and so, but that becoming a KPI, which is we call on our scorecard, um, that they're measured. I'm I'm definitely gonna try to implement that into our scorecard. I like that. So cool. So let's jump into manufacture reps and the digital shift. And for me, this is this is also my lane too. So I'm excited to hear answers on this. So are manufacturer reps particularly exposed in the shift?

SPEAKER_01 23:01

No, the opposite. They have more time. Uh I mean, I think everyone's work is going to transform and everyone's exposed to a certain degree. But, you know, uh and and you know, just as background, I've been a VP of marketing for four large publicly held distributors, right? So Granger, HD Supply, Newark Electronics, uh, and Corporate Express before it was acquired by Staples. So I've worked with countless manufacturers' reps over the years. And uh the good ones, uh, and most of them are good because it's an eat what you kill business, right? So you don't last if you're not good at it. Uh the good ones are already strategic. They already, I I can't tell you the number of manufacturers' reps I know, and they understand what's going on in their distribution client better than most people at the distribution company do. When in fact, when I get hired to speak at a vertical that I'm new to, like if I'm, you know, if if I'm talking to an industry and I don't have a lot of experience in the industry, I try to find a manufacturer's rep or two who's involved in the industry because they know where all the bodies are buried. They know every they know who's who in the zoo, they know what's going on, what the trends are, who the good operators are. They know and they don't know this because they like to tell rumors. They know this because they need to have uh inside information on everything that's happening in the industry. Um, well, that kind of knowledge does not lend itself to AI, right? And the other thing they're great at is building relationships, right? And and you know, you know, it's funny because I've been in, I've been in when I was in industrial supply, hardly anything that we did was specification and bid driven, right? It was just need driven. When I was at Granger, you needed something, I need it now, I'd order from Granger. When I got into the construction supplies world, I thought, oh, I bet this is all about price and the relationships don't matter because everything's like a lot of it's like sealed bids and stuff. Nope, just the opposite. Relationships were even more important. And if you were the sales rep at the construction supplier that had the best relationship with the contractor, you're probably gonna get the order no matter what. These relationships are absolutely essential and vital. It's really what manufacturers uh retain manufacturers' reps for is that inside knowledge and that relationship. So I think they've got much more runway than most other categories of salespeople. Now, again, if you're just the answer person, you know, and you manage orders, um, you're more exposed. But I I and and by the way, AI is going to get better at all this stuff. So I think it's not that it's less risky, but you have more time to manage the risk and adapt.

Why Manufacturer Reps Have More Runway

SPEAKER_00 25:30

I agree with that as a making factor. I mean, I mean, with all the change in technology over the past five years, and I mean, our job is to go out and specify. And so that's our job. We're the hands and feet of the factory and to get out there and to make the specification and to know who the decision makers are and bring those back through distribution. Um, that's I mean, if you're doing that model, I think to me, that's the direction my company will go with adapt with adopting the AI model. So what cultural habits and distribution are hardest to break?

SPEAKER_01 26:08

Well, the the relationship we talked about is super important, but it's just a component of the strategy. And you don't want it to be the whole strategy, right? So I think you know, there's this sense that the personal relationships are the moat, and I think in some ways they really are, right? Um, but I think don't you can't lose sight of the fact that ultimately it's about outcomes because one of the reasons that manufacturers and distributors appreciate manufacturers' reps is that they help them win more. And so if you if your win rate goes down, it doesn't matter how much they like you at some point in time, it's going to cause stress and stress on the relationship and potentially fracture it, right? So you've got to make sure you're producing insights and solving problems and driving measurable growth in an ongoing way. I don't think that's different with or without AI, but you didn't you know you didn't frame this question with AI, so I think that's just a general answer. Um I think the second hardest habit to break is that our sales is purely an art and not a science. Um you know, we have a long tradition of celebrating rainmakers, you know, top guns, the reps who just seem to get the job done no matter what. And there are people like that. We've all worked with them, and and they seem to be able to survive any transition, and uh no matter what happens, they're able to bring results. There the problem is there aren't that many of those people, and you can't replicate that. And so if you're gonna build a strong sales organization, you can't count on it all being top guns and rainmakers, right? There's just there aren't enough to go around. And if there were, you couldn't afford to pay them all. Um, and so I think you have to realize that get those rainmakers where you can, hang on to them for dear life, but then realize not everyone's gonna be like that. And so you need this more replicable, structured approach to sales for everybody else who's gonna do a good job for you. They're B players, right? They're solid, they're gonna make those sales calls from you know morning to quitting time every day. Um, and customers are gonna like them and they're gonna provide good results. That part you can structure. And so there is sort of this blend of art and science where you know you can't deny the top guns are out there and you may never understand them, but you also can't count on your entire sales force being that because there aren't enough to go around. And so I think understanding that it's this mixture of art and science for most distributors is important. Does that make sense to you as a person who's calls on a lot of distributors?

SPEAKER_00 28:28

Yes, it really does. And I think one thing that we've been doing in terms of AI is you know, have equipping them with the tools or the or knowing when to go to AI and say, hey, you know, ask ask the customer what they ask AI what the customer might need. Um, so I think it's equipping them with tools like AI and um and training and things like that that yes, that you have to do um to keep them, to get them stronger. And who knows, they could become your top gun in five years. So yeah, that's right.

SPEAKER_01 29:06

And I think that's a good point, Nancy, is that sometimes top guns are are are made and not born. Not always, but sometimes.

SPEAKER_00 29:15

Yeah. I I've I've actually I don't know if I told you this, but we we hire everybody outside the industry, and some of them haven't even been in sales. And we have one employee that she's down in Austin, and she was a bartender, and she is on fire. I mean, that girl came in, guns blazing, but you know, it was up to us to have the tools to give her to be successful, the training, the you know, you just can't you you've got to continuously train and and and help them grow.

SPEAKER_01 29:49

So how did you wind up hiring her?

SPEAKER_00 29:52

She heard about our company through a friend. And when I talked to her, I said, listen, I really need an experience wrap down there that someone because it was it was an empty territory, and she stayed on me. She called me relentlessly, and I loved her persistence. And I just said, Vina, I can't afford you right now, but I'm gonna figure this out. Like I want you because I love your enthusiasm. And she just had such a like an interest and passion for the industry that you just can't, you can't manufacture that. And so if I can find someone with passion for the industry and excitement, uh that's something you can't teach.

SPEAKER_01 30:40

Yeah, you know, I've been a professional manager since I was 24 years old. And so it's coming up on 40 years. And one of the things I've noticed, which I've never heard anybody talk about, is there does seem to be a correlation between how badly someone wants a job and how good they'll be at it if you hire them. You know, it's like if they desperately want to work for you, they desperately want this job and they're and they're enthusiastic and they tell you how much they want it, and most of the time those people do a good job if you give it to them. And and so I wrote this column a long time ago called College Degree Not Required. Because, you know, in most sales and marketing jobs and most business jobs, I don't care if someone has a degree. And I spent my corporate career wrestling with HR to get them to take college degree required off of my damn job openings because I don't care. And to me, if you're hiring a great marketer or a salesperson, whether or not they have a college degree is the same correlation as the how tall they are. Who cares? It doesn't matter, right? And uh and I'd much rather have someone who has the basic enthusiasm and aptitude and train them up on all the other stuff than get someone who's got a marketing degree who you know, whether or not that correlates into them doing a good job in a marketing role is just a crapshoot to me.

SPEAKER_00 31:56

Yeah, I mean, uh finding somebody that's just curious and willing to ask questions and grow, that's to me, that's also something that's super important. And the degree doesn't, I mean, it may or may have prepared them to answer, you know, to know that you're hiring somebody without any experience, you know, that they were disciplined enough to go through um school. But um in our job, just with all the self-autonomy, you have to be, you know, a go-getter and a hustler and all the things. So and someone that wants to get better.

SPEAKER_01 32:31

Yeah, I mean, a degree is great. I got two of them, right? I understand it's great. It's just not, it shouldn't be a s an on-off switch as to whether or not you consider someone for the role.

Hiring Hunger Over Credentials

SPEAKER_00 32:42

Right. And honestly, with all these AI tools out there, I mean, yeah, you don't you really don't need it. So I mean it answers a lot of those questions. It's really just knowing, I think, and what we do and having to know all the things, is just knowing who and where to go to to find the answers quickly. Well, let's go into um something more personal and direct for our audience. So if I'm a manufacturer rep listening, what cultural shift should I personally make?

SPEAKER_01 33:15

Well, I think there are a couple. Um, you know, stop leading with products and start leading with intelligence. And that's probably a little bit overstated because ultimately it's a lot of times it's about products. And I don't I don't I think you still need to understand the products. And um, but I think you should rely on AI to automate as much of that technical stuff as you can, and then pay more attention to your customers. Uh, you know, take take the time benefit from that time savings and learn more about your customers and their business and their strategy and networking the organization. So gain pro personal productivity with AI and then spend that time uh on the relationship and the business intelligence and strategy side. Um I'd also say no matter how old you are, you need to embrace AI. Um I think it you know, the the so you you don't you don't get a break because you're 60. Um in fact in my company, you know, my business partner who's a few years older than me has a PhD in AI, um, and he's brilliant with it. Our COO is a few years younger than me, and he's better with large language models than anybody I know. I mean, he writes code with them and he creates these dashboards with for us, and it he just he could do anything with them. It's amazing the what he produces. And you know, as I said, I'm 62 and I work with that all the time. So I think you know, there is sort of sort of this tendency as you get older to become a little slower to adopt technology sometimes. I think you can't give yourself that option uh anymore. And I also think that you know, if you're in your 40s and 50s, you're still in the prime of your career with AI and you need to embrace it as fast as possible. So I think those are the those are the you know, the I don't know if those are cultural shifts, but those are shifts that I would make uh if I was a manufacturer's rep.

SPEAKER_00 35:07

Yeah, one thing, I mean, just in I do product training for my team every week. And I've started, instead of me going to all the different websites and comparing, contrasting, you know, competition and benefits and all the features and all the things, I've really been using AI and it's cut my time and just putting that preparation in like I mean, it takes me a fourth of the time that it used to, and it lets me allow me to do other things. So, um, and I'm not technological at all. And so I'm always stumbling around, but um, I'm in the late 40s, not gonna tell you specifically, but um, but yeah, we can do it, you guys. We can do it. So um, and it's really, and that's one thing I love about like the younger generation too, because they're jumping all over it and and I ask them questions, you know, don't, you know, that hey, how would you use this? And I think if we all think collaboratively across the generations, you know, we can come up with some really cool ways that we can implement this um in our businesses. So I there's so many other things I want to ask you, but um I'm so excited that you were able to come here today. I'm I was deeply impacted from you being at Mofsi and I thought just listening to your um and to your your presentation and made my trip totally worth it. And so Oh, thank you so much. Yeah, I just so glad I rated to you at the check-in after a horrible flight experience.

SPEAKER_01 36:45

Right.

Personal Shifts And Practical Next Steps

SPEAKER_00 36:45

So getting to meet your wife, but I'm just really thankful you were here today. And um, I will link everything in that in your website and how people can contact you. Um, you're a great resource for businesses out there that are looking to implement.

SPEAKER_01 37:03

So well, thanks. And we do have a conference called Applied AI for distributors uh coming up in Chicago, June 23rd to 25th. We do have reps there sometimes and um a whole bunch of distribution companies. Uh so if you go to applied ai for distributors.com or go to our business website, distributionstrategy.com, um, you can get more information. It will sell out. So sorry for the commercial, but I do think it's highly relevant to the conversation.

SPEAKER_00 37:28

No, I think that's really important. And this is for all different industries, correct? Not just fee, service, and construction. Yeah, all industries. So wherever you are out there, um sign up. I mean, he's Ian's incredible. So I'm I'm sure he had I know he has so many more things to share with us. So thank you guys so much for joining in today and um be brave, get out there, get just you can't fail, you can't mess it up, right? Ian, just just try.

SPEAKER_01 37:56

That's right.

SPEAKER_00 37:57

Play around. So, anyways, we all have a great day, and I appreciate y'all joining in. For more inspiration, follow our social media at W3Cells. Please like, comment, and subscribe. You know, all the things we would love to connect with you.