Survive and Thrive: Dr. Carl Tolbert's Insights on AI, Leadership, and More for Reps & Manufacturers

[00:00:04] Well everybody welcome to Flowing Sales podcast again. We are honored to have Dr. Tolberg with us and He's done some really interesting research. I was recently at PTRA

[00:00:15] Heard some of his stuff on on a panel and he have a talk there that maybe we can get into here That's really interesting and so maybe I'll just turn it over to you for a second to give a brief introduction

[00:00:27] Some of the stuff you've researched and things like that. That'll tell T.S. Off here. Yeah, awesome So, after the US Navy I was in the Navy for several years. I got into manufacturing right in your

[00:00:37] LA work for Union Carbide then I went to work for Birmingham Steel and I worked for Chin and Metal Making Cutting Tools so I did a lot of the material science to the material manufacturing you know, advanced products because of US steel I got involved

[00:00:51] with automation you know motors drives and just for being you know I worked for a Comicoled Automation Direct for a few years where I was a tech support application engineer Then later we got into product engineer and then that led to industrial distributor

[00:01:05] They worked for about 20 years and became the waste president engineering for I left there Recently in the 22 to come all the way to South Dakota where I work now from a loyal electric as a senior application engineer

[00:01:16] Along the way I've been collected probably 30 certifications and two bachelor's two masters and a PhD in a post-grad economics So I then a really good at taking tests as they say

[00:01:28] That's awesome and there's not a lot of put you in unique position. I think that you've done all of those things And you've seen so much in the manufacturer world can you tell us a little bit about your dissertation and kind of what you went into there

[00:01:41] And I think it's pretty fascinating. Yeah, so I get a question like why did I study like organizational behavior coming from a math and Engineering and physics world and what it is is human behaviors far more difficult than math

[00:01:53] I mean, it's really difficult and one of my aspirations was to try to understand how decisions are made You know from a humanistic perspective Then translate that into software and automation, right?

[00:02:05] So that's kind of was one of my overarching goals now what happened was got an idea of like okay Well, how can I study the fitness of an organization the survivability of an organization from a

[00:02:17] Qualitative perspective view through the people who lived experience. I think that was a missing piece in the the academic literature And it turned out that using industrial distribution where I was working as a back drop of that and that became like the first

[00:02:31] Research of industrial distribution like it in like 50 years not guy mentioned in the talk The most of the industrial distribution research is whole cell distribution Logistics online sales inventory management supply chain

[00:02:45] It's not the lived experience equality to piece the leadership, you know this survive ability if you will I mean none of that was really kind of been touched and many many years what are some of the things that came out of that? That were maybe surprising or

[00:02:59] hurt really useful right? I mean to your point no one had studied this from a really rigorous standpoint. Right? So what stood out I broke the research in the three different groups industrial distribution leaders Repagents in brand representatives people actually worked for the factories and the perspectives

[00:03:16] I got were really interesting because it's the interaction between at three groups that make up industrial distribution and the distance to the customer of as a huge part of that ends what I mean But that is okay, so if you have a distributor

[00:03:28] You have about 1500 products and your closest to the customer right? Repagents are like the next level out and you only have about 15 products Well most manufacturers they want to get closer to the customer because that's where all they have a deficit of information

[00:03:43] Like where is my products go after the sale? So they are the farthest away, but they're all trying to get closer So that's where you get the ideas of point of sale reports PLS You have nimly advertised pricing policies. You know, you have several other things that

[00:03:58] Manufacturers have instituted in a way to get that data as a means to understand where their products going to close your customers Again, that was a fascinating detail that really wasn't found in any of the research the other key one was the idea of taking blame

[00:04:14] So repage and speaking the middle they felt that they're one of their big Responsibilities was to take blame for both the distributor and the brand so if something happened They were like hey stand on me. I'm gonna make this right when they'd pass it upstream it downstream

[00:04:29] So it's really a fascinating discussion there and it gave them a sense of reverence Which made them feel important to the process And not all brain is used reps. It's a lot of time to have a direct sales force

[00:04:40] So you don't get the same type of reverence nor the accountability is another fascinating detail They talked about a ptra This idea of a rep council You're mentoring in your first point

[00:04:53] Right the manufacturers are furthest from the customer, but a lot of times they're trying to come up with maybe new products or iterations on a product Like that's really important information to have it So is maybe that the rep council idea

[00:05:06] one of the concepts that you can bridge the gap here? Yeah, so I've been on part of several distributor councils for manufacturers over the years And I always bring up the fact that if there are reps involved because they're not always involved They actually know

[00:05:22] Where all the customers across all the distributors are So distributors generally have one piece of the picture when it comes to local market They're reps if they're there or certainly have a more complete understanding because they see everything coming in their territory

[00:05:37] And they have access to the manufacturers differently than distributors do right? So I'm an avid to advocate of that as well and I even mentioned that during the panel So I think it's a really good idea actually. Yeah, how many people do those?

[00:05:51] Is it pretty widespread or is it not so calming they come and go? So what happens with brands? This is another thing came out of the research is the larger the manufacturer the more likely the turnover of leadership is

[00:06:03] So that's a big challenge is every two to four years There's a new leader of the channel management car of the brand that deals with reps and manufacturers

[00:06:12] Generally every 10 years the manufacturer often gets in their mind that hey, you know what we can do this better than a rep So often you hear the tales of reps getting fired because of the new leader comes on board

[00:06:25] Looking for a home run, right? So it's the same key in slight for people wanting to have some type of customer counsel Distributor counsel rep counsel as far as getting that feedback. I think it's a good idea even from a distraider Perspective to have a customer Council

[00:06:41] Actually help drive them to be better. I think it's a good part of the survivability feedback that's often missing I don't think it's done quite enough. So what were manufacturers representative and out of rolling with Carolina?

[00:06:53] So we've been on a lot of these rep counsels over the years they do have cycles for the most part There's a few that had been You're in your out, you know, we're gonna have those and there are always beneficial to me

[00:07:06] It's important to have these just from a reps perspective so we can have those Conversations about okay, where's the manufacturer going what markets are they getting into? What new products

[00:07:17] Where are we heading as a team because in the day we're in this together? So we all got to be have eyes down the road Or where we're all hidden collectively and then another part was you talked about a customer counsel

[00:07:28] We've got one manufacturer that does an excellent job with this they bring in some of their key customers every year And they talk about Where are your problem areas like what what could we design and build for you that would

[00:07:42] Eliminate an issue for you and that's how they go to market and they build products that just really fit in Issue and it's all feedback. I mean at the end of the day, it's not this isn't rocket science

[00:07:53] Let's go ask the people we're gonna sell to what they need But what you think is basic is not very basic out there a lot of times somebody sitting in a corner All of us just designing something

[00:08:04] Versus asking the people that are supposed to buy it what do you need so Yes interesting to hear your take on as well. Well, you know it's the biggest product design failure ever was you know The demons

[00:08:17] Segway right you know you perfectly sample that he designed in the vacuum without a customer base Right so value proposition was created in any way shape or form And then all of a sudden you're left with something that all this investment went into

[00:08:32] That really didn't know market so that's always kind of like a cautionary tale for product development Which I've done tons of product development my pass and it's always okay Identify the pains and gains and you can try to answer those questions through development which includes personas

[00:08:48] You know people what what they want there says there's a whole subcategory there of creating personas which is part of my my current research What I'm doing right now. So it's a good segue into that no pun intended All right this segue

[00:09:03] Well, let's talk is that in line with some AI stuff you were talking about? Yeah exactly 100%. So as part of the research I did in 22 I became an expert in what they call hermenutic Sonominological research so hermenutic the nominological research all that means is it

[00:09:19] It's the lived experience But they process of hermenutics where it's you kind of embrace the bias differently when you do quality researchers like two versions one is like The guy in the white coat looking behind the mirror trying to be an objective of the observer

[00:09:35] Where you're describing what you're saying right Cermanutic just means that you're part of the research where it's interpretive right and that comes from a guy named Gatimer and then high height a higher height a girl the German process that with

[00:09:48] You win qualitative research was kind of developed not to get too deep into that But the bottom line is that the process you go through is called a hermenutic circle And you create horizons which are basically like arguably prejudices it loves you to create a persona of people

[00:10:05] Right and that's really if you think about AI in the sales process piece So you're trying to teach a voice because AI is nothing but pattern recognition So if you have the better model and better process of creating the model to teach the AI

[00:10:21] Then you're in Prague to significantly better and that's why you know I think when I talk the the resolution issue of teaching is also the challenge really what I'm Focusing is a new version of getting better resolution for the user to teach AI and I'm using her

[00:10:36] Minutic to do that because it says very unique process to its own merits So that's my current research. I know it's a little little out there, but it's When I find a lies that it'll make sense it's interesting. Can you give us maybe just an example of

[00:10:49] You know you mentioned using like I'm gonna use that example of a CRM and I'm gonna trend AI to say a certain message you just take us through an example of that. Yeah sure so just to briefly

[00:10:59] So everything's kind of based on open, open AI you know really is the base line of course You have with the GPT full point over three point oh and when I found is like all of these companies like Any word or Jasper or

[00:11:13] You know any of the bigger ones like you know what's we used to be called barred I forget what Google calls it now to new it's another company that's no longer barred but So there's like a sub-journer of AI companies that do like content

[00:11:27] Right is a specialty and that's the Jasper's the any words of the world and what you do is you You have a you can teach a brain voice of your process and then you have customer

[00:11:40] Personas or targets and the idea is that you you basically these become props You know we're all failure from the reprops and AI so you're basically taking her minute like a essay almost

[00:11:54] And you're going through the line by line of all the pains and gains created from this fusion that you create from her ManuX and then you're basically using that to install into these models either as the brand voice or as the end

[00:12:09] User target if I'm writing marketing copy again You can do two ways on focusing primarily on the target customer So if I'm trying to use industrial distribution my tiers of research on that topic And I already created the fusion of a rise in switch is the the persona

[00:12:28] I'm teaching that but I have to use like I'm going to test the software I have to use the same All the variables have to be I have to change everything in the constants and just have one variable to test If you will as far as an hypothesis

[00:12:41] Again, I know it's a little out there but I mean along with that I think there's a lot of practical application there right I think in help Firms or distributors or manufacturers

[00:12:54] Maybe to your point right better copy or even better understand the customer things like that what are some of the applications that you see and Well We're that's a good question right there and there's the god be a split here, right? So one is academics

[00:13:10] But just like plagiarism checkers. There's now AI checkers and I've tested several of them and they're very very good So they can actually determine how human your writing is Believe or not so just like plagiarism checking generally academics They want you under like 10% plagiarism for an article

[00:13:28] There's a lot of times you get quotes you get things that you know are so calm and you can't get rid of them So you know just to be unique well the same thing for AI now so I've done a a couple

[00:13:39] Consulting things for academics where I'm looking at pieces. I run them in the penile through an AI checker And shock and see 80% written by AI As an academic submitting it for publication and he didn't even believe that so what's happening is the technology so new

[00:13:58] some people are using it as a kind of a a crunch To fulfill some things that it's really a bad thing now Universities and schools are going to have to really get used to checking for AI content

[00:14:11] And it's interesting because the pattern recognition will detect is it all arises from kind of the same source through Open AI so you can actually tell if it's AI written or not they also have tools that fit on your browser

[00:14:25] That actually look at copy and web stuff and other things to see if it's AI generated Now the practical application is is just like you're saying with email sales stuff for Marketing campaigns email campaigns writing scripts actually I think AI works very well

[00:14:42] If you're writing scripts for other types of media that's now outside of writing I think that's kind of fascinating too because I think somebody it that a test I heard of

[00:14:53] Somebody writing like bellotatorian speeches through AI and they sounded amazing they were at four or five different speeches And the verbalization of that made it awesome right but if you if we've already read it or published it

[00:15:08] You might be able to detect that it was AI generated because I think we're all getting more tuned to that It's like the wolves in the mousse, you know, it's the predator prey model of

[00:15:17] Okay AI gets better or the less directing knives will we get more in tune to recognize he I generated content. I can I can tell for the most part now after working with this stuff for about a year

[00:15:29] But to your point if it rides a speech and then someone gives the speech it's another step away from Yeah, because you're you're humanizing the speech through the process of Giving so it's the interpretation and then they replay right, so it's not quite imitation

[00:15:46] So in the written word however, it's harder to mask that unless you internalize and re-write it explicitly And this is why tell people who are like will curl if I use a eyes it will use it to summarize Use it for other Areos of collecting data

[00:16:01] As an assistant to use an academic but when you go to write it you have to basically internalize it and then put it back out through synthesis Right, and that's to really the key point from an academic perspective and eventually all of us even marketing

[00:16:16] Or going up they start doing the same thing because it'll be so recognizable and do we have the stigma from our users to say hey You're using AI generate content because you're lazy or you're not created right?

[00:16:26] So how is that gonna eventually look to not now because it's so new but within five years? Yeah, do you see a lot of adoption like in the manufacturing distributor rep circles to see how much adoption do you see

[00:16:38] of AI versus how many opportunities there well if seem right now is I've seen some engineering folks use it as like Again, as a crutch Sing all right well how do I calculate torque for an electric miller?

[00:16:50] You know, it's throws up the formula so it's like a fast way of saying he here is the data here is the calculation But the problem just like when you use it to create like regular content based on

[00:17:01] Keywords or something or you're teaching it from different documents that you've the like a tone You want to get for your brand it may get it wrong right and this is the challenge is that if you're using it and you're not double checking it as a human

[00:17:16] AI knows no difference so if the pattern is x it may go down the wrong path because of something that It has a reference for but it's the wrong type of reference right?

[00:17:27] So I've seen that too. I've seen errors created and if you base your engineering or your critical designs on AI stuff And don't double check it then you have a problem potentially that's why I've seen as well. So there is any risk there

[00:17:40] So I'm hallucinating right just kind of stuff up and sometimes sounds very authoritative oh Yeah, yeah, and it's fascinating even some of the guys are created opening I this is some of their stuff that they really safeguard about right so it's like if you I have chat

[00:17:55] GPT and I ask it well how do you develop a bomb? You know say I want to and I've gone power or I want to create explosives It really won't help you because that there's keywords that their EFC cards are ready

[00:18:07] And that goes to kind of like some of the ethical parts of AI I think somebody years ago I worked on a lot of research of ethics in AI. I don't think there's an overarching theme yet

[00:18:17] But eventually there will be some type of ethical framework because it's gonna be an necessity I mean it's already part of our lives and everything we do. I mean look at the I used for traffic navigation from

[00:18:28] Like Google Maps, you know those kind of things are already there that you don't even know is there I think what people start talking about You they will never see consciousness

[00:18:37] You know that's the other part of AI that people get scared about is the terminator or you know all that stuff and it's really I'm found that they should have no worries about that because

[00:18:46] You know Patta recognition is not consciousness. So I mean people put a lot of in the that it's really not true Yeah, I think he had an interesting point is in fear like when you talk about AI

[00:18:58] Just to the masses. I think there is a certain element of fear But I look at it from our business standpoint. I look at it is another tool in the toolbox to support us

[00:19:07] To do our job. I don't look at it as a hey. I'm gonna replace somebody or I'm gonna replace this or that It's a tool that our folks can use to be more efficient

[00:19:16] It's a tool that we can utilize to make us better at what we do and like you said we can still humanize that But also have that that crunch if you will to lean on to get certain information to make us better our job. So

[00:19:30] I don't think we should be fearful of it. I think we should be excited about it and how it can enhance what we're doing each day And that's kind of what we've done with flood. I mean, we we look at that as that's the future is

[00:19:40] We want to give tools through AI that are gonna allow reps to do a better job for their manufacturers and customer Well, I kick that I mean think about how far we've came with like you know This is it was it Microsoft power BI

[00:19:54] You know they were the first ones that would create graphs based on a sentence remember So they were using like this AI engine to say alright if I need to look at how many sales or going

[00:20:05] How many BFDs are sold in Tampa, Florida and the month of August all your 10 years of data This can solidate it into that particular question and getting you some kind of graph

[00:20:15] I think that's amazing because all of a sudden big data now has the data that's hidden within big data is now easily Unraveled by AI help. I think that's something we didn't have even a few years ago, right?

[00:20:28] So you had to get like some data scientists you know some are specialists the digthroil and data And now you don't have to do that it's vastly different things are changing I think that's a huge part of this thing too that we're gonna enjoy

[00:20:40] You know from you know a CRM or just a business perspective over the next five years I mean we've seen deer foi like even even a year ago some of the stuff that we're able to do now

[00:20:50] Didn't even exist right so like we so for example to your point we can take product spec sheets all these PDFs about A lot of these reps represent a lot of lines. That's a lot of complexity and

[00:21:01] War entes and this information that information they're trying to do a consultitative sale to somebody And keep all this stuff in their minds well, AI is really good at that right? He can look through all your documentation and we've seen how you can ask a couple of

[00:21:14] Intelligent questions against the right data set of your product lines to ensure it's not making things up And it'll give you a really good like well here's here's maybe some some products you want to recommend and here's how

[00:21:25] You want to package this and oh, I didn't think about that because there's so much information to keep on top But so and I think that's just gonna keep going. I mean what do you think? What do you see 510 years from now?

[00:21:36] You know and especially with your research and you know a survive ability and maybe how AI Works itself into the lived experience right of a rep firm or distributor. What do you see that going?

[00:21:48] Yeah, that's a really great question so one one of the things that you touched on it just a second ago was as reps Also pick up the verse lines

[00:21:55] Right this came up in a lot of the discussion is during the conference is that okay if I'm a bearing in PT Repp Asian but all of a sudden picking up a servo line what do I have to do differently and then if you start seeing successes

[00:22:09] Then you start saying okay. I'm succeeding with this higher tech line and these two other lines That I'm surprised to see have synergies because you may not see a video. I will Right, so that's part of the thing is it with a eye you know more machine learning

[00:22:24] Was that I'm looking I'm looking for an hypothesis I don't have one the test. I'm looking for one so it's kind of a backwards process and that's why sometimes you have to have such an open mind We need to machine learning in the first place

[00:22:37] The answer your question about the next five years I think it's interesting and if then a reps have really that their time is now to start making better relationships

[00:22:46] Because the bigger brains they have direct sales forces they're kind of consolidating and they're moving away from the local market place I think it's a huge opportunity for reps to start actually working more closely with their independence before even more than they did previously

[00:23:02] I think that's a shift right brains will still continue to try to get close to customer student phone apps and other means there's all kinds of data And eventually POS will be instituted across most industrial markets

[00:23:17] Right now if you sell you know automation products like banner and turk POS is a standard process that you have That's not present in some other areas of distribution and rep relations

[00:23:27] You know brand relationships all brands want that because it's data for them that they currently don't have So I think there's a lot of that shifting going on and then I think the technical piece is also shifted

[00:23:41] Because the thing is you can't find easily high tech individuals to fit sales positions and any level Whether you're rep range or work distributor so we're gonna have to come up some kind of idea about how to fill the workplace deficits of knowledge over the next 10 years

[00:23:58] That's a huge huge question that they ever remember the panel brought up during those discussions Right then what do you think talking about the rep models specifically Right, yeah, I mean you know to things are kind of shifting and changing what are some ways you see

[00:24:13] Maybe with the eye or the changes that you're seeing that are happening. How does the rep for model like how do they stay relevant or maybe not even relevant But it's step beyond that how do they keep themselves irreplaceable Right and

[00:24:26] Super valuable to the to the system well I think for a lot of manufacturers a lot of brands If you do the math, it's really a cost thing to have a direct them toy it's ridiculously expensive

[00:24:37] Right, and then the problem is you won't get the coverage right so if I if I'm a big brand Then I wanted to wreck representative on my payroll then it's cost me I think the number came up was like 300 the 350,000 all in and they're covering like five states

[00:24:51] So you don't have the coverage of that are really big Opportunists right but if you have rep agents generally you have groups to cover like one person for state or two people per state

[00:25:03] You have a lot better coverage at a fraction of a cost and the local people have they know the local market Which you'll never know from a manufacturer's perspective easily right so I think from a pure economic perspective

[00:25:18] Reps are still very very important again every 10 years you have that cycle of Replacement that we can on a pinpoint through the inner of you is through the subject interviews But I think the other pieces of technical knowledge. I think that since

[00:25:32] Reps only have a maximum of 15 brands surely it's even less than that since they have about specific focus They become subject matter experts faster than say a distributor who has 1500 brains Right, so I think that's another piece and the course the focus of all weems in bigger

[00:25:50] House account is huge to one or both you came from the electronics business right the whole so business Yeah, yeah, well electrical you know, we're in the utility electrical

[00:26:00] Market yeah, I think was a brain surely it was electronic component guru and I think it's that business is more about the spec You're getting on the spec and where the distributors more transactional we still have some that with industrial distribution But it's the only in peace

[00:26:15] That the brains have to have somebody covering explicitly right and you can't always Conditioned do that and have that focus because the winds are tough since high volume But it's long gestations slow pay there's always other challenges

[00:26:32] Hainland only in businesses that distributors both like in this light so I think reps play a big part with the only in business for brands as well That you can't quite get the same way with distributors

[00:26:43] What are you most excited about right? I mean you're doing research in AI you're in your in this space like what are you most excited about? I think relationships within this business is unique

[00:26:53] You know, you can see when it when I asked a question I always ask if anybody I mean even the trainings I do is like how you got into this business and with distribution whether you're wrapped or brand or Distributor one third was random

[00:27:06] One third was friends in family and one third was like some kind of educational program in turn shit Or you went to Distribution program like Texas A and M or EC or you know UAB one of the universities that has a actual program

[00:27:19] I think it's fascinating, but what keeps people here is actually the relationships Is everybody knows everybody? It's very insistuous but in kind of a positive way Is if you're in this business you rarely ever leave

[00:27:32] I think that's curious to right so relationships. I'm curious to see how some things play out with some these bigger brand acquisitions And curious to see you I mentioned about e-commerce at on my panel

[00:27:44] I think if if a Distributor's in e-commerce and there's success will now they're gonna stick with it But if they're not then a lot of Distributor pulling the plug and just exiting because it just it can't get the traction or the focus on making e-commerce

[00:27:58] Really a valued part of their business right so we're seeing them abandon them right now, which I think is interesting So what's seeing I wow? I really curious about the mouth policies Right minimally advertised price. So you have a you know, it's that free writer problem

[00:28:11] I also talk about quite a bit so there's two there's two issues if there's a free writer problem of I did all the engineering but the customer shot me around and bought it online for $5 cheaper

[00:28:23] Right, that's a first order free writer problem the second order free writer problem is the manufacturer knows this is happening But since they're still getting the sale They really don't want to spend the money to enforce it right that's a real thing

[00:28:36] Because everybody talks about their contracts they have an enforcement mechanism But the reality is it doesn't exist unless somebody complaints So most Distributors are given up complaining that they have some online company selling its cheaper Online but inevitably that's become more of a bigger problem

[00:28:56] As we be getting more mature within this part of the business being sold online even more than it is now I think manufacturers are going to really have to continue with that and lastly the the new

[00:29:07] Non-competes rolling is recently is going to change the way people have to retain their employees I think that's actually very positive again. It's sometimes tension and conflict isn't good but it's good for organizational fitness. It's good for survivability

[00:29:24] So that tension that that creates now has to everything not to shift again The focus on Retention and then the best way possible so that's going to make actually make organizations stronger

[00:29:36] I truly believe that yeah, well they talked a lot about PTR a you know one of the main points was You know people coming into the workforce their hoppin jobs every two three four years and so the turnover is crazy to try to retain folks

[00:29:49] Yeah, you know actually in the software business that's almost they talked about portable Like a benefit packages we're all the set everybody has like the same benefit package it doesn't matter what job They go to because everybody jobs jumps job every two to three years

[00:30:04] And distribution it's not quite the same you know You have some turnover with the younger generation now, but I think if the retention was there the approach the type of job I think we would have better success But I don't think anybody has that perfect formula yet

[00:30:19] Right? I think that's really something that's I'm waiting to see kind of how that plays And since some of the crutches like the non-competes are going on I know the chamber commerce is going to like challenge it

[00:30:31] But I think it's still going to come out for the individual freedom Is really going to ring out on that when I think well yeah, we we appreciate you Jumping out and just just chatting with us. It's been I did know we were gonna get into AI today

[00:30:43] I mean that's something we do all the time and but that's that's awesome Well thank you so much. Hey, thank you