In this episode of Executive Connect, host Melissa Aarskaug sits down with Dustin Williams to unpack how AI agents, strategic outcome engineering, and smarter system design are changing the way firms source deals, run diligence, and create value. Dustin explains why so many firms are still trapped by bad data, bloated tool stacks, and outdated operating models, and why the next winners will be the ones that build systems around better decisions, faster execution, and stronger human judgment.

This is a sharp conversation on AI transformation, value creation, and what it really takes to move faster without losing control.

Chapters:

(0:23) Why private equity models break
(3:50) Bad data and weak deal flow
(7:18) What outcome engineering means
(12:53) Why humans stay in loop
(16:08) Finding the work people hate
(21:46) Why perfect plans fail
(26:28) The real problem with tool stacks
(29:21) The next edge in private equity
(32:20) Where firms should start
(35:49) Servant leadership and change
(39:43) The mindset shift leaders need

Dustin

(0:00) If you reposition those people and you put them into more prestigious work into those places (0:07) where you say your job was to make this decision and it’s so important it’s so hard to the business (0:12) and I’m going to clear the entire field for you so you can make that decision every day all day (0:17) that is you putting them up on stage telling them they’re a rock star and giving them a chance to

Melissa

(0:23) private equity has always been about leverage capital talent timing but today the most (0:31) overlooked lever isn’t financial it’s operational intelligence the firms pulling ahead aren’t just (0:40) buying good companies they’re engineering the outcomes designing systems that drive the (0:47) performance accelerate their execution and create value faster than competitors can even react (0:55) today’s guest has spent more than two decades working across industries helping executive (1:00) teams do exactly that Dustin Williams operates at the intersection of strategy technology (1:08) and execution he applies a discipline called strategic outcome engineering to help leaders (1:16) architect systems that turn ideas into measurable results this episode is not about AI agents (1:24) not as a tool but as an operating infrastructure for private equity firms that want speed (1:30) clarity and repeatable value creation welcome Dustin.

Dustin

(1:36) Hey well thanks I think you know my business better than I do at this point.

Melissa

(1:41) Well here we go we’re going to unpack it today now private equity moves fast but where do traditional operating models start to break down?

Dustin

(1:54) Well we’ve been talking to a lot of people in private equity but also family office (1:58) and recently search fund people as well and one of the very first things that I’m finding (2:03) is that people are having a hard time finding deals to source so one of the big problems that (2:10) we’ve been brought by a number of them is a lot of the data tooling that’s out there is just garbage (2:17) I don’t know if you’ve you’ve tried it but it’s like I don’t want to throw shade but let’s just (2:21) say that you know the common data source providers right you go to their website you pay tons and (2:28) tons of money to get access to a bunch of data and then when you start working your way through it (2:33) 50 of it 70 of it’s not accurate and it makes it really hard to find the thing that you’re (2:40) looking for and even when you do find those things you often still end up with a needle in (2:45) a haystack problem so if you’ve got somebody who’s looking to do let’s say medical spa roll-ups across (2:51) the sunbelt and you know they’re looking for something specific that meets their thesis (2:57) there’s a lot of disparity in those businesses so even if you find 10,000 of them in that data (3:04) somebody’s still going to have to work their way through it you’re still going to have to figure (3:08) out who you should be talking to and why what you should be saying to them and then somebody’s got (3:14) to go bang on their door and that’s one of the things that we’re finding is that a lot of the (3:20) private equity teams don’t have you know an outbound business development team they’re used (3:26) to doing a lot of things that get sent to them but those deal flows have been slowing down it’s been (3:31) harder for them to you know close out their funds or manage their roll-ups the way that they’re (3:36) supposed to. (3:37) I could keep on going on and on but I want to give you a chance to talk here but it’s been a fascinating journey to learn about this and it’s as a technologist I love pain points especially things that I could solve in interesting new ways.

Melissa

(3:50) And it’s so true though I mean we are a world with so much data right now we have the most data we’ve ever had but the most inconsistent data that we ever have seen so talk to me a little bit about why these operating models struggle to scale across these portfolios.

Dustin

(4:09) Well if you want to talk like if we continue on with that path but I can switch over into value creation or you know into some areas of due diligence but you know I’ll just keep on that path unless you want to go a different direction. (4:21) You know getting visibility into your asset class that you’re pursuing can be really really hard you know there are industry reports and they give you these numbers but when you when with something like our system right we can create brand new capabilities that really didn’t have before you didn’t have before. (4:42) So imagine having a team of NBAs that can go look at every single potential opportunity right.

(4:49) If you want to do let’s say commercial plumbing right you want to do roll-ups on commercial plumbing. (4:55) If you go looking for commercial plumbers you’re going to find that a lot of noise a lot of problems there. (5:02) There’s a lot of companies who say they’re a commercial plumber because they do some work in a restaurant or they handle some small regional bank.

(5:09) These are not the companies that are doing things like fresh build outs of manufacturing plants or you know doing the work for large business you know skyscrapers and such. (5:20) People that work on those like heavy industry kind of equipment. (5:24) So but what would it mean if you were deciding on what you were going to pursue in your fund and what you were going to do in that and you could look at all those companies and you could look at them specifically at the lens that you want to look at them for.

(5:37) So you can say I want to prioritize ones that are involved in manufacturing. (5:42) I want to look for ones that handle things like oil and gas right like there’s a lot of money to be made in oil and gas and there’s not a lot of companies operating in that space. (5:52) So if we had the ability to have an MBA go look at the entire pool and sort out all of the junk and say none of these are relevant and out of the let’s say 20,000 that we would look at we get 750 that are prime targets.

(6:11) When we look at all of that analysis in aggregate (6:14) we actually get market data and we get a visibility into a market that we’ve never had visibility into (6:20) because we look to see how they market themselves how they’re presenting themselves to the world (6:25) what environment they’re operating in what are the demographics in that area so we can give you a (6:30) fuller richer view of what that means and you might be thinking you’re going to pursue an asset class (6:36) only to find out that pool is actually not that deep and then if it takes 30 times to try to reach (6:43) out to somebody to get into a conversation with them to sell them on the idea of selling their (6:49) business when they never thought about that before that takes a lot of time and effort so your ability (6:55) to find somebody to get into a conversation is really low you’re and then the ones that you can (7:01) get in that sweet spot where you can have that moment of consideration would it be better to (7:06) understand that your total addressable market is much much smaller and then focus on something (7:11) that’s more relevant and where you might have better margins.

Melissa

(7:16) Yeah I love that I think it’s so (7:18) true and I think you know use the phrase strategic outcomes engineering right which I would argue (7:25) is maybe a little bit different or probably different than traditional strategic consulting (7:32) so talk to me a little bit about what that actually means and why outcome first matters (7:39) more than ever now ready to lead smarter and invest wiser on the executive connect podcast (7:47) we unpack executive strategies for wealth and influence hit the subscribe button now don’t just

Dustin

(7:54) watch act absolutely so this is a group that we developed inside of Google when I was working (8:02) there as a part of the data and the product team but because Google’s core business is data and AI (8:09) and ML and all of those sorts of things we were often the vanguard who had to put together the (8:15) main like backbone of the partnership deal so they would bring us in to a company who they were looking (8:22) to do a half a billion dollar deal with and you can’t just walk in the door and say if you give (8:27) me money I’ll give you a cheaper version of a thing right because what are they going to do (8:31) they’re just going to go walk to your competitor they’re going to say I don’t want to leave (8:34) give me this deal make this deal better and then I’ll just stay and keep doing the thing (8:39) but if you think about what a business needs to do to grow their value right this is not a (8:46) financial engineering problem it’s an operational engineering problem it is a market positioning (8:53) problem it is a scalability problem it is a risk problem there’s so many other problems that have (9:00) to be solved in there and in a larger business there’s a lot of people on the hook for those (9:05) problems so in order to come up with a meaningful change for the business something that you could (9:11) build real value in the company we created a pretty easy way of looking at things right we said (9:20) the world’s changed right and if we removed things out of the equation what would happen (9:28) so google’s got this principle of 10xing because they say if you try to pursue something that’s an (9:34) incremental change it’s often just as difficult than a moon shot so why not just try for a moon (9:41) shot because if you’re aiming for the moon and you make it into space it’s not a failure (9:45) right you’ve massively succeeded and if you hit the moon right bullseye your business is exploding (9:51) you’re having a great time so it really came down to a very simple logic look at how something (10:00) works end to end it starts off with where does the customer come in the door what brings them (10:06) in the door and is that door the right door for them to come in do you have all the stuff you (10:12) need on that side right the things you think about top of the funnel and all of that stuff right (10:16) and then how do we get all the way to where the business creates the value that then brings more (10:22) of those people in the door right and we want to create a 10x value is always what we want to do (10:26) because if you ask somebody for ten dollars and they’re going to make a hundred dollars out of it (10:29) they don’t tend to say no right that’s usually a done deal so if you look at all of the things (10:37) that you have to do and you say i’m going to use basic arithmetic here where can i multiply things (10:44) where can i divide things where can i add something new where can i minus something right (10:51) transformation and innovation live in that thinking and as a technologist as somebody who’s (10:59) been you know working ai now for what would what actually what we call ai you know the people in (11:04) the industry would call it ml but that’s an engineering thing uh the rest of the world (11:09) does now come to learn a bit as ai you know but the people have been doing this for a long time (11:14) you you have to build very like narrowly defined things that answer a very specific question and (11:21) is very focused so what you’re experiencing with a chatbot where it runs off and it does a million (11:26) things and it comes back and it’s like 60 right and 40 wrong and you don’t know where it’s going (11:31) from that doesn’t have you can’t do that in business right you have to stick something (11:36) in the middle of there to make a decision or to you know do a thing and it’s got to be able to do (11:41) it consistently and measurable so when you look at all those things and then you ask yourself well (11:47) you know we worked with a large insurance company and you know they said that they had a problem of (11:53) how do they how do they knew who to give insurance to well how long does it take you (11:58) takes us six weeks end to end what’s your dropout rate huge people don’t want to wait around for six (12:04) weeks they want to hit the button in their app and they want the insurance before the day is even over (12:10) but you have to do a lot more work to get to that point you have to change who you are you (12:15) have to change how you do things you have to go get data from places where you never thought to (12:19) get data before you have to see how your business makes decisions and then you have to train models (12:24) to make those same kind of decisions the cool thing is in that process we can actually get (12:29) rid of the bad decisions to some degree and it’ll be better at making really good decisions (12:35) however there’s one thing i’m going to say and i’m going to let you talk because i know i’m going (12:39) human in the loop we don’t take the people out we put them in the place where they’re most (12:47) important and we get them out of the things that they don’t want to do that they hate doing

Melissa

(12:53) yes amen to that i think it’s such an important piece we you know it’s this fear factor thing (13:00) these days with ai we’re going to lose our jobs and you know the tools are going to do everything (13:05) but you’re spot on we still need the humans and they need to be in the loop and you know we’re (13:10) hearing everyone talking about automation everything’s automation and so i want to talk a (13:16) little bit about how are ai agents fundamentally different and what you know how do they adapt in

Dustin

(13:25) time oh boy how long do we have here (13:32) um so there’s there’s a lot of ways where you might define what an agent is and how they’re (13:39) going to react is wildly different what’s been popular recently is things like open claw which (13:46) is semi it’s mostly autonomous agents running off and doing things but boy do they run off and do (13:53) things right and it’s it’s interesting to work like this it could be a little bit like riding (14:01) a bronco right i’d like to pretend i’m a texan i’m not but i would say like riding a bronco (14:08) in a rodeo can be what this experience is but then you see the potential what we were doing (14:15) you know in the designs that we worked on is taking out that element you don’t want things (14:22) to just run off and do something you need to make sure that you’re hitting quality targets you need (14:27) to make sure that you’re following business rules and in order to do that you have to give the ai (14:34) the right instructions with the right data at the right time and limit what they can do (14:41) and that’s where things are going to be radically different when you are talking to you know a major (14:47) fortune 500 company like a manufacturer who is trying to figure out whether they have broken (14:53) chicken bones going through their assembly line you can’t have that variability of an agent sitting (15:00) there and saying man i think it looks good right it has to be declarative that does not pass our (15:05) criteria so that’s what we used to do with simple models but now that we have more complex models (15:11) you need to be doing it like that as well it doesn’t mean that they’re not you know have any (15:16) agency at all they have flexibility and they’re kind of but you ever you ever go to disney world (15:22) you ever go on one of those on rails rides and it kind of feels like you got a little control (15:29) because you kind of move the wheel and it goes left to right a little bit but you can’t go (15:32) anywhere but straight right that’s what businesses actually need and when they don’t have it it fails

Melissa

(15:40) and i agree and i think it’s so kind of back to what you were saying i think one of the biggest (15:47) challenges right now is kind of with the human in mind right is translating (15:54) the strategy and the vision that we have as a company with ai into actual execution and so (16:02) let’s talk a little bit about how do ai agents help bridge that gap so we can actually get into

Dustin

(16:08) the execution yeah the easiest place to go hunt this stuff out is just ask people what they don’t (16:15) ever want to do again that is really the like i mean you talk to leadership and they’re going to (16:21) tell you all their kpis and they’re going to tell you their lofty ideas and yeah you know we want to (16:26) move towards them because they’re on the hook for delivering stuff and if you give the people below (16:31) them what they want that doesn’t necessarily mean the people paying the bills are getting what they (16:35) want so you have to make sure you understand what the north star is and what all the lighthouses are (16:41) that get us to that place but then when you go down into the weeds and you start talking to people (16:46) and you say tell me about your life tell me how your day starts tell me what you do tell me the (16:53) things that you don’t want to do tell me what you think your your colleagues suck at and that you (17:01) know you wish everybody was better at and they could all be consistent in that mess you are going (17:06) to find tedious work right things that you were super happy to do when you were you know fresh (17:13) out of college and then a year later it is the sort of thing that you are complaining to your (17:17) friends that you are going to leave the industry and become a surf instructor because 16 hours a day (17:23) of digging through a million documents your eyeballs are about to fall out and you hate your life (17:29) the moment somebody says that then the next question is how often is that and they go every (17:35) single day and they’re like okay yeah we’re on to something there and then what we do here is we (17:41) figure out and this is not something we invented this is an old six sigma black belt thing you (17:48) figure out what the costs are around those how much does it cost in time how much is that person’s time (17:55) how much does it cost in the time that it takes you from getting to the the information that you need (18:02) to the answer that you have to make the decision you need to make and if you save that time in a lot (18:09) of places it can be extremely valuable far more valuable than any people’s time right so once we (18:15) start coalescing around those things in the business right areas where you might need (18:20) uh standardization if you’ve got a call center of 500 people you’ve got a massive disparity (18:26) in how they work with people and what their experiences and what they say but if you (18:31) normalize that out with a shared knowledge with guidance from agents who are listening to the (18:38) calls because you know these are things that we’ve designed and would feed you here’s what you should (18:42) say here’s what’s coming out of the records here’s what you should think about you know here’s some (18:46) options you should talk about then what you’re doing is you’re dropping the cognitive load for (18:52) those people to the point where you’re putting in front of them a decision that they can easily (18:57) make with the right context and then you are relying on the person and their wisdom and (19:03) their intuition and their ability to know beyond the limitations of what an ai can do here (19:08) and there’s massive value to unlock there i found and i’m just going to say this really quick (19:15) i found one area of inefficiency where people were just chattering back and forth on where to send an (19:22) email we found out it cost the business one million dollars a year in person hours and then (19:29) we said if we recover one hour of those people’s day every day can we have them call up your (19:36) customers proactively and ask them if there’s any business that they could do and be a good partner (19:43) to those best customers that led to 30 million dollars a year and they paid one million dollars (19:52) for that solution to get built and then it made them 30 million dollars a year every year for the (19:58) last few years right and then we reapplied that pattern everywhere and that’s that’s such a good

Melissa

(20:05) point i think one of the things that we get into as also as a fellow engineer sometimes we get into (20:12) this you know perfect planning perfect execution but you emphasize of adaptability yeah and i love (20:22) that because in a world that’s changing so so fast we all have to be adaptable and the strategy we (20:30) started with may not be the strategy that we’re finishing but to your point if we can do and shoot (20:35) for the you know the moon the stars wherever we’re shooting and we can land like you’re you were just (20:41) explaining 30 million dollars is a lot of money and so why is it so critical to emphasize (20:49) adaptability right now versus you know perfect planning this episode is brought to you by summit (20:57) ventures if you’re an accredited investor summit gives you access to one of the greatest (21:05) tax advantage opportunities direct ownership in oil and gas their projects deliver what they call (21:13) the triple play cash flow equity growth and powerful tax benefits and here’s the best part (21:20) these investments qualify for 1031 exchanges that means you can roll gains from real estate (21:28) into energy while deferring capital gains to learn more and get a free white paper (21:34) oil and gas demystified just visit www.summitven.com forward slash executive connect

Dustin

(21:46) well so i was in enterprises and various businesses for a very very long time right (21:53) and one of the things that we noticed there is the planning problem people spend a lot of time (22:01) especially in the upper ranks i spent a lot of time writing reports that i nobody read so that (22:07) they could see my little tiny executive summary that told them what they wanted to know to make (22:12) their decisions they would spend sometimes years planning this if we were doing like a very large (22:18) merger and you know acquisition for like let’s say mid-market enterprises it might be nine months (22:25) of planning 18 months of planning whatever that is and then the plan is out of date the moment (22:32) you start right because it’s all historical already the moment you start everything that (22:37) led into it’s already passed and the world has already moved on but then you’re forced to continue (22:42) on with this plan as because you’ve got it tied up in budgets you’ve got it tied up in politics (22:48) what a better world looks like what the real future of business looks like in my opinion here is you (22:55) are going to have ai systems that are going to be augmenting the business and they’re going to be (23:00) helping to make decisions and surface information in ways that we couldn’t do before we were doing (23:08) a lot of this in google with data analytics and helping people to understand here’s a single (23:13) pane of glass here’s a digital twin of how your business and your industry operates right giving (23:18) invisibility into it and letting them make decisions quicker because if you have a digital twin and (23:23) the world’s changed and there’s a hurricane in florida you could redirect all of your trucks (23:28) into the carolinas and then when that hurricane passes you can have them drive down into florida (23:34) and get premium premium loads in the logistic industry because you’ve got stuff that is on (23:40) the verge of going bad and desperate so you know people who need to move this but if you can’t adapt (23:49) to that change for six months then somebody else is going to step in and do that right so that plan (23:56) that you make needs to be more agile needs to be more adaptive and businesses are going to be more (24:03) need to be more and more data driven i would say ai has now come in to be the biggest enabler of that (24:09) because before it was quantitative analysis here’s how the numbers roll up that’s the history (24:15) that passed now it’s qualitative analysis what does the history and what does this mean and what (24:21) does that mean all in one context what does this mean in a qualitative analysis that used to only (24:29) be the the domain of people but now what happens when i can do this a million times in two hours

Melissa

(24:35) how does that change the world well when it’s done right the ai can change the value creation (24:43) timeline and we get places faster we can scale companies i think a lot of times in the world (24:49) you know your peer was whoever had a similar revenue than you do and now it might be someone (24:56) that’s just starting their company and because they have they’re more agile to your point they’re (25:01) able to move faster than you know and nothing is big companies but we have a lot of meetings (25:06) to have meetings to have meetings for somebody to say okay this is the decision let’s go (25:10) versus some of the smaller companies you know they’re able to you know pivot quicker

Dustin

(25:18) you know what think about this how much managing up happens in a business the bigger the business (25:25) gets the higher the stakes get the less the executive leadership actually knows about what’s (25:31) going on but what happens when your ceo can go to the agents who have been analyzing every customer (25:40) support email that comes in and says i want to know what’s been trending in the last month in (25:46) my business i want to know what my customers are talking about i want a SWOT analysis tell me what (25:52) they say we’re good at tell me what we’re weak at where are opportunities that we’re missing (25:56) what threats are they making and then all that managing up goes away and all of a sudden you’re (26:03) seeing more reality about your business than you’ve probably seen ever if you came in and took (26:10) ownership of something or if you grew that business there’s a point where you feel like you’ve lost (26:15) visibility and this i think is one of the things we can give back and we can also give it in a new

Melissa

(26:21) way that’s never been done before yeah i love that i think it’s so true and i want to kind of (26:28) i’ve got so many questions i’m going through my head right now one of the things i know in my (26:33) industry that’s becoming a headache right now is the tool stack trap where we have so many tools (26:41) we’re buying so many tools tools on top of tools and we’re hoping that we have whatever the outcome (26:49) may be or the change outcome or whatever it’s for talk to me a little bit about where do you think (26:57) companies are going wrong right now with their tool sacks without actually system alignment first

Dustin

(27:04) okay well i’m going to wander into some dangerous territory and i apologize to anybody who might (27:10) want to give me money after this but i’m going to say that this actually comes from the vc world (27:15) that’s where the problem starts their model is about finding a bespoke widget in an existing (27:23) thing and capturing that one little piece of the market and then hitting hyperscale and if you can (27:29) become a unicorn great and if not you have seven years to die you are not there to survive the (27:37) survival rate for vc-backed businesses is five percent after 10 years right five percent so (27:46) there you are on the other side of it and you need an end-to-end solution every business to some (27:53) degree has a lot of standard things right there’s only so many ways a normal person should slice (27:59) a pie the people who do it into squares i’m not going to talk about you but let’s just say as a (28:05) new yorker we know what the problem here is there’s certain things that have to always be done (28:10) the same way but then there’s certain things that are so specific to your business that when you show (28:16) up you need a platform right and that used to be the way of things in the world you would get the (28:23) sales force you would get the service now you would get the entire microsoft platform these were things (28:28) that you could build an end-to-end business solution with that could handle the entire (28:35) pipeline the entire process that you had to execute but now you are stuck with all of these (28:41) one-off little tools because another industry needs that in order to hit their investment thesis

Melissa

(28:49) right yeah and i think that you know to your point um not all of these tools play (28:57) nice in the sandbox and they don’t integrate they’re complex and maybe they’re overloaded and (29:05) so really getting a clean system architecture with a strategy is something that i think is (29:14) far overlooked anymore than i see and so let’s talk a little bit about the future of this pe (29:21) operating model when we’re looking ahead what’s going to differentiate these top performing pe

Dustin

(29:29) firms i 100 believe it is and you know of course i want to sound like an ai bro but you know i i do (29:38) believe that it’s ai transformation because i just spent the last 20 years of my life before this (29:47) working on digital transformation right and it used to be that you could buy a little (29:52) manufacturer in iowa somewhere throw in an erp fix their finances a little bit get their house in (30:00) order boom value creation done right now you can sell them off and you were you know you could just (30:06) move on but that work has been done already we have a million little sas applications because (30:14) these businesses didn’t want to build their own billing tools so they needed to bid somebody (30:19) else’s to buy it and that’s that’s what flooded the industry so we have this rise of you know (30:26) sas applications and you know pe buying into this digital transformation but go to your dentist (30:34) and see how digitally trans like native they are at this point right and not to disparage dentists (30:41) i love my dentist he’s a great guy please don’t buy mpe i want him for us right but you know (30:48) everybody’s already got that where they need it where what we have is we have lots of businesses (30:55) that are drowning in operational overhead when things that had to be done that needed (31:02) qualitative subjective decision making knowledge about a business now you can’t just get that with (31:10) prompting you can’t just get that with some prompting some databases a lot of times you’re (31:13) going to need to train models and to do things and there’s not a lot of people to be able to do that (31:18) so the big companies are hiring all those people up and they’re putting them in places and saying (31:23) hey if we’re doing you know let’s say we’re doing short-term loans for a niche industries to cover (31:30) you know a three-month period that needs to and today it takes us six weeks to get that done if (31:36) we can get that down to two days and then i can have one person getting 10 times more work done (31:44) in that process then with no changes to the business other than the fact that we are getting (31:50) rid of a lot of busy work that people probably don’t want to do or you probably don’t want those (31:55) people who just want to keep on doing busy work because you know that’s not a dynamic business (32:00) right but when we get that there now all of a sudden we’ve increased that business’s flow (32:06) through rate by 10 times right but it’s an upfront investment you can’t just sit there and walk in (32:14) the door and say hey go use notion and you’re great we’ve AI’d you it’s not going to happen

Melissa

(32:20) and you know the other piece of it is i think you know AI is changing the diligence process by (32:27) a lot and we’re not spending as long and diligence we’re leveraging AI and so with (32:34) that being said where should firms start building now well you know there’s the first thing that i

Dustin

(32:42) would say is the thing that i say to any business right look at the thing that blocks you the most (32:49) what takes the most amount of time where is your most amount of risk if you have a due (32:56) diligence process that takes you six weeks and i can tell you about problems before you even get (33:04) into those first into that first week before you’ve even got into a you know call with them i can sit (33:10) there and say hey this business they’ve got people complaining that they’re going to sue them (33:15) we’re finding that the area they’re operating in is in decline right there’s all of these leading (33:21) signals that you might not have found out because you needed that inside information but when we can (33:28) do an outside in analysis before we even get into a conversation and sit there and say hey you know (33:33) if there’s something not great about these guys they’re not the cream of the crop i’m going to (33:37) put them down on the lower end of the list i’m going to rise somebody up and then when i spend that time (33:42) i want to get through that process of figuring out whether there is a no as quickly as possible (33:48) so if i can get out of that conversation before it starts ideal once i’m in it if i can find the (33:55) thing that is most likely going to fail and it’s probably not going to be your finances (34:00) it’s probably going to be something you don’t know about the business or you find out worse yet 30 (34:05) days after you purchased it but like what if we could look at every single email that’s ever been (34:11) sent out what if we can find all of those weird spots like hey their key supplier is the guy’s (34:18) brother-in-law right he’s paying lots of money there you know or maybe we find out that the (34:25) founder the owner everything has to go through them and without them there is no business and (34:31) their successor is not prepared to take ownership of that you can’t just drop somebody into that (34:37) role and say hey you’re a smart guy figure it out right maybe you can but you lose business (34:42) continuity you lose you know the institutional knowledge but what if we could capture all that (34:48) stuff what if we could figure out ahead of time and either that helps us to navigate that process (34:53) faster or to get to that no quicker so that we could pay attention to the ones that we do need

Melissa

(34:58) to say yes to yeah i love that it’s so true i’ve i’ve seen that over and over again the leadership (35:06) everything is made by one person so the entire company is really one person so let’s talk about (35:10) servant leadership your you describe your style as servant leadership how does that show up in the (35:18) transformation work you’re doing money rebels is on a mission to help professionals just like you (35:25) get their money working harder for you their clients free up an average of 35 000 dollars (35:31) their very first year without having to work extra hours to show you how they’ve put together (35:37) a powerful training called cashflow secrets and the listeners of the executive connect podcast (35:43) can get it completely free just visit moneyripples.com forward slash secrets and enter the

Dustin

(35:49) promo code exec yeah people love change they love change when it’s the change they want when it’s (35:57) the change that makes their life better what they hate is the change that they don’t understand and (36:03) they don’t know right and if you are telling somebody that they need to change then you have (36:10) to be the one that demonstrates the change this isn’t anything new right this is the thing we (36:14) tell people to do with their children right you’re you’re the people you lead are no different (36:20) if they see that you will work as hard as they are if you will deal with the pain that they deal (36:26) with that you don’t just point at things and say go you know figure it out but that you are sitting (36:31) there in the mud with them often taking on more pain than they will they will follow you right (36:40) in google i ended up in the weirdest situation right leadership told me they wanted me to change (36:47) how thousands of people worked in their sales process and we’re talking about people who are (36:53) expert sellers people have been selling for a long time but i’m the data driven guy i’m the one who (36:57) has to tell you who to focus on and what’s strategic about that business and why you should (37:01) go after this company that says they’re an ai company that company not that company that says (37:05) they’re an ai company because one’s really an ai company and the other one and they just do like (37:11) everybody else right everybody’s gonna use ai there is a huge pushback when you sit there and (37:16) say i’m going to come in and tell you how to do your job differently but when you demonstrate over (37:22) and over again on stage under the spotlight right in front of them that you’re doing that thing (37:29) then they start to feel like i should be doing that thing and then when other people get passionate (37:34) about it and they also do that thing then you have your change makers right this is not again this is (37:41) not anything that we’ve invented this is change management right like you get your change champions (37:46) that i think is the biggest thing right if you are a leader and you say that the world’s got (37:51) to change then you have to be the first one that changes the world and it’s got to be your world (37:55) and you’ve got to let everybody know that you’re different as a result of that and then you’ve got (37:59) to go find your acolytes your passionate people and they’re usually oddly enough they’re a mixture (38:06) of the people who are most positive and embracing and the most violently rejecting the person who (38:13) says no the hardest and loudest is the one that you need to say you’re in pain how can i help (38:19) and when they see that that’s actually what you’re there to do then they become your biggest change (38:25) champion then when everybody around them starts to feel that FOMO and in a sales org that is about (38:32) making money right they’re just making more deals they’re ringing the bell louder than everybody (38:37) else that’s who i want to chase after but every business every team every department’s got their (38:42) own version of that so what is that thing that people want to be show them how to get there

Melissa

(38:50) and do it the hard way yeah and i love that because you’re right i think people (38:56) don’t mind change when it’s something they understand too i think a lot of times in the world (39:02) you know it’s ai ai ai ai but i don’t know i would tell you that a lot of ceos and (39:08) executives that i work with regularly don’t fully understand how it’s affecting their (39:14) business today and they typically say it’s it’s job to understand ai but i would argue it’s all (39:21) of our jobs to understand you know ai how it’s affecting our business wherever we are (39:28) and so i want to kind of in closing i think you know we’ve covered so much but if there’s one (39:35) kind of mindset shift pe leaders should make around ai what is that yeah i’m going to double

Dustin

(39:43) down on what i was saying earlier it is ai transformation it is looking at these businesses (39:49) and thinking you know if i need to move this business let’s say 15 bump then there is (39:58) automation and augmentation challenges to solve there and finding those places in the business (40:05) where and i’m a systems person right so if you change one part of the machine like let’s say (40:11) you change the engine in your sports car because melissa i think you probably have like a really (40:16) awesome mustang from the 60s that’s all tricked out right and remember when you put in that (40:22) like that turbocharger that gave you 700 horsepower it puts i do i know right it it (40:31) puts a massive amount of strain on the other surrounding systems the transmission now needs (40:36) to be upgraded the brakes need to be upgraded you need a bigger tires hell you probably needed (40:41) wheelie bars to stop yourself from lifting off in the front right because that’s how she drives (40:46) it is identifying those blockers in the business where you can now ask this question that says (40:53) five years ago i couldn’t put automation here or i couldn’t put any kind of augmentation here (40:59) because you needed a human to make a qualitative subjective decision that required person to (41:05) understand the context and be able to reason through something now you look at those things (41:12) and you say if we’re spending 80 of our time doing x if i can bring that down to 10 of that (41:19) time now i’ve got a huge amount of time recovery in lots of different ways financial recovery (41:24) you know all of those things how just like when we did with the logistics company how can i (41:30) reapply that human capital in a place where they will be more impactful because if you remove them (41:38) and this is the big warning that i’m going to leave off with if you start removing the people (41:43) and replacing them with ai the people that are left afterwards are going to feel threatened (41:51) and they are going to push back and they are going to stop this change if you reposition those people (41:59) and you put them into more prestigious work into those places where you say your job was to make (42:05) this decision and it’s so important and it’s so hard to the business and i’m going to clear the (42:09) entire field for you so you can make that decision every day all day that is you putting them up on (42:15) stage telling them that they’re rock star and giving them a chance to shine right that’s when (42:21) people will embrace these things when you take away the stuff they don’t want to do and then (42:25) you put them on the stuff where they know they’re genuinely moving the business because i don’t (42:30) care who you work for i don’t care if you’re in waste management or whether you’re in a hedge fund (42:37) everybody who works in that business wants to feel like they are making a contribution to the

Melissa

(42:43) success of that business yeah i absolutely agree with that and i would argue that’s how you build (42:50) high performing teams and it is something that once you get them you know everybody on the yellow brick (42:56) road it’s amazing how fast things move when you have a cohesive team working together all pulling (43:03) the same direction with clear understanding and visibility of where we’re going and how we’re going (43:07) there together and so for leaders focus on value creation or operational excellence and our building (43:15) systems that actually work under pressure will link dustin’s work inside the show notes and this (43:20) conversation wasn’t just about ai trends it was about engineering outcomes that compound over time (43:28) if you enjoyed this episode of the executive connect podcast make sure you follow it and share (43:34) it with your other friends and listeners who are building real enterprise value for more conversations (43:40) on investing operations and the future of business subscribe to youtube or your favorite podcasting (43:46) channels thank you for being here today dustin that’s the executive connect podcast