Innovation at Scale: The Role of AI

0:00There's going to be a wave of people that are about to come into the workforce that they're just doing this stuff in their sleep. It's completely native to how they work and live. Welcome to the Talking AI Podcast, where we talk AI with both experts in the field and early adopters. I'm your host, Matt Page, and we're here to demystify AI for you so you can get some value from it. Let's talk some AI. Today, we're joined by Neil Goodrich, CIO of Invista Forensics, and previously CIO and Chief Innovation Officer at M. Holland. And welcome to the show, Neil. Thanks. Thanks for having me. And we obviously talk a lot about AI on the Talking AI podcast.

0:37And whenever you're talking about something new and emergent like AI and generative AI, the topic of innovation naturally comes up. And Neil, as a leader running innovation, doing it at several organizations, the burning question I got is why is change so damn hard? What is it about change that organizations just struggle with? I don't know. you think about um in your personal life you go to the gym and you you don't expect to stay the same week to week you want the change if you're out the garage trying to teach yourself how to do woodworking you don't want to stay the same so it's funny you need to work and then there's a general aversion to change but so funny we chase it now the other parts i think um maybe it's uncertainty people feel like it's going to get uncertain and they don't like the uncertainty but I think that's been something that we try to turn into a positive right from sort of change averse to like well let's go celebrate some change like that change is cool let's make a big deal out of that change right that's interesting it's like that human nature aspect of it humans just aren't good at change but that almost that that celebration that gamification of it in a sense interesting component there.

1:55In previous chats that we've had, you've talked both about little-I innovation and big-I innovation. It was actually the first time I'd heard about it framed in this way, but what does that mean? And then what is AI, AI, generative AI, whichever you want to frame it as? Is it little-I? Is it big-I? Where does it fit in this kind of spectrum? I think it's stolen originally out of the sort of horizon framework. I think McKinsey had like the big long, you have the big long project, takes a long time, it's very uncertain. And then you have the medium, the small bites. So we started thinking about that from an innovation standpoint, which is small bites, stuff that you could go after.

2:42And that's the small, the incremental piece, which is still innovation. It still creates, It's a culture of let's celebrate change. Give us your idea, right? Even though it's not a moonshot. And it's the innovation that start to expose, right? Whether it's developers learning new skills, because it's a new technology platform, and it's this little bite-sized easy thing. And then they ladder up and then, oh, we can take on the next small I project. And in the background, you've got the big I projects, right? The year-long, the 18 months, the multi-days, the uncertain projects, those to me are the big I's.

3:24It's funny, I actually think AI can be both depending on what you're doing with it, right? You can have it be really a big deal or it can be one of those bite-sized undertakings. is it a little piece of code that reads emails and makes sure that a record goes to the right place? I mean, that's innovation. That's a terrible part of somebody's job today, right? We can just take that off their desk. If you ask them, I'm pretty sure they would tell you that's innovation. Their life got better, right? The organization got more value out of that. But so it's some kind of multi-part competitive differentiator, right?

4:08you're going to turn out some new product that's powered by AI, that's also innovation, just a different category. Quick break in the pod. If you're listening to this podcast, chances are you've been thinking about how to actually use AI inside your business. And that's exactly why we built the AI Opportunity Finder. It's a free tool that helps you uncover high impact, tailored AI use cases based on your business, your goals, your pain points, and your industry. No fluff, no generic use cases, just real ideas that fit your business and they're ranked by ROI potential. It takes about three minutes to run and it's like having your own personal AI strategist for free.

4:46If you want to try it for free, check out the link in the show notes or go to hatchworks.com backslash AI dash opportunity dash finder. I don't know if I answered your question. Did I answer your question? No, you did. That's a really interesting perspective because you can't think of it on both spectrums, right? It could be to your point, like AI literally is going to, that holy shit moment of it's going to change our entire business model and we got to do something about it. Or it's like, okay, developers now have a co-pilot they're going to start using in an incremental way. Still big change, but it's, it's smaller in nature.

5:24And I guess too, you could have it to where some of those small eyes ladder up into a larger eye innovation? Probably some of those occurrences, I would think, as well, right? Yeah, hand down. We work with DePaul Innovation Lab here in Chicago. We're based in Chicago. And we gave them sort of an open challenge. We said, you know, if we give you what we have in terms of data, can you go build this tool? And they went after it. It was really cool to see they were every week learning, right? Because stuff was changing under their feet, right? And literally models were changing. Microsoft services they were using got changed in the middle.

6:07But along the way, one of the great examples, they built essentially a QA part of this tool that was supposed to ensure that the confidence in the outcome was high. Well, essentially what they were doing is they were assessing the quality of our, we do cause and origin reporting largely for the insurance industry. So we send field investigators to look at a collapsed building, a fire, and we determine what happened. So handwritten notes are a big deal in our world. They fuel the final report. They are used in legal cases. So they wrote this service that assessed the field investigators notes. And to them, that was just a thing they had to write to get out of the way to get to this outcome.

7:00And when they demoed that piece, we were all like, wait, stop. Hold on. Did you just did you just write a note quality assessor service to like stop the presses? Like we could just that's its own product right there. You just saved every technical manager in our organization, right? He doesn't have to read all those notes anymore. So you would never find that. No one's going to wake up in the morning and be like, you know what we should do? We should write a service that assesses the complete, like, that's just not on, that's not how you're going to think about it. And I think undertaking, that's the moonshots, right?

7:36Like whether or not the product ends up being what you think it's going to do, that discovery process. I used the word serendipitous yesterday and like, I got a lot of heat for it in the office. Everyone thought it was sort of a flighty word. And I was like, no man, look it up. Like it's unplanned, right? Sort of weird, lucky, unplanned. And I'm like, that's what you're after. You're going to go put yourself in circumstances so that you can maximize your chance for serendipity. Right. And so that's what happened. And we learned a bunch about other potential product ideas that were simpler. But if we went and built them, they would be part of this larger tool later.

8:19Right. And so it was a really great ladder up. I think you said ladder up earlier scenario where like build these building blocks and you recombine them at the end and they make this third tool. Right. It's cool. Yeah. I love this example. And this is kind of what triggered us chatting here today was having this discussion about this example. You mentioned like you went for the home run and you got like these hands gentle base hits out of it. I'm kind of curious, do you recommend that? Go for the home run and just you're going to naturally get some of those base hits out of it and just make sure you're looking for those?

8:55Or should you just go for some of the base hits that may be easier or maybe it's some combination in your approach to innovation? Yeah, I think we have such a lame answer, like both. But I think they do different jobs, right? So currently, we've got our team working on bite-sized, simple use cases. So what's that doing? That's continuing to expose the organization to change, right? So from a cultural perspective for the organization, they see us doing stuff. the technical team gets to put their hands on and practically apply a whole new set of tools in a low complexity low pressure situation because that's where you're going to learn best right so no one's asking when this piece of code that's going to route emails is going to be done because no one knows we can do it right so they have the space to learn so to me that's uh almost development and learning component, those bite-sized pieces.

10:02And then the bigger long arc piece, big innovation, we started with an idea that if it worked, would be powerful. So it wasn't just sort of a random idea. We were going to win either way. We were either going to get this big moonshot idea that worked, or we were going to learn why it doesn't work, what's wrong with our environment, right? And so we did learn that. We have data organization challenges that would prevent us from doing that effectively. If we really wanted to do this big tool that we were thinking about, we'd have to change a bunch of behaviors and processes. So we sort of got the recipe for the prerequisite change to do this thing.

10:43So I think that the outcome base, right, if you're thinking about, I want to do this thing, and if this doesn't work, we're at least going to learn about other alternatives or prerequisites to go do the big change and tackling stuff that's practical, gets people in there. We talk a lot about, and you and I have talked about, when somebody brings a challenge to you, the technical team only knows what they know. So they're going to go right to the tool sets that are already in their mental toolbox, right? So how do you get AI? How do you put those new AI tools in that catalog of options? And there's no fast way to do that.

11:24They have to get exposed to it. They got a wrench on the engine. They got to get their hands dirty with it. And I think that's to us why you do a portfolio of different things, because it's all different stages of learning. Yeah, you almost need that fire starter, that art of the possible so they even have an idea of what to start considering. It's the whole concept of you have your known knowns, your known unknowns, and your unknown unknowns. There's a lot in that unknown unknown category that you've got to surface. but completely off topic like this DePaul Innovation Labs it seems very interesting and kind of a cool thing is this the students doing this or is it uh who's a part of that I mean just out of curiosity it seems like a really neat thing shout out to them um they are connected to the grad they're it's graduate students um and uh the original founder still runs it who's a long-time professor there and they will leverage existing students.

12:28They will sometimes get some alumni who have some experience. So it's cool because you think about this vast network of new skills that nobody has in your workforce because when they were going to school, those skills didn't exist. And these guys are chopping at the bit to apply stuff they're learning on class in class on Tuesday, they get to come to the lab and do stuff. So, um, we, yeah, they, they do a lot of open challenge work, right? Can you figure out a way to do this? Right. And it's been a cool, it's a cool relationship. Yeah. You were telling the story and a picture like the student presenting this thing and you're like, stop, what was that thing?

13:09And the student's like freaking out. Like, what did I do? What did I do wrong? Uh, in, you know, again, off topic, I was thinking about this yesterday on a walk shower. I can't remember, but there's this whole group of kids in school now that are using these tools just naturally part of their life. They don't have all the baggage and history that we do. So once they get into the workforce, I think that's going to be really interesting because they're going to bring this whole new approach that's just native to how they do things. which gets back to the point where you know you got to start adopting this stuff because there's going to be a wave of people that are about to come into the workforce that they're just doing this stuff in their sleep it's completely native to to how they work and live it's uh it's not it's funny the technology changes but like if i say to you how do your parents use email how do you use email how does how do your younger employees how to teenagers like those are four different uses of email, right?

14:12Like it seems, and I think we came up in an era where the email was to us what AI is today, right? We just use email, email as part of that. And you look at texting behavior and the level of integration of texting behavior and the way different generations leverage the texting, right? It's all about where that technology hits you in your life cycle, right in terms of are all your working habits baked already are they being formed and how do you artificially insert stuff right as a whatever 30 40 year old employee how do you go artificially put the ai pieces in your toolbox when this kid coming out of school at 22 those are just like in there already they're just part of the option set and I think that's what sparks a lot of our sort of education piece right yeah which I guess gets back to the innovation programs you're running running making sure you kind of have a diverse group in there with with some of those younger people and just different organizations and whatnot yeah that was cool too yeah so I want to do something a little different a little fun and you can use you can cheat with chat gbt in this exercise but as I was thinking about this episode, we're talking about innovation, the process of innovation, right?

15:32Like how you go about innovation. And I was thinking AI in everything that's been going on over the past year or two has the potential to actually disrupt the process of innovation. So I'm curious, like a thought experiment between me and you, we can just riff on random ideas. Again, use AI, your favorite plot or chat GPT if you want. But where do you think, like what parts in the process do Do you think AI is either going to change the process, enhance the process? Maybe it makes it worse in some areas. Any thoughts around that? And if you want a second to think, I got a couple top of mind. I was cheating with ChatGBT ahead of time.

16:14Let's hear yours. Let's hear it. I think that would be interesting. So the first one I had, like the innovation part, right? You could do the brainstorming, the ideation, all that. But you want to make something tangible to show it off, which is the whole idea of rapid prototyping, proof of concepting, all that. Which, as you know, if you're going to do a real prototype, that's a developer resource or it's just something that's a wireframe or whatnot. But with AI, now anybody can go from 0 to 60, especially in the proof of concepting phase, very quickly. and there's actually code below it like it's playing around with claude um sonnet and their artifacts like now you can have anybody in the organization with an idea which is super cool because you have the business people that now can participate in a more intentional way in a much faster way which as you know with innovation you the faster the cycle is the more feedback loops uh we did a lab recently with one of our solution architects and he's building like a poc in a few minutes during the lab.

17:25And it's just like, you know, kind of one of those mind-blowing experiences and this is just going to be native and new. So like that inserted into the innovation process is really like interesting and compelling to me. Yeah, the more people that are putting ideas in the pool, the higher chances that you find that lightning strike, right? So you're like, how do I get more participation? And if all of a sudden, I think about a lot because I can't draw, which has been one of my great frustrations in life i like failed in art class like i could not stayed right so uh you know mid-journey has essentially i felt sort of like being in the matrix when they're like i need to fly a helicopter i can now draw effectively right so like all these things that i had in my mind that i could never really render i can do and i think about folks in your organization who are like oh yeah it's just it would be like a screen like this right that's one whole version where people can get a wireframe, render an image, right?

18:22To your, it's the prototyping, but it's also the communication and sharing and storytelling where you could start to align people or get people excited. The code underneath it, that's just all bonus rounds. Like the idea that you would be able to jump off on that. The workable prototype, the ideation is questionable. That's my initial gut reaction when you asked me that question. I was like, oh, ideation. But if you've ever asked it, if you've ever asked him this thing, like, first time you ask it, yeah, a couple of them are, you're like, oh, okay, that's good. But you keep pushing the, you know, the do again button and you start to see it.

19:02So I think your acceleration play is going to be the answer in a lot of those dimensions. Like, I don't think it's going to, it's not going to be the source of anything. It's not going to help you with the idea, right? I do think putting the power to build and show, or like, think about the departmental power user who is allowed to build Power BI reports, right, for their team. But now you've got somebody, or the person who builds power apps for their team, and now they have the ability to prototype, like, applications. Yep. yeah and so the brainstorming one's interesting because early on i had the same kind of notion i was like okay well you know the response is kind of generic and whatnot as i'm playing with it there's like this nuance you know where i find it useful is not like giving me this amazing answer out of the gate but it gives me lists of ideas relative to what i'm brainstorming on and then that triggers other ideas and then I go deeper on the ideas so it's almost like this uh um you know co-pilot terms used a lot but it's like this extra person on the team to kind of put out ideas and it's getting better with each you know iteration that comes out so that part's been kind of interesting you know just it's like this extra brainstorming I almost view it as like this extra a person in the room almost it's like this person participating in the the exercise a bit uh but you mentioned like the you're horrible at drawing hand drawing and whatnot but like now you can just do that bad wireframe drawing and say hey take a picture of it turn this into a clickable prototype and it can do that now which is like crazy cool as well yeah the um ocean that i look at the so uh we had this year, we had a person join our data reporting team, who was sort of a, we use Power BI, he was Power BI specialist, but he wasn't just a back end developer, he had spent a lot of time sort in the prototype world.

21:17And so you watched what happened when he brought a clickable prototype to a discussion, and the ability for people to rally around like, oh, no, move the button, and like you could literally like move the button while you're having this conversation so now you're talking about that was one specialist and now you can do that at scale fast and dirty enough to get on the fly to your point right you're in the middle of some kind of a discussion with people and you're like oh let me just so i think about the ability to um i guess it's not iterate but But to me, the riskiest part of all the making of digital products is always that front UI design.

21:59It's the part that has the highest number of iterations. Oh, yeah, now that you say that, the button doesn't really belong there. So the idea that you could lock that up faster, more aligned in the first iteration of the product, that to me is a straight line to getting the value out of that digital product faster. Yeah. And the guy I was talking about earlier that was doing the lab around proof of concepting, where it kind of originated from, he was on a call with a prospect talking about an idea. And he was in the background, like, building this PSC. And at the end of it, he's like, Oh, kind of like this.

22:35It's like, what? But the one you just mentioned, though, around on the data side, I think the other area that's interesting, too, is like access to not only data, but insights. And I remember back to the world where, you know, I got to put in a ticket for somebody to go create a SQL query, which led me to learn how to write SQL because I hated waiting so long. But now you can just like conversationally talk with data. I think that's another huge unlock. It's like this whole, it's overarching concept of like getting people democratization of all the things across the organization that's potentially possible in this innovation process.

23:16Yeah, the idea that, I mean, I think that's one of the Copas commercials where literally you don't have a list of Power BI reports anymore. You just show up and you're like, show me sales for the Northwest region over the last 12 months with clients who have did it and like renders it. I've yet to see that actually work, right? Our data is probably not organized well enough to get there. again prerequisite right the idea that you're all of a sudden if you want that outcome oh i just built your roadmap for you like if you want that then you're going to have to go do these other prerequisite activities um that's going to be a promised land right like the idea that job changes on the data and reporting team there's no more report builder those guys become people who are making sure the data is organized that it has relationships that it's packed right they're all about curating the data because nobody has to build the visual part anymore, which is unbelievably cool and then simultaneously terrifying.

24:23Like, for example, if you run a professional services company that builds reporting visualizations, now you're like, I don't know what to tell. So like, that's the disruption part that keeps me wringing my hands about, right? The AI piece. Like all the great things we're talking about where, yes, right. I can get a, I can render my own prototype, but democratization speed, like all that stuff, the idea, the number of people who can now contribute to the idea pool. And what's the impact of all of that? How does that change roles? Right. The idea that a developer potentially who said this, I was somewhere and so one of the panelists said this, they said, think about a developer who's not necessarily writing code anymore, but whose job is to write really great use cases and QA checks so that the automation has really strong outcomes.

25:27So that was sort of a mind blow where you're like, the job's not going away, but the roles and responsibilities inside that JD are totally different. And you're like, we're not preparing anybody for that like that those kind of transformation yeah it's kind of that orchestra that doer to orchestrator we talk a lot about i got one more for you um i think well one maybe to the research side of it like performing research which is just a pain in the ass i'm gonna go google stuff and things like that i think that process can be in like you know how big's the market all that kind of just you know stuff you can make easier uh i wonder too like this is more futuristic but like could you have ai play the role of a customer like personified as your customer and give it like real details to where it plays the role of your customer and you're actually feeding it the ideas or the prototype and then having it react versus like you know taking the time to actually put it in front of a customer that's whoa whoa i got like like the idea that you just built yourself like other like so if other people are dating their ai built models i feel like you could for sure if people i thought i read somewhere somebody fed it they're like 12 year old selves journals and then they're talking to themselves as the 12 year old so you're like why couldn't you trick it into believing it's like that's crazy that you just built your own voice of the customer um i'm not sure how you check on hallucinations or accuracy on that one know because you're like before you start you're out like building digital products and you're like the customer said they wanted it um that's a really cool well that's the problem you probably get a feed it all your feed it all your customer service logs too so you get some of those angry customers in there too because i think ai does have this tendency to be very nice a lot of the time which you know completely off topic you're talking about the ai girlfriend boyfriend that's kind of scary to think about because if it's always telling you what you want to hear maybe it's more attractive than human interactions which that's a whole dystopian type of thing that could happen you know i feel like we should all be scared when you start seeing the boston dynamics uh open ai partnership and they're like putting it in like physical bodies and you're like oh and there's there's people doing that i know figure ai it's like people doing that yeah the figure AI is backed by NVIDIA, OpenAI.

28:01That's more like purpose-built stuff, but there's definitely the AI girlfriend, boyfriends, people trying to capitalize on that opportunity as well. But yeah, so that was a fun little exercise. And I think that's one thing to think. I encourage people to do that. Start leveraging AI in these very simple thought experiment type of ways. It's just a helpful way to get started with it. But one thing we've noticed that Patrick's AI, when we're working with a client and they're trying to innovate with AI, a lot of times you'll have this, there's a lot of people in the organization using it. And typically it's a lot more than people think, even if you have these like policies and restrictions in place, they're using it.

28:47They're going to be. And then there's also this pattern of siloing where it's not intentional, but there's just these natural silos within the org. And there's like little bits of innovation happening there. But like Sally in accounting doesn't know what Bob in whatever, you know, engineering's doing. And there's, you know, this kind of ship's passing in the night. I don't know if you have any thoughts on how do you account for that? How do you avoid it? Or is that a good thing that there's like this innovation happening in this siloed way? It's almost like the top-down versus the bottoms-up approach to innovation in some ways.

29:27Yeah. So I think it's AI relevant. I think that's a broader innovation question. And one of the things that early on I learned from other people in the innovation space was one of the jobs that does is to identify people in your organization who are fundamentally wired to those opportunities. Because that's not an everybody situation, right? So running one of those suggestion box or any kind of innovation program where you allow people to self-select, one of the byproducts will be to find Sally and Bob who are doing their own things. And then you want to try to make another program where you intentionally leverage, right, more of a workshop program.

30:18Like at M Holly, we ran it quarterly. We would pick a top down strategic topic and we would grab those innovators from across. Right. And you would you would harness this thing that makes them special and they start to know who they are. Right. And that's really my answer to your question, which is you want to build a vehicle and a network so that they know who they are. and that there's this almost a, it feels like an ERG, right? Like an enterprise resource group. Like instead of people who have dogs, you're like the innovators ERG and you want to find them and then help them make relationships to one another and then leverage that community as an org because the employee is going to have a wickedly unique experience, right?

31:09All of a sudden their day job is an accountant, but they get pulled in to do all this innovation piece, and the organization gets value out of having those folks and retaining them. I like that. If I play that back, the top-down piece is make it clear the big hairy problems, the outcomes you're looking to achieve. The bottoms up is identify those people that are naturally prone to innovation. Then the other part is helping facilitate the connection, not actually dictating what to do, but just making sure that Bob knows who Sally is and that they're both doing some cool stuff. I like that. Yeah.

31:46Turn them loose on the big hairy problem, the top down hairy problem. Right. Yeah. So sticking in the same thread of kind of the process side of it, what's your take? Anything that you've seen that's effective? I've seen like, you know, stage gating type processes, you know, the incubator, the side lab, anything more tactical in the process side? uh i saw you speaking in another podcast um about how you know you may not have a ton of funding for this stuff but how do you kind of you know you can almost do it in some different ways where you're kind of doing something on the side you show the value and then it's like easy to say yes to as well right yeah so we stood up innovation programs that sort of in vista we're in the very early stages at mholland we still run up in both those cases we were coming from zero.

32:37So like, if you have somebody from IBM who wants to talk about their innovation program, they're gonna, they're gonna dust me, right? Like, so we don't have I don't have a lot of what do you do with an established program? What are the stage gating mechanisms? We're talking about how do you get it off the ground? How do you get people engaged? How do you? Yeah, which is important, right? How do you leverage? So I think about it's, it's, it's a lot of heavy lifting, like an iceberg, right? So people are going to show up to this workshop and they're going to have a blast for two hours or 90 minutes.

33:12Before that workshop, a ton of work has to go into thinking about the exercises and the pre-reads and how you're going to put people in the right mindset and like, who'd you pick? And when they're all done, there's all this work about documenting all the stuff, turning in artifacts. And then how do you curate the connections that group of people who existed there because you want them to keep talking to each other when they go back to their desks, right? That's a whole nother set of value. So there's this, it's a lot of backend work, but you have to do that for the program to be credible and for people to believe in it.

33:50And you have to, you have to create visibility, right? When someone's idea finally makes it to production, that's got to make the newsletter, right? In the town hall, when we talk about stats, You should be putting the number of new ideas that we've completed or the number of hours that the innovation team has, right? The innovation group has like saved, right? This idea that you make it present and you celebrate it is how you get that flywheel turning. um so there's there's not uh it's a lot of it's a lot of um digging ditches and like dirty work initially to get like think about how much work it is to plan a really amazing party right and like people show up and then the cleanup afterwards and so like that's a lot about any of these programs it requires people to believe that they're real so that they put their energy into it and it doesn't take a lot for you to ruin that right if you don't send the artifacts out or it's not a really compelling workshop and then people aren't going to volunteer next time and then you sort of this ship has left the armor so um scale it so you can maintain it don't over commit because delivering on those commitments is way more important than having some big, bold, fancy thing.

35:14I like that. Yeah, it's almost back to the home run versus the base hit. If you're trying to stand up an innovation program, start with the base hit within the program itself. And the customer, like AI customer idea, I was trying to find it a second ago, but just for listeners. Your virtual customer? Yeah, that idea. So where that triggered from, and I was looking it up, season two, episode seven, We had Catherine Bonjadana. So she was the past like innovation leader at Salesforce, like really cool conversation. She's got a new startup called Tough Day. So go check that out. But she's doing that.