Rethinking Workflows in the Age of AI

0:00AI is moving fast. No question about that. But I think the biggest challenge for a lot of organizations is they just weren't built for this kind of speed. My guest today says the winners won't just adopt AI. They'll redesign how decisions, learning, and accountability work. Hey, it's John Jantz here. I've got a quick question for you. Are you a consultant, agency owner, or fractional CMO who feels like you're reinventing the wheel with every new client, or worse, giving away strategy for free? Well, you're not alone. And that's why we created the Fractional CMO Plus Certification. It's a three-day live experience where you'll license the duct tape marketing proven strategy first approach.

0:39You'll learn how to turn strategy and strategy engagements into a product. Our next certification is right around the corner. Head on over to dtm.world slash certify. That's dtm.world slash certify. And book a call with a live advisor, or heck, you can just chat with our AI advisor too, to see if this is a fit for you.

1:12Hello and welcome to another episode of the Duct Tape Marketing Podcast. This is John Jantz. My guest today is Stephen Wunker. He's the managing director of New Markets Advisors, where he's advised hundreds of organizations on growth, innovation, and new market strategy. He's also the author of a book we're going to talk about today, AI and the Octopus Organization, Building the Super Intelligent Firm. So, Steve, welcome to the show. Thanks for having me on. All right. So it seems like I started here a long time listeners. Now I always start with titles, words and titles. So I think when you suggested this show, I think the thing that got my attention probably is for a lot of people, it's just the word octopus.

1:58It's a metaphor that's used a lot in business. So what's the simplest way for you to explain an octopus organization? So an octopus has a biology that is weird for us humans. And actually, it's very unusual in the animal kingdom in general. It has nine brains, one in its central head and one for each of its arms, which means each arm can sense and think and act independently. And yet all those brains are interconnected with the nerve ring. So they don't need to route everything through the central brain, but they can sort of coordinate semi-autonomously with complete contextual awareness. And it's a great metaphor for how an AI-infused organization is to operate with distributed intelligence, a lot of local sensing and acting, and yet with complete contextual awareness.

2:53So we developed that model in detail as a guideline for how organizations should adapt to really make the most out of AI. So I'm seeing a lot of organizations, especially we work with a lot of small to mid-sized businesses that really are not compartmentalized necessarily like larger organizations might be. And I get the feeling that they look at AI as like software. It's like, oh, this is just a better version of Word or something like that. So I'm curious if you're encountering that as well or if you see that as a clear sign that they're not thinking about this distributed intelligence. John, I'm seeing it all over the place.

3:33Small organizations, certainly large enterprises. I was with 100 product managers earlier this week in Denver talking to a group there, and they were reporting it even in their software companies. So they were getting a lot of requests for these very incremental improvements. And I mean, all that is nice, but the real unlock comes from rethinking the system of work and the workflows, not through swapping some regular interface with an open text box for a natural language chatbot. No, it comes through taking your 21-step process and making it three steps, albeit maybe three different steps. Yeah.

4:15Or automating the handoff between those steps, right? Yeah. So the idea, at least as I sense it from you, the idea of the eight arms is that we're pushing decisions out in a lot of cases, decentralizing. Where's the risk in that? Where does that break down? Like what role does data play in making that happen? Well, look, you need to have decent data in order to make decent decisions. Yeah. So that's certainly one. People need to know how far they can go. You also probably don't want to take a human entirely out of the process. Let me give you an example of how to do this in a marketing situation.

4:53We worked recently with a marketing department of a major health system, and they wanted to infuse AI in what they did. So one issue they would have is that they would work with the different service lines in a hospital trying to create a marketing message for them. But often the service lines didn't even know themselves what their marketing messages should be. So for the lower priority stuff, it's like the urology department wants to do some brochure about their services. They were able to put into a very simple AI system queries and a sort of interactive process to help urology come to that messaging itself, to draft messaging for it, help them create the output.

5:37And then the human can get involved and say, OK, well, how about we do this or we're not quite aligned with the brand values, so we need to go in this direction. but it took out so much of the work that marketing was spending on this relatively low priority task. And actually it was better for the people in urology as well, that they didn't have to go back and forth and back and forth every period of weeks. They could do it all with a self-service engine. So one of the things that we've also encountered is a lot of, you know, as organizations, especially if there's not like a leadership mandate for AI, A lot of organizations have various people that have said, well, I can figure out ChatGPT.

6:17And so they're using it to kind of do their work better. But there's no real central guardrails. There's no brain. There's no retention even of what they've built. I mean, how do you build a system that starts, of course, from leadership? And I know part of the answer is going to be buy-in from leadership. But how do you build something that has the guardrails that we're going to speak like the brand? We're not going to use the wrong language. So that if you have all these people in various departments or various locations, even using the tools, how do you set the guardrails up? Yeah, the era of having 900 pilots, I hope, is drawing to a close.

6:54They are distracting. They are dangerous. Yeah, maybe they got people comfortable with AI, but it is unsustainable. So, look, you need to have a common data foundation with some data quality. So definitely invest in having decent quality data. Ideally, some sort of data lake or other system to provide that a free flow of information throughout the organization. There needs to be some governance guidelines and governance process on how AI should and should not be used. But then there also needs to be a mechanism to assess these pilots that are still going to occur. But look, we have a three-step system, A, B, C.

7:34A, AI-FI the present. You want to go AI-FI what you're doing now? Great. Let's make sure it's within guidelines, but go do it. B, become great at experimentation. So what's actually your hypothesis? What are you measuring pre and post? What did you learn? How do you kill pilots that aren't working? And then C, which too few organizations are doing, is create the future. So for a handful of things, you can't do it for everything all at once. But in a handful of golden workflows, as we call them, what can you do to really rethink what you're doing and make those sort of a lighthouse for the rest of the organization.

8:10Do that in a half dozen situations and then move on to the next half dozen and the next half dozen. So I want to come back to golden workflows because I want you to explain that. But I will say another thing that we encounter a lot is that people are just applying AI to maybe a process that's non-existent or broken, as opposed to, you know, I always tell people start with workflows first and then use AI, you know, to automate them. Don't tell AI, create me a workflow for this. How do you work with organizations where they really need to, I think I said it at the beginning, they really need to rethink how they even do workflows, how they even serve their client.

8:50So you need to understand what your starting point is and where are all the disconnects. But then don't just think about what might we automate. You want to think about what humans shouldn't be doing because AI could do it better. What won't they do because it's just too time consuming, but it would be valuable. And what can't they do because it's just overwhelming in the amount of detail. Wait, you forgot whether they hate to do. That's one of my favorites. Yes, maybe that should be and shouldn't do as well. But so anyway, we have the can't, shouldn't, won't. And when you do that, then you can really rethink, OK, with AI, what makes, What does this make possible?

9:32So we did this recently, another marketing department in campaign planning. And they would spend about half a year planning campaigns for people in the business. Because there would be infinite going back and forth. And then they have to go to the agency. And all these disconnects and nobody quite knows what they want. And you go through iteration after iteration. We were able to use those principles and come up with a system that was about half the time. Could actually be a lot less. but there's still going to be some human indecision that you have to account for. But by just reducing the number of cycling, because you can real-time prototype stuff, get real decisions made right away, make sure everybody has context of what happened in the prior meeting.

10:17So you eliminate a lot of those disconnects. You could do it in half the time. Now, you can't re-engineer every process all at once, but you can do it in some of those golden workflows like that one. So again, you're going back to the golden workflow, You're saying that's basically, you know, a lot of times when people bought into this whole idea of systems, they would try to systemize everything and just get overwhelmed because there were 740 systems and 723 of them didn't matter. So as a golden workflow in your vernacular, what's a real impact one that we absolutely have to get right? Right.

10:54So I looked, I mean, campaign planning was a great example because there is real money being spent and a lot of time. There would be others, same marketing department, with press releases or even internal announcements about what was going on. People would go back and forth and back and forth. And I mean, it was a huge sink of time. And you had about 40 people just doing internal communications. And 28 of them were attorneys, though, right? Well, I mean, so you do need levels of security, right? You cannot just think we're going to replace humans with AI. It doesn't work that way. But you do want those people focused on the highest use of their skills and not helping people make decisions that AI would probably help them make even better than a human consultation.

11:41Yeah, yeah. So, I mean, we're not seeing a tremendous amount of displacement of humans with AI. There's some, in particular in things like call senders or whatever. Right, right. But more, it's just ensuring that people can focus on the best use of their skills. That's where the real productivity gains are. I suspect I wouldn't have studied to be a paralegal right now, though. No, that, well, yeah, that one is already played out, right? So, and that's the example, right? Auditors, there are some others that are really threatened, but it's a minority of what most white-collar jobs are. Well, we're finding, especially in knowledge work, that what it's doing is not displacing people, but it is asking them to do their job differently, you know, to maybe manage AI as opposed to do the stuff that AI is now capable of doing.

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13:12Our next certification is coming up soon. You can learn more at dtm.world slash certified. dtm.world slash certified. You started talking about the eight brains. I think I recall, doesn't an octopus have three hearts also? It does indeed. So how does that metaphor come into play for you? So an octopus has different hearts for different purposes. And similarly, a company needs to have different operating modes as it enters this very dynamic period of AI-led disruption, also many other disruptions too. So we talk about the analytical heart, which most companies are already pretty good at. The agile heart, which the bigger the company is, the worse it typically is at agility normally.

14:02And then the aligned heart of how do you make sure that people understand the common purpose and where people are going, particularly when there's going to be just a lot of turmoil in the workplace. And there is with the entry of AI. Being attuned to those emotional cadences in the organization is going to be really important. I mean, would that, could you break that down almost department-wise? I mean, or not even department, but function-wise? Like that, what I just heard you describing sounded like culture. It is. Yes. And culture is incredibly important. We also have another chapter on emotion and the cultural side of change.

14:41Look, we think about culture, a brick wall. The culture is the mortar in a brick wall. It is almost invisible, but it gives the whole thing shape and coherence. But you start a brick wall with the bricks, which are the hard levers of management control. the way you select people and incent them and measure them, the way you allocate resources around an organization. If you don't have that right, you could put up all the posters you want on the walls. It's not going to change a thing. So get the bricks right and then definitely think about the culture. But don't just think about it as some isolated thing.

15:19It's not. I like that because, unfortunately, you do see some examples of performative culture that then doesn't really deliver when you shine a light on what the company is actually doing. I think also in the subtitle you have the term super intelligent firm. What's a super intelligent firm mean in terms of human terms, maybe? so there's a fallacy out there that ai is going to approach general intelligence so being just like a human or super intelligent just like a human but even more so right and that is based on providing a very human model to a machine we evolved to who we are because we needed to escape the saber-tooth tiger so we have to be good at a lot of stuff yeah but machines don't they need to be good at just a handful of things.

16:06So the super intelligent firm isn't necessarily super intelligent AI. Where firms get their intelligence, where organizations get their intelligence is through collaboration of people. It's not just through like group force processing capability, right? If we want to say who has the most neurons, well, an anthill wins that contest, right? So humans can do something which octopuses can't, which is collaborate. And that's how we build civilizations and cities. AI has the potential to supercharge that collaboration by making sure the right information goes to the right people at the right time. And it's that use of AI that actually enhances our humanness.

16:47That is the most high potential use of AI because that makes us then super intelligent as firms, as organizations. So one of the things I tell people, because I think a lot of, especially in marketing, a lot of people's first reaction was, oh, look how much faster I can do stuff. And while there is a bit of truth to that, I think it's not very interesting to just produce more content. What I think is really interesting is I can iterate 200 versions of something in about the same time it took me to do one. And I think that's where the learning, because we all know that we're just guessing sometimes in marketing.

17:23And by being able to test faster and experiment faster, that's where we're going to not just produce more. We're going to produce better and we're going to produce more personalized. I wrote a Forbes profile about a year ago on a company called Movable Inc. That provides email software to companies like L.L. Bean and Victoria's Secret. L.L. Bean can run a million different variants of an email. Literally a million different variants. And of course, it's A-B testing and it's determining what's best. But it's also using that to be just super personalized in ways that we could never do as human beings.

17:59Yeah. But, you know, this is all possible now. So, yes, we have to embrace that. So what would you how does an octopus move look like for like a 20 person firm as opposed to, say, a 200 person? You know, the principles are actually often the same. The maladies may be different, right? The 200 person, 2000 person, there's a lot of discordination and siloing. Hopefully in 20 person, it's not. But you still need to think about for your prioritized workflows, the things you really want to focus on, how do those principles of moving action closer to the suction cups on the tent, right to the coalface, how does that look for you?

18:45What does AI enable in terms of what humans shouldn't be doing or can't be doing or just won't be doing because it's a poor use of their time? How would you really fundamentally rethink things? We talk a little bit about when electricity came. Initially, operators of factories swapped out their steam-powered machines for electric machines. And it's sort of equivalent to what we're doing now. And that was nice, but it actually took 35 years for the big unlock to come, which was the assembly line. The assembly line could not happen without electrification, but it was that unleashed the productivity because it was a fundamental rethinking of how work was done.

19:23So we don't have 35 years this time, but we need that equivalent of thinking about what's the equivalent of an assembly line for our companies. So if a CEO company founder is listening and they want to start adopting this, obviously they need to get a copy of the book first. Do you also work with, do you come in and work with organizations to install this? Yeah. So that's my day job. Yeah. OK. So so somebody was listening then and they said, OK, what's my 30 day plan? I mean, do you typically I'm sure it starts with an assessment, but do you also typically are there things that you often test almost right off the bat?

19:59Are there things that you tell them to stop doing right off the bat? And again, every instance is different, but are there some common things that you find? so it has to relate to your strategic priorities yeah right so ai can be better faster and cheaper all at once but to some degree there is a trade-off so what are you actually hoping to achieve and how does that fit in with your objectives what is impeding that today and then let's overlay that on where ai can be particularly useful so we're not just coming in with a hammer looking for nails but we're trying to understand what are the different priorities in the organization.

20:41And then based upon a handful of things that we can really focus on, let's figure out how to redo that. Sometimes it starts all the way with the value proposition, but it can also just be very internal process oriented as well. Awesome. Well, again, I appreciate you taking a few moments to stop by the Duct Tape Marketing Podcast. Is there someplace you would invite people to connect with you, find out more about your work, and obviously find out more about AI and the Octopus organization? Sure. You can find the book on Amazon. The website for the book is aiandtheoctopus.com. And that is actually a subdomain of our company, New Markets Advisors.

21:17Also, Clint, connect with me on LinkedIn. Feel free to write me. I do answer my emails. So send me a DM and I'll get back to you. Awesome. Well, again, I appreciate you stopping by. And hopefully we'll run into you one of these days out there on the road, Steve. My pleasure, Tom.

21:44We'll see you next time.