Dom Heinrich is a leader in design, AI, and sustainability, with two decades of experience leading global teams. He has excelled in delivering AI-powered products and services, emphasizing sustainability. Notably, Dom invented products aiding mobility for Parkinson's patients and contributed to GPT-1 development with Microsoft and Coca-Cola, showcasing his impact in AI. As a PRATT University faculty member, he lectures on AI in Digital Design and Design Business, blending deep problem-solving with elegant solutions. His work with industry giants underscores a commitment to technological innovation and a sustainable, inclusive future.
Dom on LinkedIn - https://bit.ly/48sOcMO
Dom Heinrich, bridging the worlds of sustainability, ethics, and AI in product development, ignites a crucial conversation on the resilience of human systems and our interaction with technology. As a thought leader at the Creative AI Academy and TLGG Consulting, Dom demystifies the complexities of sustainable AI applications in product management and addresses the challenges of creating resilient, ethical AI systems.
This episode navigates through the nuanced landscape of AI's role in promoting sustainable practices, enhancing the resilience of human systems, and facilitating ethical decision-making. It underscores AI's potential to revolutionise our approach to sustainability in product development, encouraging a symbiotic relationship between technology, ethics, and human well-being.
Key Highlights:
🔍 7:31 - Germany's F1 Passion & The UK's Carbon Neutrality
🔍 9:06 - Optimisation For Sustainable Product Success
🔍 15:02 - Revolutionising Refills: How AI Is Transforming Sustainability Practices
🔍 25:30 - Leveraging Technology For Sustainable Behavioural Change
Elevate your AI Game even Higher by watching Ben and Dom's Exclusive Live Stream - Decoding AI Beyond The AI Productivity Myth🌟
https://www.linkedin.com/events/71663982
Host Bio
Ben is a seasoned expert in product agility coaching, unleashing the potential of people and products. With over a decade of experience, his focus now is product-led growth & agility in organisations of all sizes.
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Ben Maynard
Product Agility Podcast
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Ben Maynard: You know, what I worry about is our
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sustainability as humans.
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I don't think that a lot of us myself included, 100% of the
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time are actually as resilient as we can be to objective truth
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and failure, and I think that a lot of what we're saying here
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helps us fail quicker.
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Brilliant helps us increase the probability of getting it right
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first time, but helps us get things wrong quicker.
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For me, when I think of mental health and I think of resiliency
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, I think of it as being able to , like a tree, being able to
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bend bend with the winds and go with it, and sometimes we
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actually we get quite brittle and the wind blows and we fall
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down and we snap.
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So I'm wondering, Dominic, when you think about sustainability
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and how we can use AI to help our products become more
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sustainable?
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Is there a challenge here that actually, as humans, we're not
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that sustainable and we're just going to?
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Some of us are going to find this whole journey hard.
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Welcome to the Product Agility podcast, the missing link
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between agile and product.
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The purpose of this podcast is to share practical tips,
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strategies and stories from world class thought leaders and
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practitioners why, I hear you ask.
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Well, I want to increase your knowledge and your motivation to
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experiment so that together we can create ever more successful
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products.
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My name is Ben Maynard and I'm your host.
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What has driven me for the last decade to bridge the gap
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between agility and product is a deep rooted belief that people
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and products evolving together can achieve mutual excellence.
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Here with Dom Heinrich again for the Product Agility podcast.
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As you can probably tell by my voice and the fact that when you
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push play, it said the product utility podcast.
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Now Dom is back with us today because we're going to be
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looking at sustainability and product and for those of you
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that perhaps haven't listened to Dom's previous episode, please
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do go back and have a listen, because we explored some really
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fascinating and then much deeper wave than I have done
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previously the impacts and uses of AI in the around innovation
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and product development.
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So it's some really awesome stuff and I do go back and give
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that a listen to or check out some of the moments that we got
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on LinkedIn and what was really clear from what Dom told us
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before was that he is an expert when it comes to artificial
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intelligence.
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If you look on LinkedIn, it will say he's a global AI leader
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.
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It would also say he's an innovation executive at TLGG
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Consulting, the co-founder of the Creative AI Academy as well
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as a lecturer in AI at Pratt University, and it's an absolute
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joy to have him back for this conversation on sustainability,
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which is an increasingly important topic and one which
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we're going to have a number of conversations on.
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So, Dom, welcome back.
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Dom Heinrich : Thank you for having me, Ben, and thank you
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for having me on a topic where we bring the both worlds
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together the artificial intelligence and how we can
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build more sustainable products.
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I'm super excited about this.
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Ben Maynard: I am too.
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I am too, so this is, but let's get straight into it.
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So the question I was going to ask was the question that we
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agreed up from, which is how can AI help us make truly
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sustainable products?
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But, just as a quick caveat for this, when we say AI, are we
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talking about always going to chat GPT or are we talking about
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a more, a slightly different incarnation of AI when we're
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talking about how it can help us make truly sustainable products
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?
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Dom Heinrich : I think we talk about many tools and
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applications.
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In the last episode we spoke a lot about JetGPT and how can it
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help us personally to make things better, and the reason a
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JetGPT or a BART is our first entry point is because it became
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so easy to talk to a model that has all this information about
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the world and allows us to have an interaction we would only
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have with experts, which we most often don't have access to.
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So I think as an entry point, that's great.
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But, to your point, there's many deep learning and machine
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learning algorithms just to narrow this a little bit down,
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because it's not all AI that can actually help us make a product
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more sustainable, move more sustainably around the world.
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I have a couple of examples I can share with you on this, but
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you're right, maybe the first starting point for us is product
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people, is AI and the JetGPT, but in the second glance, how
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can we actually leverage it in the journey itself, in the
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product journey itself?
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Ben Maynard: And say how can we leverage it to be more
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sustainable, when we're talking about sustainable here and
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perhaps it's worthwhile also to add some context around that
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because are we talking about sustainable that we can keep on
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adding to the product?
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Are we talking about sustainable because we are able
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to keep taking stuff out of the product?
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Are we talking about sustainable decision making?
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Is it about us maintaining our energy to keep on making
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important decisions and make sustainably ever increasingly
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more relevant decisions?
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Or is it, if I think back to the agile manifesto, the classic
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principle, which is we want our teams to maintain a sustainable
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pace indefinitely?
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What kind of sustainability are we going to be talking about
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here, dom?
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Dom Heinrich : I would say we talk about how it can help us to
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build more sustainable products .
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I think that's because we often have the assumption that what we
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come up with is actually truly sustainable, and I think you and
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I had a little bit of a sidebar conversation earlier on the
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topic that just because I make something sustainable at the
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first glance doesn't mean that it is truly sustainable, because
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maybe the resource is still coming from a place that makes
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it not sustainable.
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And if it doesn't come from there, when we talk about
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recycling or upcycling, then what happens then?
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Well, it's the next step to this.
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So I think, from a product development perspective, it is a
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really interesting topic to help us understand them and then
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send the process, but also understanding what is really
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truly sustainable, and I think that's broader than carbon
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emissions, it's broader than waterways, and so about the
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ethics around it and human rights around it and how to use
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data in that space, and the machines where it's running, on
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the airplanes, where we're transporting it, the waste we
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are generating.
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So I think it's multifaceted and it's super complicated and I
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think there's ways where I can really step in and help us.
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Ben Maynard: So what we're not talking about here is
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sustainability, with no caveats.
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We're talking about bear with the great products which are
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relevant in the market, first and foremost, that are
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sustainable, that we can keep growing them, but in an ethical
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way, in a way which isn't having how would you put an overly
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detrimental impact on the climate, or having any impact on
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the climate.
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We're laying on a number of really relevant and important
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things here, but this isn't just sustainability, as in I can
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sustain a note if I sing for this many minutes what we're
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talking about here is actually this is sustainability for good
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purpose, to have a positive impact.
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Dom Heinrich : I agree, it's only about this, and I remember
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we had this conversation.
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Ben, even if I'm from Germany, I'm not a huge soccer fan, but
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I'm a very big formal one fan.
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There's a lot of factories in the UK and the big goal is to be
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carbon neutral by 2030.
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And what does this actually mean?
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It's like just because I make synthetic oil now or gas.
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Where is it coming from, how is it being produced and what are
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the carbon emissions by producing the synthetic oil
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that's actually happening?
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So I think to your point, there is no such thing in total
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sustainability.
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And I have a fun fact for you, once you're ready, about the
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biomimicry professor from Pratt and how he would take this.
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I spoke with him about the topic.
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Oh yes, you will not like it.
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Ben Maynard: No, I know you told me this before and I did like
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it, but I'd want to just take a quick detour before we hit that
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junction in the road because that maybe sparks some other
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thoughts in people's minds and get back to what you were saying
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about, ultimately, the law of unintended consequences.
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You know there are some really fun videos to watch on YouTube
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about the law of unintended consequences which cover loads
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of the kind of mythical tales of the Vakoba effect or whatever
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it might be.
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We do one thing with the best of intentions but as a
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unintended consequence a very detrimental effect on the
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broader system.
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The classic one was around I think it was off the coast of
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California.
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They dumped loads of tires thinking it would make an
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artificial reef and then they just leaked out toxins for the
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last 50 years.
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You know it's going to cost infinitely more to repair that
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than they were going to say if I dump him in there.
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We see it in products.
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I think back to my conversations with Magali
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Polissier.
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We will put a feature live for a particular customer which
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isn't really in line with what we're trying to do with our
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products and then that feature is a bit of a pain in the arse.
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It causes those support tickets .
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It's quite computationally intensive.
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The customer isn't really that happy ends up having detrimental
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effects with other customers because we can't give them the
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attention that we want and we can't extend our products in
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certain ways because we put ourselves in the corner of this
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particular bespoke feature.
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We end up not being sustainable because we do what we think is
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absolutely best in this one particular context, but it isn't
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right for the product system or even in organisations.
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One department, the marketing department, will make a decision
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not picking on the marketeers here but they'll make a decision
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to do things in a certain way.
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They don't bring people on the journey.
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There's no shared understanding .
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It ends up being what we're a very local optimisation rather
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than a broader, systemic optimisation.
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And that's what we're talking about here is how do we make
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these broader, system-wide optimisations that are
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sustainable?
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Dom Heinrich : I think you brought up the most important
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point, which I think, when we go back to how AI and
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sustainability actually fit in together, is we don't know what
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we don't know in many ways because we have expertise and we
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have a knowledge and we're building, I would argue, in the
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best intent even the marketeers building in the best intent
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their solutions.
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I love actually dumping something on the marketing
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people because I feel like I'm allowed to do that 20 years in
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that industry somehow, but I have good intentions about it.
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But I think sometimes we act with the best intent but not the
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best knowledge.
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I think that's exactly where certain AI tools can actually
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step in, because suddenly I have a biomimicry scientist on my
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fingertips.
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Suddenly, I have access to environmental data or chemistry
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reactions.
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I hadn't had access to it.
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The question comes and Ben, I remember we had the conversation
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before how do I act as a human being about this?
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Is my ego in my way?
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When I put my ego aside and say , oh okay, there is actually,
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there might be something I don't see.
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There might be something I don't see where I need to ask
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the machine to help me with.
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Ben Maynard: It's expert in your pocket, as you said.
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Dom Heinrich : That's the yeah, I feel like that's the beauty of
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it.
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We I got a brief a few months back and can't really disclose
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what it was about, but it was sourcing ingredients differently
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for a drink.
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So it becomes.
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It has the same taste, but it comes from local farmers, from
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local ingredients.
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And how would I know that?
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No capability of knowing that.
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I can use my educated guess.
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I can do some research, but imagine I I basically modeled an
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environmental specialist like, modeled it in an, in a GPT model
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, in an AI model, and it helped me run analysis on things I
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found right and ingredients I found and told me how they might
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match together.
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I don't know if you heard of this, but mushrooms not this,
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not the psychedelic ones mushrooms actually tasting like
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chocolate, so you could actually use them as a replacement for
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chocolate.
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So we worked on this with companies like Nestle right, and
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so it's really interesting.
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I would not know that, but a machine can if I prompted the
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right direction, if I use my creativity on it.
00:13:02
It actually helps me explain me how it could work and how it
00:13:06
could actually have that taste.
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So that is an interesting part where it can really help us in
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product development, because it can simulate things we are not
00:13:15
able with.
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But if we are creative enough and think out of the box in that
00:13:19
moment, it can actually serve us very well.
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Ben Maynard: So is this was a product manager or someone
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coaching a product person and I'm thinking, oh, it still
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sounds wonderful, but are we talking about coming to an AI
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tool with a particular problem or intent, or can we be thinking
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about this along the lines of something speculative?
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I am not really sure what I want to find out, but I'm really
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curious if our product could be more sustainable from a I mean,
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from what perspective?
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If I'm thinking of your average product manager who's got a
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software product or part of a software product that they're
00:14:02
looking after, what kind of thing could they be going to
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chat, gpt or all barred, whatever it might be, and kind
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of paying for that, both AI model, yeah.
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Yeah, I mean, would they just be going to an AI model and saying
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help me out?
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What are some things I should be considering?
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Dom Heinrich : I think if you, there's a couple of ways to
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answer the question, but I think if you're a leader in the space
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and if you're an organization that has certain processes you
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run, then I would recommend you to build a model that actually
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monitors all the ingredients you buy, all the products you build
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, so that you get a more real-time challenge on the
00:14:41
products.
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So now I'm coming to the question you had, which is what
00:14:47
is the product person's job in that case?
00:14:49
And I think the interesting part is thinking outside of the
00:14:55
role, thinking outside of the normal challenge, the normal.
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I give you an example, which is maybe not 100% fitting but is
00:15:03
easy to grasp for everybody who's listening to us, which is
00:15:08
imagine you buy a beautiful soap , very expensive.
00:15:13
There's certain brands out there in black, good-looking
00:15:17
bottles, but you want to refill them, right yeah, and you refill
00:15:23
them with the cheaper market bottle and the refill process is
00:15:27
super messy.
00:15:28
We both know that it's like.
00:15:29
If you have ever done that, I hope you never had your kids
00:15:32
doing it, because it's a nightmare.
00:15:33
It's getting actually more messy.
00:15:34
But imagine you do this refill process and if you use an AI for
00:15:39
that to actually help you to optimize that process which is
00:15:44
meant to be more sustainable, then you will learn quickly.
00:15:48
It comes up with all sorts of ideas which are really flat and
00:15:52
no human being would use them because too complicated.
00:15:55
Right, and now go in and think about how would this work in
00:16:01
space?
00:16:02
How would I refill something in space because it's not coming
00:16:06
out of my bottle?
00:16:07
And the answer would be vacuum.
00:16:09
Instigating that question and thinking that way is what I
00:16:15
would coach a product person to say think outside your spectrums
00:16:21
, think outside your comfort zone and go, make this big leap
00:16:26
right and make this leap into.
00:16:27
How would this work on another planet, how would this work in a
00:16:31
different environment?
00:16:32
How would this work and we spoke about this then in the
00:16:35
last episode how would this work for people with disabilities?
00:16:38
And that's the moment where it actually starts opening a
00:16:43
question that's provocative, which you might not have the
00:16:46
answer, but they ask the answer and that's the interesting part.
00:16:50
Ben Maynard: Yeah, I wonder it makes me think of a conversation
00:16:53
with Magali Polissier and our last conversation as well, I
00:16:58
guess for many a very provocative question, whether
00:17:00
you're a product person, a designer, coach, anyone really
00:17:03
is.
00:17:03
Just to try and imagine if there wasn't a user interface
00:17:06
for my product and it was a prompt, how would that change
00:17:10
things?
00:17:11
Dom Heinrich : We will be just going a different way of you,
00:17:13
axe.
00:17:13
I mean, the user interface is changing massively.
00:17:17
Right, it's like we're still talking about computers and in
00:17:22
the old days you would have just had a conversation and maybe
00:17:24
scribbled something on the board .
00:17:26
And I think one of the things we touched at the topic
00:17:30
sustainability in the AI design certificate course at Pratt, and
00:17:35
what we do is we remove basically the computer and say
00:17:39
let's focus on a whiteboard most sustainable not that the
00:17:44
pencils are more sustainable, but it is.
00:17:45
You don't waste at least trees.
00:17:47
And so we start drawing things and start sketching things out
00:17:51
and in starting on a different point and have a conversation
00:17:55
with the AI.
00:17:56
So for us it's a way of teaching them how to integrate
00:18:01
an AI into the conversation, which is super interesting
00:18:04
because it can prompt you to think about certain things and
00:18:07
sketch about certain things in a way that you would never do if
00:18:12
you were just a couple of humans in the room.
00:18:13
And that's interesting, it's powerful.
00:18:16
Ben Maynard: Can you get something that can actually see
00:18:19
the whiteboard or see what's being written down?
00:18:21
That's processing that visual information?
00:18:24
Dom Heinrich : Just take a picture and upload it and then
00:18:28
we can start sketching other tools and they can render it out
00:18:31
of this.
00:18:32
They can even code the website for you.
00:18:35
Ben Maynard: So give us an example.
00:18:36
You've got this AI design course at Pratt Fantastic right.
00:18:38
Dom Heinrich : Yeah.
00:18:40
Ben Maynard: Is there a concrete example of something you could
00:18:42
share?
00:18:42
Because this sounds really fascinating and I suppose, if
00:18:45
we're talking about sustainability, I'm trying to
00:18:48
think of a way that this helps from a sustainability
00:18:52
perspective.
00:18:53
But I'm just really interested what's a concrete example of
00:18:55
something that's been drawn and then you've been prompted and
00:18:57
it's kind of got better?
00:18:59
Dom Heinrich : Yeah, I love that you go in that direction.
00:19:02
And I think to be clear maybe my example is not going into
00:19:06
sustainability for a second, but just imagine you make a sketch
00:19:10
and saying this is my joke website, right, and OpenAR
00:19:15
actually demoed that my joke website.
00:19:18
Here's a very funny joke.
00:19:19
Here's a button.
00:19:20
Press it to reveal the punchline.
00:19:23
Take a picture of it, you upload it and it writes you the
00:19:27
code for it and it writes you the content for it.
00:19:31
The interesting part is the joke was very flat, so I have
00:19:35
the suspicion that all the jokes on chatGPT are written by a
00:19:38
German, because it was not funny .
00:19:40
But I'm allowed to say this, ben.
00:19:43
But the interesting part is you don't need to have any coding
00:19:48
scope.
00:19:49
And now imagine, because we talked about this in the
00:19:52
previous podcast, I make two connections to this.
00:19:55
I'm a product person and the developer tells me it's
00:19:58
impossible.
00:19:59
I can take it and can validate it.
00:20:01
Great.
00:20:02
Now take the same thing and say we want to do this and source
00:20:09
this product in this way and fly it back to another country.
00:20:14
Is this more sustainable than just leaving the waste rotting
00:20:17
where it is?
00:20:17
Let's say we use cocoa leaves.
00:20:21
The cocoa bean has a lot of natural benefits.
00:20:24
What we take out of them basically is used for making
00:20:28
chocolate.
00:20:29
The rest is being thrown away and is just rotting where it is.
00:20:33
The question comes can we reuse the material?
00:20:37
Can we use the waste for something else?
00:20:38
Nestlé used it for a water for longevity because of the
00:20:43
benefits, but is that still sustainable?
00:20:46
Is the transportation, have more weight in the airplane, et
00:20:51
cetera, et cetera?
00:20:52
Is that actually helping?
00:20:53
Is the rotting actually the better process for our planet?
00:20:57
And so these questions you would maybe not even ask
00:21:00
yourself, but the systems would help you to actually identify
00:21:05
them and answer them.
00:21:06
And I think that's where the balance happens between
00:21:10
automation what a lot of companies talk about, which I
00:21:13
think shouldn't be their focus, and augmentations Like how is
00:21:17
this balance happening?
00:21:18
And I think that's the potential for sustainability to
00:21:21
actually not just come up with an idea that this sounds great
00:21:24
and we can save from carbon emissions.
00:21:27
No, maybe this is really.
00:21:29
If you think this through, you come maybe on five other ideas
00:21:32
how you can make this even more sustainable for the planet and
00:21:36
even better and source it somewhere else.
00:21:38
Ben Maynard: I think of sustainability.
00:21:39
Where my mind is going is, first of all, to a short recap,
00:21:44
because what we're saying here is we have an expert in our
00:21:45
pocket, which is everyone who listens to this podcast and is
00:21:48
bored of hearing me say that.
00:21:49
This expert in our pocket is well, the AI tool is available
00:21:55
to us, only limited by our own stupidity.
00:21:57
We just don't know what questions to ask it and, as we
00:22:00
learn, what better questions to ask it.
00:22:02
Who knows?
00:22:03
Or we can begin to move and, like you were saying that
00:22:05
sometimes, as product people, we need to think very out of the
00:22:09
box.
00:22:09
We need to ask ourselves very challenging questions, such as
00:22:13
what if there wasn't a user interface?
00:22:14
What if we were doing this in a different country, on a
00:22:17
different planet?
00:22:18
What if this was picked up and used by someone with a
00:22:21
disability?
00:22:22
What if this was picked up and used by somebody who wasn't our
00:22:25
target demographic?
00:22:26
What would they think about it?
00:22:27
We can begin to explore all of these what ifs and perhaps
00:22:31
that's a good coaching question structure that we can begin to
00:22:34
use with the people that we work with.
00:22:36
They say well, what if?
00:22:37
And we just do the.
00:22:39
There was a program called this Is Us and they played this game
00:22:42
called Worst Case Scenario and they would all in order to make
00:22:45
themselves feel better about something terrible that was
00:22:47
happening.
00:22:47
They'd always then challenge each other to come up with a
00:22:50
really awful worst case scenario , just to make themselves feel
00:22:52
better about how crap things were right now.
00:22:54
But we can play games like this , we can do and this is
00:22:57
something that I picked up from not a great place, but the idea
00:23:02
that you reflect stuff back.
00:23:03
So this is true right now.
00:23:04
Okay, so what if that were false?
00:23:06
How would that change our product?
00:23:07
What ideas would this generate?
00:23:09
And there's a huge coaching opportunity for us to coach
00:23:11
ourselves, for us to coach other people, maybe for AI to begin
00:23:15
to coach in some way to help challenge us to come up with
00:23:17
different and better product ideas.
00:23:18
But it's all fantastic, and then we're talking about that
00:23:22
slight segue, about the drawings , sketching something up,
00:23:25
getting some prompts, making it better, really working on that
00:23:27
design element oh, brilliant.
00:23:29
You know, what I worry about is our sustainability as humans.
00:23:32
I don't think that a lot of us myself included, 100% of the
00:23:37
time are actually as resilient as we can be to objective truth
00:23:44
and failure, and I think that a lot of what we're saying here
00:23:46
helps us fail quicker.
00:23:47
Brilliant helps us increase the probability of getting it right
00:23:50
first time, but helps us get things wrong quicker.
00:23:53
For me, when I think of mental health and I think of resiliency
00:23:56
, I think of it as being able to like a tree, being able to bend
00:23:59
bend with the winds and go with it, and sometimes we actually
00:24:02
we get quite brittle and the wind blows and we fall down and
00:24:04
we snap.
00:24:05
So I'm wondering, dom, and when you think about sustainability
00:24:09
and how we can use AI to help our products become more
00:24:11
sustainable, is there a challenge here of?
00:24:13
Actually, as humans, we're not that sustainable and we're just
00:24:16
gonna some of us are gonna find this whole journey hard.
00:24:21
Dom Heinrich : We are habit creatures and changing our habit
00:24:24
tough question.
00:24:26
Let me give you an example.
00:24:28
One of the companies I worked for a few years back decided to
00:24:32
remove all trash bins from the desks of everybody overnight I
00:24:38
was certainly an email going around about the topic and they
00:24:41
decided to centralize it, and centralize it with recycling
00:24:46
bins.
00:24:46
Do you know what happened?
00:24:48
Can you imagine?
00:24:49
Tell us, these recycling bins were trashed with everything the
00:24:56
desks looked like.
00:24:58
How probably we left our rooms as kids and got really in
00:25:02
trouble.
00:25:03
To be honest, it was disgusting and while the idea was great,
00:25:10
the communication about it was okay, but you could have
00:25:13
probably done some more.
00:25:16
Where the problem really hit the wall, or the solution hit the
00:25:19
wall, was that the idea was, in theory, great, but it lacked the
00:25:24
human laziness and behavior that you can't just suddenly
00:25:29
change.
00:25:29
When it comes to sustainability , and I think when it comes to
00:25:35
how we can leverage technology in that space is let's start
00:25:40
with what I try to solve and then let's start with
00:25:42
understanding what the human behaviors are and how we can
00:25:45
focus in their behaviors, because I don't believe, and I
00:25:49
have a great friend I love, I would love to mention any who is
00:25:54
a data guru in London actually, and she really researches
00:25:59
around behavioral change methods and I think she's really
00:26:04
successful in that case.
00:26:05
But it is a hard topic and it's not easy to solve and create
00:26:10
programs that truly change the human behavior.
00:26:13
And now we're back to your question.
00:26:15
The only problem on this planet to be more sustainable is our
00:26:21
desire of comfort and desire of laziness, our desire of
00:26:25
unwillingness, unconsciously, to change right, because we are
00:26:30
happy animals and we are creatures in the way that I like
00:26:34
to do it this way because it's convenient.
00:26:36
The question for product people is how do I identify that
00:26:40
problem and how do I understand that I can't change the human
00:26:44
without a big effort?
00:26:45
Maybe there's a solution I can find that can actually fit into
00:26:49
this behavior, and that's that is my perspective.
00:26:54
Where technology really comes in and I remember we spoke about
00:26:57
that basically the single diamond instead of the double
00:27:00
diamonds are approaching things by modeling and simulating.
00:27:03
So train a model with what I'm trying to accomplish and then
00:27:06
simulate millions of solutions, computational design basically
00:27:10
to come to an output that is really impactful.
00:27:13
I think that's where I can really help and step in.
00:27:17
Ben Maynard: What about organizational change?
00:27:18
Because I think that there is a huge industry out there around
00:27:25
helping organizations become more sustainable, helping their
00:27:28
products become more sustainable , and people look at their
00:27:30
organizational structure and the policies and processes and the
00:27:33
rules and they look at it and I mean, I don't know how many
00:27:36
times I've heard this in my career.
00:27:38
People come to me and say the way we're working isn't
00:27:41
sustainable, we need to do something different.
00:27:45
And so they say, oh, we need to embark on some level of
00:27:47
organizational change, and organizational change is always
00:27:51
fraught with difficulties.
00:27:52
I think in the agile world, there's a huge litany of failed.
00:27:56
We use inverted commons for this transformation that never
00:28:00
bore any real relevant fruit, and I think even before that,
00:28:05
there were huge organizational change efforts which never bore
00:28:07
any fruit.
00:28:08
I think that when it comes to large organizational change, I
00:28:12
don't think it should be a thing for first and foremost, just
00:28:15
for the record.
00:28:16
I think there are other ways of going about doing it.
00:28:18
So, if we're talking about sustainable change to help make
00:28:21
sustainable products, and how can AI help us with that change
00:28:26
element, which, of course, then does relate back to the
00:28:29
behaviors you were talking about ?
00:28:32
Dom Heinrich : Exactly.
00:28:32
Thank you, ben.
00:28:34
I know you're really keen on coaching cultures and coaching.
00:28:38
Do you know the Enneagram, the personality insights system?
00:28:43
If you do not know, that it's insights about your.
00:28:49
So your answer usually questions and it gives you.
00:28:53
It has nine archetypes, that's why it's called Enneagram and it
00:28:58
has nine archetypes and you fit in one of these archetypes and
00:29:02
these archetypes have certain intrinsic motivations, certain
00:29:07
behaviors, certain activation points, certain trainer points.
00:29:12
It's similar to a disc model but it's going deeper,
00:29:15
psychologically into the system.
00:29:19
And one of the people I work with a lot is Stella Sireno.
00:29:23
She's an executive coach in the New York City very well known,
00:29:29
and we approach companies from that angle.
00:29:32
So we go in and we analyze the Enneagram type of the
00:29:37
organization across the employees Meaning, if I have as
00:29:43
an example a company that's dominant by a four, which is the
00:29:48
intense, creative, I'm one of these and we are always striving
00:29:54
for uniqueness, right, we want to stand out, we want to do
00:29:57
something and say something in a very particular way.
00:30:00
You might have noticed unnoticed that that's my
00:30:03
motivation, right, if I understand that motivation, I
00:30:06
know that if I want to do an organizational change, I need to
00:30:09
account for that.
00:30:10
To take the maturity of my organization with me to make
00:30:15
sure that it triples down to the rest of the organization.
00:30:19
I think these behavioral tools and I know you asked me around
00:30:22
AI, but the AI makes the analysis for you.
00:30:25
The AI helps you to understand that, yeah, I can tell you if
00:30:29
what you're designing as an organizational structural change
00:30:32
is actually working for the Enneagram types that you have in
00:30:36
your organization.
00:30:37
So I think it's a balance.
00:30:40
And we are coming back to the topic which I know we spoke a
00:30:43
lot about is the human AI relationship.
00:30:45
There's balance between humans and our behaviors and machines,
00:30:50
and then at the planet to this, and so I think what you will see
00:30:54
in the future in approaching systems is less about human
00:30:59
technology business.
00:31:00
It's more about behaviors in a technology, aka data models and
00:31:07
context, because context means, from a cultural societies,
00:31:12
organizational term, behavors are an organizational behavior,
00:31:16
a client behavior, a customer behavior, a consumer behavior,
00:31:20
right, and they all fit into each other and they need to
00:31:22
understand the intersecting them .
00:31:23
And I think that's interesting where AI can really help us to
00:31:27
unpack these things, yes, at speed, but also depth, which we
00:31:31
are lacking based on assumptions most of the time.
00:31:36
Ben Maynard: With my mind suitably blown, I think we will
00:31:38
call it there.
00:31:39
It's been a really fascinating exploration into sustainability
00:31:43
and a few rabbit holes along the way which I think, although
00:31:47
tangentially relate to it, I think are very important and
00:31:50
very relevant to you to share.
00:31:51
So thank you so much once again for your responses and your
00:31:55
courtesy of kind of spending this time with me.
00:31:56
I know you're a busy man, so I really appreciate this time.
00:31:59
Is there any closing for something of import that you'd
00:32:03
like to share with listeners before we close off?
00:32:05
Dom Heinrich : When you approach sustainability and I know we
00:32:08
spoke about a lot about how technology can enhance these
00:32:13
things I feel approaching it from a perspective this is just
00:32:22
things through all the might not see and go beyond your
00:32:26
fascination or excitement about a solution and be curious what
00:32:31
else could you say?
00:32:32
What, if?
00:32:33
I think my takeaway would be ask yourself the question, what
00:32:38
else?
00:32:38
And I think that is what I would lead to and consider the
00:32:45
unobvious.
00:32:45
Look at the ways you produce and what else you can do with it
00:32:49
.
00:32:49
It's the simplest way of going after sustainability, to be
00:32:52
honest.
00:32:53
Ben Maynard: I wish we had more time, because there's one
00:32:57
particular technique that I use to help people discover some of
00:33:02
the non-obvious things.
00:33:03
I always say that if they're and I totally stole this from
00:33:06
Peter Senghi, the author of the Fifth Discipline that if the
00:33:09
solutions to our problems are obvious, we'd already be doing
00:33:11
them and you probably wouldn't be talking to me.
00:33:13
So we have to accept that the way you've been doing things and
00:33:17
the solutions that you've came up with aren't solving anything,
00:33:21
and the thing that will make for a difference is going to be
00:33:23
something which is non-obvious, which will probably rely upon
00:33:26
you guys getting together and really talking and exploring
00:33:30
this, creating that understanding, and I think now
00:33:32
in this world that we are faced with, finding ways to ask that
00:33:36
expert in our pocket, ask AI to help us, through some of that
00:33:40
more structured thinking, to really discover those
00:33:43
non-obvious points of leverage that will, over time, make a
00:33:47
huge impact.
00:33:49
Dom Heinrich : That's why you're running the podcast that
00:33:51
beautifully said.
00:33:53
Ben Maynard: Oh, thank you so much, dom.
00:33:54
I really hope that we do get to meet up soon and there is a
00:33:57
loose plan for it.
00:33:58
I'm excited if we do get to do that, even if it's just for a
00:34:00
quick drink and to meet you in person, because it's been an
00:34:03
absolute joy having on this episode and in the previous
00:34:07
episode.
00:34:07
As we mentioned before, people can find you on LinkedIn.
00:34:10
It's the place to find you, and if anyone is interested in
00:34:13
having a conversation with me around how to find some of those
00:34:16
non-obvious things, feel free to drop me a note on LinkedIn.
00:34:19
More than happy to have a conversation around it, dom.
00:34:22
Thank you once again.
00:34:24
Dom Heinrich : Thank you as well .
00:34:26
Ben Maynard: Everyone, thank you very much for listening.
00:34:27
We shall be back next week.
00:34:30
Dom Heinrich : Thank you to all the listeners.
00:34:31
Really excited to get feedback.
00:34:34
By the way, Reach out and challenge.
00:34:37
Ben Maynard: Reach out and touch someone, as somebody once said,
00:34:39
or challenge someone.
00:34:42
Reach out and challenge someone Would not have been such a good
00:34:45
song, would it?
00:34:45
Anyway, I'm going now.
00:34:48
Bye, everyone.
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