Innovation Storytellers

Susan Lindner
  • 5.0 (16)
  • Management
  • Weekly

Did you ever wonder how an innovation got to its finish line? How innovators saw the future, made a product, and created change – in our world and in their companies? I did. Innovation Storytellers invites changemakers to describe how they created their innovation and just as important – THE STORIES – that made us fall in love with them. Come learn how great innovations need great stories to make them move around the world and how to become a better storyteller in the process. I'm Susan Lindner, the Innovation Storyteller. But I wasn't always. I've been a wannabe revolutionary, an epidemiologist at the CDC and an AIDS educator in the brothels of Thailand helping to turn former sex workers into entrepreneurs. Trained as an anthropologist and the Founder of Emerging Media, I've spent the last twenty years working with innovators from 60+ countries. Ranging from cutting edge startups to Fortune 100 companies like GE, Corning, Citi, Olayan, and nine foreign governments, helping their leaders to tell their stories and teaching them how to become incredible advocates for their innovations. Great innovation stories make change possible. They let us step into a future we can't see yet. I started this podcast to shine a light on our generation of great innovators, to learn how they brought their innovation to life and the stories they told to bring them to the world.

  1. 1d ago

    How Do You Build Customer Centric Innovation Strategy?

    What helps an innovation earn the support, time and investment it needs to reach customers? I explore that question with David Ring, Vice President, Group Innovation at Synthomer. David's own experience taught him that meeting a technical brief does not guarantee a product will succeed. One project delivered what had been asked for, yet missed what customers actually needed. That lesson now shapes how he thinks about listening to customers, finding problems they may not voice directly, and making the case for new ideas in language decision-makers understand In this episode, of the Innovation Storytellers Show, we talk about the different stories innovation leaders need to tell scientists and senior executives, how outside partners can help companies find ideas and expertise, and why business model innovation belongs in the conversation. David shares his concerns about engineering biology and the possibility that it could create new opportunities for a polymer business. What helps good ideas move from the lab into the business, and what has helped innovation gain support in your organization? Please share your thoughts.

  2. Oct 27

    Why Innovators Need to Bring their Heart To the Office

    Why do so many brilliant innovators become less persuasive the more expert they become? In this episode of the Innovation Storytellers Show, I speak with Bob Rogers, founder of BRC Imagination Arts, about something I think many innovation leaders forget when they walk into the office: people don't leave their emotions at the door just because the conversation has become technical.   Bob has spent a career creating experiences that move people to feel something and then act. His story began as a magician at Disneyland, where he learned an idea that has stayed with him ever since. The point of a performance is not to show people how clever you are. It is to help them discover something within themselves.   The lesson became the foundation for a bigger idea: when we communicate innovation, it is about them, not us. We talk about why scientists, engineers, and technical leaders often become suspicious of emotion even though emotion frequently sits behind the reason they entered their field in the first place. Bob reminds us that many experts first fell in love with their subject as children, long before they understood the technical language, frameworks, or data that later defined their careers.   So why do we strip all of that fascination out when we present an idea to a CEO? Bob argues that if you want to change behavior, you shouldn't start with features, benefits, or a technical explanation. You need to understand the hopes, fears, problems, and ambitions of the person in front of you. We discuss why experts often know too much for their own good when it comes to communication. A CEO, by necessity, is a generalist. If your innovation story requires specialist knowledge before someone can understand why it matters, you may have already lost them. One of my favorite parts of the conversation is Bob's explanation of why the story should come before the artifact. He describes how a moon rock can become one of the most boring objects in a museum if you simply put it in a gray display case and attach a technical label. But if you first take visitors through the risk, danger, ambition, and human story of traveling to the Moon, that same gray rock becomes something extraordinary. Bob has spent decades working at the intersection of imagination, experience design, storytelling, science, and business. This conversation reminds us that innovation doesn't move forward because the facts are impressive. It moves forward when people understand why those facts matter to them. When you present your next breakthrough, do you start with the technology or with the person you need to believe in it?

  3. Oct 20

    How To Turn Water Innovation Into Customer Value

    Why do so many promising innovations succeed as pilots but struggle to become part of everyday operations? In this episode of the Innovation Storytellers Show, I speak with Ian Small, Innovation Lead at Expedition Engineering and convener of the Water Innovator Alliance, about the difficult work that begins after someone has already had the great idea. Ian works at the intersection of innovation, engineering, infrastructure, and the UK water sector, where new technologies have to satisfy regulators, operators, customers, commercial partners, and teams responsible for assets that may remain in service for more than a century. We talk about innovation happening behind infrastructure most of us rarely think about, from drones that can help identify leaking water mains to new technologies for removing PFAS and microplastics, improved sensing, water reuse, and lower-carbon approaches to flood defenses. But our conversation quickly moves beyond the technology itself. Ian explains why getting an innovation adopted can be harder than developing it in the first place. A startup may have a brilliant solution but struggle to identify the right problem, the right water company, or even the right person inside that organization. Meanwhile, large organizations can struggle to communicate their needs clearly enough for innovators to respond. The result is often an expensive gap between invention and adoption. One of my favorite parts of this conversation is Ian's approach to storytelling around pilots. His team deliberately refuses to tell only the polished success story. When something works, they also explain what failed, what proved difficult, and what still needs improvement. That history gives future teams a much clearer understanding of the risks and helps build confidence as a solution progresses from experiment to something ready for wider adoption. Ian also tells me why his team has virtually stopped using the word "innovation" on one major Environment Agency program. The word had become too closely associated with pilots and trials, while the actual objective was delivering lower-carbon solutions at scale and creating measurable value. We discuss why innovation investment needs a clearer view of value from the beginning, why organizations underestimate the work required after a successful pilot, and how storytelling can help secure the resources, runway, and confidence required for long-term adoption. Finally, when I ask Ian what innovation the world needs now, he turns to AI. He argues that we don't need another model or tool. It is that we may still be waiting for the moment when we truly understand how to use the technology we already have effectively. Perhaps that is the bigger lesson running through our entire conversation. Invention is only one part of innovation. The real value arrives when people understand how to adopt it, communicate it, and make it work at scale. How much of your innovation investment is still sitting somewhere between a successful pilot and real-world adoption?

  4. Oct 13

    HOW to Get Your People to Believe in Your AI Strategy

    How do you get employees to believe in an AI strategy when the future you are asking them to believe in has not happened yet? In this solo episode of the Innovation Storytellers Show, I want to address a question I am hearing increasingly from organizations undergoing major AI transformation: can you really manage AI-driven organizational change through storytelling? I am not sure there is another way to do it. When leadership announces an AI strategy, employees do not immediately experience that future. They experience what leaders tell them about it.  When the explanation stops at productivity, efficiency, agents, automation, and new tools, people begin writing the missing parts of the story themselves. Those private narratives tend to contain three uncomfortable words: replacement, obsolescence, and irrelevance. I have been working through this problem with a major financial services organization, and it has reinforced something I believe strongly about storytelling for AI adoption. The silence surrounding technological change can be more damaging than the technology itself. In this episode, I explain why leaders should communicate the why before the what and connect AI initiatives with the organization's wider purpose rather than simply promising productivity gains. I also talk about something many AI transformation programs seem reluctant to confront directly: fear. If employees are worried about job security, changing responsibilities, or whether their skills will still matter, avoiding those subjects will not make the concerns disappear. Leaders need to name them, discuss what is known and what remains uncertain, and provide a credible plan for how people will develop alongside the technology. This is where AI change management storytelling becomes practical. Show employees what their work could look like after the transformation. Explain what becomes easier. Describe the work they may stop doing and the skills they will have the opportunity to develop. Give them ways to provide feedback as workflows change. Then start telling the stories emerging from inside the organization. If Mary finds a better way to complete a task using AI, tell that story. If Ashok discovers a new coding workflow, let colleagues learn from it. If Juan experiments with visual AI and creates something genuinely useful, show people what happened. Those internal stories can make an AI strategy feel tangible because employees can see people like themselves participating in it. Leaders also need to use the technology themselves. Telling employees to change how they work while having little firsthand experience with AI will quickly undermine credibility. Organizations that manage AI transformation successfully may not be those with the most sophisticated technology roadmap. They may simply be the ones whose leaders never allow employees to lose sight of where the story is heading and where they belong within it. If you are responsible for communicating AI to employees, ask yourself one question. Can your people see a better version of their working lives inside the future you are asking them to build?

  5. Oct 6

    How to Take Innovation from Outcomes to Impact

    What happens when AI makes it easier than ever to produce work, but organizations still struggle to turn that activity into meaningful results? In this episode of the Innovation Storytellers Show, I speak with Dr. Mik Kersten, creator of the Flow Framework and founder of Tasktop. Mik is the author of Project to Product, and Output to Outcome, about why the AI era demands a very different way of thinking about innovation. He has spent much of his career studying how ideas move through organizations, from his early work at Xerox PARC to building technology for value stream management. One lesson has stayed remarkably consistent: large organizations rarely struggle because they lack ideas or ambition. They struggle because their structures, incentives, approvals, and operating models slow the feedback loops required for innovation. AI is making that problem much harder to ignore. When knowledge outputs become cheap and plentiful, measuring productivity by documents created, code written, or tasks completed begins to lose meaning. Mik argues that organizations need to move toward outcome-driven operating models that ask a much more useful question: did the work improve something for the customer, employee, or business? We discuss why some large companies can take around 120 days to move an idea to a customer, while smaller teams can test ideas within weeks. We also examine what happens when AI accelerates a poorly designed system and simply produces more work for humans to review. Mik explains his concept of the outcome loop, where strategy leads to outputs created by humans and AI, followed by customer and employee outcomes that inform the next round of decisions. For leaders thinking about how to communicate AI transformation, this changes the conversation from productivity to effectiveness. We also talk about storytelling for C-suite leaders and why internal examples may become some of the most persuasive tools for winning AI stakeholder buy-in. Instead of telling employees that AI transformation is inevitable, leaders can show where new ways of working are already producing results, what failed along the way, and what the organization has learned. Our conversation also raises a bigger question about human-AI collaboration. Mik believes AI should support decision-making, but accountability must remain with people. His view is simple: humans should continue to report to humans, particularly when organizations are deciding which outcomes technology should pursue. As AI gives organizations the ability to create more, faster, the competitive advantage may no longer come from the volume of work being produced. It may come from knowing which outcomes are worth pursuing in the first place. How is your organization measuring the difference between AI activity and genuine impact?

  6. Sep 29

    How Human Stories Become the Competitive Advantage in AI

    What if the biggest weakness in AI-powered innovation is that we are getting better at predicting human behavior while becoming worse at understanding what that behavior actually means? In this solo episode of the Innovation Storytellers Show, I want to talk about something I believe is becoming increasingly important for innovation leaders: AI can identify patterns, surface signals, and predict what customers may do next, but prediction is not the same as understanding. My background in anthropology has always shaped how I think about innovation. Anthropologist Clifford Geertz wrote about "thick description," the idea that observing human behavior without understanding its context can lead us to misunderstand what we are seeing completely. A wink and a twitch may look almost identical, but they mean very different things. AI faces a similar problem. A model might tell you that thousands of customers abandon their shopping carts at the same point. What it cannot reliably tell you is whether they are worried about money, overwhelmed by choice, consulting their family, reconsidering the purchase, or distracted by something happening in their lives. The behavior is visible but the meaning often is not. This creates an important challenge for AI storytelling for business leaders and anyone responsible for storytelling for AI innovation. As organizations gain access to more customer data, they also need people who can listen, interpret, question assumptions, and understand the cultural context behind what the data appears to show. In this episode, I share four ways innovation teams can interpret what AI cannot. I explain why AI should act as a scout rather than the storyteller, why customer stories should challenge data rather than confirm it, and why the strongest human-AI collaboration narrative combines machine intelligence with human judgment. Your competitors can increasingly access the same models, similar data, and comparable technology. The advantage may come from what your people understand that the machines cannot fully explain. If AI can tell us what customers are doing, are we spending enough time asking why?

  7. Sep 22

    How AI Is Killing the Best Part of Innovation: The Idea

    What happens when AI gives your organization more ideas than your people actually want to own? In this solo episode of the Innovation Storytellers Show, I want to challenge something I am seeing more frequently across innovation teams: the assumption that because AI can generate hundreds of ideas in seconds, it should automatically become our ideation partner. I think we need to question that. Most organizations are not suffering from a shortage of ideas. Employees, customers, partners, suppliers, and markets are already full of observations about products that could be improved, processes that make no sense, new business models worth testing, and customer frustrations waiting to be addressed. The problem is often that organizations are not asking the right people the right questions. AI can produce options at enormous speed, but it cannot manufacture belief. It cannot create the feeling that comes from a group of people building an idea together, choosing to champion it, and taking pride in seeing it become real. That difference matters because innovation eventually depends on execution. If teams feel disconnected from the ideas they are being asked to deliver, more ideation simply creates a larger backlog. In this episode, I look at innovation storytelling in the age of AI, why human ownership still matters, and why storytelling for AI adoption must explain why a direction matters to the people expected to make it happen. I also discuss how leaders can think differently about human-AI collaboration, communicating AI to employees, and winning AI stakeholder buy-in without reducing innovation to another exercise in generating AI output. AI absolutely belongs in innovation. The bigger question is where it adds the most value and where human judgment, imagination, conviction, and conversation still need to lead. Are we using AI to help people build better ideas, or are we slowly removing people from the process that creates belief in those ideas?

  8. Sep 15

    How to Make Your Visuals Stand Out in an AI World

    What happens to visual storytelling when everyone suddenly has access to the same powerful AI tools? In this solo episode of Innovation Storytellers, I'm looking at what it takes to create visual stories that still feel distinctive, credible, and unmistakably human in an AI-generated world. AI has made it incredibly easy to create polished graphics, videos, presentations, and infographics in seconds. But when every organization can do the same thing, visual sameness quickly becomes another form of noise. Producing more content is no longer enough. The real challenge is deciding what deserves to be communicated and finding a point of view that belongs to your organization rather than an algorithm. I share practical ways innovation teams can use visual metaphor, AI-generated drafts, storyboarding tools, customer reactions, and real-world video without surrendering the judgment that makes a story matter. I also explain why the first AI-generated output should almost never be the final deliverable. The opportunity is to use AI for speed while keeping humans firmly responsible for meaning, emotion, and choice. Because when everyone can create more content, discernment becomes the real differentiator. How are you making sure your visual storytelling still feels human when AI can generate almost anything?

See All (100)

5
out of 5
16 Ratings

About

Did you ever wonder how an innovation got to its finish line? How innovators saw the future, made a product, and created change – in our world and in their companies? I did. Innovation Storytellers invites changemakers to describe how they created their innovation and just as important – THE STORIES – that made us fall in love with them. Come learn how great innovations need great stories to make them move around the world and how to become a better storyteller in the process. I'm Susan Lindner, the Innovation Storyteller. But I wasn't always. I've been a wannabe revolutionary, an epidemiologist at the CDC and an AIDS educator in the brothels of Thailand helping to turn former sex workers into entrepreneurs. Trained as an anthropologist and the Founder of Emerging Media, I've spent the last twenty years working with innovators from 60+ countries. Ranging from cutting edge startups to Fortune 100 companies like GE, Corning, Citi, Olayan, and nine foreign governments, helping their leaders to tell their stories and teaching them how to become incredible advocates for their innovations. Great innovation stories make change possible. They let us step into a future we can't see yet. I started this podcast to shine a light on our generation of great innovators, to learn how they brought their innovation to life and the stories they told to bring them to the world.

Information

  • Creator
    Susan Lindner
  • Years Active
    2021 - 2026
  • Episodes
    100
  • Rating
    Clean
  • Copyright
    © Susan Lindner 2021
  • Show Website
    Innovation Storytellers

You Might Also Like