Innovation Management Practices

I often use Glean to understand what’s top of mind for enterprise buyers. Recently, I asked: How are enterprise leaders approaching AI change management today versus a year ago? A year ago, many leaned on pilots and PoCs. They doubled as a “change-management” strategy: a safe way to expose teams to AI in controlled doses and signal progress without tackling the harder realities of implementation and scale. But buyers are increasingly aware of the limits of this approach. Pilots can show a tool works without proving it creates business value. And because they’re often run in isolation, they can dodge the hardest challenges, like driving broad adoption, ensuring governance and permissions, and integrating with legacy systems. Over the past six months, our conversations with enterprise buyers have shifted: less about whether to pilot, and more about how to commit to intentional rollouts by defining clear business outcomes, investing in role-based enablement, and building networks of “AI champions”— employees who are early adopters and model effective use and spread best practices across the organization. AI pilots can give a comforting illusion of progress, but too often they’re used as an excuse to postpone the real work of adoption, integration, and scale. The better path is to do the research up front, ask for tailored demos, and partner with proven vendors. Then commit. Start small with specific teams or departments if you need to, but always with scale in mind: embed AI into real workflows, anchor on business outcomes, and use real change-management strategies like mobilizing your internal AI champions.

Everyone talks about AI like it’s magic—just sprinkle some algorithms, and suddenly entire industries transform overnight. I wish it were that simple. Because there’s one reality I keep coming back to, over and over again, in my work with executives, founders, and investors trying to build the “next big thing”: the law of LEGACY. People hear “legacy” and think old code and systems, Excel spreadsheets or dusty filing cabinets. But it goes much deeper. Legacy means the roads, bridges, and buildings designed for yesterday’s tools and assumptions. But it also means the societal cultural norms and the legal systems built for a pre-digital world, grinding forward at a snail’s pace while tec races ahead. The architecture of our economies is also legacy—capital flows, pensions, debt—that can’t just pivot overnight without chaos. Lastly and most importantly, legacy is our link with past through present and towards the future through the mental models running in our heads, shaping how we judge risk, trust information, and react to change. Legacy is humanity continuity law. None of these swap out with an API call. This is why we live in a two-speed world when it comes to AI bit we fail to acknowledge iti. On one hand, I see AI models evolve every few months, while the companies I advise wrestle with ERP systems from the 90s or regulators still operating in paper files. I’ve watched founders pitch groundbreaking products that look flawless in a demo—but fall apart the moment they hit real-world legacy constraints. Investors often underestimate how expensive and time-consuming it is to navigate these layers. That’s why innovation pilots stall. Why impressive demos never scale. Why billions get burned chasing “transformation” that never lands. The legacy layers of our world are ignored. Yet here’s the twist: legacy isn’t just an obstacle. It can also be a moat. The people and companies who figure out how to bridge new tech with old infrastructure, laws, and cultural contexts build advantages that pure technical innovation alone can’t replicate. Of course in the process our legacy world gets an upgrade too, but it essential to fully account legacy. My advice to all those investing or building with AI - plan for the world as it actually is—in all its messy yet layered reality. To capture it well, think of it as cake, with different flavours that will give that unforgetable taste: • The top layer is digital tech—fast, modular, exciting. The juiciest. • The middle layer is institutional systems—laws, governance, rules. A bit dry but tasty • The bottom layer is physical & cultural legacy—bricks, roads, norms, beliefs. The most solid of layers with vintage taste, no soggy bottom. When you cut through top to bottom layer, each piece has all the right balancing flavour for the unforgetable Bake Off taste. I am curious how does your cake looks and taste like lately?

Let skepticism shape your innovation, not stall you. Most rooms I’m in are brimming with Al-assisted development demos and genuine optimism about how quickly software teams can now move. That energy is real and valuable. AI is no longer just helping developers write a few lines of code faster. It increasingly helps teams refactor across files and repos, produce tests, explain unfamiliar code, and advance work through the SDLC workflows. Yet, I sometimes notice the quiet pauses before the tough questions. People worry about sounding negative, or slowing momentum, or being the only one who is uneasy. Those instincts are not only okay, but they are also just as valuable. The skepticism matters more now, not less, because the question is no longer whether AI can generate code. For me, bringing the hard questions supports progress: • What business or engineering outcome is this improving, beyond developer velocity? • Where can this fail: logic, resiliency, security, privacy, or maintainability? • What is the smallest production-relevant test that proves value? • What review, monitoring, and rollback mechanisms need to exist before we scale it? • How do we preserve human judgment where it matters most? I invite challenges to my ideas because that is how we build better ones. A few principles I’ve found useful, especially in the context of mission-critical platforms: • Challenge constructively. Do not just identify the risk and admire the problem, help design the safer path forward. • Trade “no” with “how.” If this approach is not ready, what is the fastest responsible way to learn? • Pair excitement with evidence. Instrument outcomes, test rigorously, and keep a clean rollback path. • Treat trust as a deliverable. In AI-assisted development, control is not friction. It makes speed sustainable. Our best outcomes happen when excitement fuels ambition while skepticism sharpens it. Because in this new environment, skepticism is not the enemy of innovation but is part of the engineering discipline that keeps innovation real and production worthy.

A client looked at our shortlist of innovation cases this week and said the quiet part out loud. These are too small. Nobody upstairs will care. He was right, and the reason cuts against most of what gets taught. Start with the uncomfortable part. Most corporate pilots do not fail. They succeed, and then die. The experiment works, the result is positive, and nothing happens next. We file the failures under "we learned something" and never count the successful pilots that quietly went nowhere. That is the real graveyard. This happens because the standard playbook solves the wrong risk. Lean, MVP, de-risk before you commit. All correct, and I build that way. But that method protects you from one danger: betting big and being wrong. In a startup, that is the thing that kills you. In a large company, almost nothing dies from betting big and being wrong. It dies from being too small to defend. Cost and ambition are two different dials. The playbook tells you to turn down cost, so you make the step cheap. It says nothing about ambition, so people quietly turn that one down too, at the same time. You get a cheap test of a question that did not matter. Small in cost, small in stakes, dead on arrival. Pull the dials apart. Keep the cost small. Push the stakes high. The most fundable thing in a big company is the cheap test of an expensive question, because a positive result gives someone senior a reason to spend their own capital carrying it forward. Nobody spends capital on a small win. They spend it on a small step toward a large one. So a pilot has two jobs. Reduce risk, and earn the right to the next move. If it cannot do the second, the first never mattered. Start small. Just never aim small. #Transformation #Strategy #Business #MVP #Vision

In our recent Substack, Anastasia Bektimirova made the case for why Accelerate Estonia may have something to teach the UK's Regulatory Innovation Office: "It’s hard not to pause when you come across a public sector programme whose motto is “making illegal things legal.” That line belongs to Accelerate Estonia, an innovation lab in the country’s Ministry of Economic Affairs and Communications, set up to identify and fix regulatory barriers to innovation. I first came across it in a characteristically insightful episode of the Statecraft podcast, discussing Estonia’s digital state. "Accelerate Estonia helps businesses overcome obstacles by shaping policy and, where needed, proposing legislative changes, so innovative ideas can operate lawfully from Estonia rather than stalling in a sandbox or moving overseas. Applicants are filtered for a clear need for regulatory change, scalability potential, and a ready-to-pilot concept. The focus is explicitly B2B/B2C rather than selling to government. This model sets ambition (open a market) and backs it with the unglamorous mechanics that move the needle. "What stands out is the delivery discipline. Validation stage (1-3 months) tests whether there’s a genuine legislative issue, the likely economic impact, and whether the solution is mature enough to pilot. Definition stage (3-6 months) turns that diagnosis into a delivery plan: pinning down the rule change required, the pilot and impact analysis, stakeholders and budget, and the specific R&D value. Proof stage (6-18 months) is focused on execution – draft the amendment, run the pilot, carry out the public-private cooperation plan. Finally, the results/aftercare stage presents the amendment to relevant parts of government, communicates the newly opened market, concludes cooperation, and reports the R&D value. "The method has proven to work in various domains. In health, Accelerate Estonia and the Ministry of Social Affairs have taken a self-service pharmacy model to the finish line, with amendments to the Medicinal Products Act now being introduced so 24/7 automated dispensing can legally enter the market. In education, a pilot led to draft changes to the Basic School and Upper Secondary School Act to let schools procure teaching from external providers. "As the UK builds out the Regulatory Innovation Office, tasked with reducing the burden on businesses bringing new products and services to market by supporting regulators in updating rules and speeding up approvals, Accelerate Estonia could offer a lesson in how to operationalise it. In practice, that would likely mean pairing pilots with a relevant regulator from day one, running regulatory analysis alongside technical work, and defining ‘graduation’ as a safe, evidence-based rule change that opens a market." Read (with links) here: https://lnkd.in/dA_BxR7H

Do you want to create radical innovations? Then stop thinking in just one dimension. One of the models I use most—especially when aiming for radical innovation—is the “10 Types of Innovation” by Larry Keeley and his co-authors. Why? Because it forces you to look beyond the product. Most organisations innovate in just one or two areas: • A better product • A new feature • Maybe a shiny service That’s not enough. True innovation happens when you combine multiple types: • Profit model • Network • Structure • Process • Product performance • Product system • Service • Channel • Brand • Customer engagement Here’s the key insight: If you want something truly new, you need to tick at least five of these boxes. Not one. Not two. Five. That’s when competitors struggle to copy you. That’s when customers feel the difference. That’s when innovation becomes strategic—not incremental. So next time you work on an idea, ask yourself: How many boxes are we really ticking? #innovation #strategy #businessinnovation #leadership #growthmindset #disruption #innovationmanagement #futureofwork

A fake sense of making progress by working on random experiments is the biggest risk during GenAI adoption. It's all too easy to be swayed by initial successes that seem to address aspects of a problem, leading business leaders to believe that further efforts will seamlessly extend these solutions to cover all bases. This convenient extrapolation is very risky. However, this optimism meets a harsh reality as it doesn’t happen linearly. As one goes deeper, the complexity of scaling these solutions grows exponentially to address the problem comprehensively. The extrapolation methods, that served well in the past, fall short in the unpredictable path of GenAI. While solving a problem, don’t fall in the trap of over-enthusiasm till it crosses a minimum threshold and covers a critical path for a business problem. Rigorous validation with focussed experimentation is the only way to success. Please give it to your SMEs to evaluate and get the green light. Sustainable success in business is not the product of mere excitement; it's the result of delivering tangible, impactful results. #ExperienceFromTheField #WrittenByHuman

💡 Before transitioning to industry, words like "innovation" and "disruption" were just buzzwords to me. Fast forward three years, and they’re now the heartbeat of my work in corporate R&D at ZEISS Group. 𝗟𝗲𝘁’𝘀 𝘁𝗮𝗸𝗲 𝗮 𝗹𝗼𝗼𝗸 𝗮𝘁 𝘁𝗵𝗿𝗲𝗲 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝘁𝘆𝗽𝗲𝘀 𝗼𝗳 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻: 1️⃣ 𝗦𝘂𝘀𝘁𝗮𝗶𝗻𝗶𝗻𝗴 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻: 𝗧𝗵𝗲 𝗦𝘁𝗲𝗮𝗱𝘆 𝗖𝗹𝗶𝗺𝗯 🧗♂️ 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗶𝘁? Imagine sustaining innovation as the reliable upgrade to your favorite gadget. It's all about refining existing products to better serve current customers. 𝗘𝘅𝗮𝗺𝗽𝗹𝗲: Think of adding a fifth blade to your razor or enhancing your smartphone’s camera. 𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀: Established companies thrive here! They understand their customers and have the resources to keep improving. It’s like keeping your loyal fans happy while building your empire! 2️⃣ 𝗟𝗼𝘄-𝗘𝗻𝗱 𝗗𝗶𝘀𝗿𝘂𝗽𝘁𝗶𝗼𝗻: 𝗧𝗵𝗲 𝗦𝗻𝗲𝗮𝗸𝘆 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝗿 🥷 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗶𝘁? Low-end disruption is when a nimble player targets the least demanding customers with a "good enough" product at a lower price. 𝗘𝘅𝗮𝗺𝗽𝗹𝗲: Consider steel minimills or discount retailers offering affordable options. 𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀: These disruptors start small, gaining a foothold by serving those overlooked by incumbents. As they improve, they move upmarket and challenge the giants! It’s the classic underdog story! 3️⃣ 𝗡𝗲𝘄 𝗠𝗮𝗿𝗸𝗲𝘁 𝗗𝗶𝘀𝗿𝘂𝗽𝘁𝗶𝗼𝗻: 𝗧𝗵𝗲 𝗧𝗿𝗮𝗶𝗹𝗯𝗹𝗮𝘇𝗲𝗿 🌄 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗶𝘁? New market disruption is all about creating entirely new markets by turning nonconsumers into consumers. 𝗘𝘅𝗮𝗺𝗽𝗹𝗲: The personal computer revolutionizing how we work or the transistor radio captivating a whole new generation! 𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀: Disrupters here forge new value networks and attract customers who never used the incumbents’ products. It’s like opening a door to a whole new world! Understanding these innovation types can help your business adapt to changes and seize new growth opportunities. 𝗔𝗳𝘁𝗲𝗿 𝗮𝗹𝗹, 𝗶𝘁'𝘀 𝗳𝗮𝗿 𝗯𝗲𝘁𝘁𝗲𝗿 𝘁𝗼 𝗯𝗲 𝘁𝗵𝗲 𝗱𝗶𝘀𝗿𝘂𝗽𝘁𝗼𝗿 𝘁𝗵𝗮𝗻 𝘁𝗼 𝗯𝗲 𝗱𝗶𝘀𝗿𝘂𝗽𝘁𝗲𝗱—something Shakespeare's Hamlet might have reflected on in the context of today’s business landscape: "𝗧𝗼 𝗱𝗶𝘀𝗿𝘂𝗽𝘁, 𝗼𝗿 𝘁𝗼 𝗯𝗲 𝗱𝗶𝘀𝗿𝘂𝗽𝘁𝗲𝗱, 𝘁𝗵𝗮𝘁 𝗶𝘀 𝘁𝗵𝗲 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻!" Would you like to learn more about these concepts? I strongly encourage you to explore the valuable insights of the late Clayton Christensen. 𝗛𝗮𝗽𝗽𝘆 𝗱𝗶𝘀𝗿𝘂𝗽𝘁𝗶𝗻𝗴! #innovation #disruption #optics #photonics #zeiss #teamzeiss

High-pressure, fast-paced work environments are like hot sauce on the brain—they keep everything on fire. While leaders might thrive on this continual state of excitement and ambition, expecting all employees to sustain this intensity is unrealistic. Such an environment can lead to: → Burnout → Disillusionment → High turnover But what if you’re on a mission to change the world or accomplish big things? How can you cultivate a culture of innovation that also supports a sustainable workforce? ⦿ Flexible Schedules: Foster innovation with flexible hours and remote work options, as demonstrated by Google. ⦿ Clear Boundaries: Limit after-hours work and communication to avoid burnout, a strategy championed by 37signals. ⦿ Promote Well-being: Invest in wellness programs and mental health resources, like those offered by Asana. ⦿ Create Innovation Labs: Set up dedicated spaces or times for experimentation and creativity, like 3M's famous 15% rule. ⦿ Encourage Regular Breaks: Implement mandatory downtime, similar to Slack's "no meetings" Fridays, to boost creativity and reduce fatigue. ⦿ Mentorship Programs: Pair employees with mentors to nurture growth and support, following the model used by Pixar Animation Studios to encourage creative collaboration. wearemotto.com

Beyond "Flattery": When Imitation Becomes a Strategic Drain The adage that "imitation is the greatest form of flattery" often falls flat for innovators and founders. The reality upon hitting a point of success can feel different: a tactical shift from creation to defense. Imitators, sensing opportunity, enter not to iterate but to appropriate. They replicate surface-level ideas, sow market confusion, and force the original creator into a reactive posture. The cost isn't just market share. It's a massive operational and emotional tax. Energy diverts from innovation to: *Protecting intellectual space *Re-educating the market on authenticity *Managing the noise of diluted offerings *Combating founder fatigue This dynamic, however, is a signal. It validates product-market fit and resonance. The sustainable response isn't just legal protection; it's deepening what cannot be copied: • Your unique value narrative and brand ethos • Customer community and exceptional experience • The pace of your core innovation Imitators operate on lag! By fostering an authentic culture and relentlessly evolving your core offering, you maintain the lead that matters. Question for the comments: How have you navigated the challenge of imitation while protecting your team's momentum and morale? #Innovation #Leadership #Entrepreneurship #Strategy #BusinessGrowth #StartupLife #IntellectualProperty #BrandStrategy #LBFalumni #SkyHighTower