Strategic Innovation Planning

After spending three decades in the aerospace industry, I’ve seen firsthand how crucial it is for different sectors to learn from each other. We no longer can afford to stay stuck in our own bubbles. Take the aerospace industry, for example. They’ve been looking at how car manufacturers automate their factories to improve their own processes. And those racing teams? Their ability to prototype quickly and develop at a breakneck pace is something we can all learn from to speed up our product development. It’s all about breaking down those silos and embracing new ideas from wherever we can find them. When I was leading the Scorpion Jet program, our rapid development – less than two years to develop a new aircraft – caught the attention of a company known for razors and electric shavers. They reached out to us, intrigued by our ability to iterate so quickly, telling me "you developed a new jet faster than we can develop new razors..." They wanted to learn how we managed to streamline our processes. It was quite an unexpected and fascinating experience that underscored the value of looking beyond one’s own industry can lead to significant improvements and efficiencies, even in fields as seemingly unrelated as aerospace and consumer electronics. In today’s fast-paced world, it’s more important than ever for industries to break out of their silos and look to other sectors for fresh ideas and processes. This kind of cross-industry learning not only fosters innovation but also helps stay competitive in a rapidly changing market. For instance, the aerospace industry has been taking cues from car manufacturers to improve factory automation. And the automotive companies are adopting aerospace processes for systems engineering. Meanwhile, both sectors are picking up tips from tech giants like Apple and Google to boost their electronics and software development. And at Siemens, we partner with racing teams. Why? Because their knack for rapid prototyping and fast-paced development is something we can all learn from to speed up our product development cycles. This cross-pollination of ideas is crucial as industries evolve and integrate more advanced technologies. By exploring best practices from other industries, companies can find innovative new ways to improve their processes and products. After all, how can someone think outside the box, if they are only looking in the box? If you are interested in learning more, I suggest checking out this article by my colleagues Todd Tuthill and Nand Kochhar where they take a closer look at how cross-industry learning are key to developing advanced air mobility solutions. https://lnkd.in/dK3U6pJf

Business Models as Drivers of the SDGs 🌎 Achieving the Sustainable Development Goals requires more than commitment—it demands viable models that integrate social and environmental value into core business operations. Across sectors, companies are already piloting and scaling solutions that contribute directly to global priorities. These include clean energy leasing for low-income areas, digital health tools for underserved populations, and inclusive platforms that connect small producers to formal markets. Access remains a common thread. Whether through vocational e-learning, low-cost water purification systems, or mobile connectivity for remote regions, business models are helping close persistent service gaps. At the infrastructure level, innovation is driving systemic improvements: smart urban planning, circular retail platforms, eco-design consultancies, and waste-to-resource processing are just a few examples of how core services can evolve. Technology is enabling scale. Traceability tools, digital marketplaces, and remote diagnostics are being applied to food systems, education, health, and employment—amplifying reach and lowering barriers. Circularity is gaining traction across product and service design. Models promoting reuse, bulk sales, and lifecycle consulting are reducing environmental impacts while tapping into changing consumer preferences. Partnership is emerging as a critical enabler. Initiatives that combine public, private, and civil society capabilities—through data sharing, co-investment, or joint governance—are unlocking new capacities. Business models aligned with the SDGs are not side projects. They represent a shift in how value is created and measured in a resource-constrained, rapidly changing world. #sustainability #sustainable #business #esg #SDGs

My biggest single focus has been the potential of AI for business model innovation and transformation. Here is some of the best open access research on the topic I've found along the way. Artificial Intelligence-Enabled Business Model Innovation: Competencies and Roles of Top Management — Jorzik et al. https://lnkd.in/gAUHz-dx Analysis of 45 executive interviews shows that data-visioning, ambidextrous orchestration and ecosystem brokering are the three C-suite competencies most strongly linked to successful AI-driven business-model innovation. Value Creation and Value Capture for AI Business Model Innovation: A Three-Phase Process Framework — Åström et al. https://lnkd.in/gM979gRE A longitudinal case study of an AI platform firm distils a repeatable three-phase cycle—prerequisite mapping, value-capture alignment and portfolio orchestration—that synchronizes technical value creation with revenue realisation. Firms’ Use of Predictive Artificial Intelligence for Economic Value Creation and Appropriation — Costa-Climent et al. https://lnkd.in/gJWiUA6N Survey data from 418 AI projects across five industries shows that high data quality, continuous organizational learning and partner-ecosystem density jointly predict value-creation and value-appropriation. Artificial Intelligence Capabilities for Circular Business Models: Research Synthesis and Future Agenda — Madanaguli et al. https://lnkd.in/gsDf_ubD A systematic literature review maps specific AI capabilities—such as real-time sensing and generative design—to circular-economy strategies of narrowing, slowing and closing resource loops. Transforming Business with Generative AI: Research, Innovation, Market Deployment and Future Shifts in Business Models — Singh et al. https://lnkd.in/g8NqSC9S A multi-method study of patents, funding flows and expert interviews finds that GenAI catalyszs rapid business-model churn and identifies five dominant commercial archetypes for scaling. Designing AI Implications in the Venture Creation Process — Pietronudo et al. https://lnkd.in/gxBTAJvR Conceptual analysis integrates lean-startup theory with algorithmic prediction to propose how AI tools reshape opportunity discovery, resource assembly and business-model validation in new ventures. Implementation of Artificial Intelligence: A Roadmap for Business Model Innovation — Reim et al. https://lnkd.in/g4FkTdMi A four-step managerial roadmap (capability audit, BMI opportunity scan, capability development, organisational acceptance) synthesises earlier case evidence to guide initial AI-enabled business-model changes.

Tanguy Crusson has spent 10+ years at Atlassian, where he's taken several products from zero to one, including HipChat, Statuspage, and most recently, Jira Product Discovery. In this episode, we dive deep into the struggles and lessons of innovating and building new products inside a large company. Tanguy shares candid stories about what's worked, what hasn't, and everything he's learned about successfully building 0 to 1. We cover: 🔸 Why large companies with so many advantages still fail at creating new products 🔸 How to avoid common pitfalls like competitive myopia and premature scaling 🔸 Lessons learned from acquisitions 🔸 Lessons from competing with Slack 🔸 Insights from the success of Jira Product Discovery 🔸 Tactics for protecting your “ugly babies” 🔸 The power of “lighthouse users” 🔸 The importance of having a “why now” 🔸 So much more Listen now 👇 - YouTube: https://lnkd.in/gr9f4D45 - Spotify: https://lnkd.in/gmiuz944 - Apple: https://lnkd.in/gWGAc5ZX Some key takeaways: 1. “Don’t eat your own bullshit.” When launching new products within companies that have already seen some success, it’s easy to assume that your existing playbooks will work again. But what got you here won’t take you there. You need to define, test, and validate your assumptions, because they may very well be wrong—especially when targeting new customer segments. 2. Startups benefit from starving. Starving creates hunger, which drives people to solve problems with resourcefulness and urgency. When exploring new products in a big company with excessive resources, you need to create scarcity to emulate this startup starvation. This generally means operating as a small, scrappy, siloed team. 3. The most likely outcome when launching a new product is failure—even at big companies that appear to have many advantages. It’s important to ground new product launches in this reality so that you can deter the company from over-investing, which ultimately serves to reduce hunger, slow things down, and decrease the chances of success. After all, why invest heavily in something that’s most likely to fail anyway? 4. Success for new products should be measured differently from existing ones, both in terms of metrics and time horizons. In general, new products should be judged by whether the team is answering the right questions at the right pace and whether the team is still excited about the new bet’s potential. It’s a common mistake to judge new products by metrics that a big company is used to, like MAUs or revenue. However, if a team is optimizing for MAUs or revenue before they’ve worked to understand the problem, they will be working on the wrong things. 5. Atlassian uses a four-phase approach to launching new products and deciding whether to invest in them further: Wonder, Explore, Make, Impact

Innovation isn’t just about new products. It’s about how you structure, deliver, and capture value—across your entire business model. In their book, "Ten Types of Innovation" (2013), Keeley et al. outline a powerful framework outlining no less then 10 types of innovation: Configuration 1. Profit Model – How you make money 2. Network – How you collaborate 3. Structure – How you organize 4. Process – How you operate Offering 5. Product Performance – What you offer 6. Product System – How offerings work together Experience 7. Service – How you support users 8. Channel – How you deliver value 9. Brand – How you're perceived 10. Customer Engagement – How you foster loyalty Most innovation efforts focus narrowly on the product. But real advantage comes from orchestrating multiple innovation types, often in combination. If you're looking for new strategic levers, this framework is a great place to start. Which of the ten are you already investing in?

What truly is a disruptive technology? We throw around the term freely these days to refer to any novel technology that we come across. But not all new technologies actually meet the bar. Michael Porter reminds us that a disruptive technology is one that invalidates important competitive advantages of incumbents, enabling a new entrant to leap ahead in the market. Take the Internet for example. It was disruptive where the mechanism for delivering information was fundamental to the product or service. Like travel agents or the recorded music business. But for many other markets, it wasn't disruptive at all, since it was easy for existing incumbents to simply add it as a new channel for communicating with their customers. As GenAI and LLMs become the latest technology innovation, we should ask ourselves, where will it actually be disruptive? Certainly not a chat bot that any incumbent can easily add on. But maybe in the world of search, where LLMs are finally able to deliver a superior answer, potentially disrupting the ironclad superiority Google has maintained for decades. To decide whether something is disruptive, two questions are helpful: 1) To what extent does the new technology invalidate traditional competitive advantages? 2) To what extent can incumbents embrace the technology without major negative consequences for their business? I have no doubt AI will be a disruptive technology, but think we are only in the first inning of discovering exactly where that disruption will occur.

Consumer Insights, thy name is Consumer Observation “You see, but you do not observe….Never trust to general impressions, my boy, but concentrate yourself upon details.”-Sherlock Holmes Brands, in their zest to win consumer’s heart and market share, are going all guns blazing to understand consumer behaviour. Technological advancements & multiple data sources are adding to the many ways which brands are leveraging to better understand their consumers. As much as the ways & means of capturing consumer data evolves, there is no substitute to observing & listening to consumers first hand through home visits. Afterall, consumers are real human beings and not just a data point!! The art & science of observing consumers called as ethnography helps humanize consumers for the brands serving them. A brand which has leveraged ethnographic research methodology effectively for consumer observation to fuel product innovation is Loreal. Having entered Indian market in 1992 and facing challenges from the likes of HUL, P&G, Dabur etc. Loreal, very early, understood the need for ‘close encounters’ with Indian consumers for India specific product innovation – ‘Indo-vation’. Brand has been investing in understanding consumer need through multiple ways including regular consumer home visits. And these in-the-moment, in-context consumer observation exercises have helped discover unmet consumer needs thereby triggering innovation opportunities. It was one such consumer home visit which led to the launch of Garnier Fructis Shampoo+Oil, during 2009-10. While visiting consumers, brand custodians observed that young girls realised the importance of oiling their hair as practiced by their mother but never found the time to do it. Loreal launched Garnier Fructis Shampoo + Oil eliminating the need of two separate haircare routines, thereby saving time for its consumers. No surprise that the product became highest-selling Garnier Fructis variant within a short time of its launch. Getting to know consumers is not a rocket science. All that it needs is a brand with a sincere desire to know consumers and a consumer insight gathering approach which views consumers as they are – human beings with a complex weave of emotion & rationality. Fun fact: One of the earliest success stories of ethnography driven product innovation is 3M. In the 1920s, 3M engineer Richard Drew spent several days at an auto assembly plant, observing how the workers were using his company’s sandpaper. His observations about how workers were using the product and challenges faced by them led to the birth of 3M masking tape!! #ConsumerInsights #ConsumerBehaviour #MarketResearch #Marketing #ProductInnovation

Dont become a boiled frog... The "boiled frog" metaphor is your wake-up call. Gradual changes—shifts in customer preferences, new technologies, regulatory updates, competitor moves—can sneak up on your business if you're not paying attention. To avoid getting "cooked" by disruption: ☑ Monitor Trends Continuously. ↳ Use tools like environmental scanning, PESTLE analysis, or scenario planning. ↳ Stay ahead of subtle shifts before they become seismic changes. ☑ Embrace Strategic Agility. ↳ Flexibility is your best defence. ↳ Build a strategy that pivots when trends signal opportunities or threats. ☑ Invest in Data-Driven Insights. ↳ Leverage analytics to spot patterns you might otherwise miss. ↳ Early signals lead to smarter, faster decisions. ☑ Engage in Open Strategy. ↳ Bring in diverse perspectives—employees, customers, partners—to spot emerging trends from all angles. ☑ Perform Regular Strategic Reviews. ↳ Treat strategy as a living process, not a set-it-and-forget-it document. ↳ Align it with current realities to stay relevant. The key? Be proactive. Be vigilant. Businesses that adapt to changing environments don’t just survive—they thrive. Ps. If you like content like this, please follow me 🙏

𝗘𝗔’𝘀 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 𝗳𝗼𝗿 𝗠𝗮𝘅𝗶𝗺𝗶𝘇𝗶𝗻𝗴 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗩𝗮𝗹𝘂𝗲: 𝗖𝗹𝗶𝗺𝗯 𝗧𝗵𝗲 𝗕𝗲𝗻𝗲𝗳𝗶𝘁 𝗟𝗮𝗱𝗱𝗲𝗿 Enterprise Architecture (EA) has evolved beyond governance and documentation. It's a 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻 𝗱𝗿𝗶𝘃𝗶𝗻𝗴 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆, 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻, 𝗮𝗻𝗱 𝗰𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲 𝗮𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲. Strategic EA 𝗿𝗲𝗱𝘂𝗰𝗲𝘀 𝗰𝗼𝘀𝘁𝘀, 𝗮𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗲𝘀 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻, 𝗮𝗻𝗱 𝗶𝗺𝗽𝗿𝗼𝘃𝗲𝘀 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝘃𝗲𝗹𝗼𝗰𝗶𝘁𝘆. To unlock EA’s full impact, organizations must 𝘃𝗶𝗲𝘄 𝗘𝗔 𝗮𝘀 𝗮 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗮𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗼𝗿. This begs an 𝗶𝗻𝘁𝗲𝗻𝘁𝗶𝗼𝗻𝗮𝗹, 𝗽𝗵𝗮𝘀𝗲𝗱 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵. Delivering measurable value in stages, while reducing complexity and risk. Enter the 𝗕𝗲𝗻𝗲𝗳𝗶𝘁 𝗟𝗮𝗱𝗱𝗲𝗿—a structured roadmap to realizing EA’s value. It establishes f𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗺𝗮𝘁𝘂𝗿𝗶𝘁𝘆 𝘁𝗵𝗲𝗻 𝘀𝗰𝗮𝗹𝗲𝘀 𝘁𝗼 𝗮𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗶𝗻𝗶𝘁𝗶𝗮𝘁𝗶𝘃𝗲𝘀. 𝗧𝗵𝗲 𝗕𝗲𝗻𝗲𝗳𝗶𝘁 𝗟𝗮𝗱𝗱𝗲𝗿: 𝗔 𝗦𝘁𝗲𝗽-𝗯𝘆-𝗦𝘁𝗲𝗽 𝗔𝗽𝗽𝗿𝗼𝗮𝗰𝗵 Your journey to EA maturity flows through three stages. Each unlocks layers of business value: 𝟭 | 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗘𝗔: 𝗘𝘀𝘁𝗮𝗯𝗹𝗶𝘀𝗵 𝗦𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 & 𝗩𝗶𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 Here, EA’s primary role is to align teams, standardize governance, and create an enterprise-wide architecture view. Without this, system visibility remains siloed, and strategic alignment is impossible. 𝙆𝙚𝙮 𝙄𝙣𝙞𝙩𝙞𝙖𝙩𝙞𝙫𝙚𝙨: ✔ Define governance and operating ✔ Central EA repository for decision support ✔ Map business capabilities to technology 📌 𝘽𝙪𝙨𝙞𝙣𝙚𝙨𝙨 𝙄𝙢𝙥𝙖𝙘𝙩:  ✅ Reduces redundant investment ✅ Clarity on technology landscape ✅ Improves strategic decision-making 𝟮 | 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗘𝗔: 𝗗𝗿𝗶𝘃𝗶𝗻𝗴 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 EA shifts from documentation to execution—agility, cost optimization, and time-to-market. 𝙆𝙚𝙮 𝙄𝙣𝙞𝙩𝙞𝙖𝙩𝙞𝙫𝙚𝙨: ✔ Integrate EA into transformation ✔ Optimize processes and reduce debt ✔ Support integration and interoperability 📌 𝘽𝙪𝙨𝙞𝙣𝙚𝙨𝙨 𝙄𝙢𝙥𝙖𝙘𝙩:  ✅ Accelerates time-to-value ✅ Reduces costs, increases efficiency ✅ Aligns IT with business 𝟯 | 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗘𝗔: 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝗶𝗻𝗴 𝗖𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲 𝗔𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲 At highest maturity, EA is a core part of strategy, decisions and innovation. 𝙆𝙚𝙮 𝙄𝙣𝙞𝙩𝙞𝙖𝙩𝙞𝙫𝙚𝙨: ✔ Embed EA into C-level discussions ✔ Identify strategic technology investments ✔ Drive business model innovation 📌 𝘽𝙪𝙨𝙞𝙣𝙚𝙨𝙨 𝙄𝙢𝙥𝙖𝙘𝙩: ✅ EA contributes to revenue growth ✅ Rapid adaptation to markets ✅ Scale transformation initiatives 𝗖𝗹𝗶𝗺𝗯𝗶𝗻𝗴 𝘁𝗵𝗲 𝗟𝗮𝗱𝗱𝗲𝗿 𝘁𝗼 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗘𝗔 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝗮𝗹 to 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗘𝗔 is not an overnighter. Disciplined teams that deliver tangible results gain executive buy-in and accelerate their path to value. ➕ Follow Kevin Donovan 🔔 👍 Like | ♻️ Repost 🚀 Join Architects' Hub 👉 https://lnkd.in/dgmQqfu2

Most "product strategies" die because they try to be everything to everyone. I’ve seen a lot of such strategy docs and decks. But they are often just prioritized roadmaps or broad themes that sound good. Real strategy is hard. But also much more valuable. Here’s what I’ve learned it actually takes to develop a great product strategy: ➡️ A deep understanding of the landscape Industry shifts. Market dynamics. Tech trends. Customer context. Product realities. Not just what users say but the actual Jobs to Be Done, desired outcomes, and unmet needs. Where are they stuck? What’s changing around them? What’s at stake? ➡️ A clear point of view What do we believe about this space that others don’t? What’s the differentiated bet we’re making? ➡️ Hard decisions If there aren’t tradeoffs, it’s not a strategy — it’s a wish list. A good strategy helps you say “no,” even when it’s hard. Especially then. ➡️ Alignment to company strategy A product strategy can’t live in a vacuum. It has to be anchored in — and help accelerate — your company’s broader strategy. Otherwise, you risk building a great product that wins the wrong game. ➡️ Outcomes that connect the dots There should be a visible line from customer value → business impact → the bets you’re making. People need to see how their work ladders up or it won’t stick. And here’s the part most people skip: You have to test and evolve your strategy. The best strategies aren’t static. They’re living systems. You put the strategy into motion, watch what happens, and adapt. Just like product, strategy needs feedback loops. Inspired by "Smart Business", I try to ask: -Are we learning from how the strategy is performing in the market? -What feedback are customers and teams giving us — directly or indirectly? -Where are we seeing traction? Where is reality pushing back? -Are decisions getting easier — or harder? I’ve spent years learning how to craft product strategy that’s clear, actionable, and durable. It’s both an art and a science and it gets sharper every time you put it to work. It’s a skill you build — through practice, reflection, and iteration. Next, I will write about where, who from and how I learned product strategy #productstrategy #productleadership #platformthinking #enterpriseproducts