Iterative Processes for Business Innovation

There’s no denying the efficacy of Objectives and Key Results (OKRs) in driving alignment and focus within an organization. They've been a cornerstone in the strategic toolbox of many companies. However, when it comes to catalyzing innovation, OKRs can sometimes prove to be more of a straitjacket than a springboard. Here's why: 1️⃣ OKRs can stifle creativity: OKRs are typically tied to specific, measurable outcomes. While this works well for tracking progress, it can limit expansive, generative thinking. In an effort to 'meet targets', teams might be discouraged from exploring bold, disruptive ideas. 2️⃣ OKRs can create a tunnel vision: With a laser focus on the key results, organizations might overlook peripheral opportunities or 'happy accidents' that might have tremendous innovative potential. 3️⃣ OKRs may not adapt quickly: In the ever-changing landscape of innovation, the desired outcome can shift faster than the OKRs do. Rigidity can hamper adaptability, a core trait of any innovative organization. So, if not OKRs, then what? 💡 Enter Innovation Accounting: This is a way of evaluating progress when all the metrics typically used in an established company (like revenues and profits) are effectively zero. It involves creating a balanced scorecard that takes into account not just the financials, but also aspects like customer satisfaction, market validation, and process improvements. 💡 MVP and Iterative Experimentation: Instead of focusing solely on end-goals, the innovation process should be seen as a series of hypotheses that need to be tested. Develop minimum viable products, collect data, and learn. This allows you to adapt and evolve based on real-world feedback. 💡 Pulse Metrics: These are short-term, leading indicators of success that provide insight into whether you're on the right track. They're flexible, quickly adaptable, and keep a finger on the pulse of your innovation efforts. Innovation requires the courage to venture into the unknown and the wisdom to know "failure" isn’t a roadblock, but a stepping-stone. The right measurement framework can provide the freedom to experiment, iterate, and ultimately, innovate. #Innovation #OKRs #InnovationAccounting #MVP #PulseMetrics #BusinessStrategy

Most manufacturing leaders know they need continuous improvement. Few know why it's not working. I see the same pattern repeatedly: companies launch improvement initiatives with energy, but momentum fades within months. The problem? They're missing the systematic approach that makes change stick. Here's the framework that separates sustained improvement from flavor-of-the-month programs: Measure What Matters Most organizations track too much or too little. Focus on the dimensions that drive business performance: Safety, Quality, Delivery, and Cost. The gap between current state and target state tells you exactly where to focus. Go to the Gemba You need to see where work actually flows—where delays cascade, where workarounds become standard practice, where small inefficiencies compound into major losses. Engage the Right Voices Form cross-functional problem-solving teams that include frontline employees and upstream/downstream stakeholders. Facilitate a structured problem solving process. The best solutions come from those closest to the work. Pilot, Measure, Scale Test changes on a limited scale. Measure impact rigorously. Adjust based on data, not opinions. Then, hardwire the improvement into standard work and move to the next opportunity. The difference between companies that cope and companies that transform isn't tools—it's discipline. Continuous improvement becomes a culture when there's both an expectation of excellence and a proven process for achieving it. When done right, it creates ownership, accountability, and measurable results quarter after quarter. If your improvement initiatives aren't delivering sustained results, change the framework. Implement the iterative process that measures, observes, engages, and takes action. #OperationalExcellence #LeanSixSigma #ProcessImprovement #ContinuousImprovement #GrossMargin #BusinessConsulting

🚀 Reflecting on the First 30 Days: Lessons You Can Take From Launching Our Latest MVP At UP.Labs, we launch up to 6 startups a year, and each day is a new learning opportunity on what makes a great MVP. Today, I want to share insights from one of our MVPs, which went from concept to launch in just 3.5 months. After 5 weeks in the market and thousands of dollars in sales (see graph), here's what we've learned: 🎯 Focus on the Problem Worth Solving Identifying a genuinely pressing problem has been our guiding star. It's tempting to tackle multiple issues at once, but we've found that narrowing our focus to one significant problem enhances clarity and product impact. Staying focused makes finding product-market fit easier and more effective. ⏩ Speed of Execution Our team's mantra: "Be the fastest iterating company." Theoretical solutions cannot compare to actual user feedback. Launch as quickly as possible to start learning from real users. 👤 Be Your Own User When launching your product, use it in production and experience its pain points daily. This firsthand use has provided us with clear insights and highlighted real challenges, shaping our iterative process. 📊 Metrics and Feedback A few days spent integrating the right tools for user metrics and feedback have been transformative. This investment has significantly sped up our ability to test, learn, and iterate, leading to faster enhancements and bug fixes. 🛠️ Embrace Manual Processes Our MVP involved several manual tasks. While automation was an option, manually handling these processes provided deep insights and influenced our product development toward being more user-centric. 📈 Data Integrity Data accuracy is paramount—we learned this the hard way. Always double-check and audit your data to ensure a reliable user experience. As we continue on this journey, we remain committed to solving meaningful problems, rapidly iterating based on real-world usage, and refining our approach meticulously. 💡 Key Takeaways: Solve the right problems, launch quickly, monitor rigorously, and iterate relentlessly. I’d love to hear from others navigating their MVP journeys. What have been your biggest lessons in the early days? #StartupJourney #MVP #ProductLaunch #Innovation #TechLeadership #FeedbackLoop

💎 Introducing: The Third Diamond Many innovation consultants reference a “Double Diamond”, but are they missing a third one? A practical way to translate the classic innovation cycle into four “in series” decision steps is: 1. Problem Generation 2. Problem Selection 3. Solution Generation 4. Solution Selection It’s a strong framework to ensure you’re working on problems the business is aligned on resourcing, while steering clear of “solutions in search of a problem” and the classic hammer-looking-for-nails trap. Through leading external open innovation campaigns at ExxonMobil over the years, I learned an important Truth: at large organizations, ideation shouldn’t end after solutons are chosen, and innovation campaigns that fail to yield a viable solution can still add tremendous value. After the Double Diamond concludes, I propose a third divergent phase, which I call the “Third Diamond”, focused on scouting for value in two directions: 1. Scale and transfer: Where else across the organization can validated solutions be applied? Scaling what works is essential to maximize ROI. 2. New growth: How can the technologies and themes uncovered — including those not selected — open new markets or inspire new product offerings? Great ideas for how to solve your problem are not the finish line! Two real (sanitized) examples: • No solutions were implemented at the end of an innovation cycle, yet one showcased technology solved an adjacent problem because a senior leader asked, “Where else might this apply?” • A discovered technology triggered a divergent “new market development” exploration workshop, which led to a multiple potential new product directions. Curious to hear your thoughts on this concept; have you seen it in action?

Everyone wants innovation. Few want the process. We talk to a lot of non-tech businesses trying to “modernize” — and most want to jump straight into AI, automation, dashboards. But real digital transformation happens in phases. And when companies try to skip steps, that’s when things break. Here’s the path we walk clients through at Tynrose: 🔹 Phase 1: Stabilize 1️⃣ Fix the foundation. 2️⃣ Get your systems, documentation, security, and support cleaned up. If the basics aren’t solid, nothing else will scale. 👉 Most leaders get bored here. But skipping it is why things fall apart later. 🔹 Phase 2: Standardize 1️⃣ Build consistency. 2️⃣ Define how things get done — onboarding, communication, workflows, data handling. 👉 New tech won’t fix a broken process. It’ll just expose it faster. 🔹 Phase 3: Strategize 1️⃣ Now you can innovate. 2️⃣ With stability + consistency in place, you’ve earned the right to automate, explore AI, improve experience, and unlock smarter growth. 👉 Innovation built on chaos won’t last. Bottom line: Modernization isn’t a tech project. It’s a business maturity journey. One phase at a time. Stop chasing shiny — and start building strong. #DigitalTransformation #Innovation #BusinessGrowth #Leadership #Tynrose

We launched over 600 AB tests for DTC brands this year alone. Here's my advice for those thinking about ramping up experimentation in 2025: 1. Nail the foundation first. Before you even think about testing, make sure the basics are in place: ↳ What’s your irresistible offer? Why should someone buy from you and not your competitor? Without this, even the best experiments won’t deliver results. ↳ Who’s your most profitable audience? And no, it’s not “everyone.” Narrow it down. Understand their pain points, desires, and behavior. ↳ Make sure your tracking stack is airtight, from GA4 to heatmaps. If you’re flying blind, your tests will crash. 2. Start with high-impact opportunities. We typically begin with the lowest-hanging fruit: ↳ Cart and checkout flow – because small wins here compound fast. ↳ Key product pages – first impressions can make or break conversions. ↳ Post-purchase flows – turn one-time buyers into repeat customers. Think of it as optimizing the “money paths” of your site. 3. Build a testing pipeline. Testing isn’t just about running experiments; it’s about having a system. ↳ Define goals upfront; are you optimizing for revenue, AOV, or CLV? ↳ Prioritize hypotheses by potential impact vs. ease of execution. ↳ Always, always analyze results deeply. If a test wins, dig into why. If it fails, it’s not a loss; it’s data for your next hypothesis. 4. Master iterative learning. Rarely will a single test give you a game-changing insight. It’s the pattern that emerges over 10, 20, or 50 tests that helps you unlock consistent growth. For instance: ↳ A 3% lift on the homepage. ↳ Another 2% from simplified checkout steps. ↳ Then a 7% jump from better upsell placements. These incremental gains compound into exponential growth. Testing isn’t magic; t’s discipline, data, and a relentless drive to improve.

90% of startups don’t fail because of: Bad marketing, a weak team, or even a poor product. They fail because they lack a repeatable decision-making process. Here’s the framework I use to make better, faster decisions in business. I call it “The Iteration Loop.” It’s a structured way to identify what’s working, what’s broken, and what to do next, without getting stuck in endless guesswork. It gives you a systematic way to eliminate bottlenecks, optimize execution, and scale with clarity. Here are the 6 phases: 1. Bottleneck Identification 2. Clarifying the Goal 3. Solution Brainstorming 4. Focused Execution 5. Performance Review 6. Iterate & Improve 1️⃣ Bottleneck Identification Before you can fix anything, you need to identify the real problem. Most entrepreneurs spin their wheels solving the wrong issues because they never dig deep enough. To get clarity, ask: + What's the biggest constraint stopping growth right now? + What metric, if doubled, would create the biggest impact? + What’s preventing us from getting there? If you don’t identify the root problem, every solution you apply will be wasted effort. 2️⃣ Clarifying the Goal Once you know the problem, define the exact outcome you’re solving for. I use a simple Three-Part Goal Formula: 1. What are we trying to achieve? 2. By when? 3. What constraints do we have? Vague goals lead to vague actions. Precision forces progress. 3️⃣ Solution Brainstorming Now, generate every possible solution—without filtering. Most people limit themselves to their existing knowledge, which is why they get stuck. Instead, ask: “If there were no rules, what would I do?” This opens up better, faster, and often simpler solutions you wouldn’t have otherwise considered. 4️⃣ Focused Execution Don’t test everything at once—test one variable at a time. Most teams waste months by making too many changes at once, leading to messy, inconclusive results. Instead, break it down: 1. Test one key assumption. 2. Measure one KPI that proves or disproves it. 3. Execute for a set period, then review. 4. Speed matters. Complexity kills momentum. 5️⃣ Performance Review Your data isn’t just numbers—it’s feedback on your decision-making process. Your job is to analyze: + Did the solution work? + Why or why not? + What does this tell us about our business? Every test refines your ability to make better future decisions. 6️⃣ Iterate & Improve Most companies don’t fail from making the wrong move—they fail from making no moves at all. The only way to win long-term is to keep iterating. Instead of fearing failure, build a culture that rewards learning. Failure + Reflection = Progress. If you aren’t improving your decision-making process, your business will eventually hit a ceiling. That’s why I built The Iteration Loop—so every problem becomes an opportunity for better, faster execution. P.S. If you want the scaling roadmap I used to scale 3 businesses to $100M and beyond, you can get it for free from the link in my profile.

💡Triple Diamond Design Process The "Triple Diamond" process is a process that builds upon the widely known Double Diamond design process. While the Double Diamond focuses on two main phases—problem definition and solution design—the Triple Diamond adds a third phase to add depth and breadth to the design methodology.  This variant of a triple diamond process, crafted by Ted Goas (https://lnkd.in/eJFCR8rF), adds a third diamond for iterative development. It emphasizes iterative cycles, prioritization of user needs, and continuous refinement of the solution throughout the product lifecycle. Quick overview of the 5 key phases of this process: 1️⃣ Discovery (What’s our problem?) This phase focuses on identifying the problem to solve. Goal: Understanding customer pain points & narrowing down insights into actionable focus areas. Activities: ✔ Customer empathy budding: Researching user needs. ✔ Market research: Analyzing market trends. ✔ Competitive analysis: Assessing competition. ✔ Insights prioritization: Organizing findings for strategic focus. ✔ Building product strategy: Setting goals for the product. 2️⃣ Definition (What’s our solution?) This phase focuses on solution ideation & validation. Goal: Generate multiple ideas, structure them and validate the most promising ideas Activities: ✔ Ideation: Brainstorming and generating ideas. ✔ Drafting experience workflow: Mapping out how users will interact with the solution. ✔ Wireframeing: Visualizing the solution. ✔ Initial prototyping: Creating early product models for testing. 3️⃣ Development (Let’s build our solution) This phase is about building, iterating, and refining the product. Goal: Breaking down features and iterating to reduce risks. Activities: ✔ Feature breakdown: Breaking the solution into smaller deliverable tasks. ✔ Iterative build cycle: Continuously building and improving the product. ✔ Collecting research insights: Using feedback to refine features. 4️⃣ Distribution (Initial customer feedback) Focuses on testing the product with users and preparing for the final release. Phases: ✔ Internal release: Early internal testing (alpha and beta testing) ✔ Early access program: Collecting feedback from early adopters. ✔ General (Public) release: Launching the product publicly. 5️⃣ Retro (What did we learn?) Post-release reflection phase to gather insights for future iterations. Using insights collected from feedback, metrics, and retrospective discussions to refine the product. 📕 A Comprehensive guide to product design process https://lnkd.in/eyh4YGy6 #design #designprocess #ux #uxdesign #productdesign #uidesign #ui

This slide gets copied and stolen from me more than any other. It’s the blueprint for saving 4+ years and $4+ million on failed AI initiatives. Start with an iterative PMPV framework to avoid 4 expensive mistakes. Propose – Top-down and bottom-up opportunity discovery workshops. The business articulates its needs vs. being told what should be built. The opportunity is assessed. Does it require AI, or can a less expensive technology work? Measure – AI Product Managers work with stakeholders/customers to define the problem space and assess the opportunity size. They work with the data/AI team to assess feasibility and estimate costs. Prioritize – The 3 assessments allow the business to reach a consensus on a value-based prioritization without being dragged into technical solution complexity. The roadmap is updated. Validate – Did the initiative deliver the expected impact, revenue, margins, etc.? If not, why, and is it salvageable? If it did, can more value be delivered quickly? How much? The roadmap is updated/reprioritized. The roadmap can’t be static. New opportunities emerge, and some opportunities don’t pan out. Businesses need to take a pipeline approach with multiple opportunities on the roadmap. It can’t be opinion-driven or abandoned for every fire drill. Opportunity size estimation is critical, or the loss from constant reprioritization cannot be quantified. Loss allows AI Product Managers to push back. That’s it. Iterative PMPV is a lightweight product strategy framework that supports the unique needs of AI features and products. Remember, frameworks are only as good as the people who manage them. No AI Product Manager == No AI products, revenue, or cost savings…just a giant cost center. #ProductManagement #AIStrategy

Innovation in business transformation emerges when customer needs are carefully researched, opportunities are defined with clarity, and solutions are shaped through ideation, prototyping, and testing until they mature into scalable impact. This approach reflects the essence of design thinking applied to organizations. Researching customer journeys uncovers insights that traditional analysis would overlook. Defining opportunities with precision provides a foundation for creativity, and structured ideation opens the path to solutions that resonate with real needs. Prototyping, with its iterative nature, reduces risk and accelerates learning. When these phases converge into a launch, the focus shifts to scaling with an MVP approach. This balance of experimentation and delivery allows companies to adapt with agility, ensuring that improvement is continuous and grounded in evidence. Such a method creates solutions while fostering a culture of listening, iteration, and measurable value creation. It raises an important question for every leader: how prepared is the organization to truly integrate this mindset into its daily processes? #DesignThinking #CustomerJourney #BusinessTransformation #Innovation #Leadership