Creating A Scalable Framework For Idea Implementation

The healthcare landscape is filled with brilliant insights and promising pilots that never scale. As human-centered designers, we excel at uncovering needs and creating compelling solutions—yet implementation remains our greatest challenge. Transforming promising pilots into widespread practices represents a profound opportunity to shape healthcare's future. When innovative approaches successfully scale, they create ripple effects—enhancing patient experiences, improving outcomes, and often reducing burden on care teams. Our opportunity lies in developing implementation approaches as thoughtful as our initial designs. Institutional inertia often presents the first major hurdle. Overcome this by starting with targeted 8-week interventions that demonstrate immediate value. Identify informal leaders who shape culture—the veteran nurse or respected physician whose opinions influence others. Create visual artifacts that make pain points undeniable and build emotional connection to the need for change. Regulatory concerns require thoughtful navigation. Invite compliance partners into design sessions from day one, giving them ownership in finding solutions. Distinguish between actual requirements and accumulated practices—you'll often find more flexibility than assumed. Consider modular implementation where less-regulated components can advance first. Address the human element of implementation. Design changes that reduce workload in visible ways—for every new step added, eliminate two. Create a "change budget" that acknowledges the cognitive costs and limits concurrent initiatives. Develop frontline champions who receive dedicated time for implementation support. For measurement challenges, create simple dashboards that include both traditional and experience measures. Develop visual data stories showing impact through multiple perspectives to build a compelling case. Establish 30-day feedback cycles where users shape refinements. When moving from pilot to scale, build solutions with a stable core and flexible edges that adapt to different contexts. Document "implementation recipes" with specific steps and resource requirements. Connect implementation teams across sites to share adaptations and solutions. By addressing these barriers with practical strategies, we can accelerate human-centered innovation in healthcare—moving from isolated bright spots to transformative change at scale.

I’ve been a huge fan of Tom Fishburne for years since we were classmates at Harvard Business School. Tom started drawing cartoons on the backs of HBS business cases, which evolve to become his famous and insightful Sky Deck cartoons.  I was always on the lookout for them. I invite my connections across all industries to subscribe to Tom’s insightful newsletter. Last week’s issue particularly resonated with me. Tom highlighted that labeling an idea as polarizing can quickly kill it, as businesses usually avoid such ideas in favor of safer, more universally appealing ones. However, there’s power in polarization. Trying to appeal to everyone often results in appealing to no one. In a cluttered world, the last thing a company can afford is to create indifference. Several years ago, I was helping the innovation group of a large carrier and saw firsthand the graveyard of idea killers. Many innovative ideas, often originating from those in the field who directly experience pain points, did not make it past the first round of evaluation. To help this carrier effectively evaluate innovative ideas and develop a repeatable process, we implemented a few key strategies: 1. Idea Champion Program: We assigned champions to promising ideas to advocate for them, gather feedback, and iterate on the concepts. 2. Cross-Functional Evaluation Committees: We created committees with members from various departments to ensure diverse perspectives in idea evaluation. 3. Fail Fast, Learn Faster: We encouraged a culture where failure is acceptable as long as we learn from it quickly. Prototyping and piloting ideas in controlled environments helped us make informed decisions. 4. Customer-Centric Approach: We focused on ideas that directly addressed customer/staff pain points, involving these stakeholders early in the development process. 5. Regular Review Cycles: We established regular review cycles for all submitted ideas to ensure they received proper attention. By implementing these strategies, we helped the carrier create an environment where innovative ideas could thrive. This process not only brought new solutions to the market but also fostered a culture of creativity and continuous improvement. Remember, the goal is not to avoid polarization but to harness it. Great ideas often provoke strong reactions, and that’s where their power lies. By creating a structured process to evaluate and nurture these ideas, we can ensure that they have the opportunity to make a significant impact. https://lnkd.in/eWfV_a-t

Planning something new? Clients of the Umbrex Innovation Practice asked us to compile a set of tools, frameworks, and templates needed to drive innovation from ideation to execution. The result is the Corporative Innovation Playbook. Whether you’re launching a centralized innovation hub, deploying design thinking at scale, or building an ecosystem of startup partners, this guide provides a comprehensive, step-by-step roadmap. Learn how to structure innovation governance, fund portfolios, build capabilities, and scale impactful initiatives—while avoiding common pitfalls and aligning with enterprise strategy. Table of Contents: Chapter 1. Foundation and Context 1.1 Purpose and Scope of the Playbook 1.2 Definitions and Taxonomy of Innovation Types 1.3 The Innovation Imperative in Corporations 1.4 Common Barriers to Innovation 1.5 Quick‑Start Assessment Checklist Chapter 2. Innovation Strategy and Governance 2.1 Aligning Innovation with Corporate Strategy 2.2 Setting Innovation Ambition and Goals 2.3 Governance Structures and Decision Rights 2.4 Strategy Development Step‑by‑Step Guide 2.5 Governance Charter Template 2.6 Executive Steering Committee Checklist Chapter 3. Portfolio Management and Funding 3.1 Portfolio Segmentation Framework (Core, Adjacent, Transformational) 3.2 Stage‑Gate vs. Venture Portfolio Approaches 3.3 Funding Models and Budget Allocation Methods 3.4 Portfolio Management Step‑by‑Step Guide 3.5 Investment Committee Checklist 3.6 Portfolio Dashboard Template Chapter 4. Culture and Leadership 4.1 Attributes of an Innovative Culture 4.2 Leadership Behaviors that Enable Innovation 4.3 Incentives and Recognition Systems 4.4 Culture Diagnostic Checklist 4.5 Leadership Activation Step‑by‑Step Guide Chapter 5 . Innovation Operating Model 5.1 Organizing for Innovation: Centralized, Hub‑and‑Spoke, Dual 5.2 Roles and Responsibilities Matrix 5.3 Process Governance and Stage Definitions 5.4 Operating Model Design Step‑by‑Step Guide 5.5 RACI Template Chapter 6. Ideation and Opportunity Discovery [abridged due to character limit] Chapter 7. Concept Development and Validation Chapter 8. Incubation and Experimentation Chapter 9. Acceleration and Scaling Chapter 10. Open Innovation and Ecosystem Partnerships Chapter 11. Corporate Venture Capital and M&A for Innovation Chapter 12. Technology and Digital Innovation Chapter 13. Metrics, KPIs, and Performance Management Chapter 14. Risk, Compliance, and Intellectual Property Chapter 15. Talent, Skills, and Capability Building Chapter 16. Infrastructure, Tools, and Platforms Chapter 17 . Communication, Change Management, and Stakeholder Engagement Chapter 18. Continuous Improvement and Innovation Maturity Chapter 19. Implementation Roadmaps and Templates

We scaled our client's creator program 10x while reducing management costs by 62%. Here's the counterintuitive approach that made it possible. Many companies struggle to scale their creator programs efficiently. Overhiring internally and increasing costs. Or. Downsizing and lacking specialized resources. The secret? Hire an experienced agency and leverage a scalable system and the right tech stack. Here's the framework we used to go from 10 to 1.7k+ creators in 12 mo: 1. Standardize onboarding: Create a frictionless opt-in process 2. Automate communication: Use tools to schedule regular check-ins and updates, reducing manual outreach 3. Implement tiered support: Offer different incentive levels based on creator performance and needs 4. Develop a knowledge base: Build a comprehensive resource center for creators to find answers on their own 5. Leverage peer-to-peer support: Foster a community where experienced creators can help newcomers 6. Use program data: Implement analytics to identify top performers and optimize resource allocation 7. Streamline content review: Create clear briefing guidelines and use social-listening AI-assisted tools to speed up the monitoring process The right tools make this system possible. Here's the tech stack we used: - Creator discovery via Meta, TikTok & YouTube APIs - Creator management platform(s) - Automated email sequences - Community management software - Analytics dashboard via AirTable - AI-powered social listening - Knowledge base software - Task management system By implementing this framework and leveraging these tools, we're able to manage 1.7k+ creators with a team of 5 - Account director - Creative strategist - Community manager - Recruitment coordinator - Marketing ops & email coordinator The impact? Millions of monthly impressions and mid-six to seven figures in tracked sales (every month). If you're hitting a wall with your creator program, it's time to rethink your approach. Scale smarter, not harder.

𝗠𝗼𝘀𝘁 𝗔𝗜 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀 𝗳𝗮𝗶𝗹 𝗻𝗼𝘁 𝗶𝗻 𝘁𝗵𝗲 𝗺𝗼𝗱𝗲𝗹, 𝗯𝘂𝘁 𝗶𝗻 𝘁𝗵𝗲 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻. Having worked across AI consulting, enterprise systems, and startups, I’ve built a repeatable framework to get AI projects from idea → impact. 𝗛𝗲𝗿𝗲’𝘀 𝗺𝘆 5-𝘀𝘁𝗲𝗽 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵: 1️⃣ 𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺, 𝗻𝗼𝘁 𝘁𝗵𝗲 𝘁𝗲𝗰𝗵 Get crystal clear on the business pain or opportunity. What KPI will you move? If it’s not measurable, don’t start yet. 2️⃣ 𝗣𝗿𝗼𝘁𝗼𝘁𝘆𝗽𝗲 𝗳𝗮𝘀𝘁, 𝗳𝗮𝗶𝗹 𝗲𝗮𝗿𝗹𝘆 Test small. Ship early. Avoid spending 6 months on the “perfect” model before knowing if anyone cares. 3️⃣ 𝗜𝗻𝘃𝗼𝗹𝘃𝗲 𝘁𝗵𝗲 𝗲𝗻𝗱-𝘂𝘀𝗲𝗿 Bring in the humans. Talk to the people who will use, trust, or be affected by the AI. Their feedback is gold. 4️⃣ 𝗣𝗹𝗮𝗻 𝗳𝗼𝗿 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 𝗳𝗿𝗼𝗺 𝗗𝗮𝘆 1 Build with ops and infra in mind — how will you monitor, retrain, rollback? If it’s not reliable, it’s not production-ready. 5️⃣ 𝗧𝗿𝗮𝗶𝗻 𝘁𝗵𝗲 𝘁𝗲𝗮𝗺, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝘁𝗵𝗲 𝘀𝘆𝘀𝘁𝗲𝗺 No AI system runs well without people who understand it. Documentation, onboarding, and stakeholder buy-in matter just as much as your code. If you’re leading or advising on AI products, feel free to borrow this framework — or drop me a message if you want to walk through it in more detail. #AIExecution #MLStrategy #ScalableAI #TechPlaybooks #DigitalProducts