1-Readiness

Ideas Aren't Enough. Is Your Company Ready For Innovation?

Why 95% of Innovation Fails—And How AI Changes Everything

After 25 years of helping Fortune 500 companies turn rough ideas into breakthrough innovations, I've learned that the problem isn't what most leaders think it is.

We're at another innovation inflection point—but most companies aren't ready for it.

For decades, we've chased the next framework promising to crack the innovation code. In the 1960s, it was about systems and scientific revolutions. The 1980s brought strategy and branding to the forefront. By the 2000s, companies were chasing disruption with frameworks like Lean Startup, Blue Ocean Strategy, and Jobs to Be Done. Each decade, new conditions emerged, creating fresh opportunities and challenges for innovators.

Now AI has fundamentally changed the game. The cost of creativity has collapsed. The speed of iteration has exploded. Large language models and autonomous agents aren't just making us build faster—they're augmenting human thinking and generating ideas at unprecedented scale.

But here's what 25 years of helping some of the world's largest companies has taught me: the bottleneck isn't the tools anymore. It's organizational readiness.

And here's the uncomfortable truth that most leaders miss: They are all bad ideas. At first.

The Innovation Reality Check: Why Most Companies Fail Before They Start

Before you brainstorm your next big idea or build another MVP, ask yourself one critical question: Is your organization actually prepared for innovation?

The statistics are sobering. Research consistently shows that 95% of new products fail to meet expectations. Yet companies continue throwing ideas at the wall, hoping something sticks. They reward predictability over exploration, punish failure instead of learning from it, and wonder why breakthrough innovation eludes them.

The problem isn't a lack of creativity or good intentions. It's that most organizations aren't structurally, culturally, or strategically aligned for innovation success. True innovation readiness requires alignment across three critical dimensions: culture, structure, and leadership. It demands people who thrive in ambiguity, systems that reward learning over certainty, and teams built to move across silos rather than get stuck inside them.

And now, it requires something entirely new: AI readiness.

Innovation today isn't just about who's in the room—it's about which tools are at the table and how fluently your team can work with them. Organizations that ignore this shift aren't preserving the status quo; they're falling behind at an accelerating pace.

The Foundation Problem: Assessing Whether You're Actually Ready

Innovation is inherently messy, nonlinear, and iterative. Jumping into it without first assessing your organization's readiness is like setting sail in a leaky boat with no weather forecast. Yet this is exactly what most companies do—they skip the foundation work and wonder why their innovation initiatives collapse under pressure.

One of the most enduring and practical tools for evaluating innovation readiness is the McKinsey 7S Framework, developed in the 1970s. This model breaks your organization into seven interdependent parts, each critical for innovation success:

Strategy: Do you have a clear strategic focus that actually supports innovation, or are you just paying lip service to it?
Structure: Is your organizational chart rigid and bureaucratic, or flexible enough for fast experimentation and cross-functional collaboration?
Systems: Are your internal processes built for compliance and control, or for iteration and learning?
Shared Values: Does your culture genuinely reward intelligent risk-taking, or does it punish any deviation from the proven path?
Style: Do your leaders model innovation behaviors through their actions, or do they manage exclusively to maintain the status quo?
Staff: Do you have people with the right mindsets—not just the right titles—to drive innovation forward?
Skills: Can your team actually execute on the innovation you're dreaming of, or are there critical capability gaps?

This isn't about achieving perfection across all seven dimensions—it's about alignment. These levers don't operate independently. If your strategy is bold but your systems are bureaucratic and your shared values favor risk aversion, you'll never achieve lift-off. The framework forces you to confront the hard truth: innovation isn't just about having good ideas; it's about building an organization capable of making those ideas real.

The Skepticism Problem

Not all companies are ready for innovation, and often their historical experiences have made them deeply skeptical about innovation approaches. As innovation researchers Govindarajan and Trimble describe, many executives harbor deep skepticism toward innovation teams: "What is this so-called innovation team going to do? Brainstorm? Sit around being creative all day? All this while the rest of us get the real work done?"

Without cultural preparation, innovation teams will be resented, underfunded, and ultimately ineffective. Before launching any initiative, organizations must ask the hard questions: Are senior leaders truly aligned—not just in words but in actual resourcing decisions? Do staff have the bandwidth and psychological safety to take meaningful risks? Does the organization know how to collaborate across traditional silos? Is failure treated as a learning opportunity or a career-ending misstep?

Ignoring these questions is like ignoring cracks in a foundation. Whatever you build will eventually collapse, no matter how brilliant the initial concept.

AI: The New Baseline for Innovation Readiness

Innovation readiness is no longer just about structure, culture, and leadership. As of now, it's also about AI readiness. Any organization claiming to be serious about innovation must have a clear perspective on how it will leverage AI—because AI is no longer optional infrastructure. It's the new baseline.

AI tools, large language models, and autonomous agents are transforming the innovation landscape in ways that go far beyond simple automation. They're not just faster calculators or better dashboards. They're becoming co-pilots, collaborators, and in some cases, autonomous problem solvers. Organizations that ignore this shift are not preserving the status quo—they're falling behind at an accelerating pace.

AI as a Core Team Member

Every cross-functional innovation team should now include AI as a default member. Whether it's a prompt-based LLM like ChatGPT, a no-code agent builder, or an analytics engine trained on real-time customer data, AI belongs in the room from day one. More importantly, the humans on the team must develop fluency in working with AI. This means mastering skills like effective prompting, critically reviewing AI outputs, stress-testing AI-generated assumptions, and refining AI-generated work.

This isn't about replacing human creativity—it's about amplifying it. AI can help teams break out of their own biases and limited frames of reference. It can explore radical directions, reframe problems, and propose pathways that wouldn't have emerged from traditional groupthink. In this way, AI acts less like an assistant and more like a provocateur, challenging teams to think bigger and faster.

Supercharging Feedback Loops

AI also fundamentally accelerates the feedback loops that innovation depends on. Iterative innovation requires the ability to take in customer data, market signals, and usage insights and adjust quickly. AI-enabled systems can scan massive inputs, summarize patterns, and generate testable responses in a fraction of the time it would take human teams to analyze and brainstorm.

More importantly, AI agents can actually execute some tests—running A/B campaigns, generating copy variations, conducting live pricing experiments—without waiting on manual workflows. This kind of speed isn't just a convenience; it's a competitive advantage that compounds over time.

Democratizing Innovation

Perhaps most significantly, AI makes innovation more accessible across the organization. Through no-code tools and intuitive interfaces, more people can contribute to the innovation process—not just product managers, strategists, or R&D teams. With proper guardrails and thoughtful design, AI can democratize creativity and expand the pool of potential innovators within any company.

But there's a critical caveat: Every innovation system that includes AI must also include a robust system for ethical use. This means defining clear governance principles around transparency, data handling, fairness, and accountability—especially when AI is customer-facing or impacts employees. Innovation built on irresponsible AI will eventually fail, whether ethically, reputationally, or operationally.

Organizations must now define their innovation technology stack as deliberately as they define their business strategy. That stack should include platforms for collaboration, insight generation, and concept testing—and yes, AI must be designed into the process from the beginning, not bolted on as an afterthought.

The Innovation Multiplier: Why Agentic Leaders Change Everything

Innovation lives and dies through people—specifically, those with what I call an "agentic mindset." These are the entrepreneurs and intrapreneurs who take initiative, embrace ambiguity, and make things happen without needing perfect clarity or explicit permission.

Agentic individuals are defined by their proactive approach to challenges. They don't wait to be told what to do; they take ownership of outcomes. Research shows that these individuals exhibit higher self-efficacy, embrace ambiguity as opportunity rather than threat, and challenge the status quo when others hesitate. They're indispensable to innovation because they act before consensus forms, drive momentum across organizational silos, and persist through the inevitable uncertainty that innovation demands.

The Profit Paradox

Here's where agentic leaders become truly valuable: they're willing to take the bigger bets that organizations often refuse to pursue. Research by George Day reveals a striking paradox in innovation investment. While 85% to 90% of innovations are minor or sustaining improvements—the safe, incremental changes that feel comfortable—just 15% of launches are seen as substantial or disruptive. Yet this small percentage of bold innovations generates 61% of total innovation-related profits.

Think about that for a moment. The vast majority of innovation effort goes toward safe, incremental improvements that generate a minority of the value. Meanwhile, the transformational innovations that drive the majority of profits receive a fraction of the attention and resources.

Organizations systematically overinvest in the safe middle and under-resource the ideas with true transformational potential. This isn't because leaders don't understand the math—it's because they don't have enough agentic leaders willing and able to champion the higher-risk, higher-reward opportunities.

Identifying and Empowering the Right People

The challenge is that agentic leaders often don't look like traditional high performers. They may not excel in the core business operations that most performance reviews measure. They thrive in uncertainty, which can make them seem unfocused or difficult to manage. They ask uncomfortable questions and challenge established processes, which can create friction with teams optimized for efficiency.

But these are exactly the qualities that innovation demands. To win at innovation, organizations must identify and empower these individuals—not just those who perform well in stable, predictable environments, but those who thrive when the path forward is unclear.

This means creating pathways where agentic leaders can drive innovation forward, even when they fail along the way. It means protecting them from the hazards of short-term metrics that punish experimentation. It means giving them autonomy to move quickly and make decisions without endless committee approvals.

Most importantly, it means recognizing that these individuals are force multipliers. One agentic leader can transform an entire team's approach to innovation, shifting the culture from risk-averse to opportunity-focused, from consensus-driven to action-oriented.

Breaking Down Silos: The Structural Imperative

Innovation ignores organizational boundaries, yet most companies are built around them. Marketing, R&D, finance, operations, market research—each function is typically optimized for efficiency within its own domain, not for collaboration across domains. This creates a fundamental mismatch between how organizations are structured and how innovation actually works.

Innovation is interdisciplinary by nature. Bringing new ideas to life requires capabilities that no single function owns. A breakthrough product might need insights from customer research, technical feasibility analysis from engineering, market positioning from marketing, financial modeling from finance, and operational planning from supply chain—all working in concert, not in sequence.

The Cross-Functional Imperative

Without cross-functional teams empowered to move at innovation speed, organizations end up with what I call "innovation theater"—lots of activity that looks like progress but lacks real execution capability. Ideas get trapped in endless PowerPoint presentations or prototype limbo because teams aren't empowered to make decisions, incentives aren't aligned across functions, or leadership loses interest after the initial kickoff.

Innovation theater happens when organizations create the trappings of innovation—labs, brainstorming sessions, pilot projects—without the structural or cultural support to execute. It looks impressive in quarterly reviews but produces no meaningful business impact.

Effective cross-functional innovation teams need formal charters that clearly define their authority and responsibilities. They need visible support from senior leadership, not just budget approval but active sponsorship. Most importantly, they need the authority to move at a different pace than the core business, with different success metrics and different tolerance for uncertainty.

The Psychological Safety Foundation

Perhaps most critically, these teams must operate with high psychological safety. Peter Drucker famously stated that most innovations result not from genius but from a purposeful search for opportunity. But that search can only happen in a culture where people feel safe to ask questions, share rough ideas, and admit what they don't know.

Amy Edmondson defines psychological safety as the belief that one won't be punished or humiliated for speaking up with ideas, questions, concerns, or mistakes. In psychologically safe environments, teams can ask the catalytic questions that spark transformation: "What would have to be true for this to work?" "Why do we assume our customer wants that?" "What if we're completely wrong about this assumption?"

Without that safety, teams conform to existing thinking. They protect their reputations by avoiding controversial ideas. They stay quiet rather than risk making noise. And innovation dies quietly in boardrooms full of polite agreement.

Google's Project Aristotle revealed the critical importance of psychological safety in determining team success. Teams with high psychological safety were 27% more likely to report strong innovation performance and 76% more likely to report high engagement scores. This research demonstrates that team dynamics and senior management support are as important—if not more important—than individual talent or technical capabilities.

Learning from Academic Traditions

Interestingly, some of the world's most innovative institutions have long understood the value of cross-disciplinary interaction. Universities like Cambridge and Oxford have structured their formal dining traditions specifically to encourage interactions among individuals from varied academic backgrounds. Cambridge's formal dinners and Oxford's High Table traditions are designed to seat guests from different fields together, fostering conversations that can lead to novel insights and unexpected collaborations.

These traditions underscore a principle that modern organizations can emulate: innovation thrives at the intersection of diverse disciplines and perspectives. Creating structured opportunities for these intersections isn't just nice to have—it's essential for breakthrough thinking.

Leadership Must Model the Change: Lessons from the Trenches

According to Prosci research, the number one predictor of successful change initiatives is visible and active executive sponsorship. Innovation is no exception. Leaders must do more than approve budgets and attend kickoff meetings—they must demonstrate genuine commitment through their actions, decisions, and daily behaviors.

This means showing up consistently, asking thoughtful questions, celebrating learning even when results disappoint, and protecting innovation teams when early experiments don't meet expectations. It means making the hard resource allocation decisions that signal innovation is truly a priority, not just a nice-to-have initiative.

A Personal Case Study: Building Upsiide

At Dig Insights, one of our biggest leadership challenges wasn't building new technology—it was bringing our own team along for the transformation. In the early days of developing Upsiide, our SaaS platform, we had no formal product manager and only a small base of external users. So we made a bold decision: we would turn our consulting team into our primary user group.

Internally, this meant asking employees to adopt new tools, develop new skills, and fundamentally reimagine their roles—not an easy ask in an industry where many saw DIY platforms as a direct threat to full-service research work.

There was quiet resistance. Some team members worried that the SaaS model was cannibalizing our traditional business. Others simply didn't have time to beta test an evolving tool while managing client deliverables. The skepticism was understandable but potentially fatal to our innovation efforts.

As a leadership team, we didn't just ask for buy-in—we actively demonstrated the path forward. We tracked client usage data and showed that companies using Upsiide licenses often increased their spend on full-service work rather than reducing it. We built systematic feedback loops, invited staff into the product development process, and consistently reframed platform adoption as a strategic advantage for their careers and the firm's future—not a risk to their roles.

Over time, the mindset shifted. Upsiide use expanded internally. Employees became advocates rather than skeptics. That internal engagement helped expose the platform to a wider base of our consulting clients, creating a virtuous cycle of adoption and improvement.

The lesson was clear: transformation doesn't happen through top-down directives or inspiring presentations. It requires active, visible leadership and a willingness to prove the value of innovation not just to the business, but to the people within it.

The Persistence Imperative

Building Upsiide wasn't a one-time decision—it was a multi-year commitment that tested every definition of persistence. Unlike our well-funded competitors who could outspend us on marketing alone, we bootstrapped the platform entirely, reinvesting our profits year after year to turn a good idea into a great product.

It wasn't easy. We felt constant pressure—internally and externally—to cut losses or scale back our ambitions. But we stayed the course by tracking progress obsessively, listening to our users, and validating that we were building something genuinely different—something more intuitive, more agile, and more actionable than existing alternatives.

We reminded ourselves and our team that the real risk wasn't in pressing forward—it was in standing still while the industry transformed around us. Over time, Upsiide grew into a globally adopted platform used by clients like Coca-Cola and Pernod Ricard.

But the real win wasn't just product success—it was organizational evolution. We didn't just pivot the platform; we had to pivot the entire company. We shifted how we worked, how we sold, and how we thought about our value proposition. We embraced an entirely new way of doing business.

The experience taught us that innovation doesn't need a perfect plan—it needs persistence. And persistence doesn't mean staying rigid in your approach. It means staying committed to the vision while constantly adapting your tactics based on what you learn.

Aligning Incentives with Innovation

You get what you reward, and most companies reward optimization rather than exploration. If your compensation and promotion systems are designed exclusively around hitting predictable targets, don't be surprised when no one takes meaningful risks.

To support genuine risk-taking and learning, organizations need to set outcome-based objectives that reflect progress, not just perfection. This might mean tracking the number of experiments run, the percentage of learnings incorporated into future iterations, or the speed with which teams can pivot when assumptions prove wrong.

The goal isn't to eliminate accountability—it's to reward teams for intelligently de-risking ideas and learning quickly, not just for commercial wins that may take years to materialize.

The Myth of the Perfect Idea: Why "Bad" Ideas Are Actually Good

Here's the counterintuitive truth that most leaders miss: They are all bad ideas. At first.

The myth of the lone genius with the perfect, fully-formed idea is not just wrong—it's actively harmful to innovation efforts. This mythology creates unrealistic expectations, paralyzes teams who wait for the "perfect" concept, and leads organizations to abandon promising ideas too quickly when they don't immediately show perfection.

The reality is that most breakthrough innovations start flawed, incomplete, or even seemingly misguided. What transforms them into market successes isn't the brilliance of the initial concept—it's the quality of the process that refines, tests, and iterates on that concept until it becomes something people actually want and businesses can successfully deliver.

Innovation is fundamentally about transformation—taking rough, half-baked ideas and putting them through a rigorous process of refinement, testing, and iteration until they become market-ready breakthroughs. This process isn't about inspiration; it's about execution.

The most successful innovations emerge from systematic approaches that combine human creativity with disciplined methodology. This means using foresight and market analysis to identify real problems worth solving. It means generating ideas through proven frameworks rather than hoping for lightning strikes of genius. It means rapidly filtering concepts based on consumer interest, feasibility, and strategic fit rather than falling in love with the first interesting idea.

Most importantly, it means building realistic prototypes and testing them with real users, then iterating based on what you learn rather than what you hoped would be true.

From Gut Feel to Data-Informed Decisions

The old model of innovation relied heavily on gut instinct and executive intuition. While these remain important, they're no longer sufficient in a world where customer preferences shift rapidly, competitive landscapes evolve constantly, and the cost of being wrong has increased dramatically.

Modern innovation requires data-informed decision making at every stage. This doesn't mean eliminating creativity or intuition—it means augmenting human judgment with systematic feedback from the market, customers, and users.

The goal is to reduce risk while increasing speed-to-market, replacing pure gut-feel innovation with approaches that combine human insight with empirical validation. This systematic approach allows teams to fail fast and cheap rather than slow and expensive, learning their way to breakthrough innovations rather than hoping to stumble upon them.

The Learning Mindset

Perhaps most importantly, successful innovation requires embracing a learning mindset rather than a knowing mindset. Teams that approach innovation with the assumption that they already know what customers want, how the market will respond, or what features matter most are setting themselves up for expensive failures.

Instead, the most successful innovators approach each project with genuine curiosity about what they might discover. They design experiments to test their assumptions rather than confirm their biases. They celebrate learning as much as they celebrate success, understanding that each "failed" experiment brings them closer to a breakthrough.

This mindset shift—from knowing to learning—is perhaps the most fundamental change organizations need to make to succeed at innovation in the modern era.

The Path Forward: Building Innovation Capability

Innovation is hard, and it fails more often than it succeeds. The statistics make that brutally clear. Most ideas don't work. Most products don't survive their first year in market. Most innovation initiatives fail to generate meaningful business impact.

But the companies that succeed at innovation don't win because they're lucky or unusually brilliant. They win because they're prepared. They've built the organizational foundation that allows innovation to thrive rather than hoping that good ideas will somehow overcome structural barriers.

The Integration Challenge

The challenge for most organizations isn't generating ideas—it's integrating all the elements necessary for innovation success. This means aligning culture, structure, and leadership around innovation goals. It means identifying and empowering agentic leaders who can drive change through uncertainty. It means building cross-functional teams with the psychological safety to take intelligent risks.

It also means embracing AI not as a threat to human creativity but as an amplifier of it. Organizations that successfully integrate AI into their innovation processes will have significant advantages in speed, scale, and creative range over those that don't.

Most importantly, it means accepting that innovation is a systematic capability that can be built and improved, not a mysterious process that depends on random flashes of genius.

The Burning Platform

For many industries, AI represents what strategists call a "burning platform"—a situation where the cost of staying the same exceeds the cost of changing. AI is reshaping customer expectations, collapsing traditional timelines, lowering barriers to entry, and rewriting job definitions across industries.

Companies that delay engagement with AI aren't staying safe—they're falling behind at an accelerating pace. AI is not just a tool; it's a change agent that organizations must build around rather than bolt onto existing processes.

What This Means for You

If you're a leader tasked with "making innovation happen" in your organization, start with an honest assessment of your readiness. Don't just ask whether you have good ideas—ask whether you're built to make ideas real.

Look for the agentic leaders in your organization—the people who take initiative, embrace ambiguity, and push through uncertainty. These individuals are often underrecognized in traditional performance systems, but they're essential for innovation success.

Build cross-functional teams with real authority to move quickly and make decisions. Create psychological safety where people can share rough ideas, ask uncomfortable questions, and admit what they don't know.

Most importantly, align your incentives with the behaviors innovation actually requires. If you reward only predictable outcomes, you'll never get breakthrough innovations.

The Question That Matters

Here's the question I want to leave you with: What "bad idea" are you sitting on right now that could change everything—if your organization was ready for it?

That rough concept you've been hesitant to share. That unconventional approach you think might work but aren't sure how to test. That ambitious vision that seems too risky for the current environment.

The idea itself isn't the limiting factor. The limiting factor is whether your organization has built the capability to take that idea and systematically transform it into something remarkable.

Innovation doesn't begin with perfect ideas. It begins with the conditions that let imperfect ones grow into breakthroughs. The companies that understand this—and act on it—will be the ones that thrive in the AI-enhanced future we're all entering.