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Innovation Isn't Broken. The System Around It Is.

5 min read

Published on February 25, 2026

Solutions: Technology & Innovation
Innovation Isn't Broken. The System Around It Is.
This insight is shared by Lotus Child, Director of Digital Experience at JAKALA, France, UK, Nordics.

Most large enterprises today are running more innovation activity than ever before — more ideas, more pilots, more initiatives, and bigger budgets to fund them. Yet confidence in innovation outcomes is falling. According to McKinsey, 84% of executives believe innovation is critical to their success, but only 6% are satisfied with their innovation performance.That's not a creativity problem. That is a system failure.

The gap is not between ambition and imagination. It is between the moment an idea enters an organization and the moment it becomes something real — if that moment ever arrives. Innovation doesn't break at the point of creation. It breaks inside the systems meant to evaluate, prioritize, and scale it.

84% of executives believe innovation is critical to their success. Only 6% are satisfied with their innovation performance. That's not a creativity problem. That is a system failure.

Why More Ideas Isn't the Problem

It might seem counterintuitive, but most large organizations don't suffer from a lack of innovation ideas; they suffer from an excess of them. Across functions and regions, initiatives pile up: pilots, proofs of concept, transformation projects, campaigns, platforms, and experiments, each competing for attention, funding, and executive sponsorship.

The result is not a shortage of creativity, but a growing inability to distinguish what truly matters from what merely exists. Innovation portfolios expand faster than leadership's ability to make clear, confident decisions. In complex enterprises, innovation rarely fails because nothing is being proposed. It fails because too many things are, and the system has no reliable way to decide what deserves to move forward.

Where Innovation Actually Breaks Down

When innovation stalls, the instinct is often to look upstream, toward ideation, creativity, or talent. In reality, most innovation fails downstream, in the less visible parts of the organization. Evaluation frameworks vary by function. Prioritization criteria shift depending on who is in the room. Governance processes optimize for consensus rather than clarity. Decisions take months, sometimes quarters, and by the time they arrive, the context has already changed.

Innovation doesn't die because ideas are weak. It dies because the system surrounding those ideas was never designed for uncertainty at scale. What works for predictable, operational work rarely works for exploratory initiatives, yet many organizations try to govern both in the same way.

The Hidden Cost of Broken Innovation Systems

The cost of this dysfunction is rarely visible on a balance sheet, but it is measurable, and the numbers are striking. We spoke with one large enterprise managing 500 innovation initiatives annually. The evaluation process alone consumed over 23,500 hours of human effort — the equivalent of eleven full-time employees whose entire working year is spent reviewing ideas, most of which will never move forward. The fully-loaded cost: approximately $4.2 million, just in evaluation overhead.

That is before accounting for the zombie project problem. According to Forrester, 20% of the average enterprise innovation portfolio consists of initiatives that should have been terminated but weren't, kept alive by organizational inertia, unclear kill criteria, or the absence of anyone with clear authority to stop them. These zombie projects don't just waste resources. They crowd out the initiatives that deserve investment, starving promising work of the funding and attention it needs to scale.

20% of the average enterprise innovation portfolio consists of zombie projects. Freeing those resources can fund two years of more strategic innovation activities.

The result is a quiet but persistent innovation tax, paid in time, attention, and opportunity, that compounds as organizations scale. Over time, this tax erodes leadership confidence in innovation portfolios, makes investment decisions harder rather than easier, and quietly drains the organization's ability to act when genuinely strategic opportunities emerge.

Why Familiar Fixes Keep Falling Short

The usual responses are predictable. Organizations deploy idea platforms to capture more input, which increases volume without improving the quality of decisions made about that volume. They launch innovation labs to protect experimentation from the core business, which isolates risk effectively but also isolates the learning, ensuring it rarely crosses back into the organization in any systematic way. Or they commission consulting engagements to redesign processes and frameworks, which often stop at diagnosis, handing detailed recommendations back to the same structural conditions that produced the problem in the first place.

Each of these responses is rational, and each addresses a real need. The problem is that none of them are designed to operate as a system. They optimize one part of the innovation process while leaving the surrounding conditions unchanged. The result is sustained activity but limited momentum: innovation that remains busy rather than scalable.

AI Is Exposing the Cracks, Not Fixing Them

None of this is lost on the AI conversation. Enterprise investment in generative AI reached $13.8 billion in 2024, a sixfold increase in a single year. Yet despite this surge, only 8% of organizations report applying AI at scale within their innovation processes. The gap between investment and impact is growing, not shrinking.

The reason is structural. AI is often positioned as the breakthrough that will finally fix enterprise innovation, generating better ideas, faster insights, and smarter recommendations. In practice, AI accelerates whatever system it is embedded in. When that system lacks clear decision criteria, shared context, and accountability structures, AI doesn't create clarity. It creates volume: more ideas, more analysis, more options, and more noise, without a corresponding improvement in the quality of decisions being made. Organizations don't become more innovative. They become more overwhelmed.

Most AI adoption strategies miss this. The bottleneck was never the speed of idea generation — it was always the system's capacity to absorb uncertainty and turn intent into action.

AI accelerates whatever system it is embedded in. If that system lacks clear decision criteria and accountability, AI doesn't create clarity. It creates volume.

Final thoughts

The Question Leaders Should Be Asking

Innovation in large organizations doesn't fail because ideas are scarce or teams lack creativity. It fails because the systems designed to evaluate, govern, and scale new initiatives were never built for uncertainty, speed, or learning at enterprise scale. As companies layer tools, processes, and AI onto these foundations, they accelerate activity without improving outcomes.

The question is not whether to invest more in innovation. Most organizations already are. The question is whether those investments are landing in the right place: not in more tools to generate ideas, but in the systems required to do something meaningful with them.

Organizations that get this right don't just move faster. They compound. Every good decision improves the quality of the next. Every terminated zombie project frees capacity for something that genuinely deserves it. Every AI-powered evaluation makes future prioritization sharper, not noisier. The innovation system becomes, over time, a structural competitive advantage, not because it generates more ideas, but because it consistently does something most organizations still struggle to do: it turns them into something real.

When your organisation generates its next great idea, does the system surrounding it give that idea a fighting chance?

Want to discuss?

Lotus Child

Lotus Child

Director of Digital Experience at JAKALA UK, France, Nordics.

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