The Selection Imperative: A New Discipline for Innovation

Yumana featured on BFM Business‍

Céline Degreef, CEO of Yumana, was invited onto the #Décryptage program on BFM Business.

Alongside Aude Kersulec, she shared insights on the evolving challenges facing innovation teams in an increasingly uncertain and demanding environment.

Introduction

Behind this conversation, a clear shift is emerging. Innovation remains a critical asset, but the rules of the game are changing. Expectations are tightening, timelines are accelerating, and innovation leaders now face a new requirement: deliver visible results and prove their value early.

For years, innovation benefited from a certain degree of flexibility. Teams had the space to explore, experiment, and even fail without being required to justify every step in real time.

That flexibility hasn’t disappeared. But it has clearly narrowed. And in some organizations, it has tightened very quickly.

Innovation is still widely seen as essential. Few leaders would question its role. What has changed, however, are the conditions under which it operates. Economic pressure has intensified, trade-offs have multiplied, and decision cycles have shortened.

With that shift comes a new expectation: demonstrate value faster. Not in two years, not at the end of a progra, but from the earliest stages.

For innovation leaders, the challenge is no longer just about generating promising ideas. But it’s deciding which ones truly deserve to move forward, which need to be refined, and which should be stopped early.

In reality, a large share of initiatives should never make it past the first review. Not because they lack potential, but because they are not yet robust enough, not clearly defined, or not grounded in a real business need.

Innovation today requires greater structure, stronger visibility, and a much sharper focus on evidence.

Innovation is becoming a discipline.

When Innovation Faces Pressure, it evolves

In an uncertain environment, companies have less patience for initiatives that remain vague for too long. Projects that look promising on paper but are hard to measure are challenged more quickly. And a high volume of initiatives, when not clearly managed, rapidly loses visibility.

Innovation teams, in turn, find themselves on the front line explaining and defending their choices.

This doesn’t mean companies expect innovation to be predictable. That would be a contradiction. But they do expect it to be understandable. They want to see what is being learned, what is being built, and what is actually changing.

This marks a significant shift. For years, success was often associated with the volume of ideas. Today, the real differentiator is the quality of decisions.

Success no longer comes from starting more projects, but from stopping the weakest ones faster.

Innovation requires more than generic tools

This is likely one of the most significant shifts. Innovation is increasingly managed as a portfolio, one that needs to be structured and guided over time.

This requires a new level of discipline. Organizations must be able to track initiatives from their earliest stages through deployment, compare them consistently, document key decisions, assess both potential and realized value and, at times, make the difficult call to stop.

Because in practice, managing innovation is also about identifying which ones should not move forward.

Across the programs we support at Yumana, the same pattern consistently emerges: the challenge is mostly about making timely decisions on which ideas do not deserve further investment rather than being about idea generation.

And this ability to filter, prioritize, and sometimes stop initiatives is becoming a critical capability. It reflects a certain level of maturity. Organizations that can focus their resources on the most promising initiatives significantly increase their chances of success.

For years, many organizations relied on improvised setups, spreadsheets here, shared documents there, internal tracking systems, and processes that varied from one team to another.

This worked as long as programs remained relatively limited in scope.

But as initiatives scaled, the same limitations began to surface: difficulty consolidating information, comparing projects objectively, tracking real progress, avoiding duplication, and maintaining a usable memory of past decisions.

And above all, difficulty making innovation understandable for those who need to evaluate, prioritize, and support it.

This is often where programs begin to slow down, due to a lack of structure and governance.

Service is the new differentiator for Innovation platforms

The innovation management software market has also evolved. A few years ago, the challenge was to prove the value of a dedicated solution. That debate is now behind us. Companies understand that they cannot effectively manage innovation using standard office tools alone, such as MS Office.

However, not all platforms deliver the same value.

Solutions that focus solely on idea collection become irrelevant in less than twelve months. They generate volume but not decisions, and very quickly, they create more frustration than impact.

The real question has shifted.

It now lies in a platform’s ability to structure decision-making, make initiatives comparable, and bring clarity to complex choices. In other words, to enable informed, confident decisions.

In practice, organizations are no longer just looking for a tool, they expect both technology and expertise to maximize the success of their innovation programs.

At Yumana, this is where the difference often lies: not in the technology alone, but in the ability to support teams over time, structure their decision-making, and make innovation visible at the executive level.

SaaS is no longer just about providing access to a platform. It has become a promise of trajectory, a key expectation for today’s innovation teams.

Innovation is becoming inherently hybrid

Another structural shift is underway: innovation no longer relies solely on internal teams... or rather, it can no longer be limited to them.

Internal contributors remain essential. They understand operational realities, customer behaviors, business constraints, and everyday friction points. They often identify emerging needs before they are explicitly formulated, making them uniquely positioned to surface relevant insights and fuel meaningful initiatives.

But they are no longer alone. Around them, a broader ecosystem has become critical: startups, technology partners, domain experts, and external stakeholders. Their value lies in their ability to bring missing capabilities, accelerate key phases, challenge perspectives, and, in some cases, significantly shorten time to market.

As a result, innovation is becoming more hybrid in nature. It operates at the intersection of multiple forms of intelligence: internal expertise rooted in the company’s reality; external contributors driving openness and acceleration; and increasingly, the tools that orchestrate and connect both.

This hybrid model requires new management approaches. Identifying the right partner or launching a proof of concept is no longer enough. Organizations must be able to qualify opportunities, monitor collaborations, maintain a clear view of their pipeline, and ensure that the most promising initiatives are not lost in fragmentation.

Community dynamics as a strategic driver of high-performing innovation

As innovation becomes more structured and performance-driven, one might expect the community dimension to lose importance. The opposite is true. The more demanding decision-making becomes, the more critical the quality of contributions. And the more programs are expected to demonstrate value, the more community engagement matters.

Engaging a community goes far beyond launching an idea call and waiting for input. It requires creating the right conditions for participation, designing a clear and motivating experience, and encouraging people to contribute, comment, follow, and return. It also means sustaining momentum over time and preventing engagement from fading once the initial excitement wears off.

This is where activation mechanisms (such as gamification, visibility, and overall user experience) become essential. They directly impact a program’s ability to last, attract relevant contributions, and mobilize the right stakeholders at the right moment. This is what ultimately creates collective energy.

High-performing innovation is rarely a tooling issue. It is almost always an activation challenge.

AI is becoming integrated in the daily workflows of innovation teams

It is impossible to address innovation today without considering artificial intelligence. In a short time, it has established itself as a key lever for innovation teams, supporting multiple stages of the innovation cycle.

It first delivers value where it enhances speed and depth: idea generation, brainstorming, reframing, challenging contributions, and enriching thinking. It is also increasingly relevant on the governance side, helping identify weak signals, guide decisions, suggest next steps, and streamline execution.

What matters is no longer just the performance of individual features. The real shift lies in the continuous role AI plays within the system. It acts as a layer of assistance, support, and insight... a presence that does not replace human judgment but makes processes more responsive and structured.

This dynamic is only set to accelerate. We are already seeing the emergence of AI agents capable of contributing to idea campaigns, supporting program managers in prioritization, and helping maintain momentum across initiatives.

AI is no longer just enhancing interfaces, it is beginning to shape the very rhythm of innovation programs.

And yet, the center of gravity remains human

This may be the most critical point to preserve in this transformation. As tools become more powerful, it becomes essential to clarify what they are truly meant to serve.

In innovation, the core resource remains human. Employees are the ones who identify needs, understand business realities, and detect meaningful tensions. Partners bring new capabilities, different speeds, and fresh perspectives. Teams connect the dots, arbitrate, and define direction.

AI can accelerate, suggest, support, and stimulate. It can increasingly contribute. But it does not replace contextual intelligence, nuanced understanding, or the judgment that remains at the heart of critical decisions.

This is where the future is taking shape: in models where innovation is neither purely human nor purely technological, but built at the intersection of both. A more collective, augmented form of intelligence, still guided by human choices.

The shifts reshaping innovation by 2027

A structural transformation is underway. Innovation is entering a new cycle, more structured, more demanding, and more value-driven.

Dispersion is no longer an option. Discipline becomes the priority: organizing exploration, making faster decisions, activating the right communities, connecting internal and external ecosystems, and demonstrating value from the very first signals.

In this context, some organizations are already pulling ahead. Not necessarily those that innovate the most, but those that make better decisions.

And that may be the real shift: innovation is becoming a matter of decisions, not intentions.