Newsletter No. 12 | Build a Learning Machine | Evolve Faster Than the Market Changes

Let’s say you’ve clearly defined the core of your business,—whether as a founder shaping a new venture or as a leader refining established business models. You’ve crafted an innovation strategy that aligns with your business’s size, maturity, and budget, and set goals across different innovation horizons. But now comes the real challenge: how do you bring this strategy to life?

When I ask clients if they’re satisfied with their implementation efforts, the answer is often no. They have the strategy, but something gets lost in the execution. Has anyone here read Principles by Ray Dalio? He suggests thinking of an organization as a "machine" built to achieve specific goals. If you’re not seeing the outcomes you want, it’s time to ask: is your machine working as it should?

One Insight from Me

According to Dalio, an organization—the "machine"—has two key parts: people and design (including culture, processes, and systems). To ensure this machine works effectively, you need to continuously compare its outcomes with your goals and make adjustments as needed. This feedback loop enables the organization to learn and adapt over time, which is critical, as survival in today’s market demands adapting as quickly—or ideally, faster—than the market changes.

But here’s where I see many organizations, especially SMEs, struggle: as leadership starts to modify this “machine,” they often fall short in explaining why changes are necessary or the reasoning behind them. Sometimes, even leadership itself feels confused or uncoordinated, as differing perspectives within the team create friction. Since an organization relies on many people, not just a few, this lack of clarity often leads to uncoordinated actions. Without shared understanding, innovation ends up happening in silos, and valuable insights remain disconnected from the broader mission.

So, how do you make innovation an organization-wide process? Sharing learnings is essential, but it requires a structured approach and a shared language that supports rapid, actionable learning. Many companies get bogged down in high-level discussions without translating them into real-world testing and documentation. In my work with clients, I encourage an “academic” approach: every challenge, every insight, documented, acted upon, and integrated into the system. Just as in academia, documentation supports shared understanding and continuous progress.

Currently, I’m helping a client transition from an outdated business model (1.0) to a stable, though limited, model (2.0) while exploring future-focused models that are more scalable (3.0). Here’s how we’re creating a learning machine that ensures the entire organization learns and adapts with each step:

1 | Establish a Clear Innovation Strategy
We begin by defining specific goals for each horizon—from phasing out outdated practices to strengthening current operations and exploring new, disruptive models. This clarity in strategy is shared across teams so that every department understands where the organization is headed and why. This collective vision sets the foundation for a cohesive learning journey.

2 | Identify and Define Concrete Challenges

From the strategy, we extract key challenges—such as exploring the existing customer base, identifying trends or validating ideas—to ensure every project is aligned with the bigger picture. By defining challenges clearly and openly, we enable each team to see how their work contributes to broader objectives, fostering a sense of shared purpose and coordinated learning.

3 | Create Clear, Accountable Work Packages
Dividing work effectively is about creating accountability, not just handing off tasks. The challenge is to avoid dividing work too early, before the tasks and their alignment with the bigger picture are fully understood. Each work package should be clearly defined, with a direct connection to the broader goals of the innovation strategy. This approach ensures that everyone understands both their specific responsibilities and how their work contributes to the overall mission, fostering alignment and preventing confusion.

4 | Leverage Open Innovation for Rapid Learning
Engaging with external talent injects fresh perspectives that challenge assumptions and prompt new questions—questions we may overlook ourselves. In philosophy, it's often said that we come to know ourselves through others. Similarly, working with externals reveals blind spots and encourages us to explore ideas from different angles. This ultimately enriches the organization’s thinking, pushing boundaries and enabling rapid learning by inviting critical examination from outside perspectives.

5 | Implement, Document, and Iterate
This is where Dalio’s feedback loop becomes critical—by comparing outcomes with goals and making adjustments, we refine the machine with each cycle. Documenting and sharing these outcomes across the organization enables everyone to learn from each project, ensuring that insights don’t stay siloed but inform the next iteration of strategy. This continuous feedback loop turns individual projects into coordinated organizational learning, strengthening the entire organization.

This is what I call a learning machine—where innovation isn’t isolated but evolves through continuous, organization-wide learning.

One Question for You

Is your machine delivering the outcomes you want?

One Opportunity for Us

You clarified the strategy, identified the challenges, and outlined the next steps—but are things still not moving forward for you? Sometimes, the roadblock isn’t a lack of direction; it’s a resource problem. Many clients find they simply don’t have the time or budget to fully execute the plan on their own. That’s where student talent becomes a game-changer: a cost-effective, high-value resource that can drive projects forward.

For the past six years, I’ve been harnessing the talent of Master’s students specializing in business innovation to support these efforts. Now, I’m building a dedicated talent pool that my clients can tap into. I understand that working with external talent comes with its own challenges—finding, guiding, and aligning them with your goals takes time. By creating a shared talent pool, I aim to make this process seamless, offering you access to motivated talent who can validate ideas, document learnings, and bring fresh perspectives, all within a structured framework aligned directly with your strategy.