On Innovation Strategy: Bridging Data, AI, and Organisational Culture

(Also on Medium)

As part of my journey studying innovation strategy and now delving into culture in the Cambridge Judge CTO Programme, I’ve been reflecting on how these two critical areas intersect. This post represents my views to bridge the two, exploring how strategy and culture must work together to make innovation impactful, adaptable, and meaningful, especially as I straddle both data and machine learning? as product platforms for our gaming business.

I was inspired by Tiankai Feng ’s analogy of business, data, and AI strategies as Lego sets. To take this analogy further, I’d add that the data and AI Lego sets are incomplete without being connected to the business Lego set, that's when the true fun begins! This is the core takeaway from my exploration of these two modules. Strategy and culture must align to ensure innovation is not just built but embraced, adopted, and scaled.

Drawing from my experience of working on platforms that have acted as catalysts for product evolution across three organisations, I’d like to share key insights, lessons, and pitfalls to consider when embarking on an innovation strategy.

Keeping the Human Lens

An innovation strategy is often framed as a means to pursue the next big idea, adopt cutting-edge technologies, or maintain a competitive edge. But in reality, innovation is fundamentally about solving problems that matter and delivering outcomes that drive value.

Whether dealing with data platforms, AI, or ML, the question isn’t “What can we build?” but rather, “What impact do we want to create, or what problem do we need to overcome, and why is this innovation the right answer?”

Innovation strategies cannot exist in isolation. They require cultural alignment, adaptability, and a human centred approach. Strategies that fail to connect to real business outcomes risk becoming abstract, exclusive, or irrelevant.

At the heart of any successful innovation strategy is the ability to anchor decisions to clear, measurable outcomes. This means flipping the traditional technology first mindset into one that focuses on solving business problems.

Instead of asking, “How do we implement AI for personalisation?” the question becomes, “How do we improve player retention by 20% where we cannot simply throw more people at the problem?” AI is then positioned as the enabler, not the end goal.

Bust the Halo Effect and Engage Diverse Perspectives

One of the greatest challenges in innovation strategy is the halo effect of the expert. When strategies are driven exclusively by a small group of technical experts, they often become insular and fail to resonate with the broader team.

I’ve been there myself, caught in the trap of championing data back in the 2010s. I was so convinced of its potential that I became a cheerleader, fully “drinking the Kool-Aid” but unintentionally leaving others behind. I’ve also played the role of the “preacher” consultant, where my enthusiasm came across as telling rather than engaging.

To make innovation truly stick, we need to move away from these dynamics by fostering inclusivity and collaboration. Strategies must bring everyone along on the journey, not just those who already believe.

My takeaway, bust the Halo Effect by flattening hierarchies, share early and encourage co-creation, and actively seek to translate complexity. Address cognitive biases such as overconfidence and the curse of knowledge, simplify the practical outcomes.?

Balance Short-Term Wins with Long-Term Vision

The idea of starting small and failing fast is a powerful one, but it comes with its own risks. Focusing exclusively on short-term pilots or proofs of concept can lead to stagnation if there’s no pathway to scale.? A robust innovation strategy balances quick wins with a clear roadmap for scaling successful experiments. There has to be a duality -?

Short term: Use pilots to test hypotheses, build momentum, and demonstrate value.

Long term: Define how these pilots integrate into scalable solutions that drive sustained impact.

An ML-driven recommendation system piloted on a small segment of users can be mapped into a broader personalisation strategy, scaling over 18 months to deliver organisation-wide value.

Engage Your Inner Sceptic Through the “So What?” Test

Scepticism plays a vital role in innovation strategy by forcing clarity and ensuring ideas are grounded in practical realities, and is another technique to bust the confirmation bias of experts. Tough questions can transform vague ideas into actionable plans.

To engage your inner sceptic, for every proposed initiative, ask, “So what?” until it ties directly to a meaningful outcome.?

“We’re implementing an AI-powered recommendation engine.” → “So what?” → “So we personalise content.” → “So what?” → “So we improve player retention by 15%.” → “Oh great, and we can measure if the change is making a difference in retention, maybe we should have some leading metrics to ensure we are in the right direction!”?

The “So What?” the test helps ensure decisions are based on outcomes, not assumptions which may have been driven by cognitive biases.?

Build Belief Through Inclusion, Not Imposition

Innovation strategies succeed when they are believed in, not when they are simply sold or told. Building belief requires inclusivity, clarity, and alignment across teams—and that starts with the leadership.

To build belief, the C-suite must actively champion the strategy, but they also need to be brought into the process as collaborators, not just as an audience. They are not expected to be experts in innovation, if they were, they’d likely be writing the strategy themselves. However, they need to trust in the innovation and its value. This trust comes from providing them with:

A compelling reason for the innovation: Why is it necessary, and why now?

A clear understanding of the costs: Not just the potential impact, but the investment and risks involved.

Additionally, leaders need support in crafting their own narrative about the innovation. A well-crafted strategy should empower them with the right tools and language to explain why this innovation matters to the rest of the organisation, building alignment and belief at every level.

Innovation Strategy has to be a Living Framework

Innovation strategy is not a static plan, it’s a living framework that evolves through collaboration, execution, and learning. For innovation strategies to succeed and survive, they must adapt to emerging needs while maintaining focus on outcomes.

To ensure longevity and impact, my takeaway principles?

Keep the human lens by anchoring decisions in real-world outcomes.

Bust the halo effect by making the strategy inclusive and accessible, and early.

Balance short and long term, you have to combine quick wins with scalable vision.

Engage the sceptic in you, challenge assumptions to ensure clarity and focus.

Build belief, and this has to include the C-Suite, wider ownership will propagate trust across the organisation.

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