From Information to Impact: How data drives real change

In today’s fast-moving business environment, strategy leaders are under more pressure than ever to turn data into meaningful decisions. To explore how organisations can move beyond dashboards and reporting to truly embed data into their strategic DNA, we sat down with Damien Thompson, Head of Technology Strategy & Data at Cricket Australia.

Drawing on his first-hand experience leading national technology, data, and analytics initiatives, Damien shares how he and his team have transformed data from a by-product into a driver of real-time fan engagement, cultural change, and smarter decision-making across one of Australia’s most iconic sporting organisations. Q1. How are leading organisations today moving beyond dashboards and reports to actually embed data at the core of strategic decision-making?

Data becomes powerful when it moves from being a rear-view mirror to becoming the steering wheel.

More dashboards don’t equal better decisions. In fact, this sort of sprawl often makes it much harder to find the signal in the noise. Real value comes from embedding data directly into the decision loop, where context and timing matter more than sheer volume. Organisations that I see doing that well are the ones shaping decisions in the moment, not looking backwards at reports reflecting on what could have been.

In reality that means focusing on a few principles: accelerating the time from data to insight; democratising access but curating it carefully to avoid information overload; and critically, partnering the numbers with narrative – creating the “so what” moments which drive action. Increasingly, we’re seeing decision intelligence platforms bring this to life by blending AI with human judgment to surface the right insight at the right time.

I’ve seen this play out first hand. At Cricket Australia we built a national data platform unifying customer, participant, and behavioural data, which powered real-time fan engagement rather than static reporting. Through a national ERP/CRM and BI transformation, we embedded insights into executive dashboards that allowed leaders to prioritise programs using live metrics, rather than gut feel. Those are the moments where data stops being a by-product and becomes core to intelligent and proactive decisions. Q2. What do you see as the biggest barriers that stop insights from being translated into real competitive advantage — and how can strategy leaders overcome them?

Real competitive advantage isn’t in having insights - it’s in building the culture and governance to act on them.

Interesting, the biggest barrier today isn’t technical as it has been in the past, it’s cultural. Insights only create advantage when we have alignment between incentives, governance, and accountability to create outcomes. Too often, siloed data and weak governance means our leaders are forced to rely on instinct or intuition, even when the evidence points elsewhere. Governance itself can also be misapplied and result as red tape, rather than the enabler of trust and action it can be.

Real progress comes when insights are anchored to outcomes that align to your strategy and people people genuinely care about them -  and when acting on them is rewarded. It’s a key opportunity for strategy leaders to guard against blind faith in data as well, remember that signals always need context - chasing short-term noise can be just as risky as ignoring the evidence.

I’ve seen this work in practice. As a federated group of organisations it was necessary to establish a national cohort of data champions made up of people embedded in their businesses. These group shared learnings and approaches across the organisations and not only lifted awareness but created momentum for action, because the insights were owned by the people closest to the work. Drawing back to the importance of governance, establishing national technology, data and privacy governance committees were key to ensure insights weren’t left on the shelf but became funded initiatives with executive ownership.

Q3. In fast-moving markets, how can strategy teams strike the right balance between rigorous analysis and the need for speed in decision-making?

Lasting success comes from knowing when to go fast, and when to slow down and get it right.

Not every decision needs perfect data. The balance lies in triaging, applying full rigor to the big bets, while allowing agile, “good enough” insights to drive the rest. The balance is a thin line - speed without discipline creates costly mistakes, while over-engineering every analysis slows momentum.

The goal is to right-size analysis to the importance of the decision and that requires deep involvement with your business leaders to understand the size of the prize and their risk appetite. Developing organisational muscles around test-and-learn and failing fast makes it possible to move quickly and then iterate based on adoption and results.

Both approaches have their place. Last season we launched new features in the Cricket Live app through rapid test and learn iterations, learning quickly through test harnesses and deep engagement with our CX experts. However, for a national ERP replacement across nine businesses, we deliberately applied rigorous analysis and discovery to ensure stability, compliance, and long-term reliability. The art is knowing which model to apply.

Q4. Where does human judgment fit in a world increasingly shaped by AI, analytics, and predictive modelling?

The future belongs to organisations that get this balance right - where AI does the heavy lifting, and people focus on the decisions that matter most.

That’s a question playing out very broadly across society more generally. AI is exceptional at surfacing patterns at speed, but humans still frame the questions and apply context. For where AI is currently, the strongest model is human-in-the-loop, not human out-of-the-loop – though any management consultant can tell you the answer is always “it depends”. Data can tell you what is happening, but judgment decides why it matters and what to do next.

Both humans and machines carry bias, which makes this partnership essential. Leaders need to be aware not just of their own biases but those that could be baked into the training and implementation of the models employed – challenging their own instincts as much as they interrogate the models. Value comes from redirecting our judgment to higher-order choices that shape direction rather than micromanaging the analysis, but always with an awareness of what is happening under the hood.

I’ve seen AI models change the game, from predicting player injuries to anticipating customer churn to proactively curating content for our fans based on their preferences and observed behaviours. The key has been that that coaches, medics, and marketers applied their judgment before action. The combination of statistical signal and human expertise created the confidence to make the right calls.

Q5. What cultural or organisational shifts are required to make a business truly data-driven, rather than just data-aware?

The real marker of a data-driven business is curiosity -  when people at every level are empowered to ask better questions and act with confidence.

Becoming data-driven is a significant mindset shift – moving from producing reports to cultivating curiosity, trust, and empowerment takes time and trust. Understanding that data should fuel better questions, not drive blind obedience to metrics is key for leaders to ensure that “data-driven” doesn’t translate to tunnel vision, where context and even ethics are can be lost. In many ways the aim should be “data-informed.”

It’s an exciting space for leaders to play today, to role-model data-informed decision-making, rewarding experimentation, and creating safe spaces for learning. Building a cohort of data interpreters who bridge business and technology is a game changer, turning technical outputs into insights that teams can act on with real confidence.

This concept of data interpreters has been powerful across Cricket’s national teams, embedding people into operational teams has helped shift the culture from awareness to adoption. Likewise, a shared Technology services model embedded reporting directly into workflows, reducing the gap between data access and meaningful action. That’s when culture truly changes.

Q6. What emerging data capabilities (AI, real-time analytics, digital twins, etc.) do you think will have the biggest impact on strategy in the next 3–5 years?

The winners won’t just move fast - they’ll move fast in the right direction.

Everything is moving fast in data and AI (increasingly so), but speed alone isn’t the differentiator. Leaders need to think in terms of vectors - speed and direction - with clear direction as the non-negotiable. Observability, ownership, and the ability to simplify complexity will separate those who create impact from those who just chase hype.

Real-time analytics, generative AI, and digital twins will all matter, but the real edge comes when they’re interoperable and embedded into workflows with governance that builds trust. The real question for strategy leaders isn’t which technology will dominate, but who can bring them together in a way that simplifies decisions and creates clarity of direction.

What excites me most is the convergence we are experiencing - of Cricket’s rich real-time and historical data, our increasingly digital venues, high-speed networks, and the expanding ecosystems of partners. Together we are able to create truly personalised, “phygital” (physical/digital) experiences; where every fan, whether in the stadium or at home, is connected to the game in ways that feel immediate, immersive, and uniquely theirs.

At a grassroots level, Cricket’s deep historical data gives us the ability to leverage digital twins of athletes, modelling and coaching that can guide a grassroots player with the same intelligence we use at the elite level. Imagine a young cricketer in regional Australia accessing a virtual coach powered by the knowledge of decades of performance, helping them develop, learn, and emulate their heroes.

That’s the future: blending real-time and historical insights to transform how we engage fans and how we help them grow their love of the game. While these examples draw from sport, the possibilities extend far beyond - into education, health, and industries that want to harness data to unlock human potential. That’s a horizon I’m excited to see us move towards. Outro

Damien’s perspective makes it clear that becoming truly data-driven isn’t about chasing the latest tool or trend. It’s about building the culture, governance, and curiosity that turn information into action. His examples from Cricket Australia show what’s possible when insights are embedded into workflows, leaders role-model data-informed decision-making, and teams are empowered to act with confidence.

As strategy leaders look ahead to an AI-powered future, Damien’s reminder rings true: the real advantage lies not just in speed, but in moving fast in the right direction.