Building a data-driven culture: Top priorities for CDO’s

by Jason Foster, CEO, strategist, advisor and author

Data culture has become one of the biggest priorities for organisations looking to get more value from data and AI. Across industries, leaders are investing in data literacy programmes, internal communications campaigns, training initiatives and transformation programmes designed to help people become more data-driven.

The aspiration is absolutely the right one. Organisations want their teams to embrace data, make better decisions and use insights to improve performance. Yet despite the effort and investment, many still struggle to achieve the outcomes they are looking for.

Adoption remains low. Executive buy-in is difficult to secure. Data initiatives fail to scale. Value is hard to demonstrate.

This can feel like failure at the final hurdle.

But in our experience, a strong data culture is often the result of strategic decisions made much earlier in the journey. And the problem we’re seeing is a misdiagnosis of the symptoms, and the wrong approach taken to creating that culture. What works best is not solving data culture at the end but creating the right conditions for that culture you’re after to naturally emerge.

Why data culture has become such a dominant topic

Earlier this year, Cynozure research found that data culture and literacy ranked as the number one priority for data leaders in 2026.

Source: The Next Horizon Data, AI and Impact – Download the full report here

At the same time, the research highlighted several persistent challenges:

Lack of buy-in remains one of the biggest barriers to progress

Most organisations are still not measuring the impact of their data and AI investments, making it difficult to demonstrate value

Many have delivered successful projects or proofs of concept, but relatively few have been able to scale those successes consistently across the wider organisation

These challenges create understandable frustration. Organisations invest heavily in data platforms, analytics capabilities and AI solutions, but the results often fall short of expectations.

When that happens, culture becomes the default explanation.

The problem is not that culture doesn’t matter. It absolutely does. The issue is that many organisations are trying to solve the wrong problem.

Solving for data culture vs. solving data culture

When organisations tell us they have a data culture problem, the symptoms are usually familiar. People aren’t using the dashboards that have been built. Data products aren’t getting the engagement that was expected. Business teams seem disconnected from data initiatives, while leaders question whether their investment is delivering value.

As Leanne Lynch, CIO at ISS, a leading facilities management organisation, explains:

“I genuinely think the technology is the easy part of the journey. Putting technology in place is relatively straightforward. Getting people to adopt it and trust it is where you have to really focus.”

The common response is to focus on culture through training, communications and awareness programmes. Yet these initiatives often struggle to deliver lasting change because they address the symptoms rather than the underlying cause.

To resolve this we’ve consistently seen organisations take one of three approaches:

Build the technology first and drive adoption later
Start with culture and literacy before building solutions
Try to do both at the same time
While each starts with good intentions, they all assume that culture can be created directly

People don’t engage with data because they’ve been told it’s important. They engage when it helps them solve a problem, make a better decision or improve an outcome they care about. Business leaders aren’t focused on dashboards or governance frameworks; they’re focused on growth, customer experience, operational efficiency and risk. Data only becomes relevant when it helps improve those outcomes.

As I mentioned in a recent webinar:

“Usually it’s a problem with how the work being done in data isn’t connected to things people actually care about – better customer experience, improved revenue performance, reduced cost of operations, better supply chain performance and fewer customer complaints.”

The challenge, therefore, isn’t persuading people that data matters. It’s demonstrating how data and AI can help solve real business problems, improve critical decisions and deliver measurable business impact.

What successful organisations do differently

The organisations that make the greatest progress tend to share a number of common characteristics:

They start with business decisions rather than technology. They understand the strategic and operational decisions that drive performance and focus their efforts on improving those decisions.
They prioritise meaningful change over deliverables. Dashboards, platforms and models are important, but they are only valuable if they change behaviour or improve outcomes. Success is measured by the impact delivered, not the assets created.
They adopt a product mindset. Rather than treating data initiatives as projects with a start and end date, they treat them as products that evolve over time. They are continuously improved, measured and refined based on feedback and results.
They measure what matters. They define the business outcomes they want to achieve from the outset and establish meaningful measures of success. This allows them to understand whether they’re creating value, learn what works and continuously improve the impact of their data and AI investments.
They make impact visible. They communicate the value being created across the organisation, building confidence, securing executive buy-in and creating momentum for future investment.

These principles shift the conversation away from data for data’s sake and towards the outcomes that matter most to the business.

Data belongs to the organisation

Another common characteristic of successful organisations is a shared understanding of ownership.

Too often, data is viewed as the responsibility of a data team, CIO or Chief Data Officer. While those functions play a critical role, lasting success requires a much broader level of engagement.

Leanne captured this perfectly during our recent webinar:

“Data doesn’t belong to the CIO and it doesn’t belong to the CDO. It belongs to the organisation.”

Creating value from data requires participation from across the business. Leaders need to trust and use data in their decision-making. Operational teams need to understand their role in creating and maintaining high-quality information. Everyone has a part to play.

Importantly, that understanding is not built through communications campaigns alone. It develops when people see how their contribution helps deliver outcomes that matter.

Reframing the conversation

Perhaps the most useful way to think about data culture is to stop treating it as the primary objective, and instead:

Focus on creating business impact, as opposed to creating a data culture
Build products that evolve and improve over time instead of delivering a finite project or dashboard and moving on
Measure outcomes, not deliverables, or outputs, or systems
Focus on enabling better decisions rather than concentrating on data itself

When organisations make these shifts, something interesting happens. Adoption improves. Engagement increases. Trust grows. People begin to use data more naturally in their day-to-day work.

“Culture isn’t a starting point. Culture is often an outcome that you achieve by changing the way that you work.”

The real opportunity lies in tackling meaningful business challenges though data and AI. Get that right, and the data culture you’re looking for is far more likely to follow.

So perhaps it’s time to stop trying to create a data culture. Instead, create the conditions in which one naturally emerges.

Cynozure is a consultancy that helps leaders ensure data and AI investment translates into clear P&L impact. The company works with organisations to shape data and AI strategies tied to business goals, design and deliver data and decision products that drive real outcomes, build architectures and governance that enable fast and safe platforms, improve data culture and literacy, and define and track your ROI from data and AI investment.

Cynozure also runs the CDO Hub, an exclusive members’ community where data leaders collaborate, share, learn and grow, and produces the Hub & Spoken podcast, one of the most listened to podcasts in the industry. The company has been recognised as one of The Sunday Times’ fastest-growing private companies and as DataIQ’s Best Place to Work in Data in both 2023 and 2024. Cynozure is a certified B Corporation.

If you’re interested in talking with the team, please get in touch or consider attending one of our upcoming events.