Why you need a data culture — and how to build one that wins

Summary:

• The best data cultures value technical skill as much as data literacy, recognise data ownership, and centre ethics, trust and transparency
• Success looks very different depending on the organisation; a winning data culture helps consider what to measure, prioritise and ignore
• Data literacy as an employee standard is vital because a strong data culture is maintained in day-to-day operations
• Winning data cultures strike a pragmatic balance between valuing processes and valuing outputs

We don’t need to convince people that data matters anymore. From the boardroom to the shop floor, information is now a familiar part of decision making. Dashboards and performance packs are embedded in how organisations run. And yet, most people also instinctively know that data on its own is not enough — which brings us to culture.

What do we mean by ‘data culture’?

Culture is often described as ‘the way we do things around here’. It’s what people do when nobody is watching: the habits and behaviours that shape daily work.

A data culture is not simply having dashboards or an AI strategy. It is the extent to which data is used, challenged, respected and embedded across the organisation. It’s whether people feel confident asking questions — and safe using data-based evidence to go against the status quo. It’s whether data is used to learn and improve, or to control and blame.

The healthiest data cultures intersect technology and humanity, valuing data literacy as much as technical skill. Ownership is recognised — who controls information, who benefits from it, and who is exposed by it — yet ethics, trust and transparency are core, not optional.

A strong data culture is about curating the right information, at the right level, at the right time — while making it easy to understand.
This selectiveness depends on clarity about what actually matters. Without an agreed performance framework, organisations risk being transparent about the wrong things. Vanity measurements crowd out sanity metrics. Activity is mistaken for progress — and things get lost in the noise.

Why a data culture matters

Winning looks very different depending on where you sit.
In the public sector, winning is rarely about beating a competitor. It is about outcomes such as improving health, education and safety. Success is measured in trust, legitimacy and long-term impact as well as efficiency. In the private sector, winning is often framed in financial terms.

A winning data culture helps organisations critically consider what to measure, prioritise and ignore: profit versus revenue; outcomes versus volumes; satisfaction versus social media likes. These choices shape behaviour more powerfully than strategy documents ever could.
Without a healthy data culture, organisations struggle in familiar ways: low-quality data, slow decisions, mistrust of numbers and endless debate about whose figures are ‘right’. Data sharing becomes a test of trust. When people do not understand why data is collected, how it will be used or who benefits, information is distorted or withheld. That is data politics in action.

Leadership sets the tone — people sustain it

Culture starts at the top. Leaders play a key role in setting the vision, the strategy, and the role data plays within it, including what good performance looks like at different levels of the organisation.
But culture is sustained — or undermined — in the day to day. By whether information is shared or hoarded, whether teams respect data quality under pressure, and whether concerns about bias, ethics or misuse are raised or ignored.

This is where data literacy becomes critical. Not everyone needs to be a data scientist, but everyone needs enough understanding to interpret information responsibly, ask intelligent questions and be able to recognise when storytelling is being used to mask the truth or genuinely add additional value to a point of view.

It is also where leadership judgement matters most. The strongest data cultures are pragmatic. Leaders prioritise valuable information outputs even when the underlying process is imperfect or manual, but — crucially — they also champion the right investment in the back-end: integrations, data quality, shared definitions and reporting infrastructure.

Too often, organisations tilt too far one way or the other. Business teams tolerate inefficient processes because the analysis is good, or data engineering teams push for necessary platform investment but struggle to articulate value in terms senior leaders recognise. Winning cultures strike a balance.

AI, curiosity and the cultural shift

Artificial intelligence has re-energised interest in data, and exposed weaknesses just as quickly.

Technically, models are only as good as the data they are trained on. Culturally, AI is driving curiosity. People want to understand how models work, what data they rely on and what decisions they influence.

That curiosity creates an opportunity to upskill at scale — not just in tools, but in critical thinking, ethics and governance. Questions about fairness, explainability and accountability are now live operational issues. A strong data culture creates space to address them openly, rather than treating them as blockers to innovation.

Transparency, timeliness and motivation

Some of the most effective data cultures are built around openness and speed, supported by clarity on what is being measured and why.
Retailers that share performance information with people working in stores help teams see how their actions connect to wider outcomes. In some cases, performance is linked to modest bonuses or recognition. The signal matters just as much as the amount. 

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In the public sector, financial incentives are often constrained. But transparency still matters. Sharing performance information can create a sense of progress, professional pride and personal growth, particularly when missions are complex and results are long-term.

Timeliness is critical. Perfect information delivered late is rarely useful. Finance teams that reduce month-end close cycles, supermarkets that track performance through the day, or contact centres that adjust staffing in near-real-time all reinforce the same lesson: data earns its place when it can still change outcomes.

That, in turn, shapes technology choices. The goal is not more dashboards. It is simple, trusted information, delivered quickly and aligned to clear performance measures and paired with the confidence and permission to act.

So how do you build a data culture that wins?

While every organisation is different, the following key principles work for most:

• Start with purpose. Be clear about what winning means for your organisation, and how data supports it
• Invest in people, not just platforms. Data literacy, ethics and curiosity matter as much as architecture
• Be transparent by default. Share information widely and responsibly, focusing on what genuinely matters
• Acknowledge politics and power. Data is never neutral. Name the tensions rather than pretending they don’t exist
• Lead by example. Leaders who use data thoughtfully, champion data quality and admit when judgement overrides the numbers give others permission to do the same

Ultimately, a data culture is not about replacing human judgement with algorithms. It is about strengthening judgement with evidence, honesty and shared understanding.

That is how organisations — public and private — give themselves the best chance of winning, however they define it.

David Geere FBCS CITP helps clients turn data strategy into outcomes, build governance, and lead complex transformation across public and private sectors. He joined BCS in 2000, and became a BCS Fellow in 2022.