24. How to communicate data value to non-technical stakeholders

One of the most persistent challenges in data strategy is not technical in nature. It is the gap between those who understand data and those who make decisions about it. Finance directors, board members, and senior managers are often unfamiliar with terms like data lineage, schema integrity, or pipeline latency. Yet these same leaders are responsible for approving investment in data infrastructure, signing off on compliance programmes, and setting the strategic direction of the business. If data professionals cannot communicate value in language that resonates with their audience, the opportunity to secure meaningful support is lost. The most effective approach is to translate data quality and capability into outcomes that business leaders already care about. Rather than explaining how data is structured, it is more persuasive to describe what poor data costs the organisation in missed revenue, wasted operational effort, or regulatory risk. A CFO who hears that incomplete customer records resulted in failed invoice matching, or that data errors delayed a product launch by six weeks, understands the issue immediately. Framing data value in terms of business consequences rather than technical metrics makes the conversation relevant and actionable. Visualisation and storytelling also play a significant role. Dashboards that connect data quality scores to revenue outcomes, or that show trends in data accuracy over time alongside customer retention rates, allow non-technical stakeholders to engage with information that would otherwise feel abstract. The goal is not to simplify data to the point of distortion, but to present it through a lens that aligns with what leadership teams are already measuring and discussing in their quarterly reviews and board meetings. Building a shared vocabulary across the organisation is equally important. When finance, operations, and IT teams use different terminology to describe the same data assets, misunderstandings accumulate and progress stalls. Establishing a common language, whether through regular cross-functional briefings, plain-English data glossaries, or structured communication templates, creates the conditions in which data value can be recognised and acted upon at all levels. Over time, this cultivates a culture where data is understood not as a technical concern confined to one department, but as a genuine organisational asset with measurable financial implications.