Standardising data structures
How structured, standardised data drives measurable business growth
Many organisations understand that data is a strategic asset, yet few make the most of it. Companies continue to invest heavily into digital platforms and tools, but many still struggle to turn their information into actionable insights. Poor data quality can remove around 20% of potential revenue and consumes as much as 30% of operational budgets. This reduces efficiency, slows decision making and limits innovation. Research from McKinsey shows that businesses using data effectively outperform competitors.
In contrast, organisations burdened with unstructured or isolated data face persistent challenges. As a result, many have focused on improving visibility, oversight and governance. These steps help, but they do not resolve the deeper issue. To unlock real value, companies need a clear strategy that strengthens structure and standardisation across all data sources.
Moving from data disorder to clarity
When information is scattered or inconsistently formatted, it becomes difficult to build an accurate view of performance. For example, product codes that differ between systems can delay forecasting. Teams are then forced to manually reconcile data. Similarly, inconsistent customer records can slow service teams and undermine confidence in reporting. In some cases, companies are unable to answer basic questions such as weekly sales volumes or predict demand reliably. Over time, this erodes strategic clarity and makes it harder for leadership teams to act with confidence.
Although many organisations prioritise data observability, oversight and governance, these practices do not fix the underlying fragmentation that prevents meaningful analysis. Businesses need a strategic, structured approach that standardises, aligns and enriches data across systems. This encourages shared definitions across teams, reduces duplication and improves coordination. With this foundation in place, smarter planning becomes possible. Achieving this level of clarity requires a phased approach.
Why structure and standardisation matter
The journey starts with cleansing. Removing outdated or unnecessary information, and ensuring data sits in a logical and usable format, is essential. Once data is cleansed, standardisation creates the foundation for meaningful structure. Organisations can turn to ontologies to organise information. These define key concepts, attributes and the relationships between various data sources. Setting this semantic framework ensures that processes stay aligned and gives both people and machines a shared understanding of terms.
This structure makes it simpler to locate and reuse information, and supports automated reasoning and more advanced analytics as datasets expand.
Unlocking value from unstructured data
A significant opportunity lies in unstructured data, which IDC estimates accounts for 90% of enterprise information. These sources include text files, audio, meeting notes, transcripts, emails and system logs. They hold enormous value, although they are often hard to interpret or analyse at scale.
Technical limits, rather than lack of intent, usually hold organisations back. Techniques such as tagging, generating metadata and linking entities help convert unstructured information into accessible and analysable assets. Through semantic enrichment, organisations can add context and make this data discoverable.
This approach also builds a shared view of how customers, products and business units connect with one another. The result is a more joined-up understanding of operations. Knowledge discovery becomes far faster because enriched data is easier to search, navigate and reuse.
Turning disciplined data management into stronger outcomes
Every organisation will take its own route, but the fundamentals of a strong data strategy remain consistent. Data must be easy to find, cleansed and structured in a consistent way. When these conditions are in place, information shifts from being a scattered collection of records to a resource that informs decisions across the organisation.
Without these foundations, the advantages of a data-driven approach remain out of reach. With them, companies can act with more speed and certainty. They can bring products to market more efficiently, give teams the ability to use technologies such as AI to enhance their work and strengthen their long-term planning. A complete, unified data strategy becomes a core driver of performance that helps the organisation adapt, grow and compete in a changing world.