Top five data hygiene practices for digital transformation
By Robert Platt
Good data hygiene is no longer a technical nice-to-have – it’s a strategic necessity. Clean, well-governed data drives smarter decisions, improves efficiencies, and unlocks commercial value.
As more industries embrace digital transformation, they must first tackle foundational data hygiene challenges. Drawing from insights from Intent Communications’ De-mystifying Digitalisation and AI in Maritime campaign, running over the course of 2026, here are the top five best practices every company should adopt:
- Establish strong master data management (MDM):
Master data management provides a single, authoritative source for core business data such as customers, suppliers, products, and employees. Without MDM, organisations risk duplication, inconsistency, and conflicting records. Creating a “single source of truth” is the foundational prerequisite for unlocking downstream AI and Machine Learning benefits. It ensures that key data remains accurate, synchronised, and accessible across departments, creating a reliable foundation for reporting, analytics, and decision-making. Without this clarity, data remains fragmented and unreliable.
- Standardise data quality and format:
Inconsistent formats and poor-quality inputs are among the biggest barriers to effective data use. Standardising how data is entered, stored, and maintained – including naming conventions, formats, validation rules, and taxonomies – helps eliminate ambiguity. Regular data cleansing and automated quality checks ensure information remains usable and trustworthy, reducing time spent correcting errors later.
- Actively repurpose data:
Data should not sit idle once its original purpose has been served. Organisations can extract far more value by repurposing existing data across teams and functions. For example, operational data can inform strategy, while customer insights can guide product developments, and historical performance data can improve forecasting. Don’t let collected data become dead weight. Treating data as a reusable asset maximises return on collection efforts and supports innovation. It can turn a data liability into a potential new revenue stream, maximising the value of every byte of data collected.
- Mitigate fear of liability through clear governance:
Many companies underuse valuable data due to concerns around privacy, compliance, or misuse. Clear governance frameworks help address the fear that data sharing will be used against operators (ie, in legal discovery or for higher insurance premiums). Define ownership, access permissions, usage policies, and retention guidelines so teams understand what they can and cannot do with data. Establish clear, anonymised, and legally protected frameworks for sharing non-commercially sensitive data to foster industry collaboration and safety. This strong governance builds confidence, reduces risks, and enables responsible data sharing across the organisation and beyond.
- Sweat your low-hanging fruit data:
Not all data initiatives need to be complex or costly. Leverage readily available, existing regulatory datasets – such as Automatic Identification System (AIS) or mandated fuel consumption data (for CII compliance) – to extract immediate commercial and operational value. This provides quick wins and builds organisational muscle in data utilisation. Start by identifying readily available datasets that can deliver quick wins – such as improving existing reports, consolidating duplicate records, or automating manual processes. These early successes demonstrate value, build momentum, and justify further investment in more advanced data programmes.
Maintaining good data hygiene requires ongoing attention, but the payoff is substantial – better insights, reduced risk, and stronger business performance.
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