A fleet is not digitally mature simply because it uses many tools in parallel. What matters is whether data flows consistently and tools improve decision-making.
Data quality, system integration, operational usage, governance and adaptability.
It starts with concrete process chains, not benchmark slides.
Robust prioritisation: master data, roles or interfaces first.
A useful maturity model for maritime operators comprises five dimensions that must be assessed independently. The first dimension is data quality: are master data consistent? Are running hours, equipment IDs and spare part references uniformly maintained? This dimension is the foundation – without it, all further steps remain fragile.
The second dimension is system integration: how well do the existing systems communicate with one another? Can data from the PMS flow automatically into the procurement system or reporting, or are there media breaks where information is transferred manually? In many fleets, three to five systems exist in parallel with no or only rudimentary connections.
The third dimension is operational usage: are digital tools actually employed in daily operations? Or do they exist formally whilst actual decisions are made on the basis of spreadsheets, emails or personal experience? Usage rate is one of the most honest indicators of digital maturity.
The fourth dimension is governance: are there clear responsibilities for data quality, system changes and user training? Do defined processes exist for introducing new tools or decommissioning old ones? Governance is the organisational framework that holds the other dimensions together.
The fifth dimension is adaptability: can the organisation integrate new requirements – such as regulatory changes like CII or EU ETS – into its digital infrastructure within a reasonable timeframe? Or does every new requirement necessitate a special project with external consultants?
Many operators attempt to assess their digital maturity internally. This is sensible in principle but frequently fails due to two factors: overestimation and a missing benchmark. The IT department rates the system landscape as good because everything runs. The operational side perceives the same landscape as inadequate because the data is wrong.
A realistic assessment must bring both perspectives together. It must ask questions such as: what percentage of equipment entries in the PMS are complete and current? How often are data between vessel and shore manually corrected? How many decisions per week are based on data from the official system versus unofficial sources?
The benchmark matters too. Digital maturity is relative – not every operator needs the same level. A feeder operator with five vessels has different requirements than a tanker company with forty ships and complex compliance obligations. The benchmark must fit the business model.
What an assessment should deliver in any case: an honest stocktake of the current situation, a prioritisation of next steps and a realistic estimate of effort. Glossary-rich maturity slides without operational relevance are worthless.
Compared with aviation and the automotive industry, shipping lags behind in digital maturity – this is no secret. The reasons are well known: limited connectivity, heterogeneous fleets, rotating crews and a conservative investment culture.
But within shipping, there are substantial differences. Large container lines and specialised offshore operators have invested heavily in recent years and work with integrated platforms, standardised processes and dedicated digitalisation teams. At the other end of the spectrum are tramp operators and small bulker companies still working with paper-based documentation and isolated systems.
The middle group is particularly interesting: operators with ten to thirty vessels who have introduced individual digital tools but pursue no overarching strategy. For this group, a maturity analysis is especially valuable because it reveals where existing investments deliver the greatest leverage – and where they are falling flat.
A maturity analysis is not an end in itself. It must lead to action. Three rules for effective use: first, focus the analysis on specific process chains – not the entire organisation. A maintenance process chain from damage report through to spare part delivery is a better subject of analysis than the digital maturity of the whole company.
Second, translate the results into a maximum of three action areas. Attempting to implement ten recommendations simultaneously means implementing none. Third, review the maturity level regularly – annually, for instance. Digital maturity is not a state but a process.
The most common findings in practice: master data quality as the first action area, followed by interface clean-up between PMS and procurement, followed by clear role definitions for operational ownership. Technology rarely comes first – organisation and data take priority.
A maturity assessment that asks vessel crews to fill out new questionnaires on top of their existing reporting burden tends to produce reluctant, defensive answers rather than an honest picture. The more reliable approach draws primarily on data that already exists: usage logs from the PMS and procurement system, the age and completeness of equipment records, the volume of open change requests, and how often shore staff manually correct data received from vessels. Interviews are still necessary, but they should be reserved for filling specific gaps the existing data cannot answer, not for generating the assessment from scratch.
Timeboxing the assessment matters as much as the method. An open-ended review that drags on for months loses momentum and starts to feel like an audit rather than a diagnostic. A tighter assessment, focused on two or three process chains rather than the whole organisation, delivers usable findings within weeks and keeps the operational side engaged instead of treating every question as one more distraction from running the fleet. The findings should go back to both the shore team and the vessels involved, since crews who never hear the outcome of an assessment they contributed to are unlikely to cooperate with the next one.
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