While data quality and integration obviously play a prominent role, the human element is also fundamental to ensuring the success of digital solutions. Platforms, algorithms, and software are created by humans, for humans – with people and data working hand in hand to help companies achieve their efficiency and sustainability goals.

The shipping sector is under greater pressure from its customers and investors to demonstrate sustainability – and these people represent one aspect of the human element story that is shaping decarbonisation and digitalisation. Good data management helps shipowners measure their emissions levels, giving them a fact-based picture of their compliance and helping them keep track of progress towards their environmental, social and governance (ESG) goals. This will be key for environmental reporting to authorities, and will also help companies prove that they “walk the talk” to avoid accusations of greenwashing.

Good data management also facilitates information sharing between the different stakeholders involved, including partners, service providers, suppliers, regulators and investors – ensuring that they have an up-to-date picture of the situation and are all moving in the same direction.

Creating a digital culture

Cap: Arnaud Dianoux, CEO & Co-Founder – Opsealog

But change management and the creation of a digital culture can be challenging for companies looking to expand their use of data and reap the benefits of digitalisation. Our experience in the offshore sector has shown that we need to persuade people who are currently managing their operations though spreadsheets to come on board by listening to their concerns, understanding their challenges, and helping them to realise that digitalisation is there to serve them, not the other way around. 

We need to help people talk about the realities on the ground and create the dialogue needed to move forward. For example, during efficiency meetings, shipowners and charterers can provide insights that sometimes cannot be seen in the data, and can explain trends detected by, but not explained by, algorithms – a clear demonstration of the importance of the human element.

The importance of the human experience cannot be overstated, and investment in design is important to ensure that users feel comfortable and familiar with the different interfaces, graphs and reports they use. This familiarity helps create trust between the data integrator and the company and enables an organisational culture where people are open-minded and willing to test new solutions and new ways of working.

How to achieve big results from limited data

We need to accompany each company and each person on their digital journey, even though they might have different starting points. That journey need not be long and arduous. Our experience has shown that tremendous progress can be achieved with a small amount of data, if that data is of good quality.

From data on the position of vessels in real time, reporting and weather, we can get important insights into how the vessel is operated, and how much could be saved by making practices more efficient. For example, in our pilot project with Identec and Shell’s fleet in Nigeria, we were able to create an algorithm that delivered important insights into operational patterns solely by using data on GPS positioning (which was updated every few minutes), and combining it with weather data and the operation of the vessel as reported by the captain through noon reports and e-reporting solutions.

It is important to choose which data elements will be meaningful and then ensure that data quality is sufficient to feed in to algorithms and create real value. It is also important to remember that the data processes we have in place today will need to be constantly updated throughout the industry’s sustainability transition. For example, at present, measurements are based on the fuels currently on the markets, and the way we collect and process data will have to evolve to respond to the arrival of new fuels.

The future will also see artificial intelligence and machine learning play an even greater role than they do already, due to their capacity to handle large volume of data. But it is still the human element that will bring that data to life and set and achieve goals with it.

Marex Media