One of the foundations to an effective energy transition strategy is the Discover phase. This consists of three actions designed to set out the problem, gather the information required to begin solving it, and put in place tried and tested techniques to turn data into understanding.
Confronting decarbonisation means different things to different companies. To many, decarbonisation represents an opportunity to operate a leaner and more efficient fleet at a reduced cost. To others, it is necessary to access more lucrative contracts, or better finance rates. For a few, a minimal compliance approach might suffice in the short term.
Defining a route to decarbonisation requires businesses to know their desired outcomes in detail. Ask probing questions and commit to honest answers: Does the company still want to be operating ships in 2030 and beyond? If so, which ships? Which trade routes? Which charterers, cargo owners, trade partners, port states, financiers, and insurers does the company need to work with to remain competitive? What effects are emerging regulations, policies and laws likely to have on current fleet renewal programs and asset values?
Try to distil this learning into a single short statement which defines the decarbonisation challenge from a company-centred perspective.
“One of the biggest opportunities we have in the maritime sector is to use the data we already have. There are large amounts of interesting data not being used and dying on paper or in spreadsheets in email inboxes.”
Arnaud Dianoux, Founder and Co-Founder at Opsealog
Once the desired outcomes of the decarbonisation program have been established, the next action step is to gather raw data. This means measuring as much as possible as accurately as possible. Vessel operators who contend with CII, EEXI, EU ETS, MRV, IMO DSC etc. will already be familiar with the growing importance of collecting data from their ships and operations.
It is important to remember that the data already gathered for compliance purposes may also provide the key to making improvements to safety, efficiency, cargo throughput, and profitability. Many conventional sources of ship data are likely to be recorded already in one way or another. These include vessel position, course, speed, trim angles, weather, sea state, and tidal conditions, engine parameters such as fuel flow, power and load settings, exhaust gas temperatures, propeller revolutions-per-minute, roll, pitch, yaw, surge, and sway parameters, berth or gantry crane productivity, idle time, and others.
But the most effective decarbonisation strategies look beyond obvious data sources to uncover more “speculative” data. This is data which may not have a pre-established relevance, but could yield new insights or avenues of understanding. This data could include generator load demands, cabin temperatures and humidity, deck lighting configurations, typical handling strategies for responding to bad weather and counter currents on passage, fuel consumptions at anchor or while awaiting port services such as tugs and pilots.
It is important to recognise two key factors in data collection: accuracy and consistency. A powerful way to ensure both of these conditions are met is to consider which data could be collected and recorded digitally.
While it is likely that noon reports will continue to provide a vital data link with vessels at sea, some operators augment this with high frequency data streamed directly from sensors. This dramatically increases the amount of data points gathered (known as “resolution”), without placing additional demands on officers and crew. Where this is implemented, it is vital to ensure that data quality is considered. Your software or platform provider should provide a robust mechanism for identifying erroneous data in automated data streams.
Analysing data in complex problem solving is a specialist field of expertise. However, the basic principles are simple and taking a structured and logical approach is the most important thing.
Visualisation is perhaps the most powerful tool when analysing data. A graph which plots a parameter over time, or collelates it with a related parameter (for example, a speed – consumption curve) can be a simple but effective way of spotting trends. Use the mission statement produced in step 1 (define) and consider the range of data identified in step 2 (gather) to decide what insights could be generated during analysis.
Focussed Gap Analysis
It is now possible to conduct a gap analysis. This method builds a picture of the “present state” and “target state”, revealing the gap between them. For example, comparing an attained CII rating with a required CII rating for a particular vessel will show the gap between compliant and non-compliant. Calculating a ‘D’ or ‘E’ rating will require a corrective action plan and this alone provides a specific goal (produce a corrective action plan) and a defined timeline (1 – 3 years depending on the rating).
In summing up, the Discover phase is paramount in devising an effective maritime energy transition strategy. It necessitates a methodical approach starting with defining the specific decarbonisation goals, gathering pertinent data, both conventional and speculative, and then analysing it systematically. Visualisation tools aid in discerning patterns, while a focussed gap analysis pinpoints the chasm between the current scenario and the intended outcome. Employing this structured framework not only streamlines the complex process of decarbonisation but also sets the foundation for informed and actionable strategies in the maritime sector.