Fast-forward 8 years and what turned out to be an early foray into a nascent field, has evolved into a full-blown revolution. Data is now gathered, processed and used in novel ways to support decision-making in the maritime industry. I work every day at Vortexa  with a unique and exciting setup that consists of the very best data scientists, engineers and energy analysts in the industry. With our technology and expertise we are truly able to harness the power of data. Our aim is to increase transparency and make sense of what is hidden from the view of not only the general public, but often also from insiders, in what still remains an opaque and complex industry. Understanding the way troves of data are being employed and how this impacts our industry is the subject of this month’s newsletter.

Firstly, data needs to be accessed and or acquired. Usually that’s not the difficult part as most companies will be able to source data the same way as everyone else, by using their own. Having access to multiple datasets is more challenging, especially when this involves data not easily accessible to the general public such as information on vessel bookings, also known as fixtures, or detailed cargo information, usually only accessible through port agent records. The difficult part – and the one most companies fail at – is integrating that data into their respective workflows. That means extracting its value and making it available to decision-makers in a fast way, and most importantly in a language that is understood and easily digestible, which is easier said than done! The risk is that large amounts of data will be gathered and end up as what I call “data silos” within the organisation without any significant value extracted. Like a ship owner once said to me: “It’s no use hiring fifteen PhDs if you don’t have a vision for your data!”. So what would a vision for one’s data look like in the maritime space? Time to introduce Freight Analytics 101.

Freight analytics 101 ?

Before defining freight analytics, it’s worth focusing on analytics. So how have analytics come about? Gil Press, senior technology contributor at Forbes, argues it emerges from the marriage of the very old field of statistics with the relatively new one of computer science. In turn, analytics are now understood to belong in four different fields, a classification we explored during our most recent event: The Rise of Freight Analytics (available on-demand if you click here). We are going to walk through each of them and use an example relevant to the freight industry:

Descriptive analytics

Descriptive analytics use data to describe (surprise) what’s happened and/or what is happening. An example of this in freight would be the aggregation of tonne-miles data on the VLCC Middle East to Asia route. This analysis could then be used to look at the impact of Covid-19 on volumes on this route for example. Shipowners can use this analysis to track their performance against competitors for example, to measure how well utilised their fleet is versus others.

Diagnostic analytics

This type of analytics is a bit more subtle. Beyond descriptive capabilities it seeks to answer the question “why did this happen?”. An example of its application can be seen through the business case of our data partners, Windward. By analysing vessel behaviours, Windward are able to assess why a vessel may have come under the threat of sanctions following suspect and/or potentially illicit activities. In turn this allows their clients to address sanctions risk and take the appropriate actions to protect themselves against it.

Predictive analytics

Predictive analytics is currently the name of the game. The introduction of technology such as machine learning, that allows us to predict possible outcomes, really starts to introduce a wide range of possibilities. Infinite really, only limited by one’s imagination. Seeing what the future holds seems a lot more possible with predictive analytics. Vortexa’s freight analytics such as vessel availability, that allow to assess how many vessels will be able to be in one place at a given time in the future, allows to infer critical information as to the future of freight rates and/or one’s own trading opportunities, for example. Our use of our proprietary machine learning technology allows the extraction of more value from our data, to better meet our users’ needs.

Prescriptive analytics

An enhanced version of predictive analytics, prescriptive analytics are the ultimate goal when it comes to harnessing the power of data. This is the moment you hear the slot machine go bonkers in the casino. Prescriptive analytics encompasses using analytics to not only show you what happened, what is happening and what could happen but also goes as far as recommending a certain course of action based on all the latter. Taking the example of a list of available vessels generated by an analytics dashboard, prescriptive analytics would let that same dashboard pick the best vessel for your needs based on a range of factors that could be tailored to each user, each company. This has the potential to turbocharge earnings whilst minimising costs by increasing the efficiency of the chartering process.

What’s next? ⏰

The energy and shipping industries are worth a combined $7 trillion, yet remain ripe for disruption as most trades occur behind closed doors and flows of product away from the public eye, far out at sea. This incredibly fragmented industry could benefit tremendously from complete analytics to change the way data is being collected, processed, transformed and consumed. The goal of this month’s newsletter was to highlight how troves of data are being used in novel ways, using cutting-edge technology, to give participants in the energy freight markets an edge. I believe no company is better placed to help these participants than Vortexa.

Meet us at Posidonia 2022

Don’t miss the opportunity to meet Arthur and the rest of Vortexa’s freight team at Posidonia 2022: Click here to find out more and book a meeting.