Advanced data analytics created increased commercial value for Pelagia
2020 summer project
There are many more advantages to accessing and using data than before. Summer students from Itera were tasked by Pelagia with structuring and automating a specific type of data and looking at options for how it could generate greater commercial value.
Pelagia is one of the world’s largest producers of pelagic fish products, which it dispatches from its factories the length of Norway’s coast to markets across the world.
In addition to providing fish for human consumption, Pelagia is an important supplier of essential ingredients for all kinds of fish and animal feeds in the form of protein concentrate, fishmeal and fish oil.
Pelagia has 28 locations across Norway and countries including the United Kingdom, Ireland, Denmark and Ukraine.
June 2020 - August 2020
2x Business Consultants
Itera’s offices in Nydalen
Recent years have seen an enormous increase in the amount of data being generated. This growth is creating enormous opportunities for those businesses that manage to make use of this data in a smart way.
Pelagia had a manual process for collecting a specific type of data and no proper structure to the data it collected, and this made it difficult to use it for analytical purposes.
Pelagia therefore wanted to automate how this data was collected and to investigate whether it was possible to used advanced data analytics and machine learning to create commercial value.
The Pelagia team
In order for companies to succeed in working in a data-driven way, it is crucial that they have a good team that is capable of providing insights and leading the organisation’s data-driven development. An essential requirement for such teams to work as well as possible is that they have expertise in a range of different disciplines.
Itera provided an interdisciplinary team consisting of two developers and two business consultants. The team set up a dedicated database in Azure and linked Pelagia’s existing data to this in a structured way. The team also created methods for automatically collecting new data sets.
Using the new database, the team employed advanced data analytics and machine learning to extract insights from the data. Based on these insights, two strategies were produced, each of which would generate increased commercial value.
The project provided insight into an area with significant commercial potential for Pelagia. In concrete terms, the team’s recommendations provide the foundation for a return on investment that is ten times higher than the cost. The project also highlighted the importance of taking a more data-driven approach and provided Pelagia with specific advice on achieving this.
Despite the data processed for the project being of a specific type, other possible commercial areas were identified to which the insights from the analysis could be applied – something which demonstrated the potential of working with data and analysis in a structured way.
The team’s recommendations provided the foundation for a return on investment ten times higher than the cost