Using our Real-Time Industrial Classifications (RTICs) the report highlighted 147,000 green jobs in central London across 11 sectors. This article digs deeper into the green jobs report and how our data helped shape WPI Economics’ findings.
The goal of this project was to conduct an analysis of the green economy, particularly looking at the number of jobs within the London boroughs. The first step was finding out how many companies are in the industry and then using Lightcast data to understand jobs within those companies.
At the start of the project, WPI Economics took the Green Jobs Taskforce report and specifically used sections 2 and 3. Within these sections, there is discussion on “What is a green job?”. There is a list of industries (found on pg. 15 & 16) of which WPI Economics drew inspiration from to create our own list of industries:
- Homes and buildings
- Low carbon transport
- Climate adaptation
- Natural environment
- Industrial decarbonisation
- Green financial, professional and research services
- Reduce, reuse, recycle and repair
By comparing the original industries in the taskforce report and our own classification, you would realise that we have added in an extra industry – Green finance, professional and research services. We did this as we thought the industry was both relevant to the project and represented a significant number of the workforce.
We had to build at least one list in our Data Explorer for each of these industries, but in some cases we built up to four for a single industry. For example, Power was made up of Nuclear, Renewables, Energy Storage and Grid. Building a single list that encompasses all of these would be very difficult due to classification methods, so instead, we built a list for each industry and merged all the companies in these lists together to create a single Power industry.
Read more about how lists (and our other technologies) work.
Due to this method, we created a total of 14 machine learning lists for our eight industries. This was a joint effort between The Data City and WPI Economics. We always appreciate it when our project partners engage with the list building process and WPI Economics did exactly this. Throughout the whole project, they were always providing feedback on list keywords and example companies. Not only does this make the process smoother and faster, but it also helps us to create the best and most accurate list possible.
Once the classification for each of these industries were complete, we had a mapping of the green economy for the whole of the UK. You might be asking “why the whole of the UK? Wasn’t this project just for London?” and you’d be right. The problem we avoided by following this method, however, was getting biased results due to the language being skewed towards London-based companies. Having something like “London” in our positive keyword list would be less than ideal. This is a term that does not reflect the sector, but instead a location – this would reduce the quality of the classification.
Using our platform to filter the list down to local authorities in London was very simple. WPI Economics needed to use the list of companies that they had created in our platform and use Lightcast (formerly Emsi Burning Glass) to get jobs data from these companies. Unfortunately, at the time, they had to do this manually. Our product now includes Lightcast data (at additional cost), so doing this job again today would be substantially easier as everything they needed can be seen within The Data City platform.
WPI Economics released their reports on Green jobs and skills in London, all of which can be found on their website. They released different reports for different parts of London, all of which are incredibly in-depth; definitely worth a read.
“ The dominance of the Green Finance sector, representing more than half of central London’s green jobs, remains one of the subregion’s distinguishing features. “Green Jobs and Skills in Central London Final report | WPI Economics
The data from this project was also shared with the different boroughs that came up in the report. They were given access to the platform in order to dig deep into the data.
This project really helped us to develop further projects, and even led to more great work which is currently in progress! Sadly, we cannot speak further about this at the moment – look forward to learning more about it in the future.