This project aims to develop a way of measuring the greenness of online job adverts. Without a clear definition of what green jobs and skills are, and useful ways to measure them, policymakers, employers and other crucial actors cannot make informed decisions or plan effectively for one of our most significant workforce transitions.

We want to help solve this problem by creating an open-source approach to measure greenness at the job advert level, using a multi-dimensional measure to identify how green a given job advert is based on industry, occupation and skills. We will also be working with stakeholders to understand and design for potential applications of this data across the green jobs system.

Our aim is to support the green job sector by helping people to identify how green jobs really are. If we can create a measure or tool for this purpose, we will enable a number of different actors to make better decisions about green jobs. This might be providing job seekers with additional information, providing local government with better information on how to support skills transitions or providing policy teams with new insights on emerging green sectors or jobs.

There is a broad push at the moment to build better definitions of green jobs in order to support the UK’s move to net zero. We think we can make a unique contribution to this effort by focusing on micro-level, multi-dimensional and continuous measures that are widely usable and by making our work open and accessible to other stakeholders.

We are developing an online tool that will measure industrial, occupational and skill-level greenness which we are calling ‘GROWS’ (green roles, occupations and workforce skills) to be used on any given job advert. Our tool assesses each job against established occupational industry and skill greenness measures to determine how ‘green’ that role is.

So far, our work has focussed on capturing green measures from external sources. At the occupational level (i.e. the job role), our tool matches job advert text to datasets on the following measures:

• Green occupational category: ‘green enhanced skills’, ‘green increased demand’, ‘green new and emerging’ or ‘non-green’ found via an O*NET-based classification of occupations.
• Green timeshare: Estimates of the fraction of time spent doing green tasks (as defined by O*NET’s green tasks definitions). More about this methodology can be found on the ONS website.
• Green topic: How many green topics an occupation is linked to. This refers to the O*NET list of 72 green topics and linked occupations. For example the green topic ‘clean energy’ is linked to the occupation ‘energy engineers, except wind and solar’.

We applied these measures to job adverts by predicting the standard occupational classification (SOC) - the common classification of occupational information for the UK - from the job title, to link these to occupational datasets. We then did the same for standard industrial classification (SIC) to link to datasets for our green industry measures. For our green skills measures we directly predict skills in job adverts and then map them to the ESCO list of green skills using our existing algorithms.

By assessing job adverts against our suite of green measures, we’ve been able to identify interesting data points that give us insight into the green jobs market.

For example, through our early-stage analysis, we’ve found jobs from industries that typically have high greenhouse gas emissions that are in fact spending high proportions of their time on green tasks, and have a high proportion of green skills. Some examples would be a corporate social responsibility role in a freight and logistics company, or jobs in refuse and salvage. These jobs do not fit into the usual binary of 'green' or 'not green'.

We are in the process of improving our algorithms to match SIC and SOC codes and explore different ways to match to green skills.

This way, we will be able to more accurately link this information to external green datasets, making the tool and our assessment of job adverts more robust. We will also continue analysis of green measures to give us insight into the green jobs market.

We are now focussing our efforts on how we make our green measures useful to stakeholders interested in measuring green jobs, using our data to support their research and analysis.

This work forms part of Nesta’s sustainable future mission, which is focussing on how the switch to a greener, lower-carbon economy can also increase the UK’s productivity. One of the main ways of doing this is to create more highly skilled jobs in green industries and seek innovative ways to get more people training for and working in highly paid, highly productive green jobs. 

Our project is part of the UKRI-funded PRINZ (Productive and Inclusive Net Zero) project group, which includes researchers from Imperial College London, University of Leeds, LSE, University of Oxford and the University of Surrey. This project aims to explore the link between productivity, the transition to net zero and levelling up to create more jobs. 

Our approach builds on previous work on extracting skills from job adverts which was created by Nesta in partnership with the Department for Education and the Economic Statistics Centre of Excellence (ESCoE). The aim of the Observatory is to provide insights from online job adverts into the demand for occupations and skills in the UK. We are collecting the adverts with the permission of job sites and to date we have collected several million job postings.