3 min read
The language of jobs: Tech North’s digital jobs workshop
Who is working on jobs and skills in the UK?
There’s a rich seam of work on skills and jobs in the UK, but it’s often difficult to determine just how rich it is. We wanted to get to grips with the constellation of organisations who are mapping, providing data, and researching the modern labour market in order to create a community of practice.
Selfishly, there’s a lot we could learn from this community, and altruistically, we felt that we could each support the learning and development of one another – if only we knew who was out there.
What are other organisations doing?
Organisations are not all the same – they fulfil particular roles in the network, and have very different interests, motivations and modes of operation. In spite of this, there is much that could be gained from making all of these institutions more aware of their peers, and potential collaborators. In this sense, we looked to create a community of practice – helping each to learn from one another and grow collectively.
Firstly, Bob Clift, Head of Higher Education Programmes, and Craig Hurring, Head of Marketing and Communications at the Tech Partnership. Bob and Craig introduce attendees to their Common Language project – a programme to work towards a shared understanding from employers and higher education providers when it comes to the language used to describe skills, and components of jobs.
They identified a failure in the way skills are communicated, leading to information asymmetries when it comes to labour market opportunities. By developing a shared sense of what is meant by these skills terms, the Tech Partnership hope to reduce friction in the labour market – making it easier for graduates to get jobs, and employers to fill shortages or gaps in the workforce.
Secondly, Dr. Cath Sleeman, Quantitative Research Fellow in the Creative Economy and Data Analytics team at Nesta talked about her work using data from Burning Glass Ltd – a Boston-based company harvesting, classifying and cleaning job advertisements for the UK. Cath spoke about some of the opportunities and challenges in working with this type of data, and illustrated the value of interactive visualisation as a tool to enable exploration and interaction of job data via two projects: The UK needs a Skills Map and A closer look at Creatives.
Cath also mentioned the work that Nesta is currently doing as part of the Office of National Statistics’ (ONS) Economic Statistics Centre of Excellence – also using data from Burning Glass Ltd. to create a skills based taxonomy for jobs – a bottom up alternative to classification of jobs, as opposed to the top down Standard Occupational Classification system that is commonly used in the UK.
How can we learn from this work?
Without a central repository for these organisations, we firstly began mapping the connections between organisations based on 1) website content, and 2) the knowledge of the landscape that we had – which, through snowball sampling, led to a large cohort. This allowed us to the develop a resource – a network map that connects organisations, their placement determined by their level of connectedness.
Organisations were mapped as nodes, and the connections were plotted as vertices using the Gephi software package. All information is being pulled from an accessible cloud database, so team members and roundtable participants could add to the mapping exercise as more data points were discovered. The snowball sampling method meant it was crucial to make the data source open and accessible to all.
Purple and orange nodes represent government departments and organisations aligned to government, whilst blue nodes are private companies. Green nodes are ThinkTanks, interest groups and innovation hubs.
[button type=”default” size=”lg” link=”https://technation.io/wp-content/uploads/2017/11/MAIN-CIRCLE-1.pdf”] View the full diagram [/button]
In particular, the ONS is the most dominant organisation within the network. This finding is unsurprising given the reliance on the office’s data and existing SOC taxonomy. The most recent SOC taxonomy was developed in 2010. This is the core terms of reference in the space, and is what the majority use when analysing the labour market.
The ONS has more than 38 distinct connections with other organisations. Almost all of these connections exist where a secondary organisation uses ONS data. For instance, Tech City UK relies heavily on ONS data for the yearly Tech Nation report, whilst the Treasury make decision based this data. In the context of job role taxonomies, relying on SOCs from the ONS is potentially quite problematic as the codes are only updated every ten years. It is generally agreed that the codes are not keeping pace with the volatile dynamics of the changing labour market.
Perhaps more surprising is the fact that companies are very much at the periphery of the network. Their limited connections puts them in the outer reaches of the skills system – which, given their use, and vested interest in having a steady supply of skilled people, made us wonder how we could move these organisations further into the core of the system.
Whilst this simple network is useful, network analysis really comes into its own when using big data. Larger datasets allows the user to uncover sub-communities and perform statistical analysis on the nodes and vertices.
Additionally, I have recently commissioned Adzuna to provide digital job advertisement data for the North of England stretching back over a three year period. Each job advert will assigned a uniform role title and set of skills required to perform the role.
The role title will be broadly based on the European SOC code taxonomy. The will provide a holistic picture of skills demand across the North of England, and I anticipate this work to be rolled out across the country as part of Tech Nation. The first results should be available for release early-2018.
This article was co-authored by George Windsor, Senior Insights Manager, Tech City UK