In parts one and two of this series, we looked at how data can be used to identify the industries and occupations which give an area a competitive advantage. In this third and final part, we turn our attention to skills, looking at how localised data can help education providers and economic developers better understand which skills are in-demand in their region, and identify potential skills gaps to be filled through training. Once again, all the data used is from three adjacent LEP regions: Greater Manchester, Leeds City Region and Lancashire.
Fastest Growing Skills
We begin by looking at which skills have grown the fastest in the three LEP regions over the past year, which you can see in the charts below (you can toggle between the areas using the arrow at the top). Across all three areas, growth in the Top 20 skills is slow and steady from July through to October, with noticeable drops occurring during the second and third Lockdowns. However, this is followed by a surge in growth in February and March of this year, with a number of skills seeing strong growth across all three areas. For instance, as we would have expected, demand for Personal Protective Equipment (PPE) has grown massively in the past 12 months, with growth of 105% in Greater Manchester, 155% in Leeds City Region and 122% in Lancashire. Microsoft Azure, Supply Chain and Automation have also seen high growth across all three.
There are also a number of skills that only appear in one of these regions' Top 20s, and it is here that we can really see the value that the granular, local data brings. Here are some examples:
- Greater Manchester: Data Analysis (86% growth), DevOpps (86%), and Warehousing (76%).
- Leeds City Region: Merchandising (102%), Environment Health And Safety (91%), and Digital Marketing (80%).
- Lancashire: Plumbing (125%), Mechanics (117%), and New Product Development (91%).
One other very noticeable skill is Restaurant Operation. This is absent from all three regions' Top 20s throughout much of the period, for obvious reasons, but in February demand suddenly grows massively in anticipation of the reopening of large parts of the hospitality industry:
Another way we can look at skills demand is to look at the number of times particular skills have been mentioned in employer job postings over the past year. In the charts below, as well as separating out the three regions, we've also split the skills into those requested for occupations which are high, medium or low skilled. By and large, a lot of the same skills crop up across all three regions, with Agile Methodology and Business Development particularly prevalent in the high skilled occupations; Accounting and Personal Care prevalent in the medium skilled occupations; and Warehousing and PPE in demand in low skilled occupations. There are, however, some skills which are noticeably in-demand in just one area. For example:
- Greater Manchester: Microsoft Azure (high skilled); Forecasting (medium skilled); Customer Relationship Management (low skilled).
- Leeds City Region: Paraplanners (high); Legal Secretaries (medium); Kitchen Assistants (low).
- Lancashire: Finance Managers (high); Care Workers (medium); Domestic Assistants (low).
Finally, the issue of skills gaps hindering growth and prosperity has been cropping up time and time again over recent years, and all the more so in the post-Brexit, Covid-disruption economy. Again, data can be used to shed light on this issue, by comparing demand for certain skills in an area with the available workforce supply of those skills, highlighting where there seem to be significant gaps.
The radar chart below attempts to show this, by taking the total number of postings for a particular skill over the last year in all three LEP regions combined, then comparing this to the number of worker profiles in the same geography where this skill is mentioned in our Profile Analytics (which contains over 16 million UK worker profiles). For example, there were 36,286 unique job postings (demand) mentioning Accounting over the last year and 41,082 worker profiles (supply) that mention this skill. Hence the number of mentions of this skill in the workforce supply data is 113% that of demand for the skill in the 12 month period. This is admittedly a somewhat crude way of identifying skills gaps, not least of which because our Profile Analytics data doesn't capture all workers in an area, and also because employers and employees don't always use the same language when describing jobs and skills. Nevertheless, it does give some indication of where there might be significant skills gaps in the area, and therefore where there might be a need for courses teaching certain skills.
As you can see, there are some in-demand skills where potential supply appears to be very strong, including Business Development, Customer Relationship Management, Selling Techniques, Risk Analysis and Forecasting. At the other end of the spectrum, there are significant gaps between skills supply and demand for things like Personal Care, Nursing, Mental Health, Warehousing and Agile Methodology:
As we have shown in these three pieces, the concept of "place" is extremely important since different locations, even those in close proximity, can often have a very different mix of industries, occupations and skills. For education providers and economic developers, a good understanding of this kind of local data could well be key to helping their area to return to growth.