In Part 3 of this series, we asked how an economic developer might go about identifying the niche industries in their region. The solution we proposed was to use two economic functions which are part of our Analyst tool — Location Quotient, which can identify niche industries in terms of actual job numbers, and Shift Share, which can identify niche industries in terms of expected job growth.
However, as we stated at the end of the piece, where things become really interesting, in terms of identifying strengths, is not so much in identifying niche industries as identifying niche skills. In this piece we’ll be looking at a few ideas as to how this can be achieved.
One of the ways an economic developer might begin to approach this question is to simply look at current employment, either in terms of numbers employed, or expected growth over the next few years. Sticking with the Cumbria LEP region, which we used as an example in the last piece, the following table shows the Top 10 occupations in the region in terms of forecasted growth over the next few years:
Although this type of information is clearly useful, it doesn’t quite get to the heart of what makes a region special. In order to dig a bit deeper to identify the region’s niche occupations, and therefore the skillset that really makes it unique, we once again turn to Analyst’s Location Quotient function, which can be run for occupations as well as industries.
As a reminder, Location Quotient is a statistical measure of industry or occupation concentration in an area in comparison to the rest of the country, and it works on a benchmark basis with 1.0 indicating the national average. Occupations with a score of more than 1.0 therefore have an employment profile that is greater than the national average. The following table shows the Top 10 niche occupations at the 4-digit SOC level in the Cumbria region:
As we pointed out in Part 3 when we looked at niche industries, it will be the case that some of these occupations might only employ a few people, and so although they are niche occupations, they are not necessarily of huge significance in the region. Any economic developer using the Location Quotient function would therefore need to take into account actual job numbers as well. It is also worth noting that as with the industry data, a region’s occupational uniqueness can also be measured in terms of job growth using the Shift Share function.
So far we shown methods of identifying both niche industries and niche occupations, but in terms of using information to attract inward investment, wouldn’t the gold standard be to connect the two — that is, to take an industry and to then establish where its skills lie? By using another function built into Analyst — Staffing Patterns — we can indeed do this. This function allows us to pick any industry, even at the 4-digit SIC level , and identify which occupations are employed within the sector.
Let’s take an example. In Part 3, we identified Processing of Nuclear Fuel as Cumbria’s most niche industry, with a Location Quotient of 102.11 in 2014, set to grow to 104.46 by 2020. But what occupations does it employ? The table below shows this, with the Top 10 in terms of employment numbers listed, along with predicted growth, the proportion of the industry that each occupation makes up, wages, and educational levels:
This process of identifying which occupations an industry employs can also be done in reverse — that is, an Inverse Staffing Pattern can be run on any occupation, right down to the 4-digit SOC level, to show which industries employ people in this occupation. So for instance, the Occupation Location Quotient table above showed that the most niche occupation in the Cumbria LEP region is Rubber Process Operatives. By running an Inverse Staffing Pattern we find that of the 301 people employed in this occupation in 2014, 241 were employed in the Manufacture of rubber tyres and tubes; re-treading and rebuilding of rubber tyres sector, 51 in the Manufacture of other rubber products, and the remaining nine in sectors such as the Manufacture of other plastic products.
Having shown a number of different ways of identifying niche industries, niche skills, and how those industries and occupations relate to each other, this still raises the question of how can this sort of information be used to attract inward investment? In the final part of this series, we’ll be showing how one LEP — Thames Valley Berkshire — has been using Labour Market Data, amongst other intelligence, to produce a series of sector reports which they are using to promote the idea of investing in the region.
You can access the previous parts of this series here, here and here. For more information on how our granular data can help you identify the niche skills in your region, contact Martyn Gerard at firstname.lastname@example.org