In our recent piece for the LEP Network, we highlighted an issue which we believe LEPs need to think seriously about as they approach the forthcoming area reviews into Further Education; that it is potentially dangerous to assume that the economic needs of sub-geographies within their region are necessarily the same as the needs of the region as a whole.
Our concerns have been picked up by UKCES in a piece entitled “Statistics are no substitute for insight and judgement”, which you can access here. The piece concurred with us in highlighting the fact that local geographies are not necessarily going to have the same needs as the broader region, and in fact the demands will often be very different:
“When we say ‘local labour market’ what exactly do we mean? The regional labour market seems far too wide to be local, but street level would be too small to rely on any trends. LEP area seems closer, but there are still distinct sub-geographies that are vastly different, as the blog I read demonstrates. Take the ‘Heart of the South West LEP’ for example; From Barnstaple to Exmouth and Plymouth to Bridgwater, the LEP area covers a geography with 10 FE colleges, 4 Universities, 78,000 businesses, 17 local authorities and a population of around 1.7 million.”
The article then went on to ask how we can provide accurate local labour market information for such a large and diverse area, given the fact that sources such as Working Futures do not provide forecasts for geographies below the LEP level. The answer given in the piece was to suggest supplementing — or perhaps complementing is a better word — the more high level regional data with direct, on-the-ground local intelligence such as employer questionnaires, one-to-one interviews, and even an employer panel. Doing this would combine “valuable, rich and direct insight from a local level” with “comprehensive, robust and reliable information to produce a truly vital local labour market assessment”.
Whilst we agree that direct, local intelligence is useful and indeed needful, we believe that the sub-geography level data that the piece assumes is missing (on account of the raw data sources drilling down no further than the LEP region), is in fact available.
The approach taken by many Labour Market Information (LMI) organisations is to use the raw data for the high level geographies to make broad assumptions for what is happening at the sub-geographies. However, if — as our piece and the UKCES piece both agree — the economies in the sub-geographies are often very different from the regional economy as a whole, making such assumptions is rarely, if ever, going to produce accurate data. In fact, it will often be wildly wrong (for a more in depth look at this, you may find this article helpful).
At EMSI we take a radically different approach. Rather than making assumptions based on the high level data, what we do is to take multiple data sources (including Business Register Employment Survey (BRES), Workforce Jobs Series (WJS) and Labour Force Survey (LFS)) and by using a technique we have developed over a number of years, model them together to retain the strengths and discard the weaknesses of each source. What we end up with is a dataset that gives a complete, detailed and accurate picture not only of regional labour markets, but also of the sub-geographies within.
We can illustrate this by looking at the LEP region mentioned in the UKCES piece, Heart of the South West. This LEP is made up of the following Local Authorities: Plymouth, Torbay, East Devon, Exeter, Mid Devon, North Devon, South Hams, Teignbridge, Torridge, West Devon, Mendip, Sedgemoor, South Somerset, Taunton Deane, and West Somerset (see map).
Using our LMI tool, Analyst, we can show not only detailed and accurate data for the high-level region, but also for all the sub-geographies beneath. So for example, the following graphs show the Top 10 industries in terms of numbers employed, firstly for the Heart of the South West LEP as a whole, and then for two sub-geographies — Plymouth and North Devon — below:
As you can see, whilst there are some industries that are represented in all three geographies, there are others that are specific to the smaller areas. For instance, Building of ships and floating structures is a big employer in Plymouth (4,592 jobs), whereas it doesn’t feature at all in the Top 10 industries for North Devon or indeed the Heart of the South West LEP region as a whole. In fact, according to our data, there are only 50 people employed in the Building of ships and floating structures throughout the rest of the LEP region, which just goes to show the vital importance of being able to dig down into data for these local areas.
We might also look at expected job change for industries in the region over the next few years, and again our data allows us to show not only the broad regional figures, but also to delve down into the sub-geographies:
As above, it is crucial to note that the sub-geographies have a very different mix of industries and priorities (and the same would be true for occupations). For instance, the biggest growth industry in North Devon over the next three years is expected to be the Manufacture of pharmaceutical preparations, whereas in Plymouth the industry not only fails to make it onto the list of Top 10 growth industries, our data actually shows that there is currently no employment in the industry in Plymouth.
In conclusion, it is vital for those involved in the steering groups — whether LEPs, Local Authorities or colleges — to be aware of the industry and occupation needs not only at the regional level, but also in the sub-geographies. The UKCES article posed the question of how this can be done, and concluded that in the absence of accurate local data the most effective method is to compliment the high level data with direct employer contact. However, whilst we agree that contact with employers is important, the fact is that accurate data at the sub-geographical levels is available, as we have briefly demonstrated above. By using this data, LEPs, Local Authorities and colleges can be confident that they have the intelligence needed to understand the economic needs not only of the region as a whole, but of the smaller sub-geographies too.
For more details regarding our data and our Analyst tool, contact Andy Durman (firstname.lastname@example.org)