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Measuring only overall demand for digital skills can be misleading

The overall demand for digital skills does not tell us much about an occupation’s growth prospects. As shown in Figure 1, the occupations that are least likely to grow have a higher digital intensity. Digital intensity can be measured in different ways using the information contained in online job adverts: here, it is measured as the proportion of job adverts for that occupation that mention at least one digital skill. If anything, it appears that occupations that are most likely to decline have a higher level of demand for digital skills.

Figure 1. Digital intensity* of occupations that are most and least likely to grow.

digi skills figure 1

*Weighted average digital intensity is calculated using Labour Force Survey data on share of employment in each 4-digit Standard Occupational Classification (SOC) code

However, we see noticeable differences between the occupations when we factor in the type of digital skills required.

Certain digital skills are much more prominent in occupations with a low probability of growth

The analysis shows that skills related to using software for administrative purposes (e.g. payroll, accounting, supply chain, sales, etc.) are more prevalent in occupations that are predicted to decline. Examples of these software tools include ADP Payroll, Navision and SAP Warehouse Management.

In contrast, digital skills used in animation, engineering, education and computing are more prevalent in occupations that are predicted to grow (Figure 2). Examples of these software include Autodesk MotionBuilder, Ansys and Blackboard LMS.

Figure 2. Coefficients for 15 skill clusters that are most and least predictive of an occupation’s growth prospects.

digi skills figure 2

These findings suggest that not all digital skills will be equally important in the future. The demand for those digital skills which involve non-routine tasks, problem-solving and creation of digital content (e.g. graphic and engineering designs, software products/services, analytical outputs, etc.) is positively correlated with occupations that have brighter outlooks

The relationship between digital intensity and probability of growth is not straightforward

Some occupations are likely to grow, but are not currently digitally intensive (bottom right hand quadrant of Figure 3). These occupations include Primary and Secondary teaching professionals, Chefs, Catering and Bar managers. Other occupations, including Artists, Mechanical engineers and Telecommunications engineers, both require digital skills and are likely to grow (top right hand quadrant of Figure 3).

Figure 3. Digital intensity and occupations’ probability of growth.

digi skills figure 3

Some skills that pay relatively well are more closely associated with occupations that are expected to shrink

It is not only low paid skills that are linked to occupations that are likely to shrink. As shown in Figure 4, there are digital skills in Supply chain management, Procurement and HR management that offer a relatively high salary, but are used primarily in occupations that are likely to shrink. If these predictions are correct, then these skills may become less important in years to come.

Figure 4. Average offered salary over 2012-2017 across skill clusters most prominent in occupations least likely to grow.

digi skills figure 4

Limitations of the analysis

It is important to mention several limitations of this analysis. First, online job adverts have imperfect coverage and tend to be biased towards high-skilled occupations. There are also job adverts with incomplete information on employer requirements. This means that we are potentially missing data on demand for skills, including digital skills. At the same time, compared to alternative sources of data on skills demand, online job adverts still provide the largest sample size and highest granularity for employer skill needs. The adverts also describe digital skills in the language used by employers and because of this are more useful for job seekers and training providers.

Authors

Jyldyz Djumalieva

Jyldyz Djumalieva

Jyldyz Djumalieva

Data Science Research Fellow, Creative Economy & Data Analytics

Jyldyz is the Data Science Research Fellow at Nesta, working in the Creative Economy & Data Analytics team.

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Cath Sleeman

Cath Sleeman

Cath Sleeman

Quantitative Research Fellow, Creative Economy & Data Analytics

Dr Cath Sleeman is the Quantitative Research Fellow at Nesta

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