This landmark paper set out the case for a rigorous classification of creative industries and occupations that became the basis for the creative industry statistics of the UK’s Department of Culture, Media and Sport (DCMS), which has since become a world standard. It resulted from a collaboration between Hasan Bakhshi of the UK think tank NESTA, Alan Freeman at the Greater London Authority, and Peter Higgs of Queensland University of Technology.
It argued that despite its strengths, the DCMS classification system, dating back to 1999, contained inconsistencies which had to be addressed to make it fully fit for purpose. It presented an improved methodology which retained the strengths of the DCMS’s approach while addressing its deficiencies. Its focus was creative intensity: the proportion of total employment within an industry that is engaged in creative occupations.
Using the list of occupations which DCMS treats as ‘creative’, the intensity of the industries it defines as creative falls within a narrow range – with only minor exceptions – that is on average over 25 times greater than in the rest of the economy. This is a defining characteristic of such industries. However, DCMS’s choice of industries excluded important codes with high creative intensity that account for large amounts of employment.
In addition, DCMS’s choice of occupations was itself open to question, because the criteria by which they were classified as ‘creative’ was not clear. The paper proposed a rigorous method for determining which occupations are creative, scoring all occupations against a ‘grid’ of five theoretically grounded criteria. The core concept that this grid articulates is that of ‘non-mechanical’ labour – labour that cannot be replaced by a machine.
The paper then proposed a fully consistent classification by using these occupations to identify, on grounds of creative intensity, those industries that appeared inappropriately included and excluded in the DCMS industrial classification (the ‘baseline’). We conducted a sensitivity analysis to show that this classification lays the basis for a robust and consistent selection of industry codes. This accords with the reality, which should be squarely faced, that uncertainty is a defining feature of emergent areas subject to persistent structural change like the creative industries, and should be dealt with in a systematic way.
Our baseline classification suggested that the DCMS inappropriately excluded a large (and growing) software-related segment of the creative industries. We argued that significant numbers of new digital creative businesses in fact reside within this segment, reflecting an increasingly tight interconnection between content production and its digital interface.
Our estimates showed that creative economy employment had become a highly significant and growing component of the workforce as a whole, accounting for 8.7 per cent of it by 2010 as compared with 8.4 per cent in 2004. They also confirm a feature of DCMS’s estimates been documented in previous Nesta research: the majority of creative workers are employed outside the creative industries in the wider creative economy; this part of the creative workforce has grown particularly strongly, rising by 10.6 per cent between 2004 and 2010.
Our work showed that the creative industries do not rely, either wholly or mainly, on traditional content or ICT activities alone. Rather, a new economic phenomenon has emerged characterised by a parallel application, within single industries, of ICT and other creative skills together. This strongly suggests that any attempt to separate ICT from other creative work or to reduce the creative industries either to an offshoot of content production, or for that matter a branch of the software industry, will not succeed.
Thus our sensitivity analysis included, among other possible variants, the impact of removing the main software occupation codes from the list considered to be creative occupations. Even after this is done, software industries employing large numbers of people emerge as intensive users of the remaining creative occupations. On this alternative scenario, the software-related industries still contribute 213,000 jobs to the creative industries. The non– software creative industries are also very important employers of ICT labour.
We described our approach as a ‘dynamic’ mapping because a systematic method for identifying the ‘most creative’ industries produces a classification that does not over¬react to small fluctuations in the underlying data, but can respond to structural economic changes. Intensity data can be used to compare like with like over time. We thus derived a robust estimate of growth of creative economy employment which, between 2004 and 2010, rose by 6.8 per cent – more than five times the growth rate of the non-creative workforce, measured on a comparable basis. In 2010, almost 2.5 million were employed in the UK’s creative economy, of which 1.3 million worked in the creative industries.