Tech Nation 2016: much more than disruption
Our new Tech Nation 2016 report, done in partnership with Tech City UK, combines official and big data to measure growth in the UK digital tech economy. It also shows the spread of digital tech into other industries, and maps the networks that connect UK digital tech businesses.
Tech Nation 2016: much more than disruption
“Digital tech is a force for disruption”. Often, these words feel like a threat. They make us think of industries upended, jobs automated, business models evaporated.
But disruption has a positive flip-side: namely, diffusion. When it encourages established industries to adopt better technologies, it drives innovation - just look at how retail is being transformed by e-commerce. When it challenges existing practices and gives rise to new ones, it results in new professions, such as social marketing in advertising. When it creates new markets - or lowers barriers to entry in old ones - it creates opportunities for businesses across the country. There is nothing inevitable in diffusion though. It requires networks over which new ideas circulate and talent can collaborate, in the same way that markets enable firms to compete.
Tech Nation 2016, the report Nesta is publishing today with TechCity UK, combines official micro data and new, ‘big’ data sets, to look at growth in the digital tech economy, the diffusion of digital tech into other industries, and the networks that make this possible.[i] .
Tech Nation 2016 tells a story of digital tech growth across the UK
Our analysis shows that:
- The Digital Tech Economy - comprising people working in Digital Tech Industries and digital professionals embedded in other sectors - employs 1.56Mn people and grew almost three times faster than the rest of the workforce between 2011 and 2014.[ii]
- The Digital Tech Industries contributed £87Bn in gross value added to the economy in 2014. Workers in Digital Tech Industries are 90% more productive than those in other sectors.
- Digital tech isn’t just about London. In fact, 75% of digital tech businesses are found outside of London, and so are 80% of Digital Tech Economy jobs. Of the 27 areas that are profiled in Tech Nation 2016, 8 in 10 grew their jobs between 2011 and 2014, and the same proportion grew their contribution to the economy between 2010 and 2014, in terms of value added.
Digital tech isn’t just about Digital Tech Industries either
When we look at official labour market surveys, we find more digital professionals working outside of the Digital Tech Industries - in the public sector, finance, education or media, for example - than within. The big data sources that we have analysed allow us to dig further into the digital tech diffusion.
For example, GrowthIntel, the core data partner for Tech Nation 2016, scrapes and analyses company websites to learn what these businesses do. Their data allows us to not only study the sector in which a business operates (e.g. ‘financial services’) but also to determine if its “core capabilities” are digital (e.g. if it is a ‘fintech’ firm).[iii] The chart below shows the proportion of businesses with digital capabilities in different “non-digital sectors”.[iv] It reminds us that the web and online content are not the only drivers of digitisation in the economy. Sectors like Science and Aerospace also have large numbers of digital companies, probably reflecting the digitisation of their business processes.
We can also use this high-resolution information to measure and map the similarities and differences between digital tech businesses in interesting and novel ways.
The graph below shows the connections between GrowthIntel digital business tags (i.e. labels about business activities extracted from company websites), based on whether they “co-occur” in the same business.[v] In addition to showing the importance of data, mobile and software capabilities that are highly interconnected to many other capabilities, it also highlights the fact that Digital Tech Industries are themselves networks of capabilities that can be recombined to generate even more innovation.
The diffusion of digital know-how often happens when skilled individuals move between firms – we can look for evidence of this in the labour market data. Burning Glass, another of our Tech Nation 2016 partners, has a wealth of valuable data to shed light on this - a comprehensive, detailed, clean and timely repository of online job data, whose fields include the roles being advertised, the skills they require, salary bands and locations, and sector (see the companion Tech Nation 2016 for an indepth analysis of this data).
The chart below uses Burning Glass’s data to measure the levels of digital upskilling in different “non-digital” industries between 2012 and 2015. Again, it highlights the range of sectors that are looking for digital talent, notably including public sector areas such as Health, Defence, Social Security, and Education.
Social and industrial networking in the digital tech economy
Despite all the rhetoric about “heroic entrepreneurs” in public discourse, innovation is rarely created by individuals toiling on their own. On the contrary, innovation takes place in networks that bring together different people - those with good ideas, those with skills and those with money. The effective diffusion of digital technologies between businesses also requires these networks.
In fact, industrial clustering - the tendency of businesses to locate in the same places - is partly explained by the fact that it is easier to connect with people in your vicinity than people who are far away. Tech Nation 2016 confirms the importance of local networking for digital tech businesses - almost two-thirds of the businesses that we surveyed for the report say that local networks are an important benefit of clustering (this is the benefit that they mention most often). Our analysis of the digital tech sectors that different clusters specialise on supports the idea that digital technologies diffuse into those industries where a cluster already excels - London, a global hub in financial services, leads in fintech, for example. Cambridge, a biotech hotspot, has a strong health-tech presence.
We have used a number of novel data sources to study different aspects of networking in the Digital Tech Economy.
Locally, we have used data from Meetup.com (a website that people use to organise networking events) to analyse networking in digital tech communities across the UK. This analysis reveals 1,359 active digital tech meetup groups in 2015, involving 180,000 participants.
The chart below, based on an analysis of the tech specialisms for different meetup groups, shows how the networking scene has evolved and diversified in the UK as new digital tech areas of activity have emerged, and as more tech communities have started participating in local networks.
Regionally, we have also used common attendances at meetups to reveal the patterns of networking between tech clusters.
In the chart below, the ties between pairs of locations indicate that tech meetup users from those locations are often involved in the same meetups (the right panel normalises this data by the total levels of tech meetup activity in each pair of areas being considered).[vi]
The chart suggests that there is a great deal of informal networking going on between UK digital tech clusters, particularly in the Midlands and the North West, and in the M4 corridor west of London. This data challenges the notion that digital tech clusters operate in geographical silos and that digital tech cluster development in the UK is a zero sum game (where growth in one area is necessarily at the expense of others).
Online: Although Tech Nation 2016 confirms the importance of face-to-face interaction, digital technology of course creates new ways of communicating and collaborating with people far away too. We have explored this phenomenon using data from GitHub, a website where software developers share code and coordinate projects. As we have pointed out in previous research into the BBC’s innovation activities, code-sharing in sites such as GitHub can generate positive knowledge spillovers when this code is adapted by other users - including in other industries.
We find just under 19,000 active UK GitHub users with location data suitable for mapping. We can analyse their contributions to different projects in order to determine the programming languages they specialise in. The heat-map below shows the importance of some of these programming languages in different UK tech clusters.
We see high levels of activity in strong digital tech clusters like London, Cambridge, Bristol and Brighton. The implication is clear: UK developers in these clusters are sharing their code, enabling the diffusion of the technologies they develop, in a way that could benefit other businesses around them, and in other clusters and industries.
Conclusion: policymaking in disrupted times
Tech Nation 2016 paints a picture of a Digital Tech Economy that is disrupting, growing rapidly and crossing over into other sectors. It also shows how the diffusion of innovation that underpins this growth is enabled by strong networks - locally, regionally and online. At the same time, more diffusion, more networking themselves create further opportunities to innovate… and disrupt. Finding strategies to boost the benefits of disruption while managing its economic costs is a big challenge for policymakers - one that resources like Tech Nation 2016 and the datasets we have used in producing it can help to address.
[i] The methodology in Tech Nation 2016 contains further information about how we collected and analysed the data. See also Nesta’s Dynamic Mapping of the Information Economy for an in-depth description of the methodology used to define digital tech industries and occupations.
[ii] Digital tech industries are those that specialise in employing digital talent.
[iii] This distinction is not easy to make with official data-sources that lump businesses into mutually exclusive categories.
[iv] The sectors are defined using GrowthIntel’s proprietary sectoral classification.
[v] Note that this network map is not included in the Tech Nation 2016 report, but it is based on the data we used there.
[vi] This helps us to control for the fact that, other things being equal, locations with larger Meetup populations are likely to interact more often, even if it is only by chance.