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Looking under the hood of Tech Nation 2016: process, findings and
lessons
Juan [email protected]
READIE Research Summit, 22 March 2016
Goals & Structure• Goals of the session:– Having a practical opportunity to think about how to combine
data opportunities and policy needs– Talk to each other!– Create the seed of an amazing project that will change the
face of the digital economy in Europe• I’ll get you in the mood with a little talk about Tech Nation 2016,
a policy-relevant project to understand the digital tech economy in the UK:– Origin– Process– Impacts– Lessons
Origin
2010 Feb 2016Feb 2015~2013
GOAL: Produce a rigorous, timely map of the UK digital tech industries that speaks to a policy and industry audience. Nesta = Analytical partner.
Design featuresGOAL CHALLENGE SOLUTION
Timely, industry relevant analysis of the digital tech industries
SIC codes aren’t sufficient to do this
Use web data to identify digital tech
businesses
Policy relevant analysis including economic
measurements
Public/open data doesn’t include econ
measures
Use official micro-data and a transparent
methodology to select SICs
Consider digitisation of non-digital sectors
Few datasets measure business digitisation
Select datasets with combinations of
sector/digital capability
Measure skills base in local ecosystems
Skills supply is both formal and informal
Use web data to measure local skills and
networks
Data and research team
Nesta team included Hasan Bakhshi (lead), Juan Mateos-Garcia (quant analysis), Madeleine Gabriel (qual analysis), Cath Sleeman (interactive data viz), Matthew Williams (external, supported work with GI, GitHub, Meetup data).Analytical work August 2015-January 2016 -> VERY TIGHT.
• This includes ONS (BSD, ABS, APS) data some of which was obtained by Frontier Economics.
• We also collected HESA, RCUK data.
• TCUK also ran a business survey
• 40 qual interviews.
Briefly, on definitions
Definition of digital tech based on previous Nesta analysis, dynamic mapping method:• Based on intensity of digital
tech occupations in different industries.
• Allows distinguishing between digital tech industries and jobs, and look at digitisation in non-digital.
Impacts
Big media coverage• 39,000 visits• 8 national pieces
(Guardian, FT etc.) • 31 regional pieces,
56 trade pieces• 5 broadcasts.
Impacts (2)
Lessons & next steps• It’s not about big data OR official data OR surveys. It can (and
probably should) be all.• It’s easy to be overwhelmed by data. Use domain knowledge to
identify interesting questions to prioritise (working with TCUK was helpful for this).
• Give yourself enough time to analyse the data.• Segment outputs (headlines vs. technically complex info).What’s next?• We are now moving from static to interactive, and descriptive to
predictive.• Considering policy implications• …And starting to think about next year’s Tech Nation!
Follow-up!
• [email protected] • @JMateosGarcia• https://www.linkedin.com/in/juanmateosgarcia