New types of data - big data, open data, mashed up data - can help us understand the digital economy in new, policy-relevant ways. Here are some examples and challenges.

1. Using new types of data to
measure the digital economy
Juan Mateos-Garcia
Juan.mateos-garcia@nesta.org.uk
READIE Research Summit, 21 March 2016

2. 1: What’s the big digital data opportunity?
Some important questions:
-Where it is happening
-How is it happening?
-What are the barriers?
-Do our interventions to
support it make a
difference?
We want to measure &
understand digital
innovation &
entrepreneurship to
support them better
Why is it hard to do
this with official
data?
What is the
policy problem?
What can we do
about it?
Rear-view of the
economy based on
existing industrial codes
Data in silos, lacking a
relational dimension,
Anonymised data: we
care about outliers but
learn about averages
Hard to identify new
industries, new
digital technologies,
new clusters
Fragmented,
incomplete view of
ecosystems
Imprecise targeting
across the policy
cycle
Use unstructured
data to create our
own categories
Combine datasets,
use social network
data
Use public data
The (big, open) data revolution is multiplying the opportunities to generate,
communicate and use data insights about digital industries

3. Example 1: Measuring digital industries poorly
covered by industry (SIC) codes
We used web data to
identify and map UK games
companies, evidencing the
limitations of existing SIC
codes and revealing new
clusters.

4. Example 2: Finding
communities
We used data from
Meetup.com (a website
used to organise networking
events to) to identify
communities interested in
different tech specialisms
across the UK.

5. Example 3: Mapping networks

6. Bringing it all together: Tech Nation 2016
In Tech Nation we
combine web, open and
official data to measure
the state of the UK digital
economy, its clusters and
its networks.
This allowed us to look at
digital tech subsectors,
measure digitisation in
non-digital industries,
analyse changes in digital
salaries and map regional
tech networks...

7. New data isn’t the silver bullet for digital econ policy
● It has weird biases
● Hard to use it for time series analysis
● Black box problems
● Lacks important variables (e.g.
financials)
● Need new skills to collect, analyse
and use.
● Policymakers aren’t purely data-
driven automatons
But used judiciously, and in
combination with other datasets, it
can create new information about
the digital economy that is relevant
for policymakers.

8. What are we doing next?
-Arloesiadur: An innovation data analytics platform
for Welsh Government.
Going from…
STATIC INTERACTIVE
DESCRIPTIVE PREDICTIVE
RESEARCH APPLICATION
Project running January 2016-March 2017. We’ll keep
you posted about what we find!