1. Data Science and
Government
What is data science and how can it aid
policy making and service delivery?
Government Innovation Group (GIG)
Government Digital Service (GDS)
Government Office for Science (GO Science)

2. 2
New technology
New low priced storage in the cloud,
with software capable of gaining
speedy insights
New Approach
A ‘data first’ mindset, exploring
the data to find insights and
potential improvements
Velocity
Data generated/collected
in real-time and at frequent
Intervals. E.g. website logs
can provide data at multiple
points per second
Variety
Data collected from
multiple sources and in
complex, unstructured
formats incompatible
with traditional software
E.g. from social media
or scraped from the web
Volume
Large amounts of data that
require specialist technology
to be stored and managed
e.g. citizen tax data
Data
Science
New approach
New technology
Volume
Velocity Variety
Data science is a new way of
gaining insight – and not just from ‘big data’
Data Science and Government

3. Government has always worked with data,
but data science offers new possibilities
• Government gathers and creates vast amounts of data, and these
have long been used by skilled analysts to inform policy and
operational decisions
• Significant advances in capability and cost of technology have
opened up new opportunities in data analytics
• There are good reasons to tackle this now:
i. The need for step changes in public service productivity;
ii. The increasing maturity of the knowledge base in the UK;
iii.The strength of the government’s new digital services
3 Data Science and Government

4. 4 Data Science and Government
Data science has the potential to enhance
policy making and service delivery
Interrogation of data patterns to introduce new insights:
• Legislation.gov.uk: The National Archives are looking to improve
user experience and identify trends by exploring site search patterns.
They are also aiming to improve drafting practices by identifying
common vocabulary across legislation.
Predicting outcomes to influence policy and operational decisions:
• Analysts at the National Offender Management Service have created
a tool which can predict the likelihood of offenders to reoffend with
serious crimes

5. 5
We have identified 4 key strands on
which our agenda is focussed
There are a few examples
across government, but there
has been little strategic
planning to coordinate work or
maximise the possibilities
1. Trial Data Science alpha projects:
Developing new data science
projects and sharing learning from
existing capability across government
with a focus on catalysing activity
Barriers Actions
Data Science and Government

6. 6 Data Science and Government
There are a number of
practical barriers around skills,
technical and procurement
issues and policy
2. Build Capability:
Addressing the skills gap by hiring
external talent while working with
analytical professions and policy
makers to develop longer term plans
for building capability
3. Unlock practical barriers:
• Dealing with standards, technical
& procurement challenges
• Exploring policy uncertainty, e.g.
on data sharing
Barriers Actions
We have identified 4 key strands on
which our agenda is focussed

7. 7 Data Science and Government
There are public
acceptability risks that
need to be treated with
utmost respect
4. Work in a radically transparent way:
Using Open Policy Making techniques to
explore the potential with innovators
inside and outside government and to
develop an ethical code
Barriers Actions
We have identified 4 key strands on
which our agenda is focussed

8. • We will be conducting workshops with particular departments to
identify high priority policy or operational questions and how they can
be addressed through data science
• We will be attending further events to demonstrate the potential of
data science:
• Heads of Analysis conference – 2nd
July
• Working level practitioner’s meeting – 29th
May
• If you are interested in collaborating with us, please get in touch
8 Data Science and Government
We will be engaging more widely to explore the
priority areas and communicate the outcomes
of alpha projects