sprint policy -data science

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)

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New technologyNew low priced storage in the cloud,

with software capable of gaining speedy insights

New ApproachA ‘data first’ mindset, exploring

the data to find insights and potential improvements

VelocityData generated/collected in real-time and at frequent Intervals. E.g. website logs can provide data at multiple points per second

VarietyData collected from

multiple sources and in complex, unstructured formats incompatible

with traditional softwareE.g. from social media

or scraped from the web

VolumeLarge amounts of data that require specialist technology to be stored and managede.g. citizen tax data

DataScience

New approach

New technology

Volume

Velocity Variety

Data science is a new way of gaining insight – and not just from ‘big data’


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


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

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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



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



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 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


We will be engaging more widely to explore the priority areas and communicate the outcomes

of alpha projects

sprint policy -data science

Government & Nonprofit