Download - Keynote #2 applying behavioural insights to public policy by Rory Gallagher

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Applying behavioural insights to public policy

Dr Rory Gallagher


What are Behavioural

Insights (BI)? How can I apply BI? Where next?


Attention depletion … Let’s start with a game

(Danziger et al. 2010)


Memory game


Memory test: How did you do?

1. Apple 2. Policeman 3. Cake

4. Helicopter 5. Doctor 6. Cow

7. Golfer 8. France 9. Music Notes

10. Wheat 11. Washing Machine 13. Money

14. Clock 15. Dog


Ordering effects

Primacy Recency

Time

Rec

all


System 1

Fast thinking/Automatic intuitive, effortless

2x2

Taking your daily commute

System 2

Slow thinking/Reflective deliberate, analytic

24x17

Planning a trip overseas

“It turns out that the environmental effects on behavior are a lot stronger than most people expect”

Daniel Kahneman

We need to think differently about behaviour


Mental shortcuts or ‘heuristics’


Choosing portion size


Proximity and visibility

3.1 4.6

5.6

7.7

"far" and not visible

Close and not-visible

Far and visible Close and Visible

Number of Sweets Consumed


Most policy involves behaviour, but we often focus on the wrong things


Applying Behavioural Insights in government

Behavioural Insights

Psychology

Economics

Cognitive Sciences

Methods eg ethnography

& RCTs

Understanding how people behave in practice, so that we can design better policies & services

= Human centric services


Both BehaviouraI Insights and Design Thinking support the development of more human-centric services


Design Thinking &

UX

Human –centric

services


BI: more nuanced understanding of human behaviour and additional tools for policymakers

Regulation

Incentives

Information



“Our government will find intelligent ways to encourage, support and enable people to make better choices for themselves.”


“David Cameron’s Vanity Project”


Press coverage


BIT has grown from a small team in the heart of the UK Government…


Now 80+staff in 5 offices – London, Manchester, Sydney, NY, and now … Singapore


Guatamala: Guatamalan tax administration

UK: (i) The Behavioural Insights Team (BIT) & (ii) nudge units in 10 departments

Singapore: (i) Prime Minister’s Office (ii) Ministry of Manpower iii) MHA + transport, HDB, HPB etc

‘Nudge Units’ around the world

Denmark: The Danish Nudging Network

Norway: Greenudge

Finland: Prime Minister’s Office

Sweden: Swedish Nudging Network

Netherlands: (i) Ministry of Economic Affairs & (ii) Ministry of Infrastructure & the Environment

Canada: Policy Horizons Canada

Chicago: Chicago Nudge Unit

US: White House Social and Behavioral Sciences Team

NYC: (i) BIT North America & (ii) ideas42

Commonwealth Government: BETA

Sydney: (i) BIT Australia & (ii) Behavioural Insights Unit, New South Wales

European Commission: Behavioural Science and Foresight Team World Bank:

Development Report and behavioural trials

OECD: Behavioural science coordination

Germany: Chancellor’s Office

Moldova: UNDP/BIT collaboration

Jamaica: Finance Ministry (UNDP/BIT) Rio de Jeneiro:

Mayor’s Office

Mexico: President’s Office

Victoria: DPC NZ?


We have collaborated with a wide range of government agencies in Singapore

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Studying behaviour “can lead to better results for schemes and policies”


Our methodology


SOCIAL

TIMELY ATTRACTIVE

EASY


Easy Defaults Simplification Remove friction


Easy: Auto-enrolment in pensions

61% 83%

44%

76%

Before auto-enrolment After auto-enrolment

Large employers

Medium employers

22 percentage point increase

32 percentage point increase


5.4 million people automatically enrolled so far …

…once fully rolled out: 8-9 million people

£11 billion additional savings

Easy: Auto-enrolment in pensions


Easy: HDB redesigned letters to encourage channel migration


Easy: The new reminders did not increase payment rates

0 10 20 30 40 50 60 70 80 90 100 110 120 No. of days after letter sent

1st Reminder 2nd Reminder


Easy: But many more people paid online

N=2,510

11%

31%

Old Letter New Letter


Easy: This was effective even in older age groups

46%

23%

15%

6% 6% 5%

71%

53%

35%

26% 21% 20%

25-34 35-44 45-54 55-64 65-74 >75


SOCIAL

TIMELY ATTRACTIVE

EASY


Attractive Salience Messenger Personalisation Affect Incentive design


Attractive: placement of drinks in the hospital cafe


Attractive: Changing prices of soft drinks in vending machines

49.1% 44.1%

Standard pricing 20% red drink price increase


SOCIAL

TIMELY ATTRACTIVE

EASY


Social Norms Networks Reciprocity Active commitments Eyes & faces


Innovative use of data: reducing anti-microbial resistance by targeting over-prescribing GPs

100

110

120

130

140

150

160

July August September October November December January February March

Ant

ibio

tic it

ems

disp

ense

d p

er 1

000

wei

ghte

d po

pula

tion

(3,3

00 G

Ps )

Control Treatment


SOCIAL

TIMELY ATTRACTIVE

EASY


Timely Priming Framing Key moments


Two different conversations between a parent and child

What homework do you have this

weekend? Not much, couple of

small things. Usual really.

Conversation 1 (no text condition) Conversation 2 (text condition)

So you have a Maths test on Friday. How

much revision will you need

to do?


The impact of pre-informing parents about upcoming tests

•  Texting parents about a Maths test improved grades by the equivalent of 1 month of schooling

•  Effect for bottom ability quartile was twice as big

•  The intervention created demand for its repetition: treatment group pupils more likely to say ‘text my parents next time’


How can you help people to find employment?


We started in Loughton JCP and co-designed interventions with front line staff

Combining EAST: Loughton JCP trial


Increase in job seeker being off benefits at 13 weeks

51% 60%

Control Treatment Treatment Adjusted

4% Benefit history difference

5% Treatment effect


BIT Coach

JCP Trainer

JCP Trainer

JCP Trainer

JCP Trainer

JCP Trainer

JCP Trainer

JCP Trainer Developed a training

model in NE England. And rolled it out

nationally to 25,000 workers

Successfully replicated and adapted in both Singapore and

Australia

Rolled out across the UK


Replicated and adapted in Singapore


With similarly impressive results

32%

49%

Control Intervention

This translates to about 4,000 more job seekers per year finding jobs within 3 months


Data and personalisation

37.8

32.9 34.6

37.8

42.4

39.3

42.5

39.3 40

36.8

31.9

25.7

39.4

34.2 35.9

39.9

44.1

47

39.4

35.4 35.5

39.4

45.9

56.3

Bottom quartile

2nd quartile 3rd quartile Top quartile Top 5% Top 1%

Control Minority norm Gain-framed public services Loss-framed public services

Minority norm effective Minority norm backfires


Public engagement and accountability


‘Nudging’ ourselves


Stronger together

Re-framing problems

Qual & quant data User & systems focus

Test, learn, adapt


Design Thinking &

UX

Human –centric

services


Thank you!

Contact: [email protected] [email protected]

Download - Keynote #2 applying behavioural insights to public policy by Rory Gallagher

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